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Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures
NASA Astrophysics Data System (ADS)
Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.
Zhu, D.; Xuan, Y.; Cluckie, I.
Mitigation of wind turbine clutter in C-band weather radars for different rainfall rates
Wind farm installations relatively near to radar systems cause clutter returns which can affect the normal operation of these radars. In this paper a parametric study of the dependence of the rain characteristics in wind turbine clutter (WTC) mitigation for C-band weather radars is presented. For this aim, several realistic simulations of weather conditions have been performed.
B. Gallardo-Hernando; F. Perez-Martinez; F. Aguado-Encabo
Rainfall forecasting in a mountainous region using a weather radar and ground meteorological observations
NASA Astrophysics Data System (ADS)
Weather radars provide several types of information useful for defining the state and evolution of a rain system: the rainfall rate, the vertically integrated rainwater content, and the advection velocity. The very short-term rainfall forecasting models dedicated to the survey of catchments (particularly those subject to flash-floods) are typically designed to include one or more of these information types. A general formulation of these models associating an advective term and a dynamical term is proposed by Lee and Georgakakos (1991). The model proposed in this work extends the simplified dynamical formulation developed by Seo and Smith (1992) and French and Krajewski (1994) by explicitly accounting for orographic enhancement and by combining the dynamical component with an advection-diffusion scheme (Smolarkiewicz 1983). This paper presents an initial evaluation of the model for two rain events in the mountainous Cevennes region located in the South of France. One-hour and two-hour lead-time forecasts for four catchments are performed and compared with two simple methods: persistence and advection.
Dolcin�, L.; Andrieu, H.; French, M. N.
Benefits and limitations of using the weather radar for the definition of rainfall thresholds for debris flows. Case study from Catalonia (Spain).
NASA Astrophysics Data System (ADS)
Torrential processes such as debris flows or hyperconcentrated flows are fast movements formed by a mix of water and different amounts of unsorted solid material. They occur in steep torrents and suppose a high risk for the human settlements. Rainfall is the most common triggering factor for debris flows. The rainfall threshold defines the rainfall conditions that, when reached or exceeded, are likely to provoke one or more events. Many different types of empirical rainfall thresholds for landslide triggering have been defined. Direct measurements of rainfall data are normally not available from a point next to or in the surroundings of the initiation area of the landslide. For this reason, most of the thresholds published for debris flows have been established by data measured at the nearest rain gauges (often located several km far from the landslide). Only in very few cases, the rainfall data to analyse the triggering conditions of the debris flows have been obtained by weather (Doppler) radar. Radar devices present certain limitations in mountainous regions due to undesired reboots, but their main advantage is that radar data can be obtained for any point of the territory. The objective of this work was to test the use of the weather radar data for the definition of rainfall thresholds for debris-flow triggering. Thus, rainfall data obtained from 3 to 5 rain gauges and from radar were compared for a dataset of events occurred in Catalonia (Spain). The goal was to determine in which cases the description of the rainfall episode (in particular the maximum intensity) had been more accurate. The analysed dataset consists of: 1) three events occurred in the Rebaixader debris-flow monitoring station (Axial Pyrenees) including two hyperconcentrated flows and one debris flow; 2) one debris-flow event occurred in the Port Ain� ski resort (Axial Pyrenees); 3) one debris-flow event in Montserrat (Mediterranean Coastal range). The comparison of the hyetographs from the different devices showed that the reliability of the radar is higher for short, high intensity storms more than for long lasting, medium intensity ones. Additionally, the best fit corresponds to the situations where the storm nucleus is located near the source area of the debris flow. The results of the comparison between different rain gauges show similar trends. The ones located in the same valley as the debris flow usually show good results, but if there are orographic elements in-between the debris-flow torrent and the rain gauge or the distance is large, the results can imply a great error in the definition of rainfall intensity. Therefore, we can state that the reliability of the use of the weather radar to define rainfall thresholds is strongly depending on the type of the storm and the distance between the source area and the nucleus of the storm.
Abanc�, C.; H�rlimann, M.; Sempere, D.; Berenguer, M.
Research relative to weather radar measurement techniques
NASA Technical Reports Server (NTRS)
Research relative to weather radar measurement techniques, which involves some investigations related to measurement techniques applicable to meteorological radar systems in Thailand, is reported. A major part of the activity was devoted to instruction and discussion with Thai radar engineers, technicians, and meteorologists concerning the basic principles of radar meteorology and applications to specific problems, including measurement of rainfall and detection of wind shear/microburst hazards. Weather radar calibration techniques were also considered during this project. Most of the activity took place during two visits to Thailand, in December 1990 and February 1992.
Smith, Paul L.
Assessing the role of spatial rainfall variability on watersheds response using weather radar A case study in the Gard region, France
NASA Astrophysics Data System (ADS)
The consideration of spatial rainfall variability in hydrological modeling is not only an important scientific issue but also, with the current development of high resolution rainfall data from weather radars, an increasing request from managers of sewerage networks and from flood forecasting services. Although the literature on this topic is already significant, at this time the conclusions remain contrasted. The impact of spatial rainfall variability on the hydrological responses appears to highly depend both on the organization of rainfall fields and on the watershed characteristics. The objective of the study presented here is to confirm and analyze the high impact of spatial rainfall variability in the specific context of flash floods. The case study presented is located in the Gard region in south east of France and focuses on four events which occurred on 13 different watersheds in 2008. The hydrological behaviors of these watersheds have been represented by the distributed rainfall - runoff model CINECAR, which already proved to well represent the hydrological responses in this region (Naulin et al., 2013). The influence of spatial rainfall variability has been studied here by considering two different rainfall inputs: radar data with a resolution of 1 km x 1 km and the spatial average rainfall over the catchment. First, the comparison between simulated and measured hydrographs confirms the good performances of the model for intense rainfall events, independently of the level of spatial rainfall variability of these events. Secondly, the simulated hydrographs obtained from radar data are taken as reference and compared to those obtained from the average rainfall inputs by computing two values: the time difference and the difference of magnitude between the simulated peaks discharge. The results highly depend on the rainfall event considered, and on the level of organization of the spatial rainfall variability. According to the model, the behavior of the studied watersheds may sometimes remain very similar with a homogeneous rainfall input, whereas for some cases the differences in the peak discharges can reach up to 80%. A detailed analysis illustrates the possible role of the watershed in enhancing the effect of rainfall spatial variability. In a further step, the objective is to test the ability of four rainfall variability indicators to identify the situations for which spatial rainfall variability has the greatest influence on the watershed response. The selected indicators include those of Zoccatelli et al. (2010), and all rely on a detailed analysis of spatial rainfall organization in function of hydrological distances (i.e. the distances measured along the stream network from one point of the watershed to the outlet). The analysis of the links between these indicators and the hydrological behaviors identified is currently in progress. Reference: Naulin, J.P., Payrastre, O., Gaume, E., 2013. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France. Journal of Hydrology, 486, 88-99, doi:10.1016/j.jhydrol.2013.01.044 Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B., Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394, 148-161
Anggraheni, Evi; Payrastre, Olivier; Emmanuel, Isabelle; Andrieu, Herve
Federal Plan for Weather Radars.
National Technical Information Service (NTIS)
The plan for weather radars describes the use of national weather radar resources in providing warnings and forecasts of severe weather for all walks of life within the U.S. Information is given on disaster warnings, general weather forecasting special De...
Real-time radar rainfall estimation
NASA Astrophysics Data System (ADS)
This research reports on several aspects of real-time monitoring of the spatial and temporal distribution of rainfall from ground-based weather radar. Optimization of the performance of the National Weather Service's Precipitation Processing Subsystem (PPS) is the first objective. This is achieved by developing a calibration procedure which simultaneously estimates the optimal parameter values by providing a global assessment of the system's performance. Evaluation of the system is based on a data set consisting of two months of radar reflectivity measurements, and hourly raingage rainfall accumulations, from the Melbourne, Florida WSR-88D site. Radar-raingage root mean square (RMS) difference reduction up to 20% with respect to the default system parameter values is demonstrated. Investigation of statistical procedures for real-time adjustment of the mean-field systematic radar rainfall error is the second objective. For this purpose, a data- based Monte Carlo simulation experiment is performed. The study uses an extensive data set of hourly radar rainfall products and raingage accumulations from the Tulsa, Oklahoma WSR-88D site. This intercomparison study concluded to a bias procedure which overall appeared to perform better than the other. The main results from this research are: (1) statistical methods with optimal error model parameters perform significantly better than using only bias observations, and (2) bias adjustment is mostly effective in cold season precipitation measurements. Final objective of this research is development of a new real-time radar rainfall estimation algorithm. The new processing steps introduced in this algorithm are beam- height effect correction, vertical integration, rain classification, and continuous range effect correction. Additionally, the algorithm applies advection correction at the gridded rainfall rates to minimize the temporal sampling effect, and its calibration is cast in a recursive formulation with parameters adjusted in real- time. A new statistical method has been developed for quantification of radar rainfall products uncertainty. Evaluation of the system and the uncertainty quantification method is based on the data set from Melbourne, Florida WSR-88D site. Radar-raingage RMS difference reduction up to 50% with respect to the default PPS is demonstrated for the proposed algorithm.
Anagnostou, Emmanouil Nikolaos
Probabilistic forecasts based on radar rainfall uncertainty
NASA Astrophysics Data System (ADS)
The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.
Liguori, S.; Rico-Ramirez, M. A.
Integrated operation was simulated of ten dynamic combined sewer regulators on a Montreal interceptor. Detailed review of digital recording weather radar capabilities indicated that it is potentially the best rainfall estimation means for accomplishing the runoff prediction that ...
Rainfall small scale variability: Certain implications for radar rainfall validation problem
NASA Astrophysics Data System (ADS)
Despite recent technological advances in the area of radar hydrology, reliable quantification of radar-rainfall amounts on scales relevant to hydrological applications is not fully realized. A major problem is the lack of accurate estimation of uncertainty levels of radar-rainfall products. Discrepancies between radar and rain gauge rainfall quantities---traditionally considered as an approximation of the true ground rainfall---are mainly attributed to two main factors: rainfall small-scale natural variability and differences in sampling properties between radar and gauge. The present research addresses these issues in an attempt to develop sound validation methodologies for radar-rainfall products. In the framework of this study, some fundamental questions are posed: How is rainfall variable over scales smaller than the radar-resolved scales? What role does such variability play in the evaluation of radar-rainfall estimates? Is there a radarspace/gauge-time equivalence where the observations of both sensors are possibly comparable? This study makes use of extensive experimental rainfall multi-sensor observations collected during the field campaigns of the NASA's Tropical Rainfall Measuring Mission (TRMM) in addition to other experimental datasets. First, errors associated with gauge measurements---as the main independent data source for validation---are investigated and characterized. Then, extensive data analysis is performed to characterize rainfall variability over scales relevant to radar spatial/temporal resolutions. A statistical procedure is applied to quantify the contribution of rainfall natural variability to the significant discrepancy usually observed in radar-gauge comparisons. This eventually can be used in establishing an error budget for radar-rainfall products. Finally, a non-parametric statistical procedure is developed and applied in an effort to establish a comprehensive validation framework. A main element is a transformation model of point-to-area rainfall which is experimentally verified. The findings of this research have implications for the use of radar-rainfall data in applications such as hydrologic modeling, flood forecasting, numerical weather prediction models, and validation of other remote sensing rainfall estimates, among others.
Habib, Emad Hosny
Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall
NASA Astrophysics Data System (ADS)
Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)
Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo
Utilizing Doppler Radar to Estimate Rainfall Rates for Highway Segments
This paper will present findings and the overall methodology for estimating roadway rain rates. In order to accurately estimate rainfall rates along Interstate highways in Northeast Florida for the Florida Road Weather information System (RWIS) in near real time, the investigators developed and implemented a new methodology to geo-locate Doppler radar rain rates. The intent of this project is to
Nick Chape; Robert Richardson; J. David Lambert; Patrick Welsh
Radar Rainfall Estimates for Tropical Storm Allison
NASA Astrophysics Data System (ADS)
Tropical Storm Allison dropped more than 30 inches of rain over metropolitan Houston in June 2001, causing unprecedented flooding and more than \\$4 billion dollars of damage. Over parts of the city and Harris County, rainfall rates exceeded 3 inches per hour for eight consecutive hours. Rainfall distributions from rain gages are typically estimated by assuming a spatial geometry tied to point rain gage observations using, for example, Thiessen polygons, inverse distance squared weighting, or statistical Kriging techniques. Unfortunately, the spatial distributions inferred by these approaches have little connection with how rain actually falls. Since the release of the WSR-88D (NEXRAD) radar in the early 1990s, many hydrologists and engineers have begun used gage-adjusted radar rainfall estimates for hydrologic and water resource modeling. However, due to the extreme nature of the event, traditional radar rainfall estimation methods using uniform bias adjustment techniques severely underestimated the rainfall rates in the heaviest regions of the storm. NEXRAIN created a gage-adjusted radar rainfall dataset using over 150 rain gages and incorporating a spatial adjustment technique developed by Edward Brandes at the National Severe Storms Lab in the mid-1970s. This approached was able to characterize the most intense portions of the storm, while maintaining the spatial signature of the storm. The radar-rainfall data set used in this project was a mosaic of several WSR-88D radars that the Houston area. Slight performance characteristics between the radars caused visible discontinuities at the edges of the individual coverage areas. In addition, an area of underestimation due to the use of higher scan elevations in the immediate vicinity of the Houston radar was noted. A GIS approach was used to reduce or eliminate these spatial discontinuities. Use of these two techniques greatly improved gage-adjusted radar rainfall estimates of the extreme rainfall while preserving the spatial signature of the radar-rainfall distribution.
Hoblit, B. C.; Liu, L.; Curtis, D. C.
Aggregation and disaggregation of radar rainfall rates
NASA Astrophysics Data System (ADS)
Spatially distributed, high-resolution precipitation rates are key ingredients for modeling soil-vegetation processes, water and solute transports in mesoscale catchments, and for short-range weather prediction. The ultimate goal of our study is to develop a space-time, multilevel statistical model that merges rain radar measurements with other observations of precipitation. This is a challenging task since it aims at combining data sources with a variety of error structures, and temporal resolutions. E.g., in-situ measurements are quite accurate, but available only at sparse and irregularly distributed locations, whereas remote measurements cover complete areas but suffer from spatially and temporally inhomogeneous systematic errors. The first step towards such a space-time precipitation model is to develop a statistical model for precipitation based on radar measurements. Precipitation rates over a region of about 230� 230 km2 are provided by a composite of the two polarimetric X-band radars in Germany. The two radars are located in a distance of about 60 km in Bonn and J�lich, respectively. For the statistical model formulation we use a Gaussian Markov random field as underlying process. A Markov random field is a suitable model to account for spatial dependencies if the neighborhood can be reduced to a small region without losing information. This makes large data problems computationally feasible, since the neighborhood structure is given by a sparse precision matrix. Markov random fields are closely related to a graphical models. In processing the unadjusted radar rainfall rates, we follow D. Allcroft and C. Glasbey (2003)footnote{?bel{foot:1}David Allcroft and Chris Glasbey (2003). A latent Gaussian Markov Random Field model for spatiotemporal rainfall disaggregationJournal of the Royal Statistical Society: Series C (Applied Statistics), 52:487-498}. We start with a transformation of the precipitation rates to a truncated Gaussian distribution. The advantage of such a latent variable approach is that the occurrence as well as the intensity of rainfall are modeled by a single spatial process. The correlation function is then estimated as a function of the lag distance in space (and time) using the maximum likelihood method. Finally the Gaussian Markov random field is fitted such that its inverse is close to the empirical covariance matrix in some matrix norm. Therefore we use a minimum least squares method and implement a penalty term to assure the positive definiteness of the resulting covariance matrix. Note, that throughout our calculations we assume stationarity. The statistical model then allows for a disaggregation and aggregation of precipitation rates.
Krebsbach, K.; Friederichs, P.
Efficient Ways to Learn Weather Radar Polarimetry
ERIC Educational Resources Information Center
The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model�
Cao, Qing; Yeary, M. B.; Zhang, Guifu
Investigating rainfall estimation from radar measurements using neural networks
NASA Astrophysics Data System (ADS)
Rainfall observed on the ground is dependent on the four dimensional structure of precipitation aloft. Scanning radars can observe the four dimensional structure of precipitation. Neural network is a nonparametric method to represent the nonlinear relationship between radar measurements and rainfall rate. The relationship is derived directly from a dataset consisting of radar measurements and rain gauge measurements. The performance of neural network based rainfall estimation is subject to many factors, such as the representativeness and sufficiency of the training dataset, the generalization capability of the network to new data, seasonal changes, and regional changes. Improving the performance of the neural network for real time applications is of great interest. The goal of this paper is to investigate the performance of rainfall estimation based on Radial Basis Function (RBF) neural networks using radar reflectivity as input and rain gauge as the target. Data from Melbourne, Florida NEXRAD (Next Generation Weather Radar) ground radar (KMLB) over different years along with rain gauge measurements are used to conduct various investigations related to this problem. A direct gauge comparison study is done to demonstrate the improvement brought in by the neural networks and to show the feasibility of this system. The principal components analysis (PCA) technique is also used to reduce the dimensionality of the training dataset. Reducing the dimensionality of the input training data will reduce the training time as well as reduce the network complexity which will also avoid over fitting.
Alqudah, A.; Chandrasekar, V.; Le, M.
Australian Weather Watch Radar Home Page
NSDL National Science Digital Library
The Commonwealth Bureau of Meteorology's Weather Watch Radar website provides up-to-date radar images of the locations of rain in Australia in relation to local features such as coast lines. The newly developed Loops provide four consecutive radar images so that users can view how the weather has been changing in the last forty to fifty minutes. The website provides radar images of past cyclone events as well as updates on severe weather throughout Australia. Those interested in radar systems can discover how the weather radars work and how to interpret the maps. [RME
Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between real rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the disc...
Enhanced Weather Radar (EWxR) System
NASA Technical Reports Server (NTRS)
An airborne weather radar system, the Enhanced Weather Radar (EWxR), with enhanced on-board weather radar data processing was developed and tested. The system features additional weather data that is uplinked from ground-based sources, specialized data processing, and limited automatic radar control to search for hazardous weather. National Weather Service (NWS) ground-based Next Generation Radar (NEXRAD) information is used by the EWxR system to augment the on-board weather radar information. The system will simultaneously display NEXRAD and on-board weather radar information in a split-view format. The on-board weather radar includes an automated or hands-free storm-finding feature that optimizes the radar returns by automatically adjusting the tilt and range settings for the current altitude above the terrain and searches for storm cells near the atmospheric 0-degree isotherm. A rule-based decision aid was developed to automatically characterize cells as hazardous, possibly-hazardous, or non-hazardous based upon attributes of that cell. Cell attributes are determined based on data from the on-board radar and from ground-based radars. A flight path impact prediction algorithm was developed to help pilots to avoid hazardous weather along their flight plan and their mission. During development the system was tested on the NASA B757 aircraft and final tests were conducted on the Rockwell Collins Sabreliner.
Kronfeld, Kevin M. (Technical Monitor)
Improved radar rainfall estimation at ground level
NASA Astrophysics Data System (ADS)
A technique has been developed to provide an estimate of the rainfall reaching the earth's surface by extrapolating radar data contained aloft to ground level, simultaneously estimating unknown data in the radar volume scan. The technique has been developed so as to be computationally fast, to work in real time and comprises the following steps. A rainfall classification algorithm is applied to separate the rainfall into two separate types: convective and stratiform rainfall. Climatological semivariograms based on the rainfall type are then defined and justified by testing, which result in a fast and effective means of determining the semivariogram parameters anywhere in the radar volume scan. Then, extrapolations to ground level are computed by utilising 3-D Universal and Ordinary Cascade Kriging; computational efficiency and stability in Kriging are ensured by using a nearest neighbours approach and a Singular Value Decomposition (SVD) matrix rank reduction technique. To validate the proposed technique, a statistical comparison between the temporally accumulated radar estimates and the Block Kriged raingauge estimates is carried out over matching areas, for selected rainfall events, to determine the quality of the rainfall estimates at ground level.
Wesson, S. M.; Pegram, G. G. S.
Real-time estimation of rainfall fields using radar rainfall and rain gage data
New attempts at real-time estimation of rainfall fields using rain gage and radar rainfall data are reported. Based on multiplicative decomposition of expectation of rainfall into conditional expectation of rainfall given raining and probability of rainfall, the estimation procedures explicitly account for both within-storm variability of rainfall and variability due to fractional coverage of rainfall. As a result, in addition
D.-J. Seo
Radar Rainfall Estimates for Extreme Flood Events
NASA Astrophysics Data System (ADS)
Analyses of radar rainfall estimates from the WSR-88D radar network are presented for a sample of major flood events in the US. The framework for radar rainfall analysis is the HydroNEXRAD system and analyses highlight the utility of radar rainfall estimates for a diverse range of flood hydrology applications. The sample of flood events focuses on regions of the US with large flood potential, including the Edwards Plateau of Texas, the central Appalachians and urban watersheds of the eastern US. The basin scales of interest range from less than 10 sq. km. to more than 10,000 sq. km. We examine errors in radar rainfall estimates from the perspective of extreme flood-producing storms. Analyses for the Edwards Plateau of Texas focus on major storm events in June 1997 and July 2002. In the Delaware River basin, analyses center on a sequence of record and near-record flood events in September 2003, April 2004 and June 2005.
Baeck, M.; Smith, J. A.; Krajewski, W.; Ntelekos, A. A.; Meierdiercks, K.
Vertical and Temporal Variability of Rainfall Using a K-band Radar
NASA Astrophysics Data System (ADS)
A vertically pointing Micro Rain Radar (MRR) was installed along a tipping bucket rain gauge at a site within a distance of 58.54 km from the nearest local National Weather Service weather radar, which have an average beam height of 552 m above ground level at the collocated gauge and MRR site. The MRR data were collected at two different gate height resolutions, 35 and 100 meters. The results showed that weather radar underestimated rainfall by 30 to 40% with respect to the gauge. And the MRR rainfall derived as function of Drop Size Distribution (DSD) and fall velocity (RR) was much closer to the gauge rainfall than MRR rainfall measurements derived from the same Z-R relationship used by the National Weather Service (Rz), which significantly underestimated rainfall in both height resolutions. The examination of the rainfall statistics suggested that the height resolution of 100 m produces better estimates especially at the third gate (centered at 300 m). MRR rain rates were highly variable during the same rainfall event or across different events. Few rainfall events showed very high rain rates at higher gates, but no bright band signature was found; thus a detailed inspection of DSDs variability with height and time is being conducted along with analysis of other MRR derived rainfall parameters to understand and capture the MRR rainfall variability and abnormalities.
Mazari, N.; Sharif, H. O.; Xie, H.; Tekeli, A. E.; Habib, E. H.; Zeitler, J.
Radar rainfall estimation for the identification of debris-flow precipitation thresholds
NASA Astrophysics Data System (ADS)
Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial variogram) of the triggering rainfall. These results show that weather radar has the potential to effectively increase the accuracy of rainfall thresholds for debris flow occurrence. However, these benefits may only be achieved if the same monitoring instrumentation is used both to derive the rainfall thresholds and for use of thresholds for real-time identification of debris flows occurrence. References Nikolopoulos, E.I., Borga M., Crema S., Marchi L, Marra F. & Guzzetti F., 2014. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris-flow occurrence. Geomorphology (conditionally accepted) Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C., and Guzzetti, F., 2012. Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy, Geomorphology, 139-140, 79-90, 2012.
Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco
Airborne Differential Doppler Weather Radar
NASA Technical Reports Server (NTRS)
The Precipitation Radar aboard the Tropical Rain Measuring Mission (TRMM) Satellite has shown the potential for spaceborne sensing of snow and rain by means of an incoherent pulsed radar operating at 13.8 GHz. The primary advantage of radar relative to passive instruments arises from the fact that the radar can image the 3-dimensional structure of storms. As a consequence, the radar data can be used to determine the vertical rain structure, rain type (convective/stratiform) effective storm height, and location of the melting layer. The radar, moreover, can be used to detect snow and improve the estimation of rain rate over land. To move toward spaceborne weather radars that can be deployed routinely as part of an instrument set consisting of passive and active sensors will require the development of less expensive, lighter-weight radars that consume less power. At the same time, the addition of a second frequency and an upgrade to Doppler capability are features that are needed to retrieve information on the characteristics of the drop size distribution, vertical air motion and storm dynamics. One approach to the problem is to use a single broad-band transmitter-receiver and antenna where two narrow-band frequencies are spaced apart by 5% to 10% of the center frequency. Use of Ka-band frequencies (26.5 GHz - 40 GHz) affords two advantages: adequate spatial resolution can be attained with a relatively small antenna and the differential reflectivity and mean Doppler signals are directly related to the median mass diameter of the snow and raindrop size distributions. The differential mean Doppler signal has the additional property that this quantity depends only on that part of the radial speed of the hydrometeors that is drop-size dependent. In principle, the mean and differential mean Doppler from a near-nadir viewing radar can be used to retrieve vertical air motion as well as the total mean radial velocity. In the paper, we present theoretical calculations for the differential reflectivity and Doppler as functions of the center frequency, frequency difference, and median mass diameter. For a fixed pair of frequencies, the detectability of the differential signals can be expressed as the number of independent samples required to detect rain or snow with a particular median mass diameter. Because sampling numbers on the order of 1000 are needed to detect the differential signal over a range of size distributions, the instrument must be confined to a near-nadir, narrow swath. Radar measurements from a zenith directed radar operated at 9.1 GHz and 10 GHz are used to investigate the qualitative characteristics of the differential signals. Disdrometer and rain gauge data taken at the surface, just below the radar, are used to test whether the differential signals can be used to estimate characteristics of the raindrop size distribution.
Meneghini, R.; Bidwell, S.; Liao, L.; Rincon, R.; Heymsfield, G.; Hildebrand, Peter H. (Technical Monitor)
Next Generation Weather Radar (NEXRAD)/Air Route Surveillance Radar (ARSR) Operational Comparison.
National Technical Information Service (NTIS)
The National Weather Service (NWS), Federal Aviation Administration (FAA), and Department of Defense are in the process of fielding the Next Generation Weather Radars (NEXRAD). These doppler weather radars, also known as Weather Surveillance Radar (WSR)-8...
B. Dunbar J. Mittelman
Next Generation Weather Radar (NEXRAD)/Air Route Surveillance Radar (ARSR) Operational Comparison.
National Technical Information Service (NTIS)
The National Weather Service (NWS), Federal Aviation Administration (FAA), and Department of Defense are in the process of fielding the Next Generation Weather Radars (NEXRAD). These doppler weather radars, also known as Weather Surveillance Radar (WSR)88...
B. Dunbar J. Mittelman
Singularity-sensitive merging of radar and raingauge rainfall data
NASA Astrophysics Data System (ADS)
Traditionally, urban hydrological applications relied mainly upon rain gauge data as input as these provide accurate point rainfall estimates near the ground surface. However, they cannot capture the spatial variability of rainfall, which has a significant impact on the urban hydrological system and thus on the modelling of urban pluvial flooding. Thanks to the development of radar technology, weather radar has been playing an increasingly important role in urban hydrology. Radars can survey large areas and better capture the spatial variability of the rainfall, thus improving the short term predictability of rainfall and flooding. However, the accuracy of radar measurements is in general insufficient, particularly in the case of extreme rainfall magnitudes. This has a tremendous effect on the subsequent hydraulic model outputs. In order to improve the accuracy of radar rainfall estimates while preserving their spatial description of rainfall fields, it is possible to dynamically adjust them based on rain gauge measurements. Studies on this subject have been carried out over the last few years, though most of them focus on the hydrological applications at large scales. A couple of recent research works have examined the applicability of these adjustment techniques to urban-scale hydrological applications and concluded that these techniques can effectively reduce rainfall bias, thus leading to improvements in the reproduction of hydraulic outputs (Wang et al., 2013). However, underestimation of storm peaks can still be seen after adjustment and this is particularly significant in the case of small drainage areas and for extreme rainfall magnitudes. This may be due to the fact that the underlying adjustment techniques, mainly based upon Gaussian approximations, cannot properly cope with the non-normality observed in urban scale applications. With the purpose of improving this aspect, a methodology has been developed which identifies the local extremes or 'singularities' of radar rainfall fields and preserves them throughout the merging process (Wang and Onof, 2013). Singularities are defined through the fact that the areal average rainfall increases as a power function when the area decreases (Cheng et al., 1994). In the proposed methodology singularities are first identified and extracted from the radar rainfall field. The resulting non-singular radar field is then used in the merging process and the singularities are subsequently and proportionally added back to the final reconstructed rainfall field. A full-scale testing of this methodology in an urban area in the UK has been conducted and the result suggests that the original Bayesian data merging technique (Todini, 2001) could be effectively improved by incorporating this singularity analysis. References Cheng, Q., et al., (1994) Journal of Geochemical Exploration, 51(2), 109-130. Todini, E., (2001) Hydrology and Earth System Sciences, 5, 187-199. Wang, L. et al., (2013) Water Science & Technology, 68(4), 737-747. Wang, L. and Onof, C., (2013) Hydrofractals '13, Kos island, Greece.
Wang, Li-Pen; Willems, Patrick; Ochoa-Rodriguez, Susana; Onof, Christian
Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields
NASA Astrophysics Data System (ADS)
In this paper, we develop a storm catalog of heavy rainfall events for a region centered on the Milwaukee, Wisconsin WSR-88D (Weather Surveillance Radar - 1988 Doppler) radar. The study region includes portions of southern Wisconsin, northern Illinois and Lake Michigan. The long-term objective of this study is to develop rainfall frequency analysis methods based on a storm catalog of major rain events. The specific objectives of this study are to develop a long-term catalog of high-resolution radar rainfall fields and characterize key features of the space-time variability of rainfall. The research questions that underlie these objectives are: 1) What are the spatial heterogeneities of rainfall over the study region for major flood-producing storm systems? 2) What are the key elements of storm evolution that control the scale-dependent properties of extreme rainfall? The storm catalog contains a record of the 50 �largest� storm days during the 1996-2011 observation period. We show that mean rainfall for the 50 largest storm days exhibits pronounced spatial heterogeneity with a broad maximum in western Wisconsin and a minimum in the eastern portion of the study region over Lake Michigan. We also show that there is a narrow line of maximum mean rainfall extending from west to east along the Wisconsin-Illinois border. This feature is tied to a maximum in the probability of daily rainfall exceeding 100 mm. There are characteristic elements to the storm life cycle of heavy rainfall days that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain area exceeding 25 mm h- 1 and development of a large stratiform rain area during the night and early morning.
Thorndahl, S�ren; Smith, James A.; Baeck, Mary Lynn; Krajewski, Witold F.
Tests of Radar Rainfall Retrieval Algorithms
NASA Technical Reports Server (NTRS)
The NASA/JPL Airborne Rain Mapping Radar (ARMAR) operates at 14 GHz. ARMAR flew on the NASA DC-8 aircraft during Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE), collecting data in oceanic mesoscale convective systems, similar to those now being observed by the Tropical Rainfall Measuring Mission (TRMM) satellite, which includes a 14-GHz precipitation radar. Several algorithms for retrieving rain rate from downward looking radars are in existence. These can be categorized as deterministic and stochastic. Deterministic algorithms use the path integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the attenuation-rainfall (k-R) relation, while another corrects the reflectivity rainfall (ZR) relation. Stochastic algorithms apply an Extended Kalman Filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. We find that the stochastic algorithm with PIA is the most robust algorithm with regard to incorrect assumptions about the drop-size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA. The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions. The underestimation is illustrated in the diagram. The algorithm labeled D IS initially assumes a DSD that is appropriate for stratiform. rain, while the rain is most likely convective. The PIA constraint causes the k-R relation to be adjusted, resulting in a much lower rain rate than the other algorithms. Additional information is contained in the original.
Durden, Stephen L.
Rainfall and Flood Frequency Analysis Using High-Resolution Radar Rainfall Fields and Stochastic Storm Transposition
NASA Astrophysics Data System (ADS)
Spatial and temporal variability of rainfall fields, and their interactions with surface, subsurface, and drainage network properties, are important drivers of flood response. 'Design storms,' which are commonly used for flood risk assessment, however, are assumed to be uniform in space and either uniform or highly idealized in time. The impacts of these and other common assumptions on estimates of flood risk are poorly understood. We present an alternative framework for flood risk assessment based on stochastic storm transposition (SST). In this framework, "storm catalogs" are derived from a ten-year high-resolution (15-minute, 1 km2) bias-corrected radar rainfall dataset for the region surrounding Charlotte, North Carolina, USA. SST-based rainfall frequency analyses are developed by resampling from these storm catalogs to synthesize the regional climatology of extreme rainfall. SST-based intensity-frequency-duration (IFD) estimates are driven by the spatial and temporal rainfall variability from weather radar observations, are specifically tailored to the chosen catchment, and do not require simplifying assumptions of storm structure. We are able to use the SST procedure to reproduce IFD estimates from conventional methods for small urban catchments in Charlotte. We further demonstrate that extreme rainfall can vary substantially in time and in space, with important flood risk implications that cannot be assessed using conventional techniques. When coupled with a physics-based distributed hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, SST enables us to examine the full impact of spatial and temporal rainfall variability on flood response and flood frequency. The interactions of extreme rainfall with spatially distributed land use, soil properties, and stormwater management infrastructure are assessed for several nested urban catchments in Charlotte. Results suggest that these interactions, which cannot be fully accounted for using standard frequency analysis techniques, are important controls on flood response. We compare the results of SST-based flood frequency analyses to peak streamflow observations and to the results of other frequency analysis techniques.
Wright, Daniel; Smith, James; Baeck, Mary Lynn
Performance of high-resolution X-band radar for rainfall measurement in The Netherlands
NASA Astrophysics Data System (ADS)
This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.
van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.
Performance of high-resolution X-band radar for rainfall measurement in The Netherlands
NASA Astrophysics Data System (ADS)
This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.
van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.
Performance of high-resolution X-band radar for rainfall measurement in The Netherlands
NASA Astrophysics Data System (ADS)
This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The high spatial (120 m) and temporal (16 s) resolution of the radar combined with the extent of the database make this study a climatological analysis of the potential for high-resolution rainfall measurement with non-polarimetric X-band radar over completely flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.
van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.
Weather Radar Quantification of Bird Migration.
National Technical Information Service (NTIS)
Radar has become an important tool for bird migration studies, but estimating bird densities from echo densities on the radar screen has often been difficult if not impossible. The following paper reports on the use of the Weather Bureau's new WSR-57 rada...
S. A. Gauthreaux
Stochastic Modeling of Daily Rainfall for Pricing Weather Derivatives
NASA Astrophysics Data System (ADS)
Weather derivatives are getting to be powerful tools for weather risk hedging. A popular method which draws out valid prices of weather derivatives is a stochastic modeling approach. In the method, expected payoffs of weather derivatives based on stochastic weather models are regarded as their valid prices. Although useful stochastic models of temperature have been shown, stochastic models of daily rainfall are still being developed. Therefore, it is considered that pricing of daily rainfall derivatives is difficult. This paper shows a new stochastic daily rainfall model for pricing daily rainfall options. The new model in which a modified geometric distribution model is applied can express stochastic features of daily rainfall. Furthermore, this paper also shows that the combination model of the Markov chain rainy day model and the new model can express stochastic features and risks of daily rainfall option payoffs.
Kubo, Osamu; Kobayashi, Yasuhiro
Radar rainfall estimation as an optimal prediction problem
NASA Astrophysics Data System (ADS)
A formulation of the radar rainfall estimation problem as optimal statistical prediction of area-averaged rainfall accumulations based on the radar measured reflectivity is presented. Questions of the estimation and validation of such optimal prediction procedures based on large samples of synchronous radar and raingage measurement are analyzed. Our approach accepts the truth that radar cannot mimic the near-point raingage sampling and that proper quantification of the area-point difference is necessary. The questions and consequences which originate from our formulation of the radar rainfall estimation/validation problem are formalized statistically and investigated using both statistical modeling and data analysis. A general definition of the error of the radar rainfall predictions in terms of bivariate probability distributions of the radar and true rainfalls is discussed. The raingage representativeness error structure is analyzed based on the available data. An analytically tractable statistical model of the radar-raingage comparisons is developed. It shows the large impact of the estimation method on the resulting reflectivity-rainrate conversion and the incompleteness of the system due to the radar and raingage errors. These effects prove the need of additional data on the raingage area-point difference structure. Next, an Error Separation Method for the error variance estimation of the radar rainfall predictions is developed. This method is based on additional data on the rainfield small scale correlation structure. Finally, a global optimization approach to the multiparameter radar rainfall prediction is developed. The prediction algorithm is designed to minimize the error variance of the final radar rainfall product. The general radar rainfall estimation/validation methodologies developed here can also be applied to other remote sensing rainfall estimation problems. The work is concluded with a summary discussion of the obtained results and of the research directions that might stem from those results.
Ciach, Grzegorz Jan
Spaceborne Radar Measurements of Rainfall Vertical Velocity
NASA Technical Reports Server (NTRS)
This paper studies the performance of a spaceborne precipitation radar in measuring vertical Doppler velocity of rainfall. As far as a downward pointing precipitation radar is concerned, one of the major problems affecting Doppler measurement at the nadir direction arises from the Non-Uniform Beam-Filling effect (NUBF). That is, when significant variation in rain rate is present within the radar IFOV (Instrument Field of View) in the along track direction. the Doppler shift caused by the radial component of the horizontal speed of the satellite is weighted differently among the portions of IFOV. The effects of this non-uniform weighting may dominate any other contribution. Under this condition, shape, average value and width of the Doppler spectrum may not be directly correlated with the vertical velocity of the precipitating particles. However, by using an inversion technique which over-samples the radar measurements in the along track direction, we show that the shift due to NUBF can be evaluated, and that the NUBF induced errors on average fall speed can be reduced.
Im, Eastwood; Tanelli, Simone; Giuli, Dino; Durden, Stephen L.; Facheris, Luca
High-resolution rainfall estimation for Helsinki urban area using Helsinki radar network
NASA Astrophysics Data System (ADS)
High resolution precipitation data is a crucial factor for hydrological applications in urban areas. Small fluctuations in precipitation fields are of great importance considering the fast response of urban catchments due to the dominance of impervious surfaces. High resolution precipitation observations are needed in order to characterize these fluctuations. Weather radar provides high spatial resolution precipitation estimations. However, the quality of its observations in an urban environment is significantly degraded, among other things, by ground clutter and beam-blockage. A solution for this problem is to use a radar network, where the data gaps of one radar will be filled by using observations from the others. Very few cities have dedicated weather radar networks. In some cities, like Helsinki, there are several weather radars covering the metropolitan area, but they are operated by different organizations. In this study, we show how such systems can be used to build a network and what is the advantage of using radarnetworks for estimating precipitation in urban catchments. The urban Helsinki area is covered by observations from three individual-purpose C-band weather radars (Helsinki University's Kumpula (KUM), Vaisala Oy's Kerava (KER) and Finnish Meteorological Institute's Vantaa (VAN)). We used the data from these radars to form a network and we design a similar task which runs at the same time in each radar couple of times per day. Nonetheless, it is challenging to make them observe at the same area at exactly the same time, which could lead to fast changing, short precipitation events being missed. Hence, synchronization and temporal resolution are the main concerns when building a network. Consequently, to decrease the impact of these restrictions in the Helsinki radar network we propose the use of the optic flow interpolation algorithm to retrieve information in between two radar observations and use the retrieved dataset from the three radars to estimate rainfall. The accuracy of this method is studied by comparing the composite rainfall estimation with both single radar observations and ground measurements.
Rojas, Laura; Nordling, Kalle; Cremonini, Roberto; Moisseev, Dmitri; Chandrasekar, Venkatachalam
Real-time estimation of mean field bias in radar rainfall data
To reduce systematic errors in radar rainfall data used for operational hydrologic forecasting, the precipitation estimation stream in the National Weather Service (NWS) uses procedures that estimate mean field bias in real time. Being a multiplicative correction over a very large area, bias adjustment has a huge impact, particularly on volumetric estimation of rainwater, and hence performance of the procedure
D.-J Seo; J. P Breidenbach; E. R Johnson
Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin
NASA Astrophysics Data System (ADS)
Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.
Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.
Calibrating LAWR weather radar using laser disdrometers
NASA Astrophysics Data System (ADS)
Estimation of the radar reflectivity from Local Area Weather Radars (LAWR) is investigated. Normally, the LAWR system operates with the Dimensionless Radar Output (DRO) instead of dBZ, because the absolute scaling to dBZ is unknown for the LAWR. A transformation methodology is proposed for LAWR DRO-dBZ conversion. The method applies dBZ observations from ground based disdrometers. The paper illustrates the possibility of establishing a direct relationship between the LAWR DRO estimates and the physical radar reflectivity of the precipitation. Also, rain intensity estimate from the LAWR system, by means of the Marshall-Palmer relation, is conducted nonlinearly from the DRO estimate. This diverges from prior investigations and applications of the LAWR system, which typically rely on a linear assumption between the rain intensity and the LAWR DRO.
Nielsen, J. E.; Jensen, N. E.; Rasmussen, M. R.
Automation of Cn2 profile extraction from weather radar images
NASA Astrophysics Data System (ADS)
A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating Cn2 using radar is a complicated and time consuming process. This paper presents a new software program which is being developed to automate the calculation of Cn2 over an arbitrary path. The program takes regional National Weather Service NEXRAD radar reflectivity measurements and extracts data for the path of interest. These reflectivity measurements are then used to estimate Cn2 over the path. The program uses the Radar Software Library (RSL) produced by the Tropical Rainfall Measuring Mission (TRMM) at the NASA/Goddard Flight Center. RSL provides support for nearly all formats of weather radar data. The particular challenge to extracting data is in determining which data bins the path passes through. Due to variations in radar systems and measurement conditions, the RSL produces data grids that are not consistent in geometry or completeness. The Cn2 program adapts to the varying geometries of each radar image. Automation of the process allows for fast estimation of Cn2 and supports a goal of real-time remote turbulence measurement. Recently, this software was used to create comparison data for RF scintillation measurements. In this task it performed well, extracting thousands of measurements in only a few minutes.using radar is a complicated and time consuming process. This paper presents a new software program which is being developed to automate the calculation of Cn2 over an arbitrary path. The program takes regional National Weather Service NEXRAD radar reflectivity measurements and extracts data for the path of interest. These reflectivity measurements are then used to estimate Cn2 over the path. The program uses the Radar Software Library (RSL) produced by the Tropical Rainfall Measuring Mission (TRMM) at the NASA/Goddard Flight Center. RSL provides support for nearly all formats of weather radar data. The particular challenge to extracting data is in determining which data bins the path passes through. Due to variations in radar systems and measurement conditions, the RSL produces data grids that are not consistent in geometry or completeness. The Cn2 program adapts to the varying geometries of each radar image. Automation of the process allows for fast estimation of Cn2 and supports a goal of real-time remote turbulence measurement. Recently, this software was used to create comparison data for RF scintillation measurements. In this task it performed well, extracting thousands of measurements in only a few minutes.
Burchett, Lee R.; Fiorino, Steven T.; Buchanan, Matthew
Empirically-based modeling of radar-rainfall uncertainties
NASA Astrophysics Data System (ADS)
There are large uncertainties associated with radar-based rainfall estimates, including both systematic errors and random effects from numerous sources. Their propagation through all models for which radar-rainfall is used as input or for which is used as an initial condition is necessary to enhance our understanding and interpretation of the obtained results. Despite the relevance of the topic, there is no comprehensive statistical characterization of these errors. The specific goals of this dissertation include: (1) development of an empirically-based radar-rainfall error model; (2) investigation of the sensitivity of the components of the error model to different radar setups, spatial and temporal resolutions, and geographic areas; (3) development of a generator of ensembles of probable true rainfall fields, conditioned on a given radar-rainfall map; (4) application of the error model to: (i) the flash flood forecasting problem; (ii) the evaluation of satellite-based rainfall products; and (iii) the impact of radar-rainfall uncertainties on the scaling properties of rainfall; According to the approach proposed in this study, a realistic parameterization of the relationship between true rainfall and radar-rainfall can be achieved with a model described by two elements: a systematic distortion function and a random component. These two components are identified using a non-parametric approach, and rain gauges are used as an approximation of the true ground rainfall. This model has the flexibility to account for range from the radar, different spatio-temporal scales, rain regime, and space and time dependency of the errors. The results of this study are based on large samples of radar and rain gauge data from Oklahoma, United States, and south-west Great Britain. One of the assumptions in this study is that the true ground areal rainfall can be approximated by rain gauge measurements, introducing sampling discrepancies between a radar pixel and a rain gauge. Therefore, the uncertainties associated with the approximation of an areal estimate with a point measurement (spatial sampling errors) will be investigated for different spatial and temporal scales by means of an empirically-based error model.
Villarini, Gabriele
Rainfall Measurement with a Ground Based Dual Frequency Radar
NASA Technical Reports Server (NTRS)
Dual frequency methods are one of the most useful ways to estimate precise rainfall rates. However, there are some difficulties in applying this method to ground based radars because of the existence of a blind zone and possible error in the radar calibration. Because of these problems, supplemental observations such as rain gauges or satellite link estimates of path integrated attenuation (PIA) are needed. This study shows how to estimate rainfall rate with a ground based dual frequency radar with rain gauge and satellite link data. Applications of this method to stratiform rainfall is also shown. This method is compared with single wavelength method. Data were obtained from a dual frequency (10 GHz and 35 GHz) multiparameter radar radiometer built by the Communications Research Laboratory (CRL), Japan, and located at NASA/GSFC during the spring of 1997. Optical rain gauge (ORG) data and broadcasting satellite signal data near the radar t location were also utilized for the calculation.
Takahashi, Nobuhiro; Horie, Hiroaki; Meneghini, Robert
Analyzing and modeling complex weather radar data with data-driven approaches
NASA Astrophysics Data System (ADS)
In the field of radar hydrology the utilization of data-driven models seems promising because the data volume produced by weather radar networks is considerably large. Reams of gigabytes of data are stored in the archives. However, these complex datasets are not easy to investigate. Data-driven approaches aim to extract and model patterns and regularities that are hidden in the datasets. This study presents data-driven models for three aspects of radar hydrology: data analysis, rainfall-runoff prediction, and radar rainfall estimation. The Principle Component Analysis (PCA) has been used to capture the essence in weather radar measurements and to provide methods for describing patterns in the spatial radar data. For this analysis, volumes that are scanned concurrently by two radar stations of the Austrian weather radar network were used for plausibility reasons. Artificial Neural Networks (ANNs) were applied to predict the runoff of a small Alpine catchment. Several input configurations and network architectures were investigated. The models were trained on various lead times and the ANNs consistently perform better than simpler approaches like Model Trees (MTs) applied on the same dataset. When forecasting three time steps ahead, the ANN model reaches an efficiency coefficient of 97.4 % compared to 90.9 % of the MT. Data-driven models were also used to improve weather radar estimates of rainfall. By means of ANNs the radar reflectivity Z above a rain gauge was mapped to the rain rate R on the ground. The so modeled relationship was tested on a different location. The deviations could be decreased and the correlation coefficient increased compared to applying the standard Z - R relationship. The relative improvements range from 7 to 34 % depending on model and performance measure. The measures are even better than the Z - R relationship retrospectively optimized for this very location.
Teschl, Reinhard; Teschl, Franz; Randeu, Walter L.
Radar subpixel-scale rainfall variability and uncertainty: a lesson learned from observations of a dense rain-gauge network
NASA Astrophysics Data System (ADS)
Hydrological models for runoff estimations and flash-flood predictions are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires improving our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges, containing 27 gauges covering an area of about 4 km2, was installed near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability in remote-sensing at subpixel-scale resolution. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The zero-distance correlation between rain gauges was high (0.92 on the 1-min scale) and increased as the time scale increased. The variance of the differences between radar pixel rainfall and averaged point rainfall (the variance reduction factor - VRF) was 1.6%, as measured for the 1-min scale. It was also found that at least four uniformly distributed rain stations are needed to represent the rainfall on the radar pixel scale. The radar-rain gauge error was mainly derived from radar estimation errors as the gauge sampling error contributed up to 22% to the total error. The radar rainfall estimations improved with increasing time scale and the radar-to-true rainfall ratio decreased with increasing time scale. Rainfall measurements collected with this network of rain gauges in the coming years will be used for further examination of rainfall's spatial and temporal variability.
Peleg, N.; Ben-Asher, M.; Morin, E.
NSDL National Science Digital Library
This middle/junior high school activity asks students to create a physical shoebox model to simulate the tracking of a storm by modern weather radar and to use the model to distinguish between areas of storm intensity and internal air circulation. Computer models from the Internet are available for those wishing to create images of the shoebox model data. The exercise is part of the Atmospheric Visualization Collection (AVC), which focuses on data from the Atmospheric Radiation Measurement (ARM) program.
Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds
NASA Astrophysics Data System (ADS)
Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.
Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea
Modeling of Radar-Rainfall Uncertainties for Hydrologic Applications: Preliminary Results
NASA Astrophysics Data System (ADS)
It is well acknowledged that radar-based estimates of rainfall are affected by several sources of uncertainties (e.g., mis-calibration, beam blockage, anomalous propagation and ground clutter), which are both systematic and random in nature. Improved characterization of these errors would result in our improved understanding and interpretation of the results from those studies in which these estimates are used as input (e.g., hydrologic modeling) or initial condition (e.g., rainfall forecasting). Building on earlier efforts, the authors apply a data-driven multiplicative model, in which the relation between true rainfall and radar rainfall can be described in terms of the product of a systematic and a random component. The systematic components accounts for both unconditional and conditional biases. The conditional bias is parameterized by a power-law function. The random component, which represents the random fluctuations remaining after correcting for systematic uncertainties, is characterized in terms of its probability distribution, and spatial and temporal dependencies. The space-time dependencies are computed using the non-parametric Kendall's tau measure. The authors present a methodology based on dynamic copulas to generate ensembles of random error fields with the prescribed spatial and temporal dependencies. They discuss application of this model to flash flood forecasting. The focus area of this study is Clear Creek, which is a densely instrumented experimental watershed in eastern Iowa Results are based on about three years of radar data from the Davenport Weather Surveillance Radar 88 Doppler (WSR-88D) radar, and processed through the Hydro-NEXRAD system. The spatial and temporal resolutions are 0.5 km and hourly. The radar data are complemented by rainfall measurements from 11 rain gages located within the catchment, which are used as an approximation of the true ground rainfall.
Villarini, G.; Seo, B.; Serinaldi, F.; Krajewski, W. F.
Sensitivity Studies of the Radar-Rainfall Error Models
NASA Astrophysics Data System (ADS)
It is well acknowledged that there are large uncertainties associated with the operational quantitative precipitation estimates produced by the U.S. national network of WSR-88D radars. These errors are due to the measurement principles, parameter estimation, and not fully understood physical processes. Comprehensive quantitative evaluation of these uncertainties is still at an early stage. The authors proposed an empirically-based model in which the relation between true rainfall (RA) and radar-rainfall (RR) could be described as the product of a deterministic distortion function and a random component. However, how different values of the parameters in the radar-rainfall algorithms used to create these products impact the model results still remains an open question. In this study, the authors investigate the effects of different exponents in the Z-R relation (Marshall- Palmer, NEXRAD, and tropical) and of an anomalous propagation (AP) removal algorithm. Additionally, they generalize the model to describe the radar-rainfall uncertainties in the additive form. This approach is fully empirically based and rain gauge estimates are considered as an approximation of the true rainfall. The proposed results are based on a large sample (six years) of data from the Oklahoma City radar (KTLX) and processed through the Hydro-NEXRAD software system. The radar data are complemented with the corresponding rain gauge observations from the Oklahoma Mesonet, and the Agricultural Research Service Micronet.
Villarini, G.; Krajewski, W. F.; Ciach, G. J.
Data processing techniques for airport surveillance radar weather sensing
Discusses data processing techniques that can provide high quality, automated weather information using the FAA's existing Airport Surveillance Radars (ASR-9). The cost of modifying the ASR-9 is significantly less than that for deployment of the dedicated terminal Doppler weather radar. These techniques have been implemented on a prototype ASR-9 weather surveillance processor (WSP) and have been tested operationally at the
Mark E. Weber; Richard L. Delanoy; E. S. Chornoboy
One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...
Terrain and Weather Effects on Doppler Radar Navigation Systems.
National Technical Information Service (NTIS)
The effects of terrain and weather conditions upon airborne doppler radar performance are described. The extensive flight test data compiled by military and commercial users of the doppler radar and theoretical knowledge of propagation and scattering theo...
E. Laskowski
Calibration of Local Area Weather Radar�Identifying significant factors affecting the calibration
NASA Astrophysics Data System (ADS)
A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses on calibration. The data processing for handling the partial beam filling issue was found to be essential to the calibration. LAWR uses a different calibration process compared to conventional weather radars, which use a power-law relationship between reflectivity and rainfall rate. Instead LAWR uses a linear relationship of reflectivity and rainfall rate as result of the log transformation carried out by the logarithmic receiver as opposed to the linear receiver of conventional weather radars. Based on rain gauge data for a five month period from a dense network of nine gauges within a 500 � 500 m area and data from a nearby LAWR, the existing calibration method was tested and two new methods were developed. The three calibration methods were verified with three external gauges placed in different locations. It can be concluded that the LAWR calibration uncertainties can be reduced by 50% in two out of three cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model.
Pedersen, Lisbeth; Jensen, Niels Einar; Madsen, Henrik
Multi-scale evaluation of the IFloodS radar-rainfall products
NASA Astrophysics Data System (ADS)
Rainfall products estimated using ground-based radars are often used as reference to assess capabilities and limitations of using satellite rainfall estimates in hydrologic modeling and prediction. During the spring of 2013, NASA conducted a hydrology-oriented field campaign called Iowa Flood Studies (IFloodS) in the central and northeastern Iowa in the United States, as a part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related rainfall processes and the predictability in flood forecasting. While there are multiple types of rainfall data sets (e.g., satellite, radar, rain gauge, and disdrometer) available as the observational assets of IFloodS, the authors focus on the evaluation of multi-scale rainfall products observed from ground-based radars. The radar-only products used in the evaluation are the NEXRAD single polarization products (i.e., Stage IV, NMQ Q2, and Iowa Flood Center rainfall maps) and products generated using dual-polarization procedures (i.e., the U.S. National Weather Service operational and Colorado State University experimental blended precipitation processing algorithms) with comparable space and time resolution. The NASA NPOL S-band radar products are also evaluated and compared with the aforementioned NEXRAD products. The uncertainty for different temporal and spatial resolution products is characterized using ground reference data of dense rain gauge and disdrometer networks. This multi-scale characterization is required for hydrologic modeling frameworks that assess model predictive abilities as a function of space and time scales.
Seo, Bong-Chul; Krajewski, Witold; Cunha, Luciana; Dolan, Brenda; Smith, James; Rutledge, Steven; Petersen, Walter
Boston Area NEXRAD (Next Generation Weather Radar) Demonstration (BAND).
National Technical Information Service (NTIS)
The Boston Area NEXRAD Demonstration (BAND) was formulated to assess the operational utility of Next Generation Weather Radar (NEXRAD) algorithms and display products in three seasons of New England weather. BAND was a cooperative effort which utilized th...
D. E. Forsyth M. J. Istok T. D. O'Bannon K. M. Glover
Precipitation thresholds and debris flow warning: comparing gauge versus weather radar detection
NASA Astrophysics Data System (ADS)
Methods relying on rainfall thresholds for debris-flow warning have a long tradition in geomorphology. Usually, the precipitation thresholds are developed based on rain gauge and debris flows data. However, it is well known that extreme rainfall sampling errors over rugged topography may lead to biased precipitation thresholds. At least two reasons contribute to such sampling errors: i) the regions of complex topography have low rain gauge densities; ii) orography may enhance intense precipitation at very localized places. We studied six storm events that triggered several debris flows each over the Trentino-Alto Adige Region, in the central Italian Alps, between 2005 and 2010. The region is monitored by i) a rain gauge network with an average density of 1/100 km2 and ii) a C-band radar instrument. Radar data have been accurately corrected for errors due to ground clutter contamination, beam blockages, vertical profile of reflectivity, attenuation and wet radome in order to obtain a high quality set of radar-based rainfall fields. We characterized the variability of each rainfall event using space (horizontal) and time variograms and we investigated the altitude (vertical) distribution of rainfall using hypsometric rainfall moments. We also defined the local severity of the rainfall accumulations over the debris flow areas for different time accumulations. We used the radar precipitation fields to represent space-time rainfall variability and we simulated gauge sampling with a stochastic model accounting for sub-grid variability of precipitation and for gauge measurement errors. We show that rain gauges systematically underestimate the local severity over the proven debris flow triggering locations. This leads to biased precipitation thresholds. In this respect gauge spatial sampling appears inappropriate both in the horizontal and in the vertical dimensions while the usual gauge time sampling looks appropriate. Moreover, this shows the potential of rainfall estimates based on weather radar for debris flows warning.
Marra, Francesco; Borga, Marco; Creutin, Jean-Dominique
Radar Signatures for Severe Convective Weather
NSDL National Science Digital Library
This resource is intended for use as a job aid by operational weather forecasters in live warning situations and as a reference tool to better understand some aspects of severe thunderstorm warning events. Thumbnail images show typical representatives for sixteen radar reflectivity and velocity signatures as well as three primary severe storm types. Each signature links to content describing detection techniques and conceptual and diagnostic information to help determine storm severity. The majority of the examples shown are southern hemisphere storms in Australia; examples from the northern hemisphere are noted.
Guarente, Bryan; Muller, Bruce
Weather radar to prevent air crashes
NASA Astrophysics Data System (ADS)
An operational demonstration of Terminal Doppler Weather Radar (TDWR) at Stapleton International Airport, Denver, finishes August 31. For 2 months, TDWR has been used to detect wind shear and other hazardous weather around air terminals and to provide warnings to air traffic controllers and pilots in time to avert accidents.The biggest hazard for aircraft approaching or departing terminals is the microburst, a form of wind shear. Microbursts are produced by a small-scale, powerful downdraft of cold, heavy air occurring beneath a thunderstorm, rain shower, or cumulus cloud. As the downdraft reaches Earth's surface, it spreads out horizontally (see Figure 1). An aircraft flying through a microburst at low-altitude encounters a strong headwind, then a downdraft, and finally a tailwind that causes a sharp reduction in speed and loss of lift. This deadly sequence of events has caused at least 30 accidents and 500 deaths in the United States since the mid-1960s.
Bush, Susan M.
Radar-based rainfall estimation: Improving Z/R relations through comparison of drop size distributions, rainfall rates and radar reflectivity patterns
NASA Astrophysics Data System (ADS)
The relation between the measured radar reflectivity factor Z and surface rainfall intensity R - the Z/R relation - is profoundly complex, so that in general one speaks about radar-based quantitative precipitation estimation (QPE) rather than exact measurement. Like in Plato's Allegory of the Cave, what we observe in the end is only the 'shadow' of the true rainfall field through a very small backscatter of an electromagnetic signal emitted by the radar, which we hope has been actually reflected by hydrometeors. The meteorological relevant and valuable Information is gained only indirectly by more or less justified assumptions. One of these assumptions concerns the drop size distribution, through which the rain intensity is finally associated with the measured radar reflectivity factor Z. The real drop size distribution is however subject to large spatial and temporal variability, and consequently so is the true Z/R relation. Better knowledge of the true spatio-temporal Z/R structure therefore has the potential to improve radar-based QPE compared to the common practice of applying a single or a few standard Z/R relations. To this end, we use observations from six laser-optic disdrometers, two vertically pointing micro rain radars, 205 rain gauges, one rawindsonde station and two C-band Doppler radars installed or operated in and near the Attert catchment (Luxembourg). The C-band radars and the rawindsonde station are operated by the Belgian and German Weather Services, the rain gauge data was partly provided by the French, Dutch, Belgian, German Weather Services and the Ministry of Agriculture of Luxembourg and the other equipment was installed as part of the interdisciplinary DFG research project CAOS (Catchment as Organized Systems). With the various data sets correlation analyzes were executed. In order to get a notion on the different appearance of the reflectivity patterns in the radar image, first of all various simple distribution indices (for example the Gini index, Rosenbluth index) were calculated and compared to the synoptic situation in general and the atmospheric stability in special. The indices were then related to the drop size distributions and the rain rate. Special emphasis was laid in an objective distinction between stratiform and convective precipitation and hereby altered droplet size distribution, respectively Z/R relationship. In our presentation we will show how convective and stratiform precipitation becomes manifest in the different distribution indices, which in turn are thought to represent different patterns in the radar image. We also present and discuss the correlation between these distribution indices and the evolution of the drop size distribution and the rain rate and compare a dynamically adopted Z/R relation to the standard Marshall-Palmer Z/R relation.
Neuper, Malte; Ehret, Uwe
Spatial and temporal modeling of radar rainfall uncertainties
NASA Astrophysics Data System (ADS)
It is widely acknowledged that radar-based estimates of rainfall are affected by uncertainties (e.g., mis-calibration, beam blockage, anomalous propagation, and ground clutter) which are both systematic and random in nature. Improving the characterization of these errors would yield better understanding and interpretations of results from studies in which these estimates are used as inputs (e.g., hydrologic modeling) or initial conditions (e.g., rainfall forecasting).
Villarini, Gabriele; Seo, Bong-Chul; Serinaldi, Francesco; Krajewski, Witold F.
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Propagation of radar rainfall uncertainty in urban flood simulations
NASA Astrophysics Data System (ADS)
This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimate
Liguori, Sara; Rico-Ramirez, Miguel
Phased Array Radar Polarimetry for Weather Sensing: Challenges and Opportunities
It is becoming widely accepted that radar polarimetry provides accurate and informative weather measurements, while phased array technology can shorten data updating time. In this paper, a theory of phased array radar polarimetry is developed, and the relationship between the wave field at the radar antenna coordinate and that at the hydrometeors is established, along with the correction matrix to
Guifu Zhang; Richard Doviak; Dusan Zrnic; Jerry Crain
Simulation of Radar Rainfall Fields: A Random Error Model
NASA Astrophysics Data System (ADS)
Precipitation is a major input in hydrological and meteorological models. It is believed that uncertainties due to input data will propagate in modeling hydrologic processes. Stochastically generated rainfall data are used as input to hydrological and meteorological models to assess model uncertainties and climate variability in water resources systems. The superposition of random errors of different sources is one of the main factors in uncertainty of radar estimates. One way to express these uncertainties is to stochastically generate random error fields to impose them on radar measurements in order to obtain an ensemble of radar rainfall estimates. In the method introduced here, the random error consists of two components: purely random error and dependent error on the indicator variable. Model parameters of the error model are estimated using a heteroscedastic maximum likelihood model in order to account for variance heterogeneity in radar rainfall error estimates. When reflectivity values are considered, the exponent and multiplicative factor of the Z-R relationship are estimated simultaneously with the model parameters. The presented model performs better compared to the previous approaches that generally result in unaccounted heteroscedasticity in error fields and thus radar ensemble.
Aghakouchak, A.; Habib, E.; Bardossy, A.
Comparison of rainfall profiles retrieved from dual-frequency radar and from combined radar and passive microwave radiometric measurements
NASA Technical Reports Server (NTRS)
Precipitation profiles retrieved from a dual frequency X- and Ka-band radar and from an X-band radiometer are analyzed. Profiles from combined radar and microwave radiometer measurements are compared to those from dual frequency radar measurements to study the performance of the combined radar-radiometer retrievals. A method for the retrieval of rainfall rate profiles from attenuated radar returns and passive radiometric data is presented. The results suggest that the operation of a single frequency radar with multifrequency passive radiometers may provide cost-effective spaceborne measurements of global tropical rainfall distributions. The possible use of this methodology for the Tropical Rainfall Measuring Mission is considered.
Weinman, J. A.; Meneghini, R.; Nakamura, K.
Simulation of radar reflectivity and surface measurements of rainfall
NASA Technical Reports Server (NTRS)
Raindrop size distributions (RSDs) are often estimated using surface raindrop sampling devices (e.g., disdrometers) or optical array (2D-PMS) probes. A number of authors have used these measured distributions to compute certain higher-order RSD moments that correspond to radar reflectivity, attenuation, optical extinction, etc. Scatter plots of these RSD moments versus disdrometer-measured rainrates are then used to deduce physical relationships between radar reflectivity, attenuation, etc., which are measured by independent instruments (e.g., radar), and rainrate. In this paper RSDs of the gamma form as well as radar reflectivity (via time series simulation) are simulated to study the correlation structure of radar estimates versus rainrate as opposed to RSD moment estimates versus rainrate. The parameters N0, D0 and m of a gamma distribution are varied over the range normally found in rainfall, as well as varying the device sampling volume. The simulations are used to explain some possible features related to discrepancies which can arise when radar rainfall measurements are compared with surface or aircraft-based sampling devices.
Chandrasekar, V.; Bringi, V. N.
Simulation of a weather radar display for over-water airborne radar approaches
NASA Technical Reports Server (NTRS)
Airborne radar approach (ARA) concepts are being investigated as a part of NASA's Rotorcraft All-Weather Operations Research Program on advanced guidance and navigation methods. This research is being conducted using both piloted simulations and flight test evaluations. For the piloted simulations, a mathematical model of the airborne radar was developed for over-water ARAs to offshore platforms. This simulated flight scenario requires radar simulation of point targets, such as oil rigs and ships, distributed sea clutter, and transponder beacon replies. Radar theory, weather radar characteristics, and empirical data derived from in-flight radar photographs are combined to model a civil weather/mapping radar typical of those used in offshore rotorcraft operations. The resulting radar simulation is realistic and provides the needed simulation capability for ongoing ARA research.
Clary, G. R.
Correlation of S-Band Weather Radar Reflectivity and ACTS Propagation Data in Florida
NASA Technical Reports Server (NTRS)
Previous work has shown that Ka-band attenuation due to rainfall and corresponding S-band reflectivity are highly correlated. This paper reports on work whose goal is to determine the feasibility of estimation and, by extension, prediction of one parameter from the other using the Florida ACTS propagation terminal (APT) and the nearby WSR-88D S-band Doppler weather radar facility operated by the National Weather Service. This work is distinguished from previous efforts in this area by (1) the use of a single-polarized radar, preventing estimation of the drop size distribution (e.g., with dual polarization) and (2) the fact that the radar and APT sites are not co-located. Our approach consists of locating the radar volume elements along the satellite slant path and then, from measured reflectivity, estimating the specific attenuation for each associated path segment. The sum of these contributions yields an estimation of the millimeter-wave attenuation on the space-ground link. Seven days of data from both systems are analyzed using this procedure. The results indicate that definite correlation of S-band reflectivity and Ka-band attenuation exists even under the restriciton of this experiment. Based on these results, it appears possible to estimate Ka-band attenuation using widely available operational weather radar data. Conversely, it may be possible to augment current radar reflectivity data and coverage with low-cost attenuation or sky temperature data to improve the estimation of rain rates.
Wolfe, Eric E.; Flikkema, Paul G.; Henning, Rudolf E.
Effect of radar-rainfall uncertainties on the spatial characterization of rainfall events
NASA Astrophysics Data System (ADS)
Remotely sensed precipitation products, due to their large areal coverage and high resolution, have been widely used to provide information on the spatiotemporal structure of rainfall. However, it is well known that these precipitation products also suffer from large uncertainties that originate from various sources. In this study, we selected radar-rainfall (RR) data corresponding to 10 warm season events over a 256 � 256 km2 domain with a data resolution of 4 � 4 km2 in space and 1 h in time. We characterized their spatial structure using correlation function, power spectrum, and moment scaling function. We then employed a recently developed RR error model and rainfall generator to obtain an ensemble of probable rainfall fields that are consistent with the RR estimation error structure. We parameterized the spatial correlation functions with a two-parameter power exponential function, the Fourier spectra with a power law function, and the moment scaling functions with the universal multifractal model. The parameters estimated from the ensemble were compared with those obtained from the RR products to quantify the impact of radar-rainfall estimation errors on the spatial characterization of rainfall events. From the spatial correlation and power spectrum analyses, we observed that RR estimation uncertainties introduce spurious correlations with greater impact for the smaller scales. The RR errors also significantly bias the estimation of the moment scaling functions.
Mandapaka, Pradeep V.; Villarini, Gabriele; Seo, Bong-Chul; Krajewski, Witold F.
Experimental calibration of a cost-effective X-band weather radar for climate ecological studies in southern Ecuador
NASA Astrophysics Data System (ADS)
In this paper setup, operational problems and a straightforward calibration approach for a cost-effective X-Band radar are presented. The LAWR (Local Area Weather Radar) system is based on conventional ship radar technology which is adapted to register rainfall within a range of about 60 km with a spatial resolution of 500 m per pixel. The instrument offers neither Doppler processing nor vertical scan capabilities but uses 20� wide (vertical) beam. The calibration suffers from an unfavorably distributed and very sparse rain gauge network, heavy clutter contamination of the signal and obstructions by surrounding terrain. A specific scaling approach is developed, that includes satellite data on cloud frequency and distribution, to overcome these limitations. Observed clutter is removed and missing values are replaced by bilinear interpolation of the undisturbed signals. A temporal and spatial bias of the radar signal is corrected using an omni-directional spatial distribution hypothesis. This is possible because of the location of the radar site in the transition zone between high rainfall on the eastern Andean slopes and low rainfall on the leeward side. A further limitation of the system is that the LAWR does not provide information on the measured reflectivity Z but dimensionless counts (8 bit resolution). Calibration is performed assuming a linear relation between radar output and rainfall as recommended by the systems manufacturer. The intercomparison of rain gauge and scatterometer data with calibrated radar rainfall reveals a good performance of the developed calibration approach.
Rollenbeck, R�tger; Bendix, J�rg
Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network
NASA Astrophysics Data System (ADS)
Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.
Peleg, N.; Ben-Asher, M.; Morin, E.
A feasibility study of rain radar for the Tropical Rainfall Measuring Mission. VI - A case study of rain radar system
NASA Astrophysics Data System (ADS)
A case study of the rain radar system for the Tropical Rainfall Measuring Mission has been conducted, considering pulse compression radar versus conventional type radar, active array radar with solid state power amplifiers versus passive array radar with TWTA, and various antenna types. The characteristic parameters, power consumptions, weights, and sizes of six different cases are presented. It is found that the most suitable candidate for the mission is the nonpulse compression active array radar with planar array.
Okamoto, Ken'ichi; Awaka, Jun; Kozu, Toshiaki
Resolving Interference from an Airport Surveillance Radar to a Weather Radar.
National Technical Information Service (NTIS)
In response to interference from an S-band (2700-2900 MHz) airport surveillance radar (ASR) to a meteorological (weather) radar in the same band, measurements were performed at the field location of the two radars to determine the interference mechanism a...
F. H. Sanders J. R. Hoffman Y. Lo
Transforming Nexrad Radar Rainfall Maps to Flood Inundation Maps
The Arc Hydro geographic data model for representing water resources features of the landscape is a customization of ArcGIS for representation of water resources features of the landscape. Arc Hydro is used here to integrate the HEC-HMS and HEC-RAS flood simulation models so as to transform Nexrad radar rainfall data into flood inundation maps through the HEC models. An automated
D. R. Maidment; O. Robayo
Principles of weather radar network design at attenuating frequencies
The Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is investigating the use of dense networks of short-range radars for weather sensing. A first test-bed of this new paradigm is currently deployed in southwest Oklahoma. The potential benefits of closely deployed, overlapping, short-range weather radars are easy to see intuitively, amounting to a greater ability to measure
F. Junyent; S. Lim; V. Chandrasekar
Evaluation of Various Radar Data Quality Control Algorithms Based on Accumulated Radar Rainfall Statistics
NASA Technical Reports Server (NTRS)
The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.
Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)
Probabilistic online runoff forecasting for urban catchments using inputs from rain gauges as well as statically and dynamically adjusted weather radar
NASA Astrophysics Data System (ADS)
We investigate the application of rainfall observations and forecasts from rain gauges and weather radar as input to operational urban runoff forecasting models. We apply lumped rainfall runoff models implemented in a stochastic grey-box modelling framework. Different model structures are considered that account for the spatial distribution of rainfall in different degrees of detail. Considering two urban example catchments, we show that statically adjusted radar rainfall input improves the quality of probabilistic runoff forecasts as compared to input based on rain gauge observations, although the characteristics of these radar measurements are rather different from those on the ground. Data driven runoff forecasting models can to some extent adapt to bias of the rainfall input by model parameter calibration and state-updating. More detailed structures in these models provide improved runoff forecasts compared to the structures considering mean areal rainfall only. A time-dynamic adjustment of the radar data to rain gauge data provides improved rainfall forecasts when compared with rainfall observations on the ground. However, dynamic adjustment reduces the potential for creating runoff forecasts and in fact also leads to reduced cross correlation between radar rainfall and runoff measurements. We conclude that evaluating the performance of radar rainfall adjustment against rain gauges may not always be adequate and that adjustment procedure and online runoff forecasting should ideally be considered as one unit.
L�we, Roland; Thorndahl, S�ren; Mikkelsen, Peter Steen; Rasmussen, Michael R.; Madsen, Henrik
Real-time rainfall forecasting using weather satellite imagery
NASA Astrophysics Data System (ADS)
Taiwan locates at the center of the western Pacific Rim and is particularly vulnerable to threat by typhoons. In average, there are 3.5 typhoons pass through Taiwan annually. Typhoons often draw huge amount and high intensity rainfalls, resulting in high casualties and severe property damages. For example, during the passage of Typhoon Nari in September 2002, more than 700mm rainfall was recorded near the capital city Taipei, causing extensive inundation and tremendous property damages in the city. Recent events and studies indicate that accurate real-time rainfall forecasting is crucial for flood forecasting since most watersheds in Taiwan have short time-of-concentrations (Tc). In this study we propose a real-time rainfall forecasting approach using GMS weather satellite imagery. The approach composes a multi-spectral spatial convolution (MSSC) scheme that yields a 3-hour lead rainfall forecast and a Kalman filtering algorithm for real-time parameter update. Using a single GMS thermal infrared band, the spatial convolution scheme can be expressed by the following equation: [ R(x,y)=sumlimits{x'=x-?}x+? {sumlimits{y'=y-?}y+? {T({x}',{y}')f(x-{x}',y-{y}')} } =sumlimitsi=1^N {T(i;x,y)f(i;x,y)} ] where R(x,y), T(x,y) and f(x,y) represent rainfall, cloud-top- temperature and kernel function weight at location (x, y). The spatial convolution is carried out within a(2?-1)� (2?-1) moving window. Using rainfall measurements of a network of 37 raingauge stations within the study area and cloud-top-temperatures derived from GMS images, the kernel function weights can be solved by a least square estimator: [ {R(1)} {R(2)} ?ots {R(n)} ]=[ {T(1,1)} & {T(1,2)} & \\cdots & {T(1,N)} {T(2,1)} & {T(2,2)} & \\cdots & {T(2,N)} ?ots & ?ots & ddots & ?ots {T(n,1)} & {T(n,2)} & \\cdots & {T(n,N)} ] [ {f(1)} {f(2)} ?ots {f(N)} ] where N is the total number of pixels in the moving window and n is the number of raingauge stations. The above equation can also be expressed as R=T\\cdot F, and the least square estimator of the kernel function is TRIAL RESTRICTION. In order to yield rainfall forecast, 3-hour lead accumulative rainfalls are used in the above equation. A multiple bands version of the above matrix equation is also developed using three thermal IR bands of the GMS satellite. During a typhoon event the kernel function may change with time and Kalman filtering is implemented using kernel function weight TRIAL RESTRICTION as the state vector. Results of a cross validation scheme reveal that the correlation between rainfall measurements and real-time forecasted rainfalls by spatial convolution and Kalman filtering ranging from 0.74 to 0.93 in most raingauges, indicating a great potential of real-time rainfall forecasting using weather satellite imagery.
Cheng, K. S.; Wei, C.
ASR(Airport Surveillance Radar)-9 Weather Channel Test Report.
National Technical Information Service (NTIS)
The ASR-9, the next generation airport surveillance radar, will be deployed by the FAA at over 100 locations throughout the U.S.. The system includes a weather channel designed to provide ATC personnel with timely and accurate weather reflectivity informa...
D. C. Puzzo S. W. Troxel M. A. Meister M. E. Weber J. V. Pieronek
The Nation's weather services and the wind energy industry share common goals of enhancing the Nation's economy and quality of life for its citizens. Unfortunately, we have observed that sometimes the best locations for developing a wind energy project are near established weather radar sites, since both usually desire optimal siting on high, unobstructed terrain. In recent years, NEXRAD system
Ron Guenther
Phase noise effects on turbulent weather radar spectrum parameter estimation
NASA Technical Reports Server (NTRS)
Accurate weather spectrum moment estimation is important in the use of weather radar for hazardous windshear detection. The effect of the stable local oscillator (STALO) instability (jitter) on the spectrum moment estimation algorithm is investigated. Uncertainty in the stable local oscillator will affect both the transmitted signal and the received signal since the STALO provides transmitted and reference carriers. The proposed approach models STALO phase jitter as it affects the complex autocorrelation of the radar return. The results can therefore by interpreted in terms of any source of system phase jitter for which the model is appropriate and, in particular, may be considered as a cumulative effect of all radar system sources.
Lee, Jonggil; Baxa, Ernest G., Jr.
A multisource scheme based on NWP and MSG data to correct non-precipitating weather radar echoes
NASA Astrophysics Data System (ADS)
Weather radar quantitative precipitation estimates (QPE) are one of the usual tools to monitor rainfall intensity remotely by forecasters on duty or by automatic systems such as hydrological models. Derivation of radar QPE requires a set of robust quality control procedures to address a number of different factors. In particular, significant departures from the standard temperature and moisture atmospheric vertical profiles may increase dramatically the refraction of the radar beam. This anomalous propagation (AP or anaprop) of the microwave radar energy may therefore increase the number of spurious echoes due to ground clutter and contribute, with non-realistic rainfall, to the estimated precipitation field. Based on previous experience of geostationary satellite imagery usage to depict cloud-free areas in precipitation analysis systems, a methodology to incorporate Meteosat Second Generation (MSG) observations and NWP data in the quality control of weather radar QPE was implemented considering two different algorithms. They were validated with two different verification data sets, built with manually edited radar data and rain gauge observations using HKS, PC and FAR scores. The evaluation of the scores was performed for weak (<15 dBZ), stronger and all echoes and for day, night and day and night conditions. One of the methods dealing with weak echoes at night improved PC from 80 to 97% and decreased FAR from 0.32 to 0.19. The results obtained indicate that the technique shows potential for operational application complementing other existing methodologies designed to improve the quality of weather radar precipitation estimates.
Magaldi, Adolfo Vicente; Bech, Joan; Lorente, Jer�nimo
Quantitative precipitation estimation for an X-band weather radar network
NASA Astrophysics Data System (ADS)
Currently, the Next Generation (NEXRAD) radar network, a joint effort of the U.S. Department of Commerce (DOC), Defense (DOD), and Transportation (DOT), provides radar data with updates every five-six minutes across the United States. This network consists of about 160 S-band (2.7 to 3.0 GHz) radar sites. At the maximum NEXRAD range of 230 km, the 0.5 degree radar beam is about 5.4 km above ground level (AGL) because of the effect of earth curvature. Consequently, much of the lower atmosphere (1-3 km AGL) cannot be observed by the NEXRAD. To overcome the fundamental coverage limitations of today's weather surveillance radars, and improve the spatial and temporal resolution issues, the National Science Foundation Engineering Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) was founded to revolutionize weather sensing in the lower atmosphere by deploying a dense network of shorter-range, low-power X-band dual-polarization radars. The distributed CASA radars are operating collaboratively to adapt the changing atmospheric conditions. Accomplishments and breakthroughs after five years operation have demonstrated the success of CASA program. Accurate radar quantitative precipitation estimation (QPE) has been pursued since the beginning of weather radar. For certain disaster prevention applications such as flash flood and landslide forecasting, the rain rate must however be measured at a high spatial and temporal resolution. To this end, high-resolution radar QPE is one of the major research activities conducted by the CASA community. A radar specific differential propagation phase (Kdp)-based QPE methodology has been developed in CASA. Unlike the rainfall estimation based on the power terms such as radar reflectivity (Z) and differential reflectivity (Zdr), Kdp-based QPE is less sensitive to the path attenuation, drop size distribution (DSD), and radar calibration errors. The CASA Kdp-based QPE system is also immune to the partial beam blockage and hail contamination. The performance of the CASA QPE system is validated and evaluated by using rain gauges. In CASA's Integrated Project 1 (IP1) test bed in Southwestern Oklahoma, a network of 20 rainfall gauges is used for cross-comparison. 40 rainfall cases, including severe, multicellular thunderstorms, squall lines and widespread stratiform rain, that happened during years 2007 - 2011, are used for validation and evaluation purpose. The performance scores illustrate that the CASA QPE system is a great improvement compared to the current state-of-the-art. In addition, the high-resolution CASA QPE products such as instantaneous rainfall rate map and hourly rainfall amount measurements can serve as a reliable input for various distributed hydrological models. The CASA QPE system can save lived and properties from hazardous flash floods by incorporating hydraulic and hydrologic models for flood monitoring and warning.
Chen, Haonan
Close-range radar rainfall estimation and error analysis
NASA Astrophysics Data System (ADS)
It is well-known that quantitative precipitation estimation (QPE) is affected by many sources of error. The most important of these are 1) radar calibration, 2) wet radome attenuation, 3) rain attenuation, 4) vertical profile of reflectivity, 5) variations in drop size distribution, and 6) sampling effects. The study presented here is an attempt to separate and quantify these sources of error. For this purpose, QPE is performed very close to the radar (~1-2 km) so that 3), 4), and 6) will only play a minor role. Error source 5) can be corrected for because of the availability of two disdrometers (instruments that measure the drop size distribution). A 3-day rainfall event (25-27 August 2010) that produced more than 50 mm in De Bilt, The Netherlands is analyzed. Radar, rain gauge, and disdrometer data from De Bilt are used for this. It is clear from the analyses that without any corrections, the radar severely underestimates the total rain amount (only 25 mm). To investigate the effect of wet radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation up to ~4 dB. The calibration of the radar is checked by looking at received power from the sun. This turns out to cause another 1 dB of underestimation. The effect of variability of drop size distributions is shown to cause further underestimation. Correcting for all of these effects yields a good match between radar QPE and gauge measurements.
van de Beek, C. Z.; Leijnse, H.; Hazenberg, P.; Uijlenhoet, R.
Transforming Nexrad Radar Rainfall Maps to Flood Inundation Maps
NASA Astrophysics Data System (ADS)
The Arc Hydro geographic data model for representing water resources features of the landscape is a customization of ArcGIS for representation of water resources features of the landscape. Arc Hydro is used here to integrate the HEC-HMS and HEC-RAS flood simulation models so as to transform Nexrad radar rainfall data into flood inundation maps through the HEC models. An automated workflow sequence is established using Map2Map: an ArcGIS version 9 toolbox and Model Builder that accomplishes all the desired data transformations between the GIS and the two hydrologic models including time series data exchange for rainfall, flows and water surface elevations. An example application is presented for Salado and Rosillo Creeks in San Antonio.
Maidment, D. R.; Robayo, O.
The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys
NASA Technical Reports Server (NTRS)
This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.
Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.
New Approaches to Rainfall and Flood Frequency Analysis Using High Resolution Radar Rainfall Fields and Stochastic Storm Transposition
NASA Astrophysics Data System (ADS)
Conventional techniques for rainfall and flood frequency analysis in small watersheds involve a variety of assumptions regarding the spatial and temporal structure of extreme rainfall systems as well as how resulting runoff moves through the drainage network. These techniques were developed at a time when observational and computational resources were limited. They continue to be used in practice though their validity has not been fully examined. New observational and computational resources such as high-resolution radar rainfall estimates and distributed hydrologic models allow us to examine these assumptions and to develop alternative methods for estimating flood risk. We have developed a high-resolution (1 square km, 15-minute resolution) radar rainfall dataset for the 2001-2010 period using the Hydro-NEXRAD processing system, which has been bias corrected using a dense network of 71 rain gages in the Charlotte metropolitan area. The accuracy of the bias-corrected radar rainfall estimates compare favorably with rain gage measurements. The radar rainfall dataset is used in a stochastic storm transposition framework to estimate the frequency of extreme rainfall for urban watersheds ranging the point/radar pixel scale up to 240 square km, and can be combined with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to estimate flood frequency analysis. The results of these frequency analyses can be compared against the results of conventional methods such as the NOAA Atlas 14 precipitation frequency estimates and peak discharge estimates prepared by FEMA and the North Carolina state government.
Wright, D. B.; Smith, J. A.; Villarini, G.; Baeck, M. L.
Networked weather radar system using coherent on receive technology
NASA Astrophysics Data System (ADS)
The Engineering Research Center for Collaborative Adapting Sensing of the Atmosphere (CASA) was established to improve the coverage of the lowest portion of the atmosphere through coordinated scanning of low-power, short-range, networked radars (referred to as Distributed Collaborative Adaptive Sensing (DCAS)). The first DCAS technology demonstration test-bed has been deployed in south-west Oklahoma in early 2006: a network of four, low-power, short-range, dual polarization, Doppler radar units, referred to as IPI (after CASA's Integrated Project 1). This dissertation is devoted to documenting the IP1 system. Special emphasis is placed on the aspects that enable coordinated radar operation and on other features that provide substantial improvements over existing approaches. In particular, the IP1 radar network can sample the atmosphere with high spatio-temporal resolution and at low altitudes. The dual polarization capabilities and simultaneous multiple radar observations of weather phenomena enable the retrieval of enhanced data products including attenuation corrected reflectivity, dual polarization parameters, and vector wind fields. In addition, the modular radar control, data processing, and communications software architecture allows variations in the network topology, control, and weather information extraction, making the extension of the network easy through the addition of potentially heterogeneous radar nodes.
Junyent, Francesc
Estimating subcatchment runoff coefficients using weather radar and a downstream runoff sensor.
This paper presents a method for estimating runoff coefficients of urban drainage subcatchments based on a combination of high resolution weather radar data and flow measurements from a downstream runoff sensor. By utilising the spatial variability of the precipitation it is possible to estimate the runoff coefficients of the separate subcatchments. The method is demonstrated through a case study of an urban drainage catchment (678 ha) located in the city of Aarhus, Denmark. The study has proven that it is possible to use corresponding measurements of the relative rainfall distribution over the catchment and downstream runoff measurements to identify the runoff coefficients at subcatchment level. PMID:24056426
Ahm, Malte; Thorndahl, S�ren; Rasmussen, Michael R; Bass�, Lene
Terminal Doppler Weather Radar (TDWR) Moving Target Simulator (MTS) at Orlando, Florida.
National Technical Information Service (NTIS)
Monitoring the performance of Doppler weather radars presents special problems since target returns cannot be verified by reference to other systems (e,g ., as ASR-9 aircraft reports can be compared with beacon replies). The Terminal Doppler Weather Radar...
W. H. Drury J. M. Frankovich
Towards a better representation of radar-rainfall: Filling gaps in understanding uncertainties
NASA Astrophysics Data System (ADS)
Radar-rainfall uncertainty quantification has been recognized as an intricate problem due to the complexity of the multi-dimensional error structure, which is also associated with space and time scale. The error structure is usually characterized by two moments of the error distribution: bias and error variance. Despite numerous efforts to investigate radar-rainfall uncertainties, many questions remain unanswered. This dissertation uses two statistical descriptions (mean and variance) of the error distribution to highlight and describe some of the remaining gaps in representing radar-rainfall uncertainties. The four central issues addressed in this dissertation include: 1. Investigation of radar relative bias caused by radar calibration. 2. Statistical modeling of range-dependent error arising from the radar beam geometry structure. 3. Scale-dependent variability of radar-rainfall and rain gauge error covariance. 4. Scale-dependence of radar-rainfall error variance. The first two issues describe systematic features of main error sources of radar-rainfall. The other two are associated with quantifying radar error variance using the error variance separation (EVS) method, which considers the spatial sampling mismatch between radar and rain gauge data. This study captures the main systematic features (systematic bias arising from radar calibration and range-dependent errors) of radar measurements without using ground reference data and the error variance structure with respect to the spatio-temporal transformation of the measurements for further applications to hydrologic fields. Such consideration of radar-rainfall uncertainties represented by error mean and variance can enhance the characterization of the uncertainty structure and yield a better understanding of the physical process of precipitation.
Seo, Bong Chul
During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.
Chiswell, S.; Buckley, R.
Adjusting weather radar data to rain gauge measurements with data-driven models
NASA Astrophysics Data System (ADS)
Weather radar networks provide data with good spatial coverage and temporal resolution. Hence they are able to describe the variability of precipitation. Typical radar stations determine the rain rate for every square kilometre and make a full volume scan within about 5 minutes. A weakness however, is their often poor metering precision limiting the applicability of the radar for hydrological purposes. In contrast to rain gauges, which measure precipitation directly on the ground, the radar determines the reflectivity aloft and remote. Due to this principle, several sources of possible errors occur. Therefore improving the radar estimates of rainfall is still a vital topic in radar meteorology and hydrology. This paper presents data-driven approaches to improve radar estimates of rainfall by mapping radar reflectivity measurements Z to rain gauge data R. The analysis encompasses several input configurations and data-driven models. Reflectivity measurements at a constant altitude and the vertical profiles of reflectivity above a rain gauge are used as input parameters. The applied models are Artificial Neural Network (ANN), Model Tree (MT), and IBk a k-nearest-neighbour classifier. The relationship found between the data of a rain gauge and the reflectivity measurements is subsequently applied to another site with comparable terrain. Based on this independent dataset the performance of the data-driven models in the various input configurations is evaluated. For this study, rain gauge and radar data from the province of Styria, Austria, were available. The data sets extend over a two-year period (2001 and 2002). The available rain gauges use the tipping bucket principle with a resolution of 0.1 mm. Reflectivity measurements are obtained from the Doppler weather radar station on Mt. Zirbitzkogel (by courtesy of AustroControl GmbH). The designated radar is a high-resolution C-band weather-radar situated at an altitude of 2372 m above mean sea level. The data-driven models exhibit different performances on the various input configurations. Also data transformations were applied. The logarithm recommends itself for this transformation because the original Z-R-relationship is a power function, and the logarithm linearises this non-linear relationship. The MT which is a piecewise linear model performs best on logarithmised data. The IBk works well when transforming the reflectivity data in rain rate first. Overall the ANN exhibits the best performance showing a 10 % improvement in correlation and RMSE compared to the standard Z-R-relationship. When applying the vertical profile of reflectivity as input parameter, the correlation exhibits a more than 30 % improvement. The results indicate that the vertical profile of reflectivity provided by weather radars yields not only information on the type of precipitation, whether it is stratiform or convective. In data-driven models the vertical profile of reflectivity can help to get better estimates of rain rates on the ground, even in mountainous terrain without low-altitude radar measurements.
Teschl, Reinhard; Randeu, Walter; Teschl, Franz
Weather Radars and Lidar for Observing the Atmosphere
NASA Astrophysics Data System (ADS)
The Earth Observing Laboratory (EOL) at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado develops and deploys state-of-the-art ground-based radar, airborne radar and lidar instruments to advance scientific understanding of the earth system. The ground-based radar (S-Pol) is equipped with dual-wavelength capability (S-band and Ka-band). S-Pol is the only transportable radar in the world. In order to capture faster moving weather events such as tornadoes and record observations of clouds over rugged mountainous terrain and ocean, an airborne radar (ELDORA) is used. It is the only airborne Doppler meteorological radar that is able to detect motions in the clear air. The EOL is in the process of building the first phase of a three phase dual wavelength W/Ka-band airborne cloud radar to be called the HIAPER Cloud Radar (HCR). This phase is a pod based W-band radar system with scanning capability. The second phase will add pulse compression and polarimetric capability to the W-band system, while the third phase will add complementary Ka-band radar. The pod-based radar is primarily designed to fly on the Gulfstream V (GV) and C-130 aircraft. The envisioned capability of a millimeter wave radar system on GV is enhanced by coordination with microwave radiometer, in situ probes, and especially by the NCAR GV High-Spectral Resolution Lidar (HSRL) which is also under construction. The presentation will describe the capabilities of current instruments and also planned instrumentation development.
(Vivek) Vivekanandan, J.
Doppler weather radar as a meteorite recovery tool
NASA Astrophysics Data System (ADS)
We report the use of Doppler weather radar as a tool for locating meteorites, both at the time of a fall and from archived radar data. This asset is especially useful for meteorite recovery as it can provide information on the whereabouts of falling meteorites in "dark flight" portion of their descent where information on their flight paths cannot be discerned from more traditional meteorite location techniques such as eyewitness accounts. Weather radar data can provide information from detection in three distinct regimes: (A) direct detection of the rapidly moving, optically bright fireball by distant radars, (B) detection of falling debris to include hand-sample sized rocks, and (C) detection of dust produced by detonation events that can occur tens of minutes and many kilometers laterally removed from the actual fireball locality. We present examples of each, as well as comparisons against man-made debris from a re-entering Soyuz rocket and the Stardust Sample Return Capsule. The use of Doppler weather radar as a supplement to traditional meteorite recovery methods holds the promise of improving both the speed and total number of meteorite recoveries, thereby increasing the number of freshly fallen meteorites for scientific study.
Fries, Marc; Fries, Jeffrey
Use of radar and automatic weather stations in avalanche forecasting
The following sources of information have been investigated and their data evaluated in order to issue avalanche warnings in case of catastrophic situations such as in February 1984 in the Swiss Alps: -Daily measurement of snow depth -Data of automatic weather stations. They transmit every 10 minutes precipitation, wind, temperature etc. -Images of 2 radars. Every 10 minutes the user
Doppler weather radar with predictive wind shear detection capabilities
NASA Technical Reports Server (NTRS)
The status of Bendix research on Doppler weather radar with predictive wind shear detection capability is given in viewgraph form. Information is given on the RDR-4A, a fully coherent, solid state transmitter having Doppler turbulence capability. Frequency generation data, plans, modifications, system characteristics and certification requirements are covered.
Kuntman, Daryal
Signal analysis and modeling of wind turbine clutter in weather radars
Lately, the continuing expansion of wind energy industry has led to the installation of several wind farms which are often in the vicinity of the weather radars. This is a source of growing concern for the weather radar community since wind turbines interfere with the normal operation of the weather radars. The wind turbine tower can drive the receivers into
Kumar Vijay Mishra; V. Chandrasekar
GNU Radio based software-defined FMCW radar for weather surveillance application
In this paper, a GNU Radio based software-defined FMCW (Frequency Modulated � Continuous Wave) radar is studied for weather surveillance application. The FMCW radar that has been gaining popularity due to the use of solid state microwave amplifier to generate a signal source is proposed for the design since the current weather surveillance radar is usually using a pulse-radar type
Aditya Prabaswara; Achmad Munir; Andriyan Bayu Suksmono
Verification of TMI-Adjusted Rainfall Analyses of Tropical Cyclones at ECMWF Using TRMM Precipitation Radar.
NASA Astrophysics Data System (ADS)
A validation of passive microwave adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates.
Benedetti, A.; Lopez, P.; Moreau, E.; Bauer, P.; Venugopal, V.
An ERS-1 synthetic aperture radar image of a tropical squall line compared with weather radar data
A radar image acquired by the C-band synthetic aperture radar (SAR) aboard the European Remote Sensing satellite ERS-2 over the coastal waters south of Singapore showing radar signatures of a strong tropical squall line (�Sumatra Squall�) is compared with coincident and collocated weather radar data. Squall line features such as the gust front, areas of updraft convergence, and rain areas
I.-I. Lin; W. Alpers; V. Khoo; H. Lim; T. K. Lim; D. Kasilingam
Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar
NASA Astrophysics Data System (ADS)
This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.
Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.
Hydroclimatologic Analyses of Extreme Rainfall and Flooding in Atlanta, Georgia Using Long-Term Radar-Rainfall Datasets
NASA Astrophysics Data System (ADS)
A 10-year radar rainfall dataset is being developed for the Atlanta, Georgia metropolitan area using the Hydro-NEXRAD algorithms. Radar rainfall fields are constructed at 15 minute time resolution and 1 km spatial resolution; observations from a dense network of rain gages are used for multiplicative bias correction. The high-resolution dataset will permit the investigation of urban effects on the initiation and evolution of heavy rainfall events. In addition, the climatology of extreme rainfall-runoff relationships will be examined with the aim of improving the understanding of the water balance and flood response of urban catchments during extreme rainfall events. Analyses relating the temporal and spatial distribution of rainfall to basin scale and land-use/land-cover characteristics will assist in developing urban flood frequency relationships. Events of particular interest are the floods of September 20-21, 2009 and May 3-4, 2010, which caused heavy damage and fatalities in portions of the southeastern US including Atlanta. Similar bias-corrected radar datasets in development for the Baltimore, Charlotte, and Milwaukee metropolitan areas will allow for the comparison of climatology of extreme rainfall and urban flooding in different regions of the United States and under different climate regimes.
Wright, D. B.; Smith, J. A.; Baeck, M. L.; Villarini, G.
Radar Scan Strategies for the Patrick Air Force Base Weather Surveillance Radar, Model-74C, Replacement
NASA Technical Reports Server (NTRS)
The 45th Weather Squadron (45 WS) is replacing the Weather Surveillance Radar, Model 74C (WSR-74C) at Patrick Air Force Base (PAFB), with a Doppler, dual polarization radar, the Radtec 43/250. A new scan strategy is needed for the Radtec 43/250, to provide high vertical resolution data over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) launch pads, while taking advantage of the new radar's advanced capabilities for detecting severe weather phenomena associated with convection within the 45 WS area of responsibility. The Applied Meteorology Unit (AMU) developed several scan strategies customized for the operational needs of the 45 WS. The AMU also developed a plan for evaluating the scan strategies in the period prior to operational acceptance, currently scheduled for November 2008.
Short, David
The Atmospheric Imaging Radar (AIR) for high-resolution observations of severe weather
Rapid updates are a highly desired feature in the field of mobile weather radars. Various techniques have been used to improve volume update times, including the use of agile and multi-beam radars. Imaging radars, similar in some respects to phased arrays, steer the radar beam in software, thus requiring no physical motion. In contrast to phased arrays, imaging radars gather
Brad Isom; Robert Palmer; Redmond Kelley; John Meier; David Bodine; Mark Yeary; Boon Leng Cheong; Yan Zhang; Tian-You Yu; Mike Biggerstaff
High-resolution Radar Rainfall Records for Assessment of Hydroclimatology of the Christina River Basin
NASA Astrophysics Data System (ADS)
A high-resolution 15-minute, 1 km2 radar rainfall data set for the warm season during the period of 2001-2010 was developed for the 1440 km2 Christina River Basin. Daily rainfall observations from rain gauges were used to bias correct radar fields derived from volume scan reflectivity observations from the NEXRAD WSR-88D radar at Fort Dix, NJ. The bias-corrected radar rainfall data were used to assess the spatial and temporal structure of rainfall over the Christina River Basin and its four sub-watersheds: White Clay Creek (277 km2), Red Clay Creek (140 km2), Brandywine Creek (842 km2), and the tidal Christina River (202 km2). High-quality rain gauge data from within the intensively studied 7.5 km2 3rd order east fork of the east branch of White Clay Creek were supplemented with the additional spatial rainfall distribution information provided by the radar rainfall product to create a more complete picture of prescription patterns over this long-term highly-instrumented research watershed. The high-resolution long-term bias-corrected radar rainfall data set will also be used in hydrologic modeling for the Christina River Basin Critical Zone Observatory.
Bates, N. S.; Baeck, M. L.; Smith, J. A.; Damiano, S. G.; Aufdenkampe, A. K.
Evaluation of Raindrop Size Distributions to Improve Radar Rainfall Estimation during the Colorado Flood
NASA Astrophysics Data System (ADS)
During the period of 9-16 September 2013, a large area of greater than 150 mm of rain, with local amounts of up to 450 mm, fell over a large part of the Colorado Front Range foothills and adjacent plains. This extreme rainfall event caused severe flooding of main river channels and some localized flash flooding which resulted in millions of dollars of damage to private and public properties. The rainfall regime associated with this extreme precipitation event was atypical of storms usually observed in this region. As a result, the radar rainfall algorithms tuned for this region significantly underestimated the total amount of rainfall. In order to quantify the underestimation and provide insight for improving the radar rainfall estimates for this unique precipitation regime, a comparison study has been conducted using data from several disdrometers that were operating throughout the event. Disdrometers observed over 5000 minutes of rainfall during the event. Analysis of the raindrop spectra indicated that most of the rainfall was comprised of a large number of small drops (< 2 mm in diameter). The raindrop spectra have been stratified by the precipitation regime. For these different regimes, new radar rainfall estimators are being derived from the raindrop spectra. The new estimators will be applied to the radar data to provide new rainfall estimates. These estimates will be evaluated using independent rain gauge data. The presentation will provide an overview of the Colorado Flood and a summary of results from the precipitation analysis.
Kucera, Paul; Klepp, Christian
Status of TRMM Project: Rain Radar in the Tropical Rainfall Measuring Mission.
National Technical Information Service (NTIS)
Presented in viewgraph format, the rain radar development for TRMM (Tropical Rainfall Measuring Mission) satellite conducted by Communications Research Laboratory (CRL) are outlined. Topics addressed include: schedule of TRMM Project; U.S./Japan responsib...
K. Okamote
Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia
NASA Astrophysics Data System (ADS)
Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.
Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.
The ELDORA/ASTRAIA Airborne Doppler Weather Radar: High-Resolution Observations from TOGA COARE.
NASA Astrophysics Data System (ADS)
The ELDORA/ASTRAIA (Electra Doppler Radar/Analyese Stereoscopic par Impulsions Aeroporte) airborne Doppler weather radar was recently placed in service by the National Center for Atmospheric Research and the Centre d'�tude des Environnements Terrestre et Planetaires in France. After a multiyear development effort, the radar saw its first field tests in the TOGA COARE (Tropical Oceans-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment) field program during January and February 1993. The ELDORA/ASTRAIA radar (herein referred to as ELDORA) is designed to provide high-resolution measurements of the air motion and rainfall characteristics of very large storms, storms that are frequently too large or too remote to be adequately observed by ground-based radars. This paper discusses the measurement requirements and the design goals of the radar and concludes with an evaluation of the performance of the system using data from TOGA COARE.The performance evaluation includes data from two cases. First, observations of a mesoscale convective system on 9 February 1993 are used to compare the data quality of the ELDORA radar with the National Oceanic and Atmospheric Administration P-3 airborne Doppler radars. The large-scale storm structure and airflow from ELDORA are seen to compare quite well with analyses using data from the P-3 radars. The major differences observed between the ELDORA and P-3 radar analyses were due to the higher resolution of the ELDORA data and due to the different domains observed by the individual radars, a result of the selection of flight track past the storm for each aircraft. In a second example, the high-resolution capabilities of ELDORA are evaluated using observations of a shear-parallel mesoscale convective system (MCS) that occurred on 18 February 1993. This MCS line was characterized by shear-parallel clusters of small convective cells, clusters that were moving quickly with the low-level winds. High-resolution analysis of these data provided a clear picture of the small scale of the storm vertical velocity structure associated with individual convective cells. The peak vertical velocities measured in the high-resolution analysis were also increased above low-resolution analysis values, in many areas by 50%-100%. This case exemplifies the need for high-resolution measurement and analysis of convective transport, even if the goal is to measure and parameterize the large-scale effects of storms. The paper concludes with a discussion of completion of the remaining ELDORA design goals and planned near-term upgrades to the system. These upgrades include an implementation of dual-pulse repetition frequency and development of real-time, in-flight dual-Doppler analysis capability.
Hildebrand, Peter H.; Lee, Wen-Chau; Walther, Craig A.; Frush, Charles; Randall, Mitchell; Loew, Eric; Neitzel, Richard; Parsons, Richard; Testud, Jacques; Baudin, Fran�ois; Lecornec, Alain
Estimation of rainfall field by combining radar data and raingauge observations: the modified conditional merging technique
NASA Astrophysics Data System (ADS)
The estimation of rainfall fields, especially its spatial distribution and position is a crucial task both for rainfall nowcasting and for modeling catchment response to rainfall. Some studies of literature about multisensor datafusion prove that combining data from raingauges and radar represents the best way to obtain an enhanced ad more reliable estimation of QPE and of the associated river discharge. Sinclair and Peagram (2004) have proposed the Conditional Merging (CM) technique, a merging algorithm which extract the information content from the observed data and use it within an interpolation method to obtain the rainfall maps. The raingauges provide a punctual measure of the ground-observed rainfall while the remote sensors (radar network or satellite constellation) supply rainfall estimation maps which give an idea of the correlation and structure of covariance of the observed field. In this work is presented an algorithm called Modified Conditional Merging that is based on CM and which is used for real-time estimation of the optimal rainfall maps. The area of interest is Italy, where are both available a dense network of raingauge measurements (about 2000 stations) and a QPE estimated by the Italian Radar composite. The main innovation respect to classical CM is to estimate the structure of covariance and the length of spatial correlation ?, for every raingauge, directly from the cumulated radar rainfall fields. An application to several test cases together with the evaluation of algorithm performances are presented and discussed.
Pignone, F.; Rebora, N.; Silvestro, F.
Attenuation of Weather Radar Signals Due to Wetting of the Radome by Rainwater or Incomplete Filling of the Beam Volume
NASA Technical Reports Server (NTRS)
A search of scientific literature, both printed and electronic, was undertaken to provide quantitative estimates of attenuation effects of rainfall on weather radar radomes. The emphasis was on C-band (5 cm) and S-Band (10 cm) wavelengths. An empirical model was developed to estimate two-way wet radome losses as a function of frequency and rainfall rate for both standard and hydrophobic radomes. The model fits most of the published data within +/- 1 dB at both target wavelengths for rain rates from less than ten to more than 200 mm/hr. Rainfall attenuation effects remain under 1 dB at both frequencies regardless of radome type for rainfall rates up to 10 mm/hr. S-Band losses with a hydrophobic radome such as that on the WSR-88D remain under 1 dB up to 100 mm/hr. C-Band losses on standard radomes such as that on the Patrick AFB (Air Force Base) WSR-74C can reach as much as 5 dB at 50 mm/hr. In addition, calculations were performed to determine the reduction in effective reflectivity, Z, when a radar target is smaller than the sampling volume of the radar. Results are presented for both the Patrick Air Force Base WSR-74C and the WSR-88D as a function of target size and range.
Merceret, Francis J.; Ward, Jennifer G.
Development of High Altitude UAV Weather Radars for Hurricane Research
NASA Technical Reports Server (NTRS)
A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.
Heymsfield, Gerald; Li, Li-Hua
Assimilation of Doppler Weather Radar Data in WRF Model for Simulation of Tropical Cyclone Aila
NASA Astrophysics Data System (ADS)
For the accurate and effective forecasting of a cyclone, it is critical to have accurate initial structure of the cyclone in numerical models. In this study, Kolkata Doppler weather radar (DWR) data were assimilated for the numerical simulation of a land-falling Tropical Cyclone Aila (2009) in the Bay of Bengal. To study the impact of radar data on very short-range forecasting of a cyclone's path, intensity and precipitation, both reflectivity and radial velocity were assimilated into the weather research and forecasting (WRF) model through the ARPS data assimilation system (ADAS) and cloud analysis procedure. Numerical experiment results indicated that radar data assimilation significantly improved the simulated structure of Cyclone Aila. Strong influences on hydrometeor structures of the initial vortex and precipitation pattern were observed when radar reflectivity data was assimilated, but a relatively small impact was observed on the wind fields at all height levels. The assimilation of radar wind data significantly improved the prediction of divergence/convergence conditions over the cyclone's inner-core area, as well as its wind field in the low-to-middle troposphere (600-900 hPa), but relatively less impact was observed on analyzed moisture field. Maximum surface wind speed produced from DWR-Vr and DWR-ZVr data assimilation experiments were very close to real-time values. The impact of radar data, after final analysis, on minimum sea level pressure was relatively less because the ADAS system does not adjust for pressure due to the lack of pressure observations, and from not using a 3DVAR balance condition that includes pressure. The greatest impact of radar data on forecasting was realized when both reflectivity and wind data (DWR-ZVr and DWR-ZVr00 experiment) were assimilated. It is concluded that after final analysis, the center of the cyclone was relocated very close to the observed position, and simulated cyclone maintained its intensity for a longer duration. Using this analysis, different stages of the cyclone are better captured, and cyclone structure, intensification, direction of movement, speed and location are significantly improved when both radar reflectivity and wind data are assimilated. As compared to other experiments, the maximum reduction in track error was noticed in the DWR-ZVr and DWR-ZVr00 experiments, and the predicted track in these experiments was very close to the observed track. In the DWR-ZVr and DWR-ZVr00 experiments, rainfall pattern and amount of rainfall forecasts were remarkably improved and were similar to the observation over West Bengal, Orissa and Jharkhand; however, the rainfall over Meghalaya and Bangladesh was missed in all the experiments. The influence of radar data reduces beyond a 12-h forecast, due to the dominance of the flow from large-scale, global forecast system models. This study also demonstrates successful coupling of the data assimilation package ADAS with the WRF model for Indian DWR data.
Srivastava, Kuldeep; Bhardwaj, Rashmi
Processing of Indian Doppler Weather Radar data for mesoscale applications
NASA Astrophysics Data System (ADS)
This paper demonstrates the usefulness of Indian Doppler Weather Radar (DWR) data for nowcasting applications, and assimilation into a mesoscale Numerical Weather Prediction (NWP) model. Warning Decision Support System Integrated Information (WDSS-II) developed by National Severe Storm Laboratory (NSSL) and Advanced Regional Prediction System (ARPS) developed at the Centre for Analysis and Prediction, University of Oklahoma are used for this purpose. The study reveals that the WDSS-II software is capable of detecting and removing anomalous propagation echoes from the Indian DWR data. The software can be used to track storm cells and mesocyclones through successive scans. Radar reflectivity mosaics are created for a land-falling tropical cyclone�Khaimuk of 14 November 2008 over the Bay of Bengal using observations from three DWR stations, namely, Visakhapatnam, Machilipatnam and Chennai. Assimilation of the quality-controlled radar data (DWR, Chennai) of the WDSS-II software in a very high-resolution NWP model (ARPS) has a positive impact for improving mesoscale prediction. This has been demonstrated for a land-falling tropical cyclone Nisha of 27 November 2008 of Tamil Nadu coast. This paper also discusses the optimum scan strategy and networking considerations. This work illustrates an important step of transforming research to operation.
Roy Bhowmik, S. K.; Sen Roy, Soma; Srivastava, Kuldeep; Mukhopadhay, B.; Thampi, S. B.; Reddy, Y. K.; Singh, Hari; Venkateswarlu, S.; Adhikary, Sourav
A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis
NASA Astrophysics Data System (ADS)
This study presents an analysis of a severe weather case that took place during the early morning of the 2nd of November 2008, when intense convective activity associated with a rapidly evolving low pressure system affected the southern coast of Catalonia (NE Spain). The synoptic framework was dominated by an upper level trough and an associated cold front extending from Gibraltar along the Mediterranean coast of the Iberian Peninsula to SE France, which moved north-eastward. South easterly winds in the north of the Balearic Islands and the coast of Catalonia favoured high values of 0-3 km storm relative helicity which combined with moderate MLCAPE values and high shear favoured the conditions for organized convection. A number of multicell storms and others exhibiting supercell features, as indicated by Doppler radar observations, clustered later in a mesoscale convective system, and moved north-eastwards across Catalonia. They produced ground-level strong damaging wind gusts, an F2 tornado, hail and heavy rainfall. Total lightning activity (intra-cloud and cloud to ground flashes) was also relevant, exhibiting several classical features such as a sudden increased rate before ground level severe damage, as discussed in a companion study. Remarkable surface observations of this event include 24 h precipitation accumulations exceeding 100 mm in four different observatories and 30 minute rainfall amounts up to 40 mm which caused local flash floods. As the convective system evolved northward later that day it also affected SE France causing large hail, ground level damaging wind gusts and heavy rainfall.
Bech, Joan; Pineda, Nicolau; Rigo, Tomeu; Aran, Montserrat; Amaro, J�ssica; Gay�, Miquel; Ar�s, Joan; Montany�, Joan; der Velde, Oscar van
Superconducting Narrowband Filter for Receiver of Weather Radar
NASA Astrophysics Data System (ADS)
We have developed a high-temperature superconducting (HTS) filter with narrow bandwidth characteristic for receiver of weather radar in order to reduce interference between adjacent radar channels. To realize a filter with which a narrow bandwidth and low insertion loss are compatible, resonators with high unloaded Q (Qu) value are required. Hairpin microstrip resonators with 1.5 times wavelength were adopted to suppress the radiation loss and achieve a high Qu value. The developed HTS filter has 8-pole quasi-elliptic function response for sharp skirt characteristic. The measured frequency response of the developed filter shows center frequency of 5370MHz, insertion loss of 2.04dB and maximum return loss of 15dB, which agrees with the designed responses.
Kawaguchi, Tamio; Shiokawa, Noritsugu; Nakayama, Kohei; Watanabe, Takatoshi; Hashimoto, Tatsunori; Kayano, Hiroyuki
Estimation of rainfall field by combining radar data and raingauge observations: the modified conditional merging technique
NASA Astrophysics Data System (ADS)
Estimation of rainfall field by combining radar data and raingauge observations: the modified conditional merging technique N. Rebora, F. Pignone, F. Silvestro The estimation of rainfall fields, especially its spatial distribution and position is a crucial task both for rainfall nowcasting and for modeling catchment response to rainfall. Some studies of literature about multisensor datafusion prove that combining data from raingauges and radar represents the best way to obtain an enhanced ad more reliable estimation of QPE and of the associated river discharge. Sinclair and Peagram (2004) have proposed the Conditional Merging (CM) technique, a merging algorithm which extract the information content from the observed data and use it within an interpolation method to obtain the rainfall maps. The raingauges provide a punctual measure of the observed "real" rainfall while the remote sensors (radar network or satellite constellation) supply rainfall estimation maps which give an idea of the correlation and structure of covariance of the observed field. In this work is studied an enhanced algorithm based on CM, called Modified Conditional Merging, which can be used in real-time to produce the optimal rainfall maps. The area of interest is Italy, where are both available a dense network of raingauge measurements (about 2000 stations) and a QPE estimated by the Italian Radar composite. The main innovation respect to classical CM is to estimate the structure of covariance and the length of spatial correlation ?, for every raingauge, directly from the cumulated radar rainfall fields. The advantages of this method is to estimate the local characteristic of the domain to obtain information at smaller scale, very useful for convective events. An operative use and a validation are presented and discussed.
Pignone, Flavio; Rebora, Nicola
A Radar Climatology of Extreme Rainfall in the Front Range of the Rocky Mountains
NASA Astrophysics Data System (ADS)
Analyses of the spatial and temporal distribution of extreme rainfall in the Arkansas River basin above Pueblo, Colorado are based on analyses of volume scan radar reflectivity observations from the Pueblo and Denver WSR-88D radars for the period 1995 - 2004. Climatological analyses of extreme rainfall are carried out both from an Eulerian perspective, in which the time-varying distribution of rainfall at fixed locations is examined, and a Lagrangian perspective, in which distributional aspects of rainfall are based on storm tracking algorithms. Of particular interest is the spatial heterogeneity of extreme rainfall in the complex terrain of the upper Arkansas River basin. Lagrangian analyses are used to characterize the spatially varying distribution of storm initiation, storm motion and storm structure. Analyses are motivated by problems of dam safety in which distributional properties of extreme rainfall are of most interest. Climatological analyses of extreme rainfall in the upper Arkansas River basin are examined relative to the spatial and temporal properties of two extreme rain events that occurred in June 1921 and June 1964. Radar climatology indicates a lack of spatial coherence in extreme events over the basin, with the upper basin rainfall climatology exhibiting pronounced contrasts with that of the lower basin.
Javier, J. R.; Smith, J. A.; England, J. F.; Baeck, M.
X-band Polarimetric Radar Rainfall Measurements in Keys Area Microphysics Project.
NASA Astrophysics Data System (ADS)
The Keys Area Microphysics Project (KAMP), conducted as part of NASA�s Fourth Convective and Moisture Experiment (CAMEX-4) in the lower Keys area, deployed a number of ground radars and four arrays of rain gauge and disdrometer clusters. Among the various instruments is an X-band dual-polarization Doppler radar on wheels (XPOL), contributed by the University of Connecticut. XPOL was used to retrieve rainfall rate and raindrop size distribution (DSD) parameters to be used in support of KAMP science objectives. This paper presents the XPOL measurements in KAMP and the algorithm developed for attenuation correction and estimation of DSD model parameters. XPOL observations include the horizontal polarization reflectivity ZH, differential reflectivity ZDR, and differential phase shift DP. Here, ZH and ZDR were determined to be positively biased by 3 and 0.3 dB, respectively. A technique was also applied to filter noise and correct for potential phase folding in DP profiles. The XPOL attenuation correction uses parameterizations that relate the path-integrated specific (differential) attenuation along a radar ray to the filtered-DP (specific attenuation) profile. Attenuation-corrected ZH and specific differential phase shift (derived from filtered DP profiles) data are then used to derive two parameters of the normalized gamma DSD model, that is, intercept (Nw) and mean drop diameter (D0). The third parameter (shape parameter ?) is calculated using a constrained ? relationship derived from the measured raindrop spectra. The XPOL attenuation correction is evaluated using coincidental nonattenuated reflectivity fields from the Key West Weather Surveillance Radar-1988 Doppler (WSR-88D), while the DSD parameter retrievals are statistically assessed using DSD parameters calculated from the measured raindrop spectra. Statistics show that XPOL DSD parameter estimation is consistent with independent observations. XPOL estimates of water content and Nw are also shown to be consistent with corresponding retrievals from matched ER-2 Doppler radar (EDOP) profiling observations from the 19 September airborne campaign. Results shown in this paper strengthen the applicability of X-band dual-polarization high resolution observations in cloud modeling and precipitation remote sensing studies.
Anagnostou, Emmanouil N.; Grecu, Mircea; Anagnostou, Marios N.
Investigating radar subpixel-scale rainfall variability and uncertainty from observations of a super dense rain-gauge network
NASA Astrophysics Data System (ADS)
Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges, containing 27 gauges covering an area of about 4 km2, was installed in northern Israel, representing Mediterranean climate regime. This network was established for a detailed exploration of the uncertainties associated with radar and satellite rainfall resulting from rainfall variability at the subpixel-scale. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The zero-distance correlation between rain gauges was high (0.92 on the 1-min scale) and increased as the time scale increased. A difference was detected in the spatial correlations of the convective and nonconvective rainfall, as the convective rainfall correlation decreases much faster than the nonconvective one. The variance of the differences between radar pixel rainfall and averaged point rainfall (the variance reduction factor) was 1.6% for the 1-min scale. It was also found that at least four uniformly distributed rain stations are needed to adequately represent the rainfall on the radar pixel scale. The radar-rain gauge rainfall difference was mainly contributed by radar estimation errors while the gauge sampling error contributed no more than 22% to the total error. The radar rainfall estimations improved with increasing time scale and the radar-to-true rainfall ratio decreased with increasing time scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data.
Peleg, Nadav; Ben-Asher, Matan; Morin, Efrat
Rainfall frequency analysis using a hourly rainfall model calibrated on weather patterns: application on Reunion Island
NASA Astrophysics Data System (ADS)
The National Research Institute of Science and Technology for Environment and Agriculture (Irstea) has developed an original method for regional rainfall frequency analysis applied on the whole French territory: the SHYREG1 method. It is based on a stochastic hourly rainfall generator. The parameters of the rainfall generator were regionalized at the spatial resolution of 1 km2 thus allowing for the implementation of the model for every 1 km2. Frequency distributions were then derived from long simulated rainfall series for each pixel. Therefore statistical rainfall estimates of various durations (from 1h to 72h) and return periods (from 2 to 1000 years) are made available in a rainfall risk database (intensity-duration-frequency) for the entire French territory. This article presents the application of the SHYREG method in Reunion Island. Reunion Island (with a 2500-km2 surface area) is located in the south-west Indian Ocean. The climate is tropical and characterised by cyclonic rainfall. Tropical cyclones generate heavy rains: during the last one (Bejinsa) in January 2014, rainfall observed exceeded 1000 mm in Cilaos station. Likewise, world records of rainfall, lasting between 5 days (4301 mm in Commerson) and 15 days (6433 mm in Commerson), were observed in Reunion Island during the Hyacinthe Cyclone in January 19802. In mainland France, the calibration of the hourly rainfall generator depends on two seasons (winter from December to May and summer from June to November). However, in order to account for different types of events during a same season, a specific calibration of the hourly rainfall model was necessary. Four types of rainfall event were defined by M�t�o-France: cyclones, storms, hard rain and rain. M�t�o-France rainfall data, evenly located over the Island (52 hourly rain gauge stations and 98 daily rain gauge stations), were used to calibrate the hourly rainfall generator. The SHYREG parameters were regionalized based on 17 physiographic maps of the Island (relief, ocean distance, etc.) with a 1-km2 spatial resolution. For return periods of up to 10 years, the SHYREG-estimated rainfall frequency values are consistent with estimates from the GPD law according to the Nash-Sutcliffe criteria. For extreme return periods, we validate SHYREG-based rainfall frequency estimates according to criteria of reliability and stability3 and compare with the GPD performance. The stability of the frequency analysis method is defined by its capacity to produce similar results when calibrated with different data samples, its reliability by its capacity to assign accurate probabilities of occurrence to observations. Results from applying both criteria have shown that the SHYREG method is highly stable and reliable compared to the GPD law.
Aubert, Yoann; Arnaud, Patrick; Fine, Jean-alain; Cantet, Philippe
A feasibility study of rain radar for the Tropical Rainfall Measuring Mission. III - Radar type and antenna
NASA Astrophysics Data System (ADS)
The radar type and antenna design for the Tropical Rainfall Measuring Mission rain radar are discussed. Because the mission requires rapid scanning to provide continuous coverage of the swath and limited maximum output power of the final stage power amplifier, only two radar types are suitable for the mission: a passive array with TWTA and ferrite phase shifters, and an active array with solid state power amplifiers and PIN diode phase shifters. Two primary antenna designs, the planar antenna and the cylindrical parabolic antenna, are examined.
Nakamura, Kenji; Ihara, Toshio
Impact of satellite rainfall assimilation on Weather Research and Forecasting model predictions over the Indian region
NASA Astrophysics Data System (ADS)
is probably the most important parameter that is predicted by numerical weather prediction models, though the skill of rainfall prediction is the poorest compared to other parameters, e.g., temperature and humidity. In this study, the impact of rainfall assimilation on mesoscale model forecasts is evaluated during Indian summer monsoon 2011. The Weather Research and Forecasting (WRF) model and its four-dimensional variational data assimilation system are used to assimilate the Tropical Rainfall Measuring Mission 3B42 and Japan Aerospace Exploration Agency Global Satellite Mapping of Precipitation retrieved rainfall. A total of five experiments are performed daily with and without assimilation of rainfall data during the entire month of July 2011. Separate assimilation experiments are performed to assess the sensitivity of WRF model forecast with strict and less strict quality control. Assimilation of rainfall improves the forecast of temperature, specific humidity, and wind speed. Domain average improvement parameter of rainfall forecast is also improved over the Indian landmass when compared with NOAA Climate Prediction Center Morphing technique and Indian Meteorological Department gridded rainfall.
Kumar, Prashant; Kishtawal, C. M.; Pal, P. K.
The use of radar data assimilation to improve warm season heavy rainfall forecasts for use in hydrologic models
NASA Astrophysics Data System (ADS)
Warm Season convective rainfall is one of the most poorly forecast parameters in numerical models, which is unfortunate since this rainfall often occurs with very high rates which can lead to flooding if the duration of the event is sufficiently long. Because quantitative precipitation forecasting (QPF) skill has traditionally been poor, these forecasts are not used in hydrologic modeling for stream flow. Instead, stream flow forecasts are made using estimates of precipitation that has fallen, reducing the amount of lead time for warnings from what could exist if forecasts were used. Thus a continued focus in the meteorological community has been on increasing the forecasting accuracy of warm season convective rainfall. Numerical weather forecasting has always suffered from the inability to accurately observe the state of the atmosphere; thus, model initial conditions cannot accurately portray the true state of the atmosphere. These initial observations (being inaccurate to a certain degree) result in growth of error in the model through time. This presentation will focus on the the impact of adjusted initial conditions in the Weather Research and Forecasting (WRF) model through the assimilation of radar data to increase the accuracy of the initialization. The WRF has been run with convection-allowing grid spacing over a domain covering roughly 800 x 800 km centered over Iowa. The model is being run for several heavy rain events that occurred over the Midwest. The QPF skill of the model over the first 12 forecast hours with radar data assimilation will be compared to the skill of the same model without radar data assimilation. The use of radar data assimilation in the Center for the Analysis and Prediction of Storms (CAPS) ensemble has been found to noticeably improve forecasts, especially over the first 6-12 hours. This project will focus on quantifying the impact of such assimilation on rainfall forecasts in Iowa, and on hydrologic forecasts that use the QPF. If skill is found on average to improve sufficiently, it may be possible to extend warning lead time by several hours through the use of this QPF.
Moser, Benjamin; Gallus, William; Mantilla, Ricardo; Krajewski, Witold
Direct measurement of the combined effects of lichen, rainfall, and temperature onsilicate weathering
A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 ?? 2.5 kcal/mol) and olivine (21.3 ?? 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution of plagioclase and olivine underneath lichen is far more sensitive to rainfall.
Brady, P. V.; Dorn, R. I.; Brazel, A. J.; Clark, J.; Moore, R. B.; Glidewell, T.
Direct measurement of the combined effects of lichen, rainfall, and temperature onsilicate weathering
NASA Astrophysics Data System (ADS)
A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 � 2.5 kcal/mol) and olivine (21.3 � 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution of plagioclase and olivine underneath lichen is far more sensitive to rainfall.
Brady, Patrick V.; Dorn, Ronald I.; Brazel, Anthony J.; Clark, James; Moore, Richard B.; Glidewell, Tiffany
A multi-spectral spatial convolution approach of rainfall forecasting using weather satellite imagery
Flood forecasting has long been a major topic of hydrologic research. Recent events and studies indicate that the success of flood forecasting in Taiwan depends heavily on the accuracy of real-time rainfall forecasting. In this study, we demonstrate a multi-spectral spatial convolution approach for real-time rainfall forecasting using geostationary weather satellite images. The approach incorporates cloud-top temperatures of three infrared
Chiang Wei; Wei-Chun Hung; Ke-Sheng Cheng
Bird migration flight altitudes studied by a network of operational weather radars
A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which�when extended to multiple radars�enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.
Dokter, Adriaan M.; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan
On the Use of Auxiliary Receive Channels for Clutter Mitigation With Phased Array Weather Radars
Phased array radars (PARs) are attractive in weather surveillance primarily because of their capability to electronically steer. When combined with the recently developed beam multiplexing (BMX) technique, these radars can obtain very rapid update scans that are useful in monitoring severe weather. A consequence is that the small number of contiguous samples of the time series obtained can be a
Khoi D. Le; Robert D. Palmer; Boon Leng Cheong; Tian-You Yu; Guifu Zhang; Sebastian M. Torres
History of Weather Radar Research in the U.S. Air Force.
National Technical Information Service (NTIS)
From its origin in 1948 the weather radar program of the U.S. Air Force has maintained a leading role in research and development. Detection of radar echoes from the optically clear atmosphere in the early 1950's led to vigorous debate within the weather ...
J. I. Metcalf K. M. Glover
wradlib - an Open Source Library for Weather Radar Data Processing
NASA Astrophysics Data System (ADS)
Even though weather radar holds great promise for the hydrological sciences, offering precipitation estimates with unrivaled spatial and temporal resolution, there are still problems impeding its widespread use, among which are: almost every radar data set comes with a different data format with public reading software being available only rarely. standard products as issued by the meteorological services often do not serve the needs of original research, having either too many or too few corrections applied. Especially when new correction methods are to be developed, researchers are often forced to start from scratch having to implement many corrections in addition to those they are actually interested in. many algorithms published in the literature cannot be recreated using the corresponding article only. Public codes, providing insight into the actual implementation and how an approach deals with possible exceptions are rare. the radial scanning setup of weather radar measurements produces additional challenges, when it comes to visualization or georeferencing of this type of data. Based on these experiences, and in the hope to spare others at least some of these tedious tasks, wradlib offers the results of the author's own efforts and a growing number of community-supplied methods. wradlib is designed as a Python library of functions and classes to assist users in their analysis of weather radar data. It provides solutions for all tasks along a typical processing chain leading from raw reflectivity data to corrected, georeferenced and possibly gauge adjusted quantitative precipitation estimates. There are modules for data input/output, data transformation including Z/R transformation, clutter identification, attenuation correction, dual polarization and differential phase processing, interpolation, georeferencing, compositing, gauge adjustment, verification and visualization. The interpreted nature of the Python programming language makes wradlib an ideal tool for interactive data exploration and analysis. Based on the powerful scientific python stack (numpy, scipy, matplotlib) and in parts augmented by functions compiled in C or Fortran, most routines are fast enough to also allow data intensive re-analyses or even real-time applications. From the organizational point of view, wradlib is intended to be community driven. To this end, the source code is made available using a distributed version control system (DVCS) with a publicly hosted repository. Code may be contributed using the fork/pull-request mechanism available to most modern DVCS. Mailing lists were set up to allow dedicated exchange among users and developers in order to fix problems and discuss new developments. Extensive documentation is a key feature of the library, and is available online at http://wradlib.bitbucket.org. It includes an individual function reference as well as examples, tutorials and recipes, showing how those routines can be combined to create complete processing workflows. This should allow new users to achieve results quickly, even without much prior experience with weather radar data.
Pfaff, Thomas; Heistermann, Maik; Jacobi, Stephan
Rainfall estimation from X-band dual polarization radar using reflectivity and differential reflectivity
NASA Astrophysics Data System (ADS)
Radar observations of reflectivity and differential reflectivity from a measurement volume are biased due to attenuation and differential attenuation in the presence of rainfall along the path between the measurement volume and the radar. This attenuation is fairly small at S-band frequencies, but not negligible at C-band and higher frequencies such as X-band. The impact of attenuation and differential attenuation on the accuracy of rainfall estimation is studied. It is shown that the biases due to attenuation and differential attenuation nearly cancel each other when used in the rainfall algorithm that uses both reflectivity and differential reflectivity and result in small biases in the rainfall rate estimation. About 2000 X-band radar profiles were simulated based on S-band radar measurements of reflectivity and differential reflectivity, for validation purposes. Theoretical and simulation analyses show that rainfall rate computed at X-band using reflectivity and differential reflectivity without attenuation correction, results in very small bias for certain underlying mean raindrop shape models.
Gorgucci, Eugenio; Chandrasekar, V.; Baldini, L.
Development of precipitation radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite
The precipitation radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite is the first spaceborne radar to measure precipitation from space. The PR, operating at 13.8 GHz, is a 128-element active phased array that allows a fast and sophisticated cross-track scanning over a swath width of 215 km with a cross-range spatial resolution of about 4.3 km. The PR
Toshiaki Kozu; Toneo Kawanishi; Hiroshi Kuroiwa; Masahiro Kojima; Koki Oikawa; Hiroshi Kumagai; K. Okamoto; M. Okumura; H. Nakatsuka; K. Nishikawa
Effects of Systematic and Random Errors on the Spatial Scaling Properties in Radar-Estimated Rainfall
Spatial scaling properties of precipitation fields are often investigated based on radar data. However, little is known about\\u000a the effects of the considerable uncertainties present in radar-rainfall products on the estimated multifractal parameters.\\u000a The basic systematic factors that can affect the results of such analyses include the selection of a Z-R relationship, the\\u000a rain\\/no-rain reflectivity threshold, and the distance from
Gabriele Villarini; Grzegorz J. Ciach; Witold F. Krajewski; Keith M. Nordstrom; Vijay K. Gupta
Cross-validation of spaceborne radar and ground polarimetric radar observations
There is great potential for spaceborne weather radar to make significant observations of the precipitating medium on global scales. The Tropical Rainfall Mapping Mission (TRMM) is the first mission dedicated to measuring rainfall in the tropics from space using radar. The Precipitation Radar (PR) is one of several instruments aboard the TRMM satellite that is operating in a nearly circular
Steven Matthew Bolen
Experiments in Rainfall Estimation with a Polarimetric Radar in a Subtropical Environment.
NASA Astrophysics Data System (ADS)
A unique dataset consisting of high-resolution polarimetric radar measurements and dense rain gauge and disdrometer observations collected in east-central Florida during the summer of 1998 was examined. Comparison of the radar measurements and radar parameters computed from the disdrometer observations supported previous studies, which indicate that oscillating drops in the free atmosphere have more spherical apparent shapes in the mean than equilibrium shapes. Radar-disdrometer comparisons improved markedly when using an empirical axis ratio relation developed from observational studies and representing more spherical drop shapes. Fixed-form power-law rainfall estimators for radar reflectivity (ZH), specific differential phase (KDP), specific differential phase-differential reflectivity (KDP, ZDR), and radar reflectivity-differential reflectivity (ZH, ZDR) were then determined using the disdrometer observations. Relations were produced for both equilibrium shapes and the empirical axis ratios. Polarimetric rainfall estimators based on more spherical shapes gave significantly improved performance. However, the improvement was largely in bias mitigation. Rainfall estimates with the ZH-ZDR measurement pair had the highest correlation with rain gauge observations, the smallest range in bias factors from storm to storm, and the smallest root-mean-square error.
Brandes, Edward A.; Zhang, Guifu; Vivekanandan, J.
Polarimetric Radar Remote Sensing of Rainfall and Liquid Water in Clouds
NASA Astrophysics Data System (ADS)
This study focuses on investigation, development and evaluation of dual linear polarization radar techniques for measuring rainfall rates and liquid water content in clouds. The differential reflectivity (Z_ {DR}) technique and two well-known Z-R relationships (Marshall-Palmer and Jones' Thunderstorm) are evaluated through a case study which compares radar and ground-based raingauge measurements utilizing data from the MAYPOLE (1984) experiments conducted in Colorado. The horizontal storm motion and vertical transport of raindrops, as well as the consistency of the spatial and temporal averaging of the radar and raingauge data are taken into account. It is observed that the Z_{DR } technique performs consistently well in the estimation of rainfall rate R when compared with raingauges at two different locations in the storm. A cross correlation technique is proposed and applied to translating radar measurements of rainfall parameters from aloft to their corresponding ground values. Dual polarization radar measurements obtained during the MIST (1986) experiments in Alabama are utilized for this purpose. This technique is also used to estimate the storm motion direction which is necessary for the radar-raingauge comparative studies. One- and two-dimensional correlation lengths of the reflectivity factor, rainfall rate and median volume diameter fields are presented for rainfall events from both MAYPOLE and MIST experiments. Scattering and propagation properties of millimeter waves (94 and 140 GHz) in rainfall are also studied. Power law relationships based on the Marshall-Palmer drop size distribution are derived for rainfall rate R and the propagation parameters such as specific attenuation, specific differential attenuation and phase shift. It is proposed that these parameters at 94 and 140 GHz can be used for estimating path integrated rainfall rates over short propagation paths less than a few kilometers. Raindrop shape models are also shown to significantly affect the interpretation of the Doppler velocity spectrum for vertically pointing radars. A dual polarization bistatic scattering technique is proposed and illustrated for estimating cloud and fog droplet size distributions and their liquid water contents. (Abstract shortened with permission of author.).
Lure, Yuan-Ming
Advanced Precipitation Radar Antenna to Measure Rainfall From Space
NASA Technical Reports Server (NTRS)
To support NASA s planned 20-year mission to provide sustained global precipitation measurement (EOS-9 Global Precipitation Measurement (GPM)), a deployable antenna has been explored with an inflatable thin-membrane structure. This design uses a 5.3 5.3-m inflatable parabolic reflector with the electronically scanned, dual-frequency phased array feeds to provide improved rainfall measurements at 2.0-km horizontal resolution over a cross-track scan range of up to 37 , necessary for resolving intense, isolated storm cells and for reducing the beam-filling and spatial sampling errors. The two matched radar beams at the two frequencies (Ku and Ka bands) will allow unambiguous retrieval of the parameters in raindrop size distribution. The antenna is inflatable, using rigidizable booms, deployable chain-link supports with prescribed curvatures, a smooth, thin-membrane reflecting surface, and an offset feed technique to achieve the precision surface tolerance (0.2 mm RMS) for meeting the low-sidelobe requirement. The cylindrical parabolic offset-feed reflector augmented with two linear phased array feeds achieves dual-frequency shared-aperture with wide-angle beam scanning and very low sidelobe level of -30 dB. Very long Ku and Ka band microstrip feed arrays incorporating a combination of parallel and series power divider lines with cosine-over-pedestal distribution also augment the sidelobe level and beam scan. This design reduces antenna mass and launch vehicle stowage volume. The Ku and Ka band feed arrays are needed to achieve the required cross-track beam scanning. To demonstrate the inflatable cylindrical reflector with two linear polarizations (V and H), and two beam directions (0deg and 30deg), each frequency band has four individual microstrip array designs. The Ku-band array has a total of 166x2 elements and the Ka-band has 166x4 elements with both bands having element spacing about 0.65 lambda(sub 0). The cylindrical reflector with offset linear array feeds reduces the complexity from "NxN" transmit/receive (T/R) modules of a conventional planar-phased array to just "N" T/R modules. The antenna uses T/R modules with electronic phase-shifters for beam steering. The offset reflector does not provide poor cross-polarization like a double- curved offset reflector would, and it allows the wide scan angle in one plane required by the mission. Also, the cylindrical reflector with two linear array feeds provides dual-frequency performance with a single, shared aperture. The aperture comprises a reflective surface with a focal length of 1.89 m and is made from aluminized Kapton film. The reflective surface is of uniform thickness in the range of a few thousandths of an inch and is attached to the chain-link support structure via an adjustable suspension system. The film aperture rolls up, together with the chain-link structure, for launch and can be deployed in space by the deployment of the chain-link structure.
Rahmat-Samii, Yahya; Lin, John; Huang, John; Im, Eastwood; Lou, Michael; Lopez, Bernardo; Durden, Stephen
Simulation of Tornado over Brahmanbaria on 22 March 2013 using Doppler Weather Radar and WRF Model
NASA Astrophysics Data System (ADS)
A tornado accompanied with thunderstorm, rainfall and hailstorm affected Brahmanbaria of Bangladesh in the afternoon of 22 March 2013. The tornadic storms are studied based on field survey, ground and radar observations. Low level moisture influx by southerly flow from the Bay of Bengal coupled with upper level westerly jet stream causing intense instability and shear in the wind fields triggered a series of storms for the day. The exact time and locations of the storms are investigated by using the Agartala and Cox's Bazar Doppler Weather Radar (DWR). Subsequently, the storms are simulated by using the WRF-ARW model at 1 km horizontal resolution based on 6 hourly analyses and boundary conditions of NCEP-FNL. Among the typical characteristics of the storms, the CAPE, surface wind speed, flow patterns, T-? gram, rainfall, sea level pressure, vorticity and vertical velocity are studied. Results show that while there are differences of 2-3 hours between the observed and simulated time of the storms, the distances between observed and simulated locations of the storms are several tens of kilometers. The maximum CAPE was generally above 2400 J kg-1 in the case. The maximum intensity of surface wind speed simulated by the model was only 38 m sec-1. This seems to be underestimated. The highest vertical velocity (updraft) simulated by the model was 250 m sec-1 around 800-950 hPa. The updraft reached up to 150 hPa. It seems that the funnel vortex reached the ground, and might have passed some places a few meters above the surface. According to the Fujita Pearson scale, this tornado can be classified as F-2 with estimated wind speed of 50-70 ms-1. Keywords: Tornado, DWR, NCEP-FNL, T-? gram, CAPE.
Das, M. K.; Chowdhury, M.; Das, S.
The analysis of the rain drop size distribution (DSD) is a key point in the understanding of the physical processes that govern the rainfall properties widely used in meteorology, hydrometeorology, and specially in radar meteorology studies (Joss and Zawadzki 1997). In the methodology for DSD analysis proposed by Marshall and Palmer in 1948, an average DSD is determined for a
Daniel Sempere-Torres; Rafael S�nchez-Diezma; Isztar Zawadzki; J. Dominique Creutin
The Utility of X-Band Polarimetric Radar for Quantitative Estimates of Rainfall Parameters
The utility of X-band polarimetric radar for quantitative retrievals of rainfall parameters is analyzed using observations collected along the U.S. west coast near the mouth of the Russian River during the Hy- drometeorological Testbed project conducted by NOAA's Environmental Technology and National Severe Storms Laboratories in December 2003 through March 2004. It is demonstrated that the rain attenuation effects in
Sergey Y. Matrosov; David E. Kingsmill; Brooks E. Martner; F. Martin Ralph
Prediction of extreme rainfall event using weather pattern recognition and support vector machine classifier
NASA Astrophysics Data System (ADS)
A major component of flood alert broadcasting is the short-term prediction of extreme rainfall events, which remains a challenging task, even with the improvements of numerical weather prediction models. Such prediction is a high priority research challenge, specifically in highly urbanized areas like Mumbai, India, which is extremely prone to urban flooding. Here, we attempt to develop an algorithm based on a machine learning technique, support vector machine (SVM), to predict extreme rainfall with a lead time of 6-48 h in Mumbai, using mesoscale (20-200 km) and synoptic scale (200-2,000 km) weather patterns. The underlying hypothesis behind this algorithm is that the weather patterns before (6-48 h) extreme events are significantly different from those of normal weather days. The present algorithm attempts to identify those specific patterns for extreme events and applies SVM-based classifiers for extreme rainfall classification and prediction. Here, we develop the anomaly frequency method (AFM), where the predictors (and their patterns) for SVM are identified with the frequency of high anomaly values of weather variables at different pressure levels, which are present before extreme events, but absent for non-extreme conditions. We observe that weather patterns before the extreme rainfall events during nighttime (1800 to 0600Z) is different from those during daytime (0600 to 1800Z) and, accordingly, we develop a two-phase support vector classifier for extreme prediction. Though there are false alarms associated with this prediction method, the model predicts all the extreme events well in advance. The performance is compared with the state-of-the-art statistical technique fingerprinting approach and is observed to be better in terms of false alarm and prediction.
Nayak, Munir Ahmad; Ghosh, Subimal
Comparing two radar rainfall products with the help of Multifractal Analysis
NASA Astrophysics Data System (ADS)
Distributed rainfall radar data are commonly used in hydrology and increasingly used in urban hydrology. However radar validation and comparison still commonly relies on standard scores such as Nash-Sutcliffe coefficient, Correlation and Quadratic Error, which enable to grasp neither the underlying spatio-temporal structure of the studied rainfall field nor meaningful statistics, i.e. of order larger than two. We implement an innovative methodology that relies on Universal Multifractal (UM) to compare two operational radar products covering the Paris region. The UM framework has been extensively used to characterize and simulate geophysical fields extremely variable over a wide range of scales such as rainfall with the help of only three parameters, which are furthermore physically meaningful. Both M�t�o-France operational radar mosaic and the CALAMAR radar product use the same single polarization C-band radar data. However their QPE algorithms are different, as well as the calibration with rain gauges. Cartesian fields of final resolution 1 km in space and 5 min in time are used in this study. Three rainfall events that occurred in 2010 and 2011 are used, in order to quantify the quality of the adjustment process we add to this comparison a non-adjusted CALAMAR radar product. As a first step, we compare these radar products to the Val de Marne County network of 27 rain gauges distributed over a 245 Km2 area. Standard scores at various resolutions (5min, 15min, 30min and 1h) are computed. The M�t�o France radar product is better correlated with these rain gauges data than both CALAMAR products at 5min scale, but we observe the opposite when we increase the time scale. We also observe that the CALAMAR adjustment process improves the correlation with rain gauges. In a second step, both spatial (2D maps) and temporal (1D time series for each pixel) multifractal analyses are performed and the UM parameters computed. Preliminary results suggest that both products do not yield the same parameters in terms of spatial distribution and temporal evolution. CALAMAR product seems to significantly under-estimates rainfall singularities and yields a higher percentage of zero values. This may results from the fact CALAMAR replaces the ground clutters by zero values. Authors acknowledge the European INTERREG IV NEW RainGain project (http://raingain.eu) for partial financial support.
Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Bompard, Philippe; Schertzer, Daniel
Can Compressed Sensing Be Applied To Dual-Polarimetric Weather Radars?
NASA Astrophysics Data System (ADS)
The recovery of sparsely-sampled signals has long attracted considerable research interest in various fields such as reflection seismology, microscopy, and astronomy. Recently, such recovery techniques have been formalized as a sampling method called compressed sensing (CS) which uses few linear and non-adaptive measurements to reconstruct a signal that is sparse in a known domain. Many radar and remote sensing applications require efficient and rapid data acquisition. CS techniques have, therefore, enormous potential in dramatically changing the way the radar samples and processes data. A number of recent studies have investigated CS for radar applications with emphasis on point target radars, and synthetic aperture radar (SAR) imaging. CS radar holds the promise of compressing-while-sampling, and may yield simpler receiver hardware which uses low-rate ADCs and eliminates pulse compression/matched filter. The need of fewer measurements also implies that a CS radar may need smaller dwell times without significant loss of information. Finally, CS radar data could be used for improving the quality of low-resolution radar observations. In this study, we explore the feasibility of using CS for dual-polarimetric weather radars. In order to recover a signal in CS framework, two conditions must be satisfied: sparsity and incoherence. The sparsity of weather radar measurements can be modeled in several domains such as time, frequency, joint time-frequency domain, or polarimetric measurement domains. The condition of incoherence relates to the measurement process which, in a radar scenario, would imply designing an incoherent transmit waveform or an equivalent scanning strategy with an existing waveform. In this study, we formulate a sparse signal model for precipitation targets as observed by a polarimetric weather radar. The applicability of CS for such a signal model is then examined through simulations of incoherent measurements along with real weather data obtained from Iowa X-band Polarimetric (XPOL) radar units.
Mishra, K.; Kruger, A.; Krajewski, W. F.
Estimation problems in rainfall modeling
NASA Astrophysics Data System (ADS)
A special session entitled �Estimation Problems in Rainfall Modeling� was held during the 1985 AGU Fall Meeting in San Francisco, Calif. The session was chaired by Witold F. Krajewski of the Hydrologic Research Laboratory of the National Weather Service (NWS), Silver Spring, Md. The purpose of the session was to bring together researchers interested in a wide range of rainfall-related estimation problems, such as parameter estimation, state estimation, multiple sensor rainfall analysis, and estimation problems in rainfall simulation. The topics of papers presented at the session included parameter estimation of point process models, errors in radar rainfall observations, and sampling aspects of space-state representation of rainfall.
Krajewski, Witold F.; Georgakakos, Konstantine P.
Microphysical variability of tropical and mid-latitude rainfall as revealed by polarimetric radar
NASA Astrophysics Data System (ADS)
Gorgucci et al. (2006) showed that a parameter space defined by several polarimetric radar variables could be used to characterize the shape of raindrops. This study has been extended using the so-called self-consistency analysis to identify rainfall regimes, specifically warm rain coalescence compared to the melting of large ice particles that have grown by riming. For a given rainfall regime, the behavior of Kdp/Z (where Kdp is the specific differential phase and Z is the linear reflectivity) plotted against Zdr (differential reflectivity) in rain-only regions is useful in identifying precipitation physics. Kdp is proportional to water mass content and mass-weighted oblateness ratio, whereas Zdr is a measure of particle oblateness of the largest drops in a sample volume. Z is proportional to concentration and diameter. Using data from polarimetric radar observations at several places (both tropical and mid-latitude) around the globe we demonstrate microphysical variability in rainfall associated with intraseasonal variability, differences in organization (isolated convection vs. organized), and regional variability. Several of these datasets have resulted from TRMM and GPM field campaigns, including the Mid-Latitude Continental Convective Clouds Experiment (MC3E) and Iowa Flood Studies (IFloodS). Implications for Z-based rain estimation as used by the TRMM and GPM precipitation radars will be discussed. This technique could also be applied to the nation's NEXRAD WSR-88DP data to better understand the microphysical characteristics of rainfall across the U.S.
Rutledge, S. A.; Dolan, B.; Chandrasekar, C. V.; Kennedy, P.; Wolff, D. B.; Petersen, W. A.
System Concepts for the Advanced Post-TRMM Rainfall Profiling Radars
NASA Technical Reports Server (NTRS)
Global rainfall is the primary distributor of latent heat through atmospheric circulation. The recently launched Tropical Rainfall Measuring Mission satellite is dedicated to advance our understanding of tropical precipitation patterns and their implications on global climate and its change. The Precipitation Radar (PR) aboard the satellite is the first radar ever flown in space and has provided. exciting, new data on the 3-D rain structures for a variety of scientific uses. However, due to the limited mission lifetime and the dynamical nature of precipitation, the TRMM PR data acquired cannot address all the issues associated with precipitation, its related processes, and the long-term climate variability. In fact, a number of new post-TRMM mission concepts have emerged in response to the recent NASA's request for new ideas on Earth science missions at the post 2002 era. This paper will discuss the system concepts for two advanced, spaceborne rainfall profiling radars. In the first portion of this paper, we will present a system concept for a second-generation spaceborne precipitation radar for operations at the Low Earth Orbit (LEO). The key PR-2 electronics system will possess the following capabilities: (1) A 13.6/35 GHz dual frequency radar electronics that has Doppler and dual-polarization capabilities. (2) A large but light weight, dual-frequency, wide-swath scanning, deployable antenna. (3) Digital chirp generation and the corresponding on-board pulse compression scheme. This will allow a significant improvement on rain signal detection without using the traditional, high-peak-power transmitters and without sacrificing the range resolution. (4) Radar electronics and algorithm to adaptively scan the antenna so that more time can be spent to observe rain rather than clear air. and (5) Built-in flexibility on the radar parameters and timing control such that the same radar can be used by different future rain missions. This will help to reduce the overall instrument development costs. In the second portion of this paper, we will present a system concept for a geostationary rainfall monitoring radar for operations at the geosynchronous Earth Orbit (GEO). In particular, the science requirements, the observational strategy, the instrument design, and the required technologies will be discussed.
Im, Eastwood; Smith, Eric A.
Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula
NASA Astrophysics Data System (ADS)
This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.
Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.
Comparison of Spatial and Temporal Rainfall Characteristics of WRF-Simulated Precipitation to gauge and radar observations
NASA Astrophysics Data System (ADS)
Weather Research and Forecasting (WRF) meteorological data are used for US EPA air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hindcasting applications of WRF simulations match observed rainfall on a day-to-day or individual event basis, it is important that the overall spatio-temporal structure of precipitation events represents reality. It has been shown that contaminant fate-and-transport is strongly event-dependent, and the temporal structure of precipitation (and subsequent streamflows) is a major driver of instream flows relating to habitat suitability, contaminant fluxes, dilution, water supply, etc. The spatial and temporal variability of WRF-simulations in the North Carolina Piedmont and Coastal Plain was compared to two observed precipitation datasets, interpolated National Climate Data Center (NCDC) gauge and Multisensor Precipitation Estimate (MPE) radar data. NCDC data are point data comprised of rain-gauge observations, which we interpolated to the 12 km WRF grid using co-kriging (with elevation as the covariate). MPE data, also known as Stage IV NEXRAD, are Doppler-radar derived, HADS-adjusted rainfall estimates at a 4 km resolution, which we resampled to match the 12 km WRF grid. Variographic properties were used to compare spatial structure of rainfall across daily, monthly, seasonal, and annual rainfall totals during the five-year study period. In addition, the variography of a sample of storm events stratified by intensity and type (e.g., frontal , local convective, and tropical cyclones) was compared. Three-way ANOVA was used to compare variographic parameters across the datasets. Temporal structure was compared using partial autocorrelation functions and seasonal decompositions. Evaluation of modeled precipitation spatial and temporal structure, as compared with two observed datasets, allows insights into errors that propagate through stages of water quality, future scenarios, etc. when using WRF simulations. These results will guide future improvements to WRF simulations used within the EPA air and water modeling programs. These results also demonstrate differences in the spatio-temporal structure of the two observed precipitation datasets and provides guidance for use of gauge and radar precipitation data in hindcasting modeling efforts for understanding watershed function and process.
Price, K.; Purucker, T.; Andersen, T. K.; Knightes, C. D.; Cooter, E. J.; Otte, T.
Design criteria for a Multifunction Phased Array Radar integrating weather and Air Traffic Control surveillance
Cost reduction for transmit\\/receive modules makes phased array radar of potential interest to civilian users. An integrated target\\/weather surveillance at medium range, i.e. for terminal manoeuvre area in the frame of ATC and regional weather monitoring, is made possible by MPAR (multifunction phased array radar) techniques, allowing a single technology to satisfy different requirements. The main design criteria and tools
Gaspare Galati; Gabriele Pavan
Analysis of the heavy rainfall from Typhoon Plum using Doppler Radar
NASA Astrophysics Data System (ADS)
Using reanalysis and observational data and Doppler radar data, the structure and characteristics of the synoptic and mesoscale meteorological background are analyzed for a heavy rainfall over Xiaoshipeng town of Yingkou City in Liaoning province, China. The results show that: (1) several synoptic scale patterns formed the background for the heavy rainfall: the Pacific subtropical high extended to the West; a strong tropical storm named "Plum" moved to the northwest after it had landed; Northwest jet transported a lot of the water vapor to Liaoning; the weak cold air of Baikal Lake moved to south along the ridge before the northwest flow impact to Liaoning. (2) the factors conducive to strong convective precipitation: the existence of a deep wet layer, a narrow CAPE zone and a relative weak vertical wind sheer. (3) there is nonstop generation of new mesoscale convective cells during the heavy rainfall. There exists a maximum wind zone of 24m/s in the lower layer and a strong radar echo with 35dBz above 5km. And the variation of the low level southwest jet is in step with the variation of rainfall amount. The cyclonic convergence of the warm wet air in the mid-low level is a factor triggering and strengthening convection. The nonstop generation of mesoscale convective cells and the water vapor transport from the low level southwest jet are pushing the rainfall radar echo to above 40dBz and lasting for more than 5 hours and are considered the direct cause of this heavy rainfall.
Jin, W.; Qu, Y.
Modeling COSMO-SkyMed measurements of precipitating clouds over the sea using simultaneous weather radar observations
NASA Astrophysics Data System (ADS)
Several satellite missions employing X-band synthetic aperture radar (SAR) have been activated to provide high-resolution images of normalized radar cross-sections (NRCS) on land and ocean for numerous applications. Rainfall and wind affect the sea surface roughness and consequently the NRCS from the combined effects of corrugation due to impinging raindrops and surface wind. X-band frequencies are sensitive to precipitation: intense convective cells result in irregularly bright and dark patches in SAR images, masking changes in surface NRCS. Several works have modeled SAR images of intense precipitation over land; less adequately investigated is the precipitation effect over the sea surface. These images are analyzed in this study by modeling both the scattering and attenuation of radiation by hydrometeors in the rain cells and the NRCS surface changes using weather radar precipitation estimates as input. The reconstruction of X-band SAR returns in precipitating clouds is obtained by the joint utilization of volume reflectivity and attenuation, the latter estimated by coupling ground-based radar measurements and an electromagnetic model to predict the sea surface NRCS. Radar signatures of rain cells were investigated using X-band SAR images collected from the COSMO-SkyMed constellation of the Italian Space Agency. Two case studies were analyzed. The first occurred over the sea off the coast of Louisiana (USA) in summer 2010 with COSMO-SkyMed (CSK�) ScanSar mode monitoring of the Deepwater Horizon oil spill. Simultaneously, the NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the same portion of ocean. The second case study occurred in Liguria (Italy) on November 4, 2011, during an extraordinary flood event. The same events were observed by the Bric della Croce C-band dual polarization radar located close to Turin (Italy). The polarimetric capability of the ground radars utilized allows discrimination of the composition of the precipitation volume, in particular distinguishing ice from rain. Results shows that for space-borne SAR at X-band, effects due to precipitation on water surfaces can be modeled using coincident ground-based weather radar measurements.
Roberto, N.; Baldini, L.; Facheris, L.; Chandrasekar, V.
Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling
NASA Astrophysics Data System (ADS)
A new probabilistic model for daily rainfall, named MEWP (Multi Exponential Weather Pattern) distribution, has been introduced in Garavaglia et al. (2010). This model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904-2003, and a regional data set of 478 rain gauges for the period 1954-2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness. The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight : (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.
Garavaglia, F.; Lang, M.; Paquet, E.; Gailhard, J.; Gar�on, R.; Renard, B.
Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling
NASA Astrophysics Data System (ADS)
Design floods for EDF (�lectricit� de France, French electricity company) dam spillways are now computed using a probabilistic method named SCHADEX (Climatic-Hydrological Simulation of Extreme Floods) based on an extreme rainfall model named the MEWP (Multi Exponential Weather Pattern) distribution. This probabilistic model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904-2003, and a regional data set of 478 rain gauges for the period 1954-2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness.The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight: (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.
Garavaglia, F.; Lang, M.; Paquet, E.; Gailhard, J.; Gar�on, R.; Renard, B.
Phased Array Radar Polarimetry for Weather Sensing: A Theoretical Formulation for Bias Corrections
It is becoming widely accepted that radar polarimetry provides accurate and informative weather measurements, while phased-array technology can shorten data updating time. In this paper, a theory of phased array radar (PAR) polarimetry is developed to establish the relation between electric fields at the antenna of the PAR and the fields in a resolution volume filled with hydrometeors. It is
Guifu Zhang; Richard J. Doviak; Dusan S. Zrnic; Jerry Crain; David Staiman; Yasser Al-Rashid
Weather Radar Performance at Long RangeA~��---Simulated and Observed
A large set of high-vertical-resolution reflectivity profiles was used to simulate the performance of radars in the United Kingdom weather radar network. In particular, limitations in the estimation of surface precipitation due to incomplete beam filling and variability in the reflectivity profile were investigated. Marked seasonal variations in range performance were found and detection failures were shown to make a
M. Kitchen; P. M. Jackson
On the potential use of radar-derived information in operational numerical weather prediction
NASA Technical Reports Server (NTRS)
Estimates of requirements likely to be levied on a new observing system for mesoscale meteonology are given. Potential observing systems for mesoscale numerical weather prediction are discussed. Thermodynamic profiler radiometers, infrared radiometer atmospheric sounders, Doppler radar wind profilers and surveillance radar, and moisture profilers are among the instruments described.
Mcpherson, R. D.
An update on multi-channel digital receiver development for the phased array radar at the National Weather Radar Testbed
This paper describes the beginning states of a new project that will digitize radar signals coming from eight channels on the phased array antenna at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. At the current time, a single-channel digital receiver is operational to mimic the current capability. The multi-channel digital data will foster a new generation of adaptive\\/fast
M. Yeary; J. Crain; A. Zahrai; R. Palmer; M. Xue; T.-Y. Yu; G. Zhang; Y. Zhang; R. Doviak; Q. Xu; P. Chilson
On the scale-dependent propagation of hydrologic uncertainty using high-resolution X-band radar rainfall estimates
NASA Astrophysics Data System (ADS)
Radar precipitation estimates can improve hydrologic prediction over a range of spatial scales represented by both rural and urban basins. Flooding results from the combination of heavy precipitation and the distributed hydraulic and hydrologic characteristics of the basin. Accuracy and spatial scaling of radar estimated rainfall, and its impact at relevant hydrologic scales is an important determinant of hydrologic prediction accuracy and flood forecasting. Results of simulations using archival radar events are used to demonstrate the sources of uncertainty affecting site-specific flood forecasts within the distributed hydrologic model, Vflo. Radar data used in this analysis are derived from both S-band (NEXRAD/88D) and the Collaborative Adaptive Sensing of the Atmosphere (CASA), polarimetric X-band radars. X-band radars have the capability to provide higher spatial and temporal resolution than the conventional radars operating at S-band. However, compared to S-band, X-band radars have shorter wavelengths and suffer from attenuation, or even total extinction of the radar signal at short ranges from the radar. Degradation of precipitation mapping is a serious concern, especially in heavy precipitation over distances associated with watersheds prone to flooding. Compared to rain gauge accumulations, X-band radar polarimetric rainfall estimates were significantly degraded beyond about 15 km from the radars. With rainfall input derived from X-band radars, uncertainty in runoff volume scales with watershed area as a smooth monotonically decreasing function as area increases due to averaging of random errors in the input. Relative to estimates derived from S-band radar, unreliable hydrograph response was produced using X-band polarimetric rainfall estimates as input to a physics-based distributed hydrologic model, especially for watershed areas less than about 20 km 2.
Vieux, B. E.; Imgarten, J. M.
Effects of rainfall on weathering rate, base cation provenance, and Sr isotope composition of Hawaiian soils
NASA Astrophysics Data System (ADS)
A climate transect across the Kohala Peninsula, Hawaii provides an ideal opportunity to study soil processes and evolution as a function of rainfall. The parent material is the �150 ka Hawi alkali basalt aa flow, and median annual precipitation (MAP) changes from �16 cm along the west coast to �450 cm in the rain forest near the crest of the peninsula. We measured labile (plant-available) base cation concentrations and 87Sr/ 86Sr ratios of labile strontium and silicate residue from soil profiles across the transect from 18 to 300 cm MAP. Depletion of labile cations and a shift in labile 87Sr/ 86Sr ratios toward rainwater values with increasing rainfall clearly show the transition from a mineral-supported to a rainwater-supported cation nutrient budget. In contrast, increases in soil silicate residue 87Sr/ 86Sr values with increasing MAP result primarily from input of exogenous eolian material (dust derived from Asian loess), with a greater dust fraction at the high MAP sites due to aerosol washout. Most of the soil silicate strontium in high-MAP sites is still derived from the original parent material, but the shallower portions of profiles can be dust-dominated. The variations in labile 87Sr/ 86Sr with rainfall allow us to calculate weathering rates as a function of MAP. The primary uncertainty is the degree to which Sr in rainwater actually interacts with the labile cation reservoir before being flushed from the system; mass balance calculations for the 150 ka evolution of the profile suggest that only on the order of 5 to 50% of rainwater strontium exchanges with the labile reservoir. Our models suggest that the present-day supply of strontium by weathering increases steadily with rainfall in the low-MAP (<140 cm) sites, then decreases dramatically as the soils become depleted in weatherable parent material. This implies that the initial weathering rate of the high-MAP sites was very high, and that there may be some change in soil weathering behavior in the 100 to 160 cm MAP range. Weathering rates calculated from the labile 87Sr/ 86Sr are on the same order as other estimates for chemical denudation rates of basaltic terrains.
Stewart, Brian W.; Capo, Rosemary C.; Chadwick, Oliver A.
Improved accuracy of radar WPMM estimated rainfall upon application of objective classification criteria
NASA Technical Reports Server (NTRS)
Application of the window probability matching method to radar and rain gauge data that have been objectively classified into different rain types resulted in distinctly different Z(sub e)-R relationships for the various classifications. These classification parameters, in addition to the range from the radar, are (a) the horizontal radial reflectivity gradients (dB/km); (b) the cloud depth, as scaled by the effective efficiency; (c) the brightband fraction within the radar field window; and (d) the height of the freezing level. Combining physical parameters to identify the type of precipitation and statistical relations most appropriate to the precipitation types results in considerable improvement of both point and areal rainfall measurements. A limiting factor in the assessment of the improved accuracy is the inherent variance between the true rain intensity at the radar measured volume and the rain intensity at the mouth of the rain guage. Therefore, a very dense rain gauge network is required to validate most of the suggested realized improvement. A rather small sample size is required to achieve a stable Z(sub e)-R relationship (standard deviation of 15% of R for a given Z(sub e)) -- about 200 mm of rainfall accumulated in all guages combined for each classification.
Rosenfeld, Daniel; Amitai, Eyal; Wolff, David B.
The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System
NASA Astrophysics Data System (ADS)
Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective, stratiform and undefined). These are then used to obtain coherent parameter sets for the radar reflectivity-rainfall rate (Z-R) and radar reflectivity-attenuation (Z-k) relationship, specifically applicable for this event. By applying a single parameter set to correct for both sources of errors, the quality of the rainfall product improves further, leading to >80% of the observed accumulations. However, by differentiating between precipitation type no better results are obtained as when using the operational relationships. This leads to the question: how representative are local disdrometer observations to correct large scale weather radar measurements? In order to tackle this question a Monte Carlo approach was used to generate >10000 sets of the normalized dropsize distribution parameters and to assess their impact on the estimated precipitation amounts. Results show that a large number of parameter sets result in improved precipitation estimated by the weather radar closely resembling observations. However, these optimal sets vary considerably as compared to those obtained from the local disdrometer measurements.
Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko
Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall
NASA Technical Reports Server (NTRS)
Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Our analysis of discrepancies between the PR rainfall and attenuation suggests that uncertainty in the assumed drop size distribution and associated attenuation/reflectivity/rainfall relationships inherent in single-frequency radar methods is a serious issue for studies of interannual variability.
Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.
Dual polarization radar rainfall estimation using the mean linear raindrop shape model
NASA Astrophysics Data System (ADS)
Information about the shape of raindrops is critical for estimating rainfall rate with dual polarization radar. As described in the literature, the relation describing drop oblateness as a function of its equivolumetric diameter is nonlinear. In fact, there is still no consensus regarding the most appropriate equation to use to describe the shape-size relation. However, while these non-linear equations are important for studying raindrop shape, it is not clear whether they are needed to estimate an integral quantity such as rainfall rate. A rain algorithm using Zh, and Zdr and an equivalent linear shape-size model with variable slope (?) that can be determined from an equation relating it to Zh, Zdr, and Kdp measurements is analyzed. To test its performance realistic rain and radar measurement profiles reconstructed from real radar observations were used. Starting from radar profiles collected by the NCAR S-POL dual polarization radar, two different sets of radar profiles were obtained for S-, C-, and X-band assuming the raindrop shape-size relations of Pruppacher and Beard (1970) and Beard and Chuang (1986). The first model is linear and the second is a non-linear one, expressed by a fourth order polynomial. The performance of the proposed rain algorithms based on ? is compared with that of algorithms derived assuming two drop shape relations expressed by a fourth order polynomial recently proposed. The simulation procedure allows the study of the influence of DSD variability as well as the effect of measurement errors on rain rate estimations. In general, it is possible to conclude that the rain algorithm based on an equivalent linear shape-size model performs better than the THBRS and BZV algorithms, since in worst cases, the performance of the ? algorithm is not too far from the performance of the standard rain algorithm obtained assuming the two non-linear shape size relations. In summary, although the literature indicates that the relation between oblateness and diameter of raindrops can be appropriately described by a nonlinear relation, the exact knowledge of this relation is not necessary in the case of estimation of an integral quantity such as the rainfall rate. Is fact, using a simple equivalent linear shape-size model can be convenient to obtain reliable estimations.
Gorgucci, E.; Baldini, L.; Romaniello, V.
Differences of Rainfall Estimates over Land by Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and TRMM Microwave Imager (TMI)Dependence on Storm Height
It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following
Fumie A. Furuzawa; Kenji Nakamura
Network connectivity paradigm for the large data produced by weather radar systems
NASA Astrophysics Data System (ADS)
The traffic over Internet is constantly increasing; this is due in particular to social networks activities but also to the enormous exchange of data caused especially by the so-called "Internet of Things". With this term we refer to every device that has the capability of exchanging information with other devices on the web. In geoscience (and, in particular, in meteorology and climatology) there is a constantly increasing number of sensors that are used to obtain data from different sources (like weather radars, digital rain gauges, etc.). This information-gathering activity, frequently, must be followed by a complex data analysis phase, especially when we have large data sets that can be very difficult to analyze (very long historical series of large data sets, for example), like the so called big data. These activities are particularly intensive in resource consumption and they lead to new computational models (like cloud computing) and new methods for storing data (like object store, linked open data, NOSQL or NewSQL). The weather radar systems can be seen as one of the sensors mentioned above: it transmit a large amount of raw data over the network (up to 40 megabytes every five minutes), with 24h/24h continuity and in any weather condition. Weather radar are often located in peaks and in wild areas where connectivity is poor. For this reason radar measurements are sometimes processed partially on site and reduced in size to adapt them to the limited bandwidth currently available by data transmission systems. With the aim to preserve the maximum flow of information, an innovative network connectivity paradigm for the large data produced by weather radar system is here presented. The study is focused on the Monte Settepani operational weather radar system, located over a wild peak summit in north-western Italy.
Guenzi, Diego; Bechini, Renzo; Boraso, Rodolfo; Cremonini, Roberto; Fratianni, Simona
Ranger� - An Affordable, Advanced, Next-Generation, Dual-Pol, X-Band Weather Radar
NASA Astrophysics Data System (ADS)
The Enterprise Electronics Corporation (EEC) Ranger� system is a new generation, X-band (3 cm), Adaptive Polarization Doppler Weather Surveillance Radar that fills the gap between high-cost, high-power traditional radar systems and the passive ground station weather sensors. Developed in partnership with the University of Oklahoma Advanced Radar Research Center (ARRC), the system uses relatively low power solid-state transmitters and pulse compression technology to attain nearly the same performance capabilities of much more expensive traditional radar systems. The Ranger� also employs Adaptive Dual Polarization (ADP) techniques to allow Alternating or Simultaneous Dual Polarization capability with total control over the transmission polarization state using dual independent coherent transmitters. Ranger� has been designed using the very latest technology available in the industry and the technical and manufacturing experience gained through over four decades of successful radar system design and production at EEC. The entire Ranger� design concept emphasizes precision, stability, reliability, and value using proven solid state technology combined with the most advanced motion control system ever conceived for weather radar. Key applications include meteorology, hydrology, aviation, offshore oil/gas drilling, wind energy, and outdoor event situational awareness.
Stedronsky, Richard
On Utilization of NEXRAD Scan Strategy Information to Infer Discrepancies Associated With Radar and Rain Gauge Surface Volumetric Rainfall Accumulations
NASA Technical Reports Server (NTRS)
To evaluate the Tropical Rainfall Measuring Mission (TRMM) monthly Ground Validation (GV) rain map, 42 quality controlled tipping bucket rain gauge data (1 minute interpolated rain rates) were utilized. We have compared the gauge data to the surface volumetric rainfall accumulation of NEXRAD reflectivity field, (converting to rain rates using a 0.5 dB resolution smooth Z-R table). The comparison was carried out from data collected at Melbourne, Florida during the month of July 98. GV operational level 3 (L3 monthly) accumulation algorithm was used to obtain surface volumetric accumulations for the radar. The gauge records were accumulated using the 1 minute interpolated rain rates while the radar Volume Scan (VOS) intervals remain less than or equal to 75 minutes. The correlation coefficient for the radar and gauge totals for the monthly time-scale remain at 0.93, however, a large difference was noted between the gauge and radar derived rain accumulation when the radar data interval is either 9 minute, or 10 minute. This difference in radar and gauge accumulation is being explained in terms of the radar scan strategy information. The discrepancy in terms of the Volume Coverage Pattern (VCP) of the NEXRAD is being reported where VCP mode is ascertained using the radar tilt angle information. Hourly radar and gauge accumulations have been computed using the present operational L3 method supplemented with a threshold period of +/- 5 minutes (based on a sensitivity analysis). These radar and gauge accumulations are subsequently improved using a radar hourly scan weighting factor (taking ratio of the radar scan frequency within a time bin to the 7436 total radar scans for the month). This GV procedure is further being improved by introducing a spatial smoothing method to yield reasonable bulk radar to gauge ratio for the hourly and daily scales.
Roy, Biswadev; Datta, Saswati; Jones, W. Linwood; Kasparis, Takis; Einaudi, Franco (Technical Monitor)
Operational Wind Retrieval Within the Frame of the French Weather Radar Network
NASA Astrophysics Data System (ADS)
The recent deployment of an innovative triple-PRT Doppler scheme within the French operational radar network, named ARAMIS, allows collecting reflectivity and radial velocity measurements simultaneously up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of exploitation of operational radar measurements such as the long-anticipated capability to perform multiple-Doppler wind retrieval in a fully operational framework. Accordingly, and for the first time ever, a method allowing to consistently retrieve complete wind vector fields (u, v, w) in real-time from operational radar systems is being tested by the French national weather service since early 2007. This study proposes to describe the experimental setup relied upon to operationally retrieve multiple-Doppler winds in the frame of ARAMIS, as well as to investigate the potential of this new product for weather forecast applications. Using high resolution numerical wind forecasts in a variety of weather situations, we also show that these radar-derived wind fields compose unprecedented datasets to evaluate and further improve high-resolution numerical weather prediction systems being currently deployed by many national weather services.
Bousquet, O.; Tabary, P.; Parent-Du-Ch�telet, J.; P�rier, L.
Simultaneous ocean cross section and rainfall measurements from space with a nadir-looking radar
NASA Technical Reports Server (NTRS)
In the case of a nadir-looking spaceborne or aircraft radar in the presence of rain, the return power corresponding to secondary surface scattering may provide information on the properties of the surface and the precipitation. The object of the study is to evaluate a method for determining simultaneously the rainfall rate and the backscattering coefficient of the surface. The method is based upon the mirror-reflected power, which corresponds to the portion of the incident power scattered from the surface to the precipitation, intercepted by the precipitation, and again returned to the surface where it is scattered a final time back to the antenna.
Meneghini, Robert; Atlas, David
Estimates of GATE convective and stratiform rainfall derived from radar and satellite data
NASA Technical Reports Server (NTRS)
The statistics of tropical rain system structure are studied, focusing on the division between convective and stratiform rainfall over the GARP Atlantic Tropical Experiment B-scale array. The satellite IR convective/stratiform technique of Adler and Negri (1988) is used to produce hourly estimates for two day of the GATE. The estimates are verified against the radar data. The results are compared with the results of Houze and Rappaport (1984) and Cheng and Houze (1979). The possible application of the results for estimating the vertical profile of latent heating is discussed.
Negri, Andrew J.; Adler, Robert F.
Estimation of Rainfall Kinetic Energy by Rain Intensity and/or Radar Reflectivity Factor
NASA Astrophysics Data System (ADS)
This study presents an approach to estimate the rainfall kinetic energy (KE) by rain intensity (R) and radar reflectivity factor (Z) separately, or jointly, on the basis of a one- or two-moment scaled formulation. This formulation considers the raindrop size distribution (DSD) as a combination of bulk rainfall variable(s) (R or/and Z) and an intrinsic distribution g(x), which is in function of the scaled raindrop diameter x. Results from previous studies showed that g(x) remains more or less constant, hence the variability of DSD is mainly explained by the bulk rainfall variable(s). In this study, the Gamma probability density function (pdf) with two parameters is used to model the g(x). Considered the self-consistent relationships between parameters, a robust method is proposed to estimate three climatological g(x), in R-, Z- and RZ-scaled formulation respectively, with a 28-month DSD dataset collected in the Cevennes-Vivarais region, France. Three relationships (KE-R, KE-Z and KE-(R,Z)), which link the observations (R and/or Z) to rainfall kinetic energy (KE), are established based on three climatological g(x). As expected, the combination of R and Z yields a significant improvement of the estimation of KE compared to the single-moment formulations. And Z yields a better performance in KE estimating compared to the KE-R relationship. In terms of the application of these relationships based on real radar reflectivity factors and/or rain gauge measurements, the combination of R and Z yields also the best performance in estimation of KE among the three relationships. Different from the application of the disdrometer data, the performance of the real KE-Z relationship degrades compared to the real KE-R relationship, which is probably due to the sampling error of radar. However, KE estimated by radar possess the advantages in spatialization of kinetic energy over that based on rain gauge stations. This study was supported financially by the HYDRATE project of the European Community (GOCE 037024). The first author would also like to thank the SOERE RBV project which provides the travel grants for participation in AGU meeting.
Yu, N.; Delrieu, G.; Boudevillain, B.; Hazenberg, P.; Uijlenhoet, R.
Wideband Waveform Design principles for Solid-state Weather Radars
The use of solid-state transmitter is becoming a key part of the strategy to realize a network of low cost electronically steered radars. However, solid-state transmitters have low peak powers and this necessitates the use of pulse compression waveforms. In this paper a frequency diversity wideband waveforms design is proposed to mitigate low sensitivity of solid-state transmitters. In addition, the waveforms mitigate the range eclipsing problem associated with long pulse compression. An analysis of the performance of pulse compression using mismatched compression filters designed to minimize side lobe levels is presented. The impact of range side lobe level on the retrieval of Doppler moments are presented. Realistic simulations are performed based on CSU-CHILL radar data and Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) radar data.
Bharadwaj, Nitin; Chandrasekar, V.
Weathering-limited rainfall-triggered shallow mass movements in undisturbed steepland tropical rainforest
NASA Astrophysics Data System (ADS)
Rainfall-triggered landslides in undisturbed tropical rainforests may have been underestimated as contributors to slope development and denudation in the past. Theoretically, ideal conditions for such geomorphic processes, i.e. steep slopes and frequent high magnitude and intensity rainfall events, occur in a number of tropical regions, particularly within Southeast Asia. Therefore, a high frequency of occurrence of shallow slope failures was expected in the undisturbed steeplands of southeast Brunei. Stability conditions of the steep planar slopes were examined using a deterministic modelling approach in order to examine the possibility that most slopes could not fail in response to rainfall because they did not possess a sufficiently thick mantle of residual soil. A simple hillslope hydrology model based on a soil moisture balance approach was used to simulate hillslope responses to measured and simulated rainfall events. The stability of saturated slopes could then be analysed using the infinite slope model, the input shear strength parameters for which were obtained from direct shear tests and then calibrated by back-analysis of a failure which occurred in late 1991. The findings suggest that any slope of 40� and steeper should fail several times every year in response to storm events, but that in reality most of the slopes have failed previously and have not yet regained a critical depth of residual soil. Some approximate values for rates of weathering and slope development suggest that any given slope will not fail at intervals of less than 10,000 years. Therefore, the occurrence of shallow failures will be infrequent but nevertheless significant in terms of regional denudation and ecological diversity.
Dykes, A. P.
National Scale Rainfall Map Based on Linearly Interpolated Data from Automated Weather Stations and Rain Gauges
NASA Astrophysics Data System (ADS)
In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.
Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay
New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping
NASA Astrophysics Data System (ADS)
One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date the most effective methods for large scale rainfall estimates are radar, satellites, and more recently, received signal level (RSL) measurements received from commercial microwave networks (CMN). While these methods provide improved spatial resolution over traditional rain gauges, these have their limitations as well. For example, the wireless CMN, which are comprised of microwave links (ML), are dependant upon existing infrastructure, and the ML arbitrary distribution in space. Radar, on the other hand, is known in its limitation in accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rain fall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that by using the proposed new method we not only generate a more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show an improvement of rain rate estimation over CMN or radar alone, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, and the accurate rainfall measurements over large areas at sub-hourly time scales, will allow for improved understanding, initialization and calibration of hydrological and meteorological models necessary, mainly, for water resource management and planning.
Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.
Model-Based Weather Radar Remote Sensing of Explosive Volcanic Ash Eruption
Microphysical and dynamical features of volcanic ash clouds can be quantitatively monitored by using ground-based microwave weather radars. These systems can provide data for determining the ash volume, total mass, and height of eruption clouds. In order to demonstrate the unique potential of this microwave active remote-sensing technique, the case study of the eruption of Augustine Volcano in Alaska in
Frank Silvio Marzano; Sara Marchiotto; Christiane Textor; David J. Schneider
Velocity and acceleration estimation of Doppler weather radar\\/lidar signals in colored noise
The authors are interested in estimating the Doppler shift occurred in weather radar returns, which yields precipitation velocity information. Conventional techniques including the pulse pair processor rely heavily on the assumption that the additive noise is white and hence their performance degrades when the noise color is unknown. Because the data length for a given range gate is usually small,
Weige Chen; Guotong Zhou; G. B. Giannakis
A methodology for calculating the interference of wind farm on weather radar
Wind turbines may degrade the quality of the hydro-meteorological data obtained by weather radars. This degradation is difficult to estimate, and it is necessary to develop a procedure to obtain accurate results of the reflectivity values from the wind turbines and the affected area. This contribution outlines a methodology to estimate the clutter generated by a specific wind farm on
Fergal Darcy; David de la Vega
A System Concept for the Advanced Post-TRMM Rainfall Profiling Radars
NASA Technical Reports Server (NTRS)
Atmospheric latent heating field is fundamental to all modes of atmospheric circulation and upper mixed layer circulations of the ocean. The key to understanding the atmospheric heating process is understanding how and where precipitation occurs. The principal atmospheric processes which link precipitation to atmospheric circulation include: (1) convective mass fluxes in the form of updrafts and downdrafts; (2) microphysical. nucleation and growth of hydrometeors; and (3) latent heating through dynamical controls on the gravitation-driven vertical mass flux of precipitation. It is well-known that surface and near-surface rainfall are two of the key forcing functions on a number of geophysical parameters at the surface-air interface. Over ocean, rainfall variation contributes to the redistribution of water salinity, sea surface temperature, fresh water supply, and marine biology and eco-system. Over land, rainfall plays a significant role in rainforest ecology and chemistry, land hydrology and surface runoff. Precipitation has also been closely linked to a number of atmospheric anomalies and natural hazards that occur at various time scales, including hurricanes, cyclones, tropical depressions, flash floods, droughts, and most noticeable of all, the El Ninos. From this point of view, the significance of global atmospheric precipitation has gone far beyond the science arena - it has a far-reaching impact on human's socio-economic well-being and sustenance. These and many other science applications require the knowledge of, in a global basis, the vertical rain structures, including vertical motion, rain intensity, differentiation of the precipitating hydrometeors' phase state, and the classification of mesoscale physical structure of the rain systems. The only direct means to obtain such information is the use of a spaceborne profiling radar. It is important to mention that the Tropical Rainfall Measuring Mission (TRMM) have made a great stride forward towards this ultimate goal. The Precipitation Radar (PR) aboard the TRMM satellite is the first ever spaceborne radar dedicated to three-dimensional, global precipitation measurements over the tropics and the subtropics, as well as the detailed synopsis of a wide range of tropical rain storm systems. In only twelve months since launch, the PR, together with other science instruments abroad the satellite have already provided unprecedented insights into the rainfall systems. It is anticipated the a lot more exciting and important rain observations would be made by TRMM throughout its mission duration. While TRMM has provided invaluable data to the user community, it is only the first step towards advancing our knowledge on rain processes and its contributions to climate variability. It is envisioned that a TRMM follow-on mission is needed in such a way to capitalize on the pioneering information provided by TRMM, and its instrument capability must be extended beyond TRMM in such a way to fully address the key science questions from microphysical to climatic time scale. In fact, a number of new and innovative mission concepts have recently put forth for this purpose. Almost all of these new concepts have suggested the utility of a more advanced, high-resolution, Doppler-enabled, vertical profiling radar that can provide multi-parameter observations of precipitation. In this paper, a system concept for a second- gene ration precipitation radar (PR-2) which addresses the above requirements will be described.
Im, Eastwood; Smith, Eric A.
Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar
NASA Astrophysics Data System (ADS)
The NASA TRMM satellite has provided unprecedented data for over 11 years. TRMM precipitation products have advanced our understanding of tropical precipitation considerably. Field programs in the tropics, specifically TRMM-LBA (January-February 1999 in Brazil; a TRMM ground validation experiment) and NAME (North American Monsoon Experiment, summer 2004 along the west coast of Mexico) have provided opportunities to investigate the characteristics of precipitation using S-band polarimetric radar data. Both of these locales feature heavy, monsoon-like precipitation. However, there is significant variability in precipitation in these regions. In Brazil, two distinct rainfall regimes were observed. During "easterly" phase periods, precipitation was continental like, featuring deep, intense convection. During "westerly" periods, precipitation was more oceanic like, featuring weaker convection embedded in widespread stratiform precipitation. In NAME, precipitation variability was forced more by terrain, opposed to synoptic conditions, as was the case in Brazil. The National Center for Atmospheric Research S-pol radar was used to diagnose precipitation characteristics. Larger drops, larger ice mass aloft, and larger rain contents were found in the TRMM-LBA easterly phases compared to westerly events. For NAME, larger drops, larger ice mass aloft, and larger rain contents were found for coastal plain convection compared to convection over the higher terrain of the Sierra Madre Occidental or adjacent coastal waters. The effects of these differences on TRMM Precipitation Radar based rainfall estimates are investigated. These microphysical differences suggest the use of different Z-R estimators as a function of regime and elevation. It appears that the TRMM attenuation correction is inadequate for intense convection observed in these two regions.
Rutledge, S. A.; Cifelli, R.; Lang, T.; Nesbitt, S.
A Gaussian field for aggregation and disaggregation of radar rainfall data
NASA Astrophysics Data System (ADS)
The generation of reliable precipitation products that explicitly account for spatial and temporal structures of precipitation events is challenging, since it requires a combination of data with a variety of error structures and temporal resolutions. In-situ measurements are relatively accurate quantities, but available only at sparse and irregularly distributed locations. Remote measurements cover complete areas but suffer from spatially and temporally inhomogeneous systematic errors and non-linear relations between the measured value reflectivity and the precipitation rate. Our aim is to provide a statistical model based on a latent Gaussian random field that suitably models radar precipitation rates and enables us to aggregate and disaggregate them in space and time. We first transform radar rainfall rates such that they follow a truncated Gaussian distribution using a power transformation proposed by D. Allcroft and C. Glasbey (2003). The advantage of using a truncated Gaussian random field is that occurrence and intensity of rainfall are modeled using a single process. To parameterize the latent Gaussian random field we estimate the empirical correlation as function of lag distance in space using the maximum likelihood method and fit a parametric correlation function to the estimates. This yields a spatial Gaussian random field. The transformation only allocates censored values to dry locations, i.e. the locations below some threshold. In order to obtain a Gaussian random field that covers the whole domain, we need to simulate the unobserved values below the threshold conditional on the observed values. The parametrically defined Gaussian random field now allows us to aggregate and disaggregate the radar measurements to different scales and compare them to measurements from ground based instruments.
Krebsbach, Katharina; Friederichs, Petra
The Federal Aviation Administration/Massachusetts Institute of Technology (FAA/MIT) Lincoln Laboratory Doppler weather radar program
NASA Astrophysics Data System (ADS)
The program focuses on providing real-time information on hazardous aviation weather to end users such as air traffic control and pilots. Existing systems will soon be replaced by a Next Generation Weather Radar (NEXRAD), which will be concerned with detecting such hazards as heavy rain and hail, turbulence, low-altitude wind shear, and mesocyclones and tornadoes. Other systems in process are the Central Weather Processor (CWP), and the terminal Doppler weather radar (TDWR). Weather measurements near Memphis are central to ongoing work, especially in the area of microbursts and wind shear.
Evans, James E.
The Federal Aviation Administration/Massachusetts Institute of Technology (FAA/MIT) Lincoln Laboratory Doppler weather radar program
NASA Technical Reports Server (NTRS)
The program focuses on providing real-time information on hazardous aviation weather to end users such as air traffic control and pilots. Existing systems will soon be replaced by a Next Generation Weather Radar (NEXRAD), which will be concerned with detecting such hazards as heavy rain and hail, turbulence, low-altitude wind shear, and mesocyclones and tornadoes. Other systems in process are the Central Weather Processor (CWP), and the terminal Doppler weather radar (TDWR). Weather measurements near Memphis are central to ongoing work, especially in the area of microbursts and wind shear.
Evans, James E.
Networked weather radar system using coherent on receive technology
The Engineering Research Center for Collaborative Adapting Sensing of the Atmosphere (CASA) was established to improve the coverage of the lowest portion of the atmosphere through coordinated scanning of low-power, short-range, networked radars (referred to as Distributed Collaborative Adaptive Sensing (DCAS)). The first DCAS technology demonstration test-bed has been deployed in south-west Oklahoma in early 2006: a network of four,
Francesc Junyent
Comparison of Radar Rainfall Retrieval Algorithms in Convective Rain During TOGA COARE
NASA Technical Reports Server (NTRS)
The authors compare deterministic and stochastic rain-rate retrieval algorithms by applying them to 14-GHz nadir-looking airborne radar reflectivity profiles acquired in tropical convective rain during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment, The deterministic algorithms both use the path-integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the k-R relation, while the second corrects the Z-R relation. The stochastic algorithms are based on applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA, The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions.
Durden, Stephen L.; Haddad, Z. S.
Navigation errors encountered using weather-mapping radar for helicopter IFR guidance to oil rigs
NASA Technical Reports Server (NTRS)
In 1978 a joint NASA-FAA helicopter flight test was conducted to examine the use of weather-mapping radar for IFR guidance during landing approaches to oil rig helipads. The following navigation errors were measured: total system error, radar-range error, radar-bearing error, and flight technical error. Three problem areas were identified: (1) operational problems leading to pilot blunders, (2) poor navigation to the downwind final approach point, and (3) pure homing on final approach. Analysis of these problem areas suggests improvement in the radar equipment, approach procedure, and pilot training, and gives valuable insight into the development of future navigation aids to serve the off-shore oil industry.
Phillips, J. D.; Bull, J. S.; Hegarty, D. M.; Dugan, D. C.
On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar on TRMM
NASA Technical Reports Server (NTRS)
This study represents one of the first published attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Data from the first space-based rain-radar, the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of the data enables identification of rainfall patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage chances are relative to an upwind CONTROL area. It was also found that maximum rainfall rates in the downwind impact area can exceed the mean value in the upwind CONTROL area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are consistent with METROMEX studies of St. Louis almost two decades ago and more recent studies near Atlanta. Future work will investi(yate hypothesized factors causing rainfall modification by urban areas. Additional work is also needed to provide more robust validation of space-based rain estimates near major urban areas. Such research has implications for urban planning, water resource management, and understanding human impact on the environment.
Shepherd, J. Marshall; Pierce, Harold; Starr, David OC. (Technical Monitor)
Spatial-Temporal Evolution of Water Vapor during a Heavy Rain Detected by InSAR, GPS and Weather Radar
NASA Astrophysics Data System (ADS)
Interferometric Synthetic Aperture Radar (InSAR) phase signals are used to map the Earth's surface deformation, but are also affected by Earth's atmosphere. In particular, the heterogeneity of water vapor near the surface causes unpredictable phase changes in InSAR data. In the absence of deformation signals and other errors, InSAR can provide us with a spatial distribution of precipitable water vapor with unprecedented spatial resolution. On 2 September 2008, a torrential rain struck wide areas over central Japan, and Japan Aerospace exploration Agency (JAXA) carried out an emergent observation of the heavy rains by PALSAR, an L-band synthetic aperture radar sensor. On January 2010, JAXA has carried out another PALSAR measurement of the very areas, so that we could generate InSAR image of the area and examine the detailed snapshot of the regional troposphere; the weather on January 21 2010 was dry and stable. Near the Ibi River, we detected localized signals, whose amplitude reached 12.2 cm in radar line-of-sight over a spatial scale on the order of 8 km, and were unlikely to be an artifact of either ground deformation, DEM errors, or ionosphere. In our previous report (Kinoshita et al., 2010 AGU Fall Meeting), we validated this point, having shown other independent InSAR images as well as azimuth component of pixel-offset data. Then we concluded that the signal was due to the localized water vapor distribution associated with the heavy rain on September 2008. Now we compare the tropospheric delay in InSAR data with those derived from the GEONET data, the Japanese nationwide GPS network. The principle of atmospheric propagation delay in GPS is inherently the same as that of InSAR, and thus it is worth to compare the tropospheric delay data derived from GPS with those from InSAR. In this study, we generated GPS zenith total delay (ZTD) by using precise point positioning (PPP) processing. The ZTD time series of the GEONET station 950291 (Tarui) near the signal in InSAR revealed a rapid decrease in the amount of about 4 cm for 2 hours before SAR data was acquired. Additionally, we generated weather radar (WR) echo image at the moment of SAR data acquisition to compare this with the InSAR and GPS data. In the WR image, the small area with rainfall intensity greater than 80 mm/h exists at the location of tropospheric signal in InSAR. We will discuss what we can learn from InSAR, GPS and WR data.
Kinoshita, Y.; shimada, M.; Furuya, M.
A spatial daily rainfall model for interpolation of raingauge networks using artificial radar fields, for realistic hydrological modelling
NASA Astrophysics Data System (ADS)
The inherent patchiness and intermittency of daily rainfall make interpolation of sparse point measurements over a catchment very challenging. Usual methods of interpolation of daily rainfall vary from simple numerical averaging through the use of Thiessen polygons to advanced statistical methods such as Kriging. This presentation treats the interpolation problem by conditioning plausible replicas of radar-rainfields on to the point observations and examines the effectiveness of the process by cross-validation. The issues addressed include: * we use Kriging but we first Gaussianise the point rainfall data with special treatment of the zeros to eliminate skewness * Kriging gives us estimates of error in the Gaussian domain to show how good/bad are the interpolations and also offers the standard deviation at each pixel in the field * we choose the form of the [co]variogram to be used in Kriging so as to mimic nature, by using spatial observations given us by radar * the spatial structure of radar rainfall images is peculiar to the accumulation time: instantaneous radar images do not have appreciable spatial anisotropy * by contrast, morphed hourly and daily accumulations of radar images exhibit strong spatial anisotropy * we determine the characteristics of the daily accumulations of radar rainfall and find the spatial correlogram characteristics [orientation, range and ratio of minor to major axes] in the chosen region are strongly related to the radar wetted area ratio: RWAR * to proceed, we simulate correlograms for the chosen day based on the RWAR which is related to the gauge wetness ratio * simulate Gaussian radar fields based on the RWAR with the same variance as the Kriged interpolations of the point values and conditionally merge them with the gauge values, be they observations or simulations * to evaluate the worth of the process, we perform cross-validation of spatial field estimates against gauge values in 'leave-one-out' exercises * the methodology is designed to give a measure of the hydrological response's sensitivity to the uncertainty of spatial interpolation of gauge network rainfall [observed or simulated] by simulating many conditioned spatial replicates, each of which is plausible
Pegram, Geoff; Gyasi-Agyei, Yeboah
The Polarimetric Radar Estimation of Rainfall over the Amazon during TRMM-LBA
NASA Astrophysics Data System (ADS)
The Tropical Rainfall Measuring Mission (TRMM) is a NASA satellite project initiated to address a gap in our ability to accurately observe detailed rainfall patterns over the tropical continents and oceans. To support TRMM, several field campaigns were conducted. The TRMM-LBA (Large-scale Biosphere Atmosphere) experiment was conducted over the southwestern region of the Amazon (state of Rondonia, Brazil) in order to provide detailed information on the precipitation characteristics in the interior of a tropical continent. Information from TRMM-LBA will be used for validation of TRMM satellite products and for initialization and validation of cloud-resolving models and passive microwave retrieval algorithms. During the TRMM-LBA field campaign, a variety of instrumentation was deployed during the wet season (January - February 1999) to measure rainfall including several rain gauge networks, disdrometers, and the S-band polarimetric (NCAR S-POL) research radar. The focus of this study will be on the estimation, validation, and uncertainty of rain rate estimates derived from the NCAR S-POL radar. The S-POL data were carefully corrected for the presence of clear-air echo, ground clutter, anomalous propagation, partial beam blocking, precipitation attenuation, and calibration biases by applying polarimetric radar methods. Using an optimal polarimetric radar technique, maps of rain rate have been calculated from observations of S-POL horizontal reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) every ten minutes from 10 January to 28 February 1999. From these rain rate estimates, daily and 30-day rain accumulation maps have been compiled. When validated against the rain gauge totals, preliminary S-POL estimates of monthly rainfall, which utilized the equilibrium raindrop shape model of Beard and Chuang (1987), have a negative bias error in the range of -5% to -11% and a standard error of 14% to 20%. We will compare these results with the methodology of Gorgucci et al. (2000, 2001), which attempts to account for the variability in the raindrop shape-size relation. Some practical issues involved in the implementation of this method will be discussed. Finally, we will present preliminary attempts to estimate the uncertainty of the rain rates at each grid point following Bringi and Chandrasekar (2001, Ch. 8). As in BC2001, the uncertainty will be expressed as the standard deviation of R divided by R (? (R)/R). The uncertainty will be based on 1) the polarimetric algorithm and measurements utilized in the optimal rain rate approach at each point, 2) an estimate of error associated with measurement error as a function of rain rate, and 3) an estimate of the error associated with the utilized algorithm as a function of rain rate. Since there is inherent ambiguity in estimating uncertainty in this manner, we will also experiment with converting ? (R)/R into a qualitative uncertainty index (UI) ranging from 1 to 5, where 1 is very certain and 5 is very uncertain.
Carey, L. D.; Cifelli, R.; Petersen, W. A.; Rutledge, S. A.
Imaging eruption columns from the 2009 eruption of Redoubt Volcano, Alaska using Doppler weather radar
NASA Astrophysics Data System (ADS)
The U.S. Geological Survey deployed a dedicated volcano-monitoring Doppler weather radar system during the 2009 eruption of Redoubt Volcano, Alaska, enabling the collection of an unprecedented radar data set of seventeen explosive events. Radar reflectivity and radial Doppler velocity measurements were made of the column every 70-90 seconds at a vertical resolution of about 2 km. This temporal frequency is 3-6 times higher than what can be achieved by the national system of weather radars (i.e. NEXRAD), and allows for more robust comparisons with traditional geophysical monitoring data from seismic, pressure sensor, web camera and satellite images. The MiniMax-250C radar detected the eruption columns from explosive events with maximum altitudes of 9-19 km above sea level. We describe the preliminary results on imaging these eruption columns. Most of the explosive events were characterized by high radar reflectivity values of 50-60 dBZ in the central core of the eruption column and proximal cloud, which we interpret to be related to the rapid growth of tephra-ice aggregates. Time-series of radial Doppler velocity images documented the transition from turbulent mixing in the column to more uniform expansion of the proximal cloud. Vertical velocities of the eruption column top were estimated from observation of cloud rise in the reflectivity images and ranged from about 25-60 m/s. The duration of the eruptive events ranged from minutes to tens of minutes. Radar-derived duration estimates did not correlate well with seismic and pressure sensor derived durations. The observed maximum column heights were generally higher (perhaps 20% or more) than would be predicted for the mass eruption rate estimated from the mapped deposits.
Schneider, D. J.; Mastin, L. G.
Time-lapse borehole radar for monitoring rainfall infiltration through podosol horizons in a sandy vadose zone
NASA Astrophysics Data System (ADS)
shallow aquifer on the Gnangara Mound, north of Perth, Western Australia, is recharged by winter rainfall. Water infiltrates through a sandy Podosol where cemented accumulation (B-) horizons are common. They are water retentive and may impede recharge. To observe wetting fronts and the influence of soil horizons on unsaturated flow, we deployed time-lapse borehole radar techniques sensitive to soil moisture variations during an annual recharge cycle. Zero-offset crosswell profiling (ZOP) and vertical radar profiling (VRP) measurements were performed at six sites on a monthly basis before, during, and after annual rainfall in 2011. Water content profiles are derived from ZOP logs acquired in closely spaced wells. Sites with small separation between wells present potential repeatability and accuracy difficulties. Such problems could be lessened by (i) ZOP saturated zone velocity matching of time-lapse curves, and (ii) matching of ZOP and VRP results. The moisture contents for the baseline condition and subsequent observations are computed using the Topp relationship. Time-lapse moisture curves reveal characteristic vadose zone infiltration regimes. Examples are (I) full recharge potential after 200 mm rainfall, (II) delayed wetting and impeded recharge, and (III) no recharge below 7 m depth. Seasonal infiltration trends derived from long-term time-lapse neutron logging at several sites are shown to be comparable with infiltration trends recovered from time-lapse crosswell radar measurements. However, radar measurements sample a larger volume of earth while being safer to deploy than the neutron method which employs a radioactive source. For the regime (III) site, where time-lapse radar indicates no net recharge or zero flux to the water table, a simple water balance provides an evapotranspiration value of 620 mm for the study period. This value compares favorably to previous studies at similar test sites in the region. Our six field examples demonstrate application of time-lapse borehole radar for characterizing rainfall infiltration.
Strobach, Elmar; Harris, B. D.; Dupuis, J. C.; Kepic, A. W.
A TRMM Precipitation Radar-Calibrated Passive Microwave Algorithm for Overland Rainfall Estimation
NASA Astrophysics Data System (ADS)
The Tropical Rainfall Measuring Mission (TRMM) satellite carries a combination of active (Precipitation Radar, PR) and multi-channel TRMM microwave imager (TMI) sensors. These sensors advance our ability to estimate rainfall over land. Rain retrieval from PR is associated with an unprecedented accuracy. The primary aspects of PR retrieval are the precipitation classification, which is facilitated by the high vertical resolution (250 meters) reflectivity profile measurements, and an inversion algorithm controlled by a surface reference technique for path integrated attenuation and a reflectivity-to-rainfall relationship with parameters differentiated for convective and stratiform rain regimes. But is limited in terms of sampling due to the narrow PR swath width (215 km). On the other hand, TMI provides wider coverage (760 km), but its observations are associated with a more complex relationship to precipitation compared to PR (especially over land). PR rain estimates are used here for calibrating an overland TMI rain algorithm. The major objective is to investigate the regional variability in terms of the retrieval parameters and its significance to the accuracy of rain estimation. Four geographic regions consisting of Africa (AFC), Amazon (AMZ), continental US (USA), and the Ganges-Brahmaputra-Meghna (GBM) river basin in South Asia are selected. A parameter based rain algorithm is developed that includes (1) multi-channel based rain screening and convective/stratiform (C/S) classification schemes, and (2) non-linear (linear) regressions for rain rate retrieval of stratiform (convective) rain regimes. For rain rate estimation we used the 37 GHz channel for AFC, AMZ and USA regions and the 85 GHz channel for GBM region. The algorithm performance is evaluated against the latest (Version 6) TRMM-2A12 product in terms of rain detection and rain rate retrieval error statistics using PR rainfall as reference. The algorithm performs better than 2A12 V6 with the major improvement being the decrease in the retrieval error variance (correlation to PR rainfall), which is about 40% for three of the regions (USA, AFC and AMZ) and 167% for GBM. Comparison of a global versus regionally varied calibration has yielded varying performance dependence on regional calibration. Specifically, the regional calibration significance on the retrieval accuracy is low for two of the regions (AFC and USA), while moderate and high for AMZ and GBM, respectively. These differences are ascribed to differences in convective activity, particularly differences above the freezing level and ice scattering regime. This study also stresses the importance of convective/stratiform rain type classification in the accuracy of PM retrievals.
Dinku, T.; Anagnostou, E. N.
Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data.
Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of predicting CSO depth with less than 5% error for predictions more than 1 hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems. PMID:24647201
Mounce, S R; Shepherd, W; Sailor, G; Shucksmith, J; Saul, A J
Next Generation Weather Radar (NEXRAD) Principal User Processor (PUP) Operational Test and Evaluation (OTE) Operational Test Plan.
National Technical Information Service (NTIS)
The purpose of this plan is to describe and detail the procedural approach, method, and responsibilities to be employed in conducting the Operational Test and Evaluation (OTE) on the Next Generation Weather Radar (NEXRAD) Principal User Processor (PUP) sy...
B. R. Stretcher
A High-Resolution 3D Weather Radar, MSG, and Lightning Sensor Observation Composite
NASA Astrophysics Data System (ADS)
Within the research group 'Object-based Analysis and SEamless prediction' (OASE) of the Hans Ertel Centre for Weather Research programme (HerZ), a data composite containing weather radar, lightning sensor, and Meteosat Second Generation observations is being developed for the use in object-based weather analysis and nowcasting. At present, a 3D merging scheme combines measurements of the Bonn and J�lich dual polarimetric weather radar systems (data provided by the TR32 and TERENO projects) into a 3-dimensional polar-stereographic volume grid, with 500 meters horizontal, and 250 meters vertical resolution. The merging takes into account and compensates for various observational error sources, such as attenuation through hydrometeors, beam blockage through topography and buildings, minimum detectable signal as a function of noise threshold, non-hydrometeor echos like insects, and interference from other radar systems. In addition to this, the effect of convection during the radar 5-minute volume scan pattern is mitigated through calculation of advection vectors from subsequent scans and their use for advection correction when projecting the measurements into space for any desired timestamp. The Meteosat Second Generation rapid scan service provides a scan in 12 spectral visual and infrared wavelengths every 5 minutes over Germany and Europe. These scans, together with the derived microphysical cloud parameters, are projected into the same polar stereographic grid used for the radar data. Lightning counts from the LINET lightning sensor network are also provided for every 2D grid pixel. The combined 3D radar and 2D MSG/LINET data is stored in a fully documented netCDF file for every 5 minute interval, and is made ready for tracking and object based weather analysis. At the moment, the 3D data only covers the Bonn and J�lich area, but the algorithms are planed to be adapted to the newly conceived DWD polarimetric C-Band 5 minute interval volume scan strategy. An extension of the 3D composite to all of Germany is therefore possible and set as a goal.
Diederich, Malte; Senf, Fabian; Wapler, Kathrin; Simmer, Clemens
Performances comparison of pulse pair and wavelets methods for the pulse Doppler weather radar spectrum
NASA Astrophysics Data System (ADS)
In the civilian aviation field, the radar detection of hazardous weather phenomena (winds) is very important. This detection will allow the avoidance of these phenomena and consequently will enhance the safety of flights. In this work, we have used the wavelets method to estimate the mean velocity of winds. The results showed that the application of this method is promising compared with the classical estimators (pulse pair, Fourier)
Lagha, M.; Tikhemirine, M.; Bergheul, S.; Rezoug, T.; Bettayeb, M.
Technological challenges of a multifunction active phased array radar for weather, air traffic control and security applications
By means of Active Phased Array techniques, an integrated target\\/weather surveillance at medium range, i.e. for Terminal Manoeuvre Area in the frame of ATC and regional weather monitoring, is possible and affordable provided that cost reduction for Transmit\\/Receive modules makes phased array radar affordable to civilian users. The MPAR (Multifunction Phased Array Radar) architecture allows a single equipment to satisfy
G. Galati; G. Pavan; S. Scopelliti; L. Infante
Comparison of linear and logarithmic receiver signals from polarimetric weather radar echoes and their temporal decorrelation properties
Usually common polarimetric weather radar DSP-products (e.g.: reflectivity, differential reflectivity, linear depolarisation ratio - for both - co-polar and cross-polar signal components) are based on the logarithmic receiver output, because of the large dynamic range provided by the logarithmic receiver. In this paper for the first time we also use the linear receiver output to calculate common weather radar DSP-Products.
P. Tracksdorf; A. Ghorbani; M. Chandra; M. Hagen; D. Bebbington
Results of the Kansas City 1989 Terminal Doppler Weather Radar (TDWR) operational evaluation testing
NASA Astrophysics Data System (ADS)
The Terminal Doppler Weather Radar (TDWR) testbed was used at the Kansas City International (KCI) airport during the summer of 1989. The objective was to test and refine previous tested techniques for the automatic detection of low-altitude wind shear phenomena (specifically microbursts and gun fronts) and heavy precipitation in a midwest weather environment, as well as to assess possible new products such as storm movement predictions. A successful operation evaluation of the TDWR products took place at the KCI tower and terminal radar control room (TRACON). Several supervisor and controller display refinements were assessed as effective. The system was successful in terms of aircraft at KCI avoiding wind shear encounters during the operational period, and it was assessed as very good in usefulness for continuing operation by the KCI air traffic control (ATC) personnel. The probability of detection for microbursts was substantially better than that in Denver. However, the false-alarm probability was found to be substantially higher in Kansas City due to a combination of weather and clutter phenomena. By optimizing the site-adaptation capabilities of the TDWR meteorological and data quality algorithms, the required false-alarm probability was achieved. The gust front performance was generally poorer than in Denver due to a combination of unfavorable radar-airport-gust front geometry of false alarms induced by low-level jets. Gust front algorithm refinements which should provide improved performance are discussed.
Evans, J. E.
Flight investigation of helicopter IFR approaches to oil rigs using airborne weather and mapping radar
NASA Technical Reports Server (NTRS)
Airborne weather and mapping radar is a near-term, economical method of providing 'self-contained' navigation information for approaches to offshore oil rigs and its use has been rapidly expanding in recent years. A joint NASA/FAA flight test investigation of helicopter IFR approaches to offshore oil rigs in the Gulf of Mexico was initiated in June 1978 and conducted under contract to Air Logistics. Approximately 120 approaches were flown in a Bell 212 helicopter by 15 operational pilots during the months of August and September 1978. The purpose of the tests was to collect data to (1) support development of advanced radar flight director concepts by NASA and (2) aid the establishment of Terminal Instrument Procedures (TERPS) criteria by the FAA. The flight test objectives were to develop airborne radar approach procedures, measure tracking errors, determine accpetable weather minimums, and determine pilot acceptability. Data obtained will contribute significantly to improved helicopter airborne radar approach capability and to the support of exploration, development, and utilization of the Nation's offshore oil supplies.
Bull, J. S.; Hegarty, D. M.; Phillips, J. D.; Sturgeon, W. R.; Hunting, A. W.; Pate, D. P.
This paper describes the status of a project that will simultaneously digitize the radar signals coming from eight channels on the phased array antenna at the Na- tional Weather Radar Testbed (NWRT) in Norman, Ok- lahoma. At the current time, a single-channel digital receiver is operational on this S-band radar to mimic the current WSR-88D capability. The multi-channel dig- ital
M. Yeary; J. Crain; A. Zahrai; R. Kelley; J. Meier; Y. Zhang; I. Ivic; C. Curtis; R. Palmer; T.-Y. Yu; G. Zhang; R. Doviak; P. Chilson; M. Xue; Q. Xu
Application of Attenuation Correction to Precipitation Rates Derived From Terminal Doppler Weather Radar Reflectivity
NASA Astrophysics Data System (ADS)
The Federal Aviation Administration Terminal Doppler Weather Radars (TDWRs) are C band radars that offer high spatio-temporal resolution coverage over major urban areas in the United States. The National Oceanic and Atmospheric Administration, National Weather Service (NWS) has been investigating the incorporation of TDWR data for producing quantitative precipitation estimates to serve its flash and river forecast missions. As reflectivity from C-band Radars can be considerably attenuated by hydrometeors, the NWS Office of Hydrologic Development implemented an algorithm for mitigating this attenuation. In this algorithm, TDWR reflectivity is adjusted iteratively along each radial based on reflectivity and temperature data with the assumption of gamma distribution of drop size. This paper describes the concept and the implementation of the attenuation correction algorithm, and presents a series of validation case studies to examine the impacts of the correction on the accuracy of resulting radar-only QPEs during warm and cool season storm events. Serving as the validation reference is the Stage IV gauge-radar QPE produced by NWS. In order to determine the effects of ingesting spatially variable atmospheric temperature, spatially variable (3-dimensional) temperature from the Rapid Update Cycle 2 (RUC2) model is ingested, and the results are comparatively assessed along with those obtained using spatially averaged surface RUC2 temperatures. Finally, several atmospheric temperature thresholds were tested to avoid over-correction in cases with bright band enhancement. It was found that attenuation correction generally improved correlations between TDWR and StageIV precipitation estimates. The use of low-temperature cutoff criteria appeared effective in minimizing over-correction of attenuation within and beyond the bright band.
Zhang, Y.; Ding, F.; Kitzmiller, D. H.
Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall
NASA Technical Reports Server (NTRS)
Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Further analysis of the frequency distribution of PR (2A25 product) rain rates suggests that the algorithm incorporates the attenuation measurement in a very conservative fashion so as to optimize the instantaneous rain rates. Such an optimization appears to come at the expense of monitoring interannual climate variability.
Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.; Arnold, James E. (Technical Monitor)
MicroRadarNet: a Network of Weather Micro Radars for the Identification of Local High-Resolution Precipitation Patterns
NASA Astrophysics Data System (ADS)
MicroRadarNet (MRN) is a network of high-resolution, low-cost, low-power consumption micro radars for continuous, unattended meteorological monitoring. The MRN project started in the framework of the European INTERREG IIIB Alpine Space Programme (within the FORALPS project) since 2004 and was developed and operated by the Remote Sensing Group at the Politecnico di Torino from its early design stages. MRN is currently under its final pre-release testing and validation stage, cooperating with professional weather operators (e.g. civil protection offices) to run extensive on-field tests. The key aspects of MRN are a short range strategy (about thirty kilometers) and the implementation of an effective sensor network approach. Raw spatial and temporal data is processed on-board in real-time, yielding a consistent evaluation of the information from the sensor and compressing the data to be transmitted. Network servers receive and merge the data sets coming from each unit yielding a synthetic, high resolution plot of meteorological events (updated every minute). This networked approach implies in turn a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range C-band approach. An ever-growing database of meteorological events is being collected, thus providing a real-data test bench to refine assessment and data enhancement algorithms. Assessment techniques have been adopted for the estimation of precipitation, based on systematic rain gauges comparisons. Efforts were also devoted to the design and implementation of specific decluttering algorithms. New techniques to mitigate the effect of co-channel interference sources are also under testing. It is shown how these enhancement algorithms further improve the assessment process raising the overall data quality. A consistent amount of case studies clearly shows that MicroRadarNet has enough potentialities to act as a fast-reacting weather monitoring tool. The proposed strategy, based on a network of short range radars, shall effectively perform high resolution monitoring while lowering the overall operational costs. This could prevent, by design, the volumetric resolution loss at higher ranges, as well as the need for atmospheric corrections and the shielding shortcomings which typically occur in orographically complex areas.
Turso, Stefano; Zambotto, Marco; Notarpietro, Riccardo; Orione, Fiammetta; Gabella, Marco; Perona, Giovanni
Using NEXRAD Radar Rainfall to Calibrate a Development Impact Model in a Coastal Watershed
NASA Astrophysics Data System (ADS)
Low slopes and shallow, impermeable soils are characteristic of the Upper Texas Gulf Coast. These, coupled with large rainfall events, contribute to wide floodplains and ponding. Rapid, high intensity development has further exacerbated flooding in this coastal region. The Clear Creek Watershed is located in southeast Houston and empties into Galveston Bay. During the past decade, the watershed has been impacted by significant historical coastal storms and rainfall events such as Tropical Storm Allison (2001), Hurricane Ike (2008), and the April 2009 Event. In this study, we employ a calibrated, distributed hydrologic model and pre- and LID-development models to analyze how development characteristics have contributed to costly flooding in coastal watersheds. In 2012, Brody et al. used FEMA floodclaims collected over the 11-year period between 1999 and 2009 to examine the pattern of flood loss across the Clear Creek watershed. The results showed that the 100-year floodplain did not adequately represent overall or event-specific loss. Using a spatial cluster analysis, the Turkey Creek sub-area of the Clear Creek watershed was pin-pointed as an area of statistically significant flood loss, an area where there were a considerable number of high-value flood claims. This area is characterized by high-density, poorly constructed development and frequent flooding. In parallel with Brody's study of flood-risk indicators, our study aims to examine the behavior of the flood-wave in the coastal watershed and how it is affected by different development patterns. A distributed hydrologic VfloTM model was built for Turkey Creek using 2008 CCAP land cover data and calibrated using NEXRAD radar rainfall for the Hurricane Ike (2008) and April 2009 events. Once the model was calibrated, both pre- and LID-development models were built using historical land cover data. These models were used to identify how development patterns have influence the flood hydrograph. Early results indicate that the construction of impervious surfaces has greatly increased the flood peak and shortened the time to peak of the flood wave. The study will go further to identify the measures that may be taken to reduce flooding in the Clear Creek Watershed and attempt to extrapolate the best management practices for low impact development in coastal watersheds.
Sebastian, A.; Bedient, P.
Turbulence as observed by concurrent measurements made at NSSL using weather radar, Doppler radar, Doppler lidar and aircraft
NASA Technical Reports Server (NTRS)
As air traffic increases and aircraft capability increases in range and operating altitude, the exposure to weather hazards increases. Turbulence and wind shears are two of the most important of these hazards that must be taken into account if safe flight operations are to be accomplished. Beginning in the early 1960's, Project Rough Rider began thunderstorm investigations. Past and present efforts at the National Severe Storm Laboratory (NSSL) to measure these flight safety hazards and to describe the use of Doppler radar to detect and qualify these hazards are summarized. In particular, the evolution of the Doppler-measured radial velocity spectrum width and its applicability to the problem of safe flight is presented.
Lee, Jean T.
The pulse-pair algorithm as a robust estimator of turbulent weather spectral parameters using airborne pulse Doppler radar
NASA Technical Reports Server (NTRS)
The pulse pair method for spectrum parameter estimation is commonly used in pulse Doppler weather radar signal processing since it is economical to implement and can be shown to be a maximum likelihood estimator. With the use of airborne weather radar for windshear detection, the turbulent weather and strong ground clutter return spectrum differs from that assumed in its derivation, so the performance robustness of the pulse pair technique must be understood. Here, the effect of radar system pulse to pulse phase jitter and signal spectrum skew on the pulse pair algorithm performance is discussed. Phase jitter effect may be significant when the weather return signal to clutter ratio is very low and clutter rejection filtering is attempted. The analysis can be used to develop design specifications for airborne radar system phase stability. It is also shown that the weather return spectrum skew can cause a significant bias in the pulse pair mean windspeed estimates, and that the poly pulse pair algorithm can reduce this bias. It is suggested that use of a spectrum mode estimator may be more appropriate in characterizing the windspeed within a radar range resolution cell for detection of hazardous windspeed gradients.
Baxa, Ernest G., Jr.; Lee, Jonggil
Evaluation of X-band polarimetric radar estimation of rainfall and rain drop size distribution parameters in West Africa
NASA Astrophysics Data System (ADS)
As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH�KDP�ZDR works well whatever the a priori assumption made on the drop shapes. Dm retrieval based on ZDR alone performs well, but if satisfactory ZDR measurements are not available, the combination ZH�KDP provides satisfactory results for both Dm and NW if an appropriate a priori assumption on drop shape is made.
Koffi, A. K.; Gosset, M.; Zahiri, E.-P.; Ochou, A. D.; Kacou, M.; Cazenave, F.; Assamoi, P.
Analysis of daily rainfall of the Sahelian weather-station Lingu�re (Senegal) - Trends and its impacts on the local population
NASA Astrophysics Data System (ADS)
In the 20th century, the West African Sahel has been a hot-spot of climatic changes. After severe drought-events in the 1970s and 1980s which were followed by a significant drop in annual precipitation, rainfall seems to increase again during the past years. Most studies are based on monthly or yearly datasets. However, many processes and events which are important for the local population depending on rainfall are not related to monthly or annual precipitation but are related to intra-annual, often daily scales. During this study, interviews with farmers and herders were conducted in the Senegalese Sahel. The results show, that wet months with unsuitably distributed precipitation can cause more harm than bringing benefits - depending on the phenological stage of the plants. Agricultural crops for example need rainfall breaks. On the other hand, natural herbaceous vegetation tolerates longer wet periods. So, a wet season can still hide dry spells that alter crops and vegetation development. Based on the results of these interviews, this study developed two indexes, one for local farmers and one for herders separately, showing if the year was favorable for them or not. The indexes integrate the length of rainy seasons, intensity and frequency of rainfall events, breaks between events and also the previous year. This way, each year is assigned to one of 5 classes. Using daily rainfall data of the Lingu�re weather-station (from the Senegal Meteorological Service, ANACIM), trends of the indexes from 1945 to 2002 are detected and compared to results of the interviews. Statistically relating the indexes to yearly and monthly data demonstrates, how much information can be gathered by those datasets. Furthermore, changes in intensity and frequency are related with yearly and monthly sums showing relations between daily data and annual sums. For example, a high correlation (r=0.73) between the amount of rain days (> 1 mm) and the annual rainfall is observed in Lingu�re.
Strommer, Gabriel; Brandt, Martin; Diongue-Niang, Aida; Samimi, Cyrus
Spatial correlations of monthly rainfall: Applications in climatology and weather modification experiments
Spatial correlations based on monthly rainfall totals from northwest Georgia for the period 1949--77 are studied. This work, a part of the Meteorological Effects of Thermal Energy Releases (METER) Program, determines natural variability rainfall trends and assists the field studies of potential precipitation effects of the Bowen Electric Generating Plant near Cartersville, Georgia. The spatial correlations, based on the overall
A. A. N. Patrinos; N. C. J. Chen; R. L. Miller
Study on the mesoscale structure of the heavy rainfall on Meiyu front with dual-Doppler RADAR
NASA Astrophysics Data System (ADS)
This paper retrieves the three dimensional (3D) wind fields and studies the evolution of the 3D wind fields and the formation mechanism of the sudden heavy rainfall on Meiyu front on 26th-27th June 2003 in Huaihe river basin in China, using the volume scan data of the dual-Doppler radar located in Hefei and Maanshan cities. Due to the effect of the low level trough, low level jet and the convergence line at the low and medium levels, it produced a heavy precipitation in Anhui province. It shows clearly that the primary feature of this event is local, sudden and short timed. It is a convective-stratiform mixed cloud precipitation based on the radar echo analyses. The meso-?-scale convective system (M?CS) and the meso-?-scale system located on the M?CS played an important role on this heavy rainfall. The meso-?-scale convective cloud has high precipitation efficiency. The dual-Doppler retrieved wind reveals that the heavy rainfall was caused by the meso-?-scale convergence lines at the low and the medium levels. The convergence line triggered and maintained the heavy rainfall. There were strong convergence and vorticity at the low and medium levels of the M?CS. The convergence line spread from west to east and the position of the convergence line at the medium levels is westward of the ones at the low levels. When the convergence line at the low and medium levels began to weak, the precipitation began to weak too. The intensity of the precipitation weakened remarkably when the convergence line dissipated. The 3D kinematic conceptual structure model of this heavy rainfall case is also given.
Zhou, Haiguang
Variable Selection and Prediction of Rainfall from WSR-88D Radar Using Support Vector Regression
This research utilizes linear programming support vector regression to perform variable selection and rainfall estimation. Variables selected from applying linear programming support vector regression are used to perform rainfall prediction tasks using standard support vector regression and a Bayesian neural network. Ground truth rainfall data are necessary to apply intelligent systems techniques. A unique source of such data is the
Super-resolution technologies for all-weather sense and avoidance (SAA) radar
NASA Astrophysics Data System (ADS)
The sense and avoidance (SAA) and due-regard radar systems have strict requirements on size, weight and power (SWaP) and target localization accuracies. Also, the multi-mission capabilities with both weather and hard targets are critical to the survivability of unmanned aerial vehicles (UAV) in the next generation national airspace. The aperture limitations of the aircraft sensor installation, however, have prevented large antennas/arrays to be used. The tradeoffs among frequencies, resolutions and detection range/accuracies have not been fully addressed. Innovative concepts of overcoming the aperture limitation by using a special type of super-resolution technology are introduced. The first technique is based on a combination of thinned antenna array, an extension to the traditional Multiple Signal Classification (MUSIC) technique, and applying a two-dimensional sidelobe mitigation technique. To overcome the degradation of MUSIC-type of approach due to coherent radar signals, a special waveform optimization procedure is used. The techniques for mitigating artifacts due to "thinned" array are also introduced. Simulated results of super-resolution techniques are discussed and evaluated, and the capability of separating multiple targets within aperture-constrained beamwidth is demonstrated. Moreover, the potential capabilities of autonomous weather hazard avoidance are also analyzed.
Zhang, Yan Rockee; Li, Zhengzheng; Wang, Shang; Pan, Yu; Suarez, Hernan
Characteristics of velocity ambiguity for CINRAD-SA Doppler weather radars
NASA Astrophysics Data System (ADS)
The velocity ambiguity in Doppler weather radars has inhibited the application of wind field data for long time. One effective solution is software-based velocity dealiasing algorithm. In this paper, in order to better design, optimize and validate velocity dealiasing algorithms for CINRAD-SA, data from operational radars were used to statistically characterize velocity ambiguity. The analyzed characteristic parameters included occurrence rate, and inter-station, inter-type, temporal, and spatial distributions. The results show that 14.9% of cloud-rain files and 0.3% of clear-air files from CINRADSA radars are ambiguous. It is also found that echoes of weak convections have the highest occurrence rate of velocity ambiguity than any other cloud types, and the probability of ambiguity is higher in winter than in summer. A detailed inspection of the occurrence of ambiguity in various cases indicates that ambiguous points usually occur in areas with an elevation angle of 6.0�, an azimuth of 70� or 250�, radial distance of 50-60 km, and height of 5-6 km, and that 99.4% of ambiguous points are in the 1st-folding interval. Suggestions for performing dealiasing at different locations and different time points are provided.
Chu, Zhigang; Yin, Yan; Gu, Songshan
The response of the high-latitude ionosphere to the coronal mass ejection event of April 6, 2000: A practical demonstration of space weather nowcasting with the Super Dual Auroral Radar Network HF radars
The ionosphere at high latitudes is the site of important effects in space weather. These include strong electrical currents that may disrupt power systems through induced currents and density irregularities that can degrade HF and satellite communication links. With the impetus provided by the National Space Weather Program, the radars of the Super Dual Auroral Radar Network have been applied
J. M. Ruohoniemi; R. J. Barnes; R. A. Greenwald; S. G. Shepherd
Correlation Between Stable Isotope Composition and Cloud Altitude (Radar Echo Tops) in Tropical Rainfall: Puerto Rico and Hawaii
NASA Astrophysics Data System (ADS)
Observed patterns of isotopic composition of rainfall in the tropics are different than those at higher latitudes, where seasonal temperature changes have a large effect. Land surface temperatures vary little over the course of the year in the tropics, and the amount effect (involving evaporative enrichment, droplet size, and rainout processes) has been invoked as an explanation for variations in isotopic composition of rain measured at the land surface. Previous work by Scholl et al. (2009) in Eastern Puerto Rico showed that variations in the altitude (and temperature) of the clouds producing rain were highly correlated with the monthly stable isotope composition of rainfall. The altitude of rain droplets within the clouds was obtained using NEXRAD echo tops, which indicate the maximum altitude of rainfall determined by radar. Atmospheric temperature in rainfall-producing clouds was then estimated with archived NCEP data at the mean and maximum echo top altitudes for large rain events during the sampling period. Isotopic signatures associated with the major climate patterns in Puerto Rico were determined and are being utilized in local hydrological studies. For Eastern Puerto Rico, at latitude 18� N, ?18O and ?2H values and mean monthly echo top altitude were significantly correlated (average coefficient = -0.69). The analysis was repeated using a 24-month stable isotope data set of rain from sites on windward and leeward Maui, Hawaii, latitude 21� N. Results were similar; mean monthly echo top altitude was highly correlated with rainfall isotopic composition (windward site correlation coefficient = -0.86, leeward = -0.87). The data also showed a significant rainout effect in monthly samples dominated by tropical storms, where cloud heights were similar to other monthly samples but ?18O and ?2H values were much more negative. Variations in water vapor isotopic composition also affect isotopic composition of rain, and ongoing work will focus on investigating those factors further. Echo tops are a measurable parameter that reflects temperature, and to some extent, size and intensity of individual rain events. These results show that echo tops may be a good predictor for the isotopic composition of tropical rainfall where radar data are available, and that seasonal variations in cloud height can be factored into models to predict the isotopic composition of rain. High resolution (15-minute) rainfall samples for isotopic analysis were recently collected from outer rain bands of Hurricane Earl, which affected Puerto Rico August 30-31, 2010, and we hope to obtain more data during the remaining hurricane season. These data should yield information on within-storm variations in cloud echo tops and isotopic composition.
Scholl, M. A.; Coplen, T. B.
Diagnostics of rainfall anomalies in the nordeste during the global weather experiment
NASA Technical Reports Server (NTRS)
The relationship of the daily variability of large-scale pressure, cloudiness and upper level wind patterns over the Brazil-Atlantic sector during March/April 1979 to rainfall anomalies in northern Nordeste was investigated. The experiment divides the rainy season (March/April) of 1979 into wet and dry days, then composites bright cloudiness, sea level pressure, and upper level wind fields with respect to persistent rainfall episodes. Wet and dry anomalies are analyzed along with seasonal mean conditions.
Sikdar, D. M.
NSDL National Science Digital Library
This is a first grade weather unit. SEASONS Fall Winter Build a Snowman Spring Summer What things determine and effect the weather? Cloud Precipitation Sunshine Temperature Visibility Wind Direction Wind Force WEATHER VIDEOS Tornado Hurricane Hail Lightning FUN AND GAMES Dress the Bear for the Weather The Great Weather Race Game Weather coloring books for kids ...
Stearns, Ms.
NSDL National Science Digital Library
Have you ever wondered how the weather man, or meteorolgist, on TV knows what to say about tomorrow\\'s weather? It\\'s because they have certain tools that they use that help them predict what the weather will be. Throughout this school year you are going to be making tools and predicting weather just like a meterorologist! Task You are going to be weather forcasters! You are going to record and track weather patterns throughout the year. You will also use weather tools to make predictions about the weather like real weather forecasters! The Process 1. First we need to learn a little bit about weather so ...
Williams, Ms.
Validation of TRMM Precipitation Radar through Comparison of Its Multiyear Measurements with Ground-Based Radar
A procedure to accurately resample spaceborne and ground-based radar data is described and then is applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, non- attenuated WSR at Melbourne, Florida,
Liang Liao; Robert Meneghini
VPR-IE: Combining climatological VPR information from TRMM Precipitation Radar with NEXRAD-based rainfall estimates
NASA Astrophysics Data System (ADS)
The vertical profile of reflectivity (VPR) links the estimates of surface precipitation to the radar observation at higher levels. Over complex terrain, ground radars usually rely on scans at higher elevation angles to observe precipitating systems. The surface quantitative precipitation estimation (QPE) might have considerable errors if the vertical structure of precipitation is not considered because the VPR varies due to evaporation at low levels, melting, aggregation, and drop break-up. Incorporation of this VPR information is very useful for improving estimates of surface rainfall and mitigates their radar range-dependence. However, due to high variability of VPRs, a spatially and temporally representative VPR for different precipitation types and intensities poses significant challenges. Researchers at the University of Oklahoma have characterized the seasonal, spatial, type-related and intensity-related variability of VPRs using 11+ years of observations from TRMM Precipitation Radar (PR). In recent developments of the VPR-Identification and Enhancement (VPR-IE) approach, we have optimally combined the climatological VPR information to the NEXRAD-based National Mosaic and QPE (NMQ; http://nmq.ou.edu) system. Performance of latest VPR-IE algorithm is tested for the mountainous West region of the U.S., where reliable ground-based precipitation measurements are difficult to obtain due to complex terrain. Results indicate improvements in precipitation estimation following application of the VPR-IE method. Remaining challenges will be highlighted, and future directions will be discussed.
Wen, Y.; Hong, Y.; Cao, Q.; Gourley, J. J.; Zhang, J.; Kirstetter, P.
Remote rainfall sensing for landslide hazard analysis
Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.
Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay
The potential for hail and intense rainfall enhancement over urban areas: improving urban extreme weather risk assessment
NASA Astrophysics Data System (ADS)
Urban communities and their infrastructure are particularly vulnerable to the impacts of organized thunderstorm systems. Current models of urban extreme weather risk do not fully represent the complexity of the hydrometeorological processes involved, particularly in relation to intense convective precipitation and severe weather. Hail is a severe thunderstorm hazard that can be extremely damaging to property (especially automobiles, buildings and agriculture) over and in proximity to urban environments. This study identifies some of the mechanisms that future generations of catastrophe models should consider incorporating in their representation of hydrometeorlogical hazards in urban areas. In addition, such information could help to inform planning policy and improve urban resilience to extreme events. Evidence is provided that urban environments, through the existence of high-rise buildings and densely build-up areas, but also through air-pollution (aerosols) can potentially lead to an enhancement of both flooding and hail. Conclusions are drawn from two separate studies over the heavily urbanized corridor of the northeastern United States but could be expanded to apply to other urban areas. Observational and modelling (Weather Research and Forecasting - WRF) analyses of an extreme thunderstorm over the Baltimore, Maryland metropolitan area on 7 July 2004 provided evidence that the urban canopy redistributed heavy rainfall and convergence centres in the vicinity of the urban environment. Modelling analyses suggest that convective rainfall around the urban core was increased by about 30% due to the heterogeneities of land surface processes associated with the city of Baltimore. Chesapeake Bay also played an important role in rainfall distribution by acting as a divergence zone for northerly winds. Cloud-to-ground lightning analyses show that the city of Baltimore and the Chesapeake Bay combined played a role in the distribution of lightning in the periphery of the urban core. Detailed modelling analyses (WRF-Chem) of a series of convective storms over the New York City metropolitan area, suggest that under certain meteorological conditions, increased concentrations of aerosols can lead to better organization of convection, higher vertical velocities and significantly increased convective rainfall accumulations. Higher vertical velocities were more widespread and reached deeper atmospheric levels when meteorological conditions were favourable, under increased aerosol concentrations. Areas that are downstream of sources of aerosols (i.e. New York City) are more prone to experience convective enhancement.
Ntelekos, A. A.; Smith, J. A.; Krajewski, W. F.; Foote, M.
Hands-On Learning Modules for Interdisciplinary Environments: An Example with a Focus on Weather Radar Applications
ERIC Educational Resources Information Center
Learning modules provide an effective means of encouraging cognition and active learning. This paper discusses several such modules that have been developed within a course on weather radar applications intended for students from Electrical Engineering and Meteorology. The modules were designed both to promote interdisciplinary exchange between�
Chilson, P. B.; Yeary, M. B.
Next Generation Weather Radar (NEXRAD) Principal User Processor (PUP) Operational Test and Evaluation (OT and E) Operational Test Plan.
National Technical Information Service (NTIS)
The purpose of this plan is to describe and detail the procedural approach, method, and responsibilities to be employed in conducting the Operational Test and Evaluation (OT&E) on the Next Generation Weather Radar (NEXRAD) Principal User Processor (PUP) s...
B. R. Stretcher
Rain Cells Associated with Atmospheric Fronts over the Ocean Studied by Spaceborne SAR and Weather Radar Data
Spaceborne SAR images acquired over the ocean in conjunction with weather radar images are well suited to study atmospheric fronts in coastal areas. In this paper we confine ourselves to study quasi-stationary atmospheric fronts off the east coast of Taiwan which are located typically 30- 70 km offshore. These quasi- stationary atmospheric fronts were first detected on ERS SAR images
Werner Alpers; I. I. Lin
An optimal design of a cylindrical polarimetric phased array radar for weather sensing
NASA Astrophysics Data System (ADS)
An optimal design of a cylindrical polarimetric phased array radar (CPPAR) for weather sensing is presented. A recently introduced invasive weed optimization (IWO) technique is employed to obtain the desired radiation pattern of the CPPAR. Instead of optimizing each element excitation in a large array (with expensive calculation costs), the modified Bernstein polynomial distribution, defined by seven parameters, is used to optimize the current distribution for the CPPAR. The simulation results show that the desired sidelobe levels (SLLs) and beam width are achieved in a computationally effective manner. Furthermore, the imaged feed arrangement is used to suppress the cross-polarization level. Both co-polar and cross-polar radiation patterns for broadside and off-broadside directions are presented to show the performance of the optimized CPPAR.
Karimkashi, Shaya; Zhang, Guifu
Assessment of bird response to the Migratory Bird Habitat Initiative using weather-surveillance radar
In response to the Deepwater Horizon oil spill in spring 2010, the Natural Resources Conservation Service implemented the Migratory Bird Habitat Initiative (MBHI) to provide temporary wetland habitat for migrating and wintering waterfowl, shorebirds, and other birds along the northern Gulf of Mexico via managed flooding of agricultural lands. We used weather-surveillance radar to conduct broad regional assessments of bird response to MBHI activities within the Mississippi Alluvial Valley and the West Gulf Coastal Plain. Across both regions, birds responded positively to MBHI management by exhibiting greater relative bird densities within sites relative to pre-management conditions in prior years and relative to surrounding non-flooded agricultural lands. Bird density at MBHI sites was generally greatest during winter for both regions. Unusually high flooding in the years prior to implementation of the MBHI confounded detection of overall changes in remotely sensed soil wetness across sites. The magnitude of bird response at MBHI sites compared to prior years and to non-flooded agricultural lands was generally related to the surrounding landscape context: proximity to areas of high bird density, amount of forested wetlands, emergent marsh, non-flooded agriculture, or permanent open water. However, these relationships varied in strength and direction between regions and seasons, a finding which we attribute to differences in seasonal bird composition and broad regional differences in landscape configuration and composition. We detected greater increases in relative bird use at sites in closer proximity to areas of high bird density during winter in both regions. Additionally, bird density was greater during winter at sites with more emergent marsh in the surrounding landscape. Thus, bird use of managed wetlands could be maximized by enrolling lands located near areas of known bird concentration and within a mosaic of existing wetlands. Weather-radar observations provide strong evidence that MBHI sites located inland from coastal wetlands impacted by the oil spill provided wetland habitat used by a variety of birds.
Sieges, Mason L.; Smolinsky, Jaclyn A.; Baldwin, Michael J.; Barrow, Wylie C., Jr.; Randall, Lori A.; Buler, Jeffrey J.
The four cumulus cloud modes and their progression during rainfall events: A C-band polarimetric radar perspective
NASA Astrophysics Data System (ADS)
There is no objective definition to separate cumulus congestus clouds from the shallow cumulus and deep clouds. This has generated misinterpretation about the role of congestus clouds to promote deep convection through the potential of moistening the middle troposphere. In this study, an objective identification for the different tropical cumulus modes is found by examining the occurrence frequency of the cloud cell top heights (CTHs) and near-ground (at 2.5 km height) rainfall properties of these cells using a three-season database of the Darwin C-band polarimetric radar. Four cumulus modes were identified, namely a shallow cumulus mode with CTH in the trade inversion layer (1-3 km), a congestus mode with tops in the highly stable middle troposphere (3-6.5 km), a deep convective mode with tops in the region of free convection (6.5-15 km), and an overshooting convection mode with tops in the tropical tropopause layer (CTH >15 km). The study also investigates the connections between these cumulus modes during heavy rainfall events. The congestus mode occurs predominantly from ~10 h prior to the peak rainfall event to ~2 h past the event. The deep cloud populations (Modes 3 and 4) have their maxima at and shortly after the time of the rainfall peak, with maximum occurrence just below the tropical tropopause layer. A comparison of the heavy rainfall events occurring in morning (oceanic) conditions against the afternoon (continental) conditions revealed a higher ratio of the shallow to the deep cloud population and a shorter transition time from the shallow to the onset of deep population in the morning-oceanic conditions than the afternoon-land conditions. It is also found through the analysis of the large-scale moisture budget data set that for both the morning and afternoon events, the moistening peaked before the peak in the congestus populations.
Kumar, Vickal V.; Jakob, Christian; Protat, Alain; May, Peter T.; Davies, Laura
Space-Time Characteristics of Rainfall Diurnal Variations
NASA Technical Reports Server (NTRS)
The space-time features of rainfall diurnal variation of precipitation are systematically investigated by using the Tropical Rainfall Measuring Mission (TRMM) precipitation products retrieved from TRMM microwave imager (TMI), precipitation radar (PR) and TMI/PR combined algorithms. Results demonstrate that diurnal variability of precipitation is obvious over tropical regions. The dominant feature of rainfall diurnal cycle over, ocean is that there is consistent rainfall peak in early morning, while there is a consistent rainfall peak in mid-late afternoon over land. The seasonal variation on intensity of rainfall diurnal cycle is clearly evidenced. Horizontal distributions of rainfall diurnal variations indicate that there is a clearly early-morning peak with a secondary peak in the middle-late afternoon in ocean rainfall at latitudes dominated by large-scale convergence and deep convection. There is also an analogous early-morning peak in land rainfall along with a stronger afternoon peak forced by surface heating. Amplitude analysis shows that the patterns and its evolution of rainfall diurnal cycle are very close to rainfall distribution pattern and its evolution. These results indicate that rainfall diurnal variations are strongly associated with large-scale convective systems and climate weather systems. Phase studies clearly present the regional and seasonal features of rainfall diurnal activities. Further studies on convective and stratiform rainfall show different characteristics of diurnal cycles. Their spatial and temporal variations of convective and stratiform rainfall indicate that mechanisms for rainfall diurnal variations vary with time and space.
Yang, Song; Kummerow, Chris; Olson, Bill; Smith, Eric A.; Einaudi, Franco (Technical Monitor)
The New Weather Radar for America's Space Program in Florida: A Temperature Profile Adaptive Scan Strategy
NASA Technical Reports Server (NTRS)
A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar replaces the modified WSR-74C at Patrick AFB that has been in use since 1984. The new radar is a Radtec TDR 43-250, which has Doppler and dual polarization capability. A new fixed scan strategy was designed to best support the space program. The fixed scan strategy represents a complex compromise between many competing factors and relies on climatological heights of various temperatures that are important for improved lightning forecasting and evaluation of Lightning Launch Commit Criteria (LCC), which are the weather rules to avoid lightning strikes to in-flight rockets. The 0 C to -20 C layer is vital since most generation of electric charge occurs within it and so it is critical in evaluating Lightning LCC and in forecasting lightning. These are two of the most important duties of 45 WS. While the fixed scan strategy that covers most of the climatological variation of the 0 C to -20 C levels with high resolution ensures that these critical temperatures are well covered most of the time, it also means that on any particular day the radar is spending precious time scanning at angles covering less important heights. The goal of this project is to develop a user-friendly, Interactive Data Language (IDL) computer program that will automatically generate optimized radar scan strategies that adapt to user input of the temperature profile and other important parameters. By using only the required scan angles output by the temperature profile adaptive scan strategy program, faster update times for volume scans and/or collection of more samples per gate for better data quality is possible, while maintaining high resolution at the critical temperature levels. The temperature profile adaptive technique will also take into account earth curvature and refraction when geo-locating the radar beam (i.e., beam height and arc distance), including non-standard refraction based on the user-input temperature profile. In addition to temperature profile adaptivity, this paper will also summarize the other requirements for this scan strategy program such as detection of low-level boundaries, detection of anvil clouds, reducing the Cone Of Silence, and allowing for times when deep convective clouds will not occur. The adaptive technique will be carefully compared to and benchmarked against the new fixed scan strategy. Specific environmental scenarios in which the adaptive scan strategy is able to optimize and improve coverage and resolution at critical heights, scan time, and/or sample numbers relative to the fixed scan strategy will be presented.
Carey, L. D.; Petersen, W. A.; Deierling, W.; Roeder, W. P.
Stability of the U.S. weather radar network and its implications for TRMM and GPM ground validation
NASA Astrophysics Data System (ADS)
Ground validation of rainfall and reflectivity measurements from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite has relied on comparisons to measurements from ground radars (GR), in particular to those from the WSR-88D radar network over the U.S. In support of TRMM PR validation and in preparation for validation of the Dual-frequency Precipitation Radar for the upcoming Global Precipitation Measurement (GPM) mission, NASA established a Validation Network (VN) of 21 WSR-88D sites in the southeastern U.S. Quality-controlled data from these sites have been used to perform reflectivity and rain rate comparisons to TRMM PR continually since mid-2006. VN data were used to assess the stability and calibration accuracy of the WSR-88D radars. The PR-GR reflectivity and rain rate comparisons are based on a technique of 3-D volume and resolution matching between the two radar observation systems, where each matching volume is characterized by location, rain type, proximity to the bright band, and quality of the matchup in terms of beam filling and uniformity. Calibration differences between PR and GR are evaluated by inspecting stratiform rain samples above the bright band, where PR attenuation and reflectivity gradient effects are minimal. Time series of GR-PR mean reflectivity differences reveal site-specific trends in GR calibration, under the assumption that the PR calibration is stable and well known. Recent changes in the baseline calibration differences between PR and GR have occurred coincident with upgrades to dual-polarization capability at several VN WSR-88D sites. Overall, 16 of the 21 WSR-88D radars in the GPM Validation Network were found to be running measurably 'cooler' following the dual polarization upgrade, when compared to TRMM PR. These changes are evident in the long-term trend of PR-GR reflectivity comparisons, and in specific examples of short-term anomalies in WSR 88D calibration. Additional, independent evidence of such calibration changes was found in comparisons of WSR-88D rain rates to rain gauge measurements. The calibration offsets that occurred in WSR-88D radars following the dual polarization upgrade needs to be factored into post-launch GPM ground validation as well as ground-based radar rainfall estimation via traditional Z-R relationships and newer dual-polarization rain rate estimation.
Morris, K. R.; Schwaller, M.; Marks, D. A.; Wolff, D. B.; Petersen, W. A.; Pippitt, J. L.
Structure of precipitating systems over Taiwan's complex terrain during Typhoon Morakot (2009) as revealed by weather radar and rain gauge observations
NASA Astrophysics Data System (ADS)
Behavior of the Typhoon Morakot (2009) rainbands over Taiwan is documented. Unstable air that is continuously lifted by topographic forcing results in torrential rainfall. Rainfall amounts on the lee side are only 30% of those on the windward side of the mountains. A wind maximum that takes place above the mountain crest can be explained theoretically. Rainfall estimation using the dual-polarimetric radar gives satisfactory results in mountainous terrain.
Liou, Yu-Chieng; Wang, Tai-Chi Chen; Tsai, Yi-Chun; Tang, Yu-Shuang; Lin, Pay-Liam; Lee, Yung-An
Effects of rainfall on weathering rate, base cation provenance, and Sr isotope composition of Hawaiian soils
A climate transect across the Kohala Peninsula, Hawaii provides an ideal opportunity to study soil processes and evolution as a function of rainfall. The parent material is the ?150 ka Hawi alkali basalt aa flow, and median annual precipitation (MAP) changes from ?16 cm along the west coast to ?450 cm in the rain forest near the crest of the
The correlation between radar reflectivity (Z) and rainfall rate (R) is known to have accuracy problems due to several factors including attenuation, variation of hydrometeor distributions, etc. Therefore, recent studies have used differential reflectivity (ZDR) and specific differential phase (KDP ) obtained by a dual- polarimetric radar for estimating the two parameters of the Gamma drop-size distribution (DSD), hence pro-
Michihiro Teshiba; Robert D. Palmer; Phillip B. Chilson; Alexander V. Ryzhkov; Terry J. Schuur
Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France
NASA Astrophysics Data System (ADS)
The present study explores the application of a data assimilation (DA) procedure to correct the radar rainfall inputs of an event-based, distributed, parsimonious hydrological model. An extended Kalman filter algorithm was built on top of a rainfall-runoff model in order to assimilate discharge observations at the catchment outlet. This work focuses primarily on the uncertainty in the rainfall data and considers this as the principal source of error in the simulated discharges, neglecting simplifications in the hydrological model structure and poor knowledge of catchment physics. The study site is the 114 km2 Lez catchment near Montpellier, France. This catchment is subject to heavy orographic rainfall and characterised by a karstic geology, leading to flash flooding events. The hydrological model uses a derived version of the SCS method, combined with a Lag and Route transfer function. Because the radar rainfall input to the model depends on geographical features and cloud structures, it is particularly uncertain and results in significant errors in the simulated discharges. This study seeks to demonstrate that a simple DA algorithm is capable of rendering radar rainfall suitable for hydrological forecasting. To test this hypothesis, the DA analysis was applied to estimate a constant hyetograph correction to each of 19 flood events. The analysis was carried in two different modes: by assimilating observations at all available time steps, referred to here as reanalysis mode, and by using only observations up to 3 h before the flood peak to mimic an operational environment, referred to as pseudo-forecast mode. In reanalysis mode, the resulting correction of the radar rainfall data was then compared to the mean field bias (MFB), a corrective coefficient determined using rain gauge measurements. It was shown that the radar rainfall corrected using DA leads to improved discharge simulations and Nash-Sutcliffe efficiency criteria compared to the MFB correction. In pseudo-forecast mode, the reduction of the uncertainty in the rainfall data leads to a reduction of the error in the simulated discharge, but uncertainty from the model parameterisation diminishes data assimilation efficiency. While the DA algorithm used is this study is effective in correcting uncertain radar rainfall, model uncertainty remains an important challenge for flood forecasting within the Lez catchment.
Harader, E.; Borrell-Estupina, V.; Ricci, S.; Coustau, M.; Thual, O.; Piacentini, A.; Bouvier, C.
Tropical convective systems life cycle characteristics from geostationary satellite and precipitating estimates derived from TRMM and ground weather radar observations for the West African and South American regions
NASA Astrophysics Data System (ADS)
In the tropics most of the rainfall comes in the form of individual storm events embedded in the synoptic circulations (e.g., monsoons). Understanding the rainfall and its variability hence requires to document these highly contributing tropical convective systems (MCS). Our knowledge of the MCS life cycle, from a physical point of view mainly arises from individual observational campaigns heavily based on ground radar observations. While this large part of observations enabled the creation of conceptual models of MCS life cycle, it nevertheless does not reach any statistically significant integrated perspective yet. To overcome this limitation, a composite technique, that will serve as a Day-1 algorithm for the Megha-Tropiques mission, is considered in this study. this method is based on a collocation in space and time of the level-2 rainfall estimates (BRAIN) derived from the TMI radiometer onboard TRMM with the cloud systems identified by a new MCS tracking algorithm called TOOCAN and based on a 3-dimensional segmentation (image + time) of the geostationary IR imagery. To complete this study, a similar method is also developed collocating the cloud systems with the precipitating features derived from the ground weather radar which has been deployed during the CHUVA campaign over several Brazilian regions from 2010 up to now. A comparison of the MCSs life cycle is then performed for the 2010-2012 summer seasons over the West African, and South American regions. On the whole region of study, the results show that the temporal evolution of the cold cloud shield associated to MCSs describes a symmetry between the growth and the decay phases. It is also shown that the parameters of the conceptual model of MCSs are strongly correlated, reducing thereby the problem to a single degree of freedom. At the system scale, over both land and oceanic regions, rainfall is described by an increase at the beginning (the first third) of the life cycle and then smoothly decreases as the system shrinks and dissipates. The evolutions of the precipitating properties associated to MCSs indicate that the life cycle of these systems can be described by three phases: initiation, mature and dissipation. This pattern is robust across the entire monsoonal region and the scale factors of this idealized model indicate complex regional specificities.
Fiolleau, T.; Roca, R.; Angelis, F. C.; Viltard, N.
NSDL National Science Digital Library
This course handout covers the processes and effects of weathering. The purpose of this handout is to contrast weathering and erosion, contrast and discuss chemical and mechanical weathering, list the products resulting from the chemical weathering of igneous rocks, and list and discuss the factors that influence the type and rate of rock weathering. Many photographs accompany this summary which depict weathered landscapes. Links are provided to the online Physical Geology resources at Georgia Perimeter College.
Gore, Pamela
Reconstruction of reflectivity vertical profiles and data quality control for C-band radar rainfall estimation
Microwave Doppler radars are considered a fairly established technique to retrieve rain rate fields from measured reflectivity volumes. However, in a complex orographic environment radar observations are affected by several impairments which should be carefully evaluated. Together with the enhancement of ground-clutter effects, the major limitation is represented by partial or total beam blocking caused by natural obstructions which very
A. Fornasiero; P. P. Alberoni; G. Vulpiani; F. S. Marzano
Error Structure of Multiparameter Radar and Surface Measurements of Rainfall Part 1. Differential Reflectivity.
National Technical Information Service (NTIS)
Fluctuations in the radar measurements of ZDR are due to both signal power fluctuations and the cross-correlation between the horizontal and vertical polarized signals. In Part I of this study, these signals are simulated for an S-band radar for backscatt...
V. Chandrasekar V. N. Bringi
Comparison of TRMM precipitation radar and microwave imager rainfall retrievals in tropical cyclone inner cores and rainbands
NASA Astrophysics Data System (ADS)
Tropical Rainfall Measuring Mission (TRMM) rainfall retrieval algorithms are evaluated in tropical cyclone (TC) inner cores (IC), inner bands (IB), and outer rainbands (OB). In total, 1329 IC, 2149 IB, and 4627 OB storm regions are analyzed using data from a 12-year TRMM Tropical Cyclone Precipitation Feature (TCPF) database containing 1013 TCs viewed from December 1997 to December 2009. Attention is focused on the difference between the Precipitation Radar (PR) 2A25 and the TRMM Microwave Imager (TMI) 2A12 rainfall algorithms. The PR 2A25 produces larger mean rain rates than the TMI 2A12 in inner cores and inner bands, with the greatest difference occurring in hurricanes. This discrepancy is caused mostly by the TMI 2A12 significantly underestimating regions of moderate to heavy rain >15 mm hour-1 or when the PR reflectivity is greater than 30 dBZ. The TMI 2A12 rain rates are most closely related to the percentage coverage of 85 GHz polarization-corrected brightness temperature (PCT) <225 K in the IC and 85 GHz PCT <250 K in the IB and OB. These convective parameters are good predictors of the mean TMI 2A12 rain rate, but significant ice scattering is not always present in areas of heavy rain that are often widespread in TC inner regions. As a result, the TMI 2A12 algorithm may poorly measure the rain rate, particularly in the inner core of hurricanes.
Zagrodnik, Joseph P.; Jiang, Haiyan
Lithological and textural controls on radar and diurnal thermal signatures of weathered volcanic deposits, Lunar Crater region, Nevada
NASA Technical Reports Server (NTRS)
Radar backscatter intensity as measured by calibrated synthetic aperture radar (SAR) systems is primarily controlled by three factors: local incidence angle, wavelength-scale roughness, and dielectric permittivity of surface materials. Radar observations may be of limited use for geological investigations of surface composition, unless the relationships between lithology and the above characteristics can be adequately understood. In arid terrains, such as the Southwest U.S., weathering signatures (e.g. soil development, fracturing, debris grain size and shape, and hill slope characteristics) are controlled to some extent by lithologic characteristics of the parent bedrock. These textural features of outcrops and their associated debris will affect radar backscatter to varying degrees, and the multiple-wavelength capability of the JPL Airborne SAR (AIRSAR) system allows sampling of textures at three distinct scales. Diurnal temperature excursions of geologic surfaces are controlled primarily by the thermal inertia of surface materials, which is a measure of the resistance of a material to a change in temperature. Other influences include albedo, surface slopes affecting insolation, local meteorological conditions and surface emissivity at the relevant thermal wavelengths. To first order, thermal inertia variations on arid terrain surfaces result from grain size distribution and porosity differences, at scales ranging from micrometers to tens of meters. Diurnal thermal emission observations, such as those made by the JPL Thermal Infrared Multispectral Scanner (TIMS) airborne instrument, are thus influenced by geometric surface characteristics at scales comparable to those controlling radar backscatter. A preliminary report on a project involving a combination of field, laboratory and remote sensing observations of weathered felsic-to basaltic volcanic rock units exposed in the southern part of the Lunar Crater Volcanic Field, in the Pancake Range of central Nevada is presented. Focus is on the relationship of radar backscatter cross sections at multiple wavelengths, apparent diurnal temperature excursions identified in multi-temporal TIMS images, surface geometries related to weathering style, and parent bedrock lithology.
Plaut, Jeffrey J.; Rivard, Benoit
Simultaneous ocean cross-section and rainfall measurements from space with a nadir pointing radar
NASA Technical Reports Server (NTRS)
A modified version of the surface-target-attenuation radar described by Meneghini et al. (1983) is proposed which permits simultaneous measurement of ocean radar cross sections and path-average rain rates using a nadir-pointing satellite-borne microwave radar. The basic concept is explained and illustrated; the equations describing the data reduction are derived; some preliminary numerical computations based on a 7.5-m-diameter 10-kW 1.33-microsec-pulse radar operating at 1.87 cm from an altitude of 500 km are performed; and the major error sources (mismatches between rain scattering volumes and additional multipath contributions) and limitations (nadir pointing) are discussed. It is suggested that the system could provide a nadir calibration for wide-swath observing systems such as scanning microwave radiometers.
Atlas, D.; Meneghini, R.
Weather modification from cooling towers: A test based on the distributional properties of rainfall
A statistical technique for the treatment of data from weather modification experiments is presented. This work, a part of the Meteorological Effects of Thermal Energy Release (METER) Program, is aimed at determining the potential precipitation modification effects of the Bowen Electric Generating Plant near Cartersville, Georgia. For that purpose a network of 49 recording raingages and four recording windsets situated
A. A. N. Patrinos; K. O. Bowman
Geostatistical interpolation of hourly precipitation from rain gauges and radar for a large-scale extreme rainfall event
NASA Astrophysics Data System (ADS)
SummaryThe methods kriging with external drift (KED) and indicator kriging with external drift (IKED) are used for the spatial interpolation of hourly rainfall from rain gauges using additional information from radar, daily precipitation of a denser network, and elevation. The techniques are illustrated using data from the storm period of the 10th to the 13th of August 2002 that led to the extreme flood event in the Elbe river basin in Germany. Cross-validation is applied to compare the interpolation performance of the KED and IKED methods using different additional information with the univariate reference methods nearest neighbour (NN) or Thiessen polygons, inverse square distance weighting (IDW), ordinary kriging (OK) and ordinary indicator kriging (IK). Special attention is given to the analysis of the impact of the semivariogram estimation on the interpolation performance. Hourly and average semivariograms are inferred from daily, hourly and radar data considering either isotropic or anisotropic behaviour using automatic and manual fitting procedures. The multivariate methods KED and IKED clearly outperform the univariate ones with the most important additional information being radar, followed by precipitation from the daily network and elevation, which plays only a secondary role here. The best performance is achieved when all additional information are used simultaneously with KED. The indicator-based kriging methods provide, in some cases, smaller root mean square errors than the methods, which use the original data, but at the expense of a significant loss of variance. The impact of the semivariogram on interpolation performance is not very high. The best results are obtained using an automatic fitting procedure with isotropic variograms either from hourly or radar data.
Haberlandt, Uwe
An Experimental Multi Sensor Rainfall Estimation Technique
NASA Astrophysics Data System (ADS)
In this preliminary study, an attempt was made to estimate rainfall using rainfall information from several sources such as rain gauges and remotely sensed radars and satellites. The data used were collected from the Tropical Storm Allison for the period June 5-9, 2001 over the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) region. The rain gauge data used were the hourly reports received at WGRFC for operational use. The radar rainfall estimates used were hourly products from the WSR-88D Precipitation Processing System. The satellite estimates used were operational rainfall product from the Geostationary Operational Environmental Satellite produced by the National Environmental Satellite Data and Information Service. In addition to these data, lightning data from the National Lightning Detection Network made available through the Advanced Weather Interactive Processing System (AWIPS) were also used. Hourly collocated rain gauge, radar, satellite and lightning data has been collected for the 5 day period and is called total data set. From this total data set, rain gauges under the influence of lightning were identified as convective cases and rest were identified as stratiform cases. As a first step, multiple regression models were developed using rain gauge measurements as predictands and radar, satellite, lightning and various multiplicative combinations of these as predictors. Models were developed for the total, convective and stratiform cases. Preliminary results indicate that the convective model showed improvement over the total and stratiform models. These results and results from other model building techniques such as Neural Networks will be presented.
Kondragunta, C. R.
NSDL National Science Digital Library
The National Oceanic and Atmospheric Administration (NOAA) provides these two Websites on weather. The first site serves as a major hub for information related to weather, with links to primary data sources, forecasts, maps, images (such as the latest satellite imagery for North America), and a wealth of other data, including space weather. Researchers will also find links to national weather research centers and other related agencies.
NSDL National Science Digital Library
What are the different types of weather? In this project you will compare different types of weather by drawing pictures and making it into a flip book. First you will begin by learning about the different types of weather. Read about each topic. Then get together with your partner and draw a picture of each type of weather. 1. Thunder storm Thunder storm Thunder storm Kids 2. Lightning Lightning Lightning picture 3. Tornado Tornadoes Tornado Kids 4. ...
Jennie, Miss
Simultaneous Ocean Cross-Section and Rainfall Measurements from Space with a Nadir-Pointing Radar.
National Technical Information Service (NTIS)
A method to determine simultaneously the rainfall rate and the normalized backscattering cross section of the surface was evaluated. The method is based on the mirror reflected power, p sub m which corresponds to the portion of the incident power scattere...
R. Meneghini D. Atlas
Detection of Subsurface Defects in Levees in Correlation to Weather Conditions Utilizing Ground Penetrating Radar
NASA Astrophysics Data System (ADS)
Ground Penetrating Radar (GPR) has been used for many years in successful subsurface detection of conductive and non-conductive objects in all types of material including different soils and concrete. Typical defect detection is based on subjective examination of processed scans using data collection and analysis software to acquire and analyze the data, often requiring a developed expertise or an awareness of how a GPR works while collecting data. Processing programs, such as GSSI's RADAN analysis software are then used to validate the collected information. Iowa State University's Center for Nondestructive Evaluation (CNDE) has built a test site, resembling a typical levee used near rivers, which contains known sub-surface targets of varying size, depth, and conductivity. Scientist at CNDE have developed software with the enhanced capabilities, to decipher a hyperbola's magnitude and amplitude for GPR signal processing. With this enhanced capability, the signal processing and defect detection capabilities for GPR have the potential to be greatly enhanced. This study will examine the effects of test parameters, antenna frequency (400MHz), data manipulation methods (which include data filters and restricting the range of depth in which the chosen antenna's signal can reach), and real-world conditions using this test site (such as varying weather conditions) , with the goal of improving GPR tests sensitivity for differing soil conditions.
Martinez, I. A.; Eisenmann, D.
NEXRAD Single and Dual Polarization Radar-Rainfall Product Comparison for the NASA Iowa Flood Studies (IFloodS)
NASA Astrophysics Data System (ADS)
During the months of April to June 2013, NASA conducted a field experiment called Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission in the central and northeastern Iowa in the United States. The purpose of IFloodS is to enhance the understanding of flood-related precipitation processes in events worldwide. While there are multiple rainfall data sets (satellite, radar, and ground reference data products) available as legacy from IFloodS, the authors focus on the comparison of the NEXRAD single and dual polarization precipitation products to evaluate potential benefits of using dual polarization data for flood-related precipitation events. The Hydro-NEXRAD and CSU (Colorado State University)-HIDRO blended precipitation processing algorithms were used to generate single and dual polarization products, respectively. Data from four NEXRAD radars (Des Moines, IA; Davenport, IA; Minneapolis, MN; and La Crosse, WI) were combined to cover the study area. Uncertainties of both products using dense networks of ground reference (e.g., rain gauge and disdrometer) are characterized. Major differences and similarities based on the observed precipitation cases are also discussed.
Seo, B.; Dolan, B.; Krajewski, W. F.; Rutledge, S. A.; Petersen, W. A.
High-Resolution Rainfall Rate and DSD Estimation From X-Band Polarimetric Radar Measurements
This study describes newly developed attenuation correction and microphysical retrieval methods for X-band polarimetric radar (XPOL). It concentrates on exploring the dependence of the retrieval on raindrop size distribution variability, and its sensitivity with respect to the selection of oblateness-size relation (or axial ratio) and maximum diameter limit. Variations in the assumed form of the raindrop axial ratio may result
Marios N. Anagnostou; Emmanouil N. Anagnostou; J. Vivekanandan
Spaceborne radar measurements of verticle rainfall velocity: the non-uniform beam filling considerations
NASA Technical Reports Server (NTRS)
In this paper, the characteristics of the Doppler power spectrum observed by a spaceborne precipitation radar, under on Uniform Beam Filling (NUBF) condion will be presented, and the expected performance of some standard Doppler estimators and that of a new inversion technique will be investigated and compared.
Im, E.; Tanelli, S.; Durden, S. L.; Facheris, L.; Giuli, D.; Smith, E. A.; Haddad, Z. S.
MicroRadarNet: A network of weather micro radars for the identification of local high resolution precipitation patterns
In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network.Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors
Stefano Turso; S. Paolella; M. Gabella; G. Perona
A Probable Unexplored Meteorite Fall Found in Archived Weather Radar Data
NASA Astrophysics Data System (ADS)
Imagery from NEXRAD radar archives appears to show a meteorite fall at a location defined by eyewitness accounts of a bright meteor event just north of Jacksonville, Illinois, on 04 Feb 2007. Archived radar data may contain many undiscovered falls.
Fries, M.; Fries, J.; Schaefer, J.
A mobile X-POL weather radar for hydrometeorological applications in the metropolitan area of S�o Paulo, Brazil
NASA Astrophysics Data System (ADS)
This paper presents the first mobile X-band dual-polarization Doppler weather radar termed MXPOL operated by the Laboratory of Hydrometeorology (LABHIDRO) of the University of S�o Paulo, S�o Paulo, Brazil. It is used in graduate and under graduate courses, real-time monitoring and nowcasting of severe weather in the Metropolitan Area of S�o Paulo (MASP). It is one of the first of its kind to be used operationally to provide real-time high spatial resolution polarimetric data. MXPOL is an important component of a Hydrometeorological Forecast System (Pereira Filho et al., 2005) for MASP. This manuscript presents some instances of MXPOL polarimetric measurements of weather systems and their respective microphysical, dynamical and boundary layer features that can improve nowcasting.
Pereira Filho, A. J.
A mobile X-POL weather radar for hydrometeorological applications in the metropolitan area of S�o Paulo, Brazil
NASA Astrophysics Data System (ADS)
This paper presents the first mobile X-band dual-polarization Doppler weather radar termed MXPOL operated by the Laboratory of Hydrometeorology (LABHIDRO) of the University of S�o Paulo, S�o Paulo, Brazil. It is used in graduate and under graduate courses, real time monitoring and nowcasting of severe weather in the Metropolitan Area of S�o Paulo (MASP). It is one of the first of its kind to be used operationally to provide real time high spatial resolution polarimetric data. MXPOL is an important component of a Hydrometeorological Forecast System (Pereira Filho et al., 2005) for MASP. This manuscript presents some instances of MXPOL polarimetric measurements of weather systems and their respective microphysical, dynamical and boundary layer features that can improve nowcasting.
Pereira Filho, A. J.
Wind Turbine Clutter mitigation for weather radar by Adaptive Spectrum Processing
Wind Turbine Clutter (WTC) is the radar clutter caused by strong backscatter from large wind turbines within the radar vicinity. Due to the rotation of the rotor blades, the Doppler spectrum of WTC varies from scan to scan. This time-varying radar signature results in the failure of classic ground clutter filter techniques. The Adaptive Spectrum Processing (ASP) algorithm proposed in
Fanxing Kong; Yan Zhang; Robert Palmer
Campaign mode observation of tropical convection using ground-based radar systems
Tropical convection plays an important role in enhancing rainfall and also creates uncertainty in the model-based predictions of weather in tropics due to the latent heat released into the troposphere. Ground-based radar systems are important tools available for the effective characterization of convective events. Availability of different radar systems ideally suited to study tropical convection in an area popularly known
Lekshmi Vijayan; G. Viswanathan; R. Ranga Rao; A. R. Jain; D. Narayana Rao; V. K. Anandan; P. Rajesh Rao; S. Kalyana Sundaram; R. Suresh; S. B. Thampi
Correcting the radar rainfall forcing of a hydrologic model with data assimilation: application to flood forecasting in the Lez Catchment in Southern France
NASA Astrophysics Data System (ADS)
For flood prediction and watershed characterization, radar data can provide a key advantage in terms of temporal and spatial resolution, as runoff generation is sensitive to rainfall location. However, the radar data input to the hydrological model is subject to uncertainties related to a non-linear vertical reflectivity profile (Borga, 2002), calibration of the Z-R relationship and beam blocking effects (Vieux & Bedient, 2004). Specifically for the Lez catchment, radar data quality varies on a seasonal basis and is degraded in winter (Coustau et al., 2011). These uncertainties translate to errors in the simulated discharges. Data assimilation techniques can be applied to improve the quality of radar data or parameters input to the hydrological model. Rainfall inputs were corrected by a factor of ?, calculated separately for each event by assimilating observed discharges. This coefficient was compared with the mean field bias (MFB), a corrective coefficient determined using ground rainfall measurements (Vieux & Bedient, 2004). Simulations were then performed in the context of 'real-time' peak discharge prediction and corrected using data assimilation. A set of 18 rainfall events was used to simulate discharges for the 114 km2 Lez Catchment, which is subject to heavy orographic rainfall and characterized by a karstic geology. A distributed, event-based, parsimonious hydrological model was used, with runoff production controlled by a modified SCS method, parameterized by S, representing the initial soil moisture deficit (Coustau et al., 2011). Application of the data assimilation algorithm was carried out in two different modes: re-analysis, in which all observations during the flood event are assimilated and prevision, in which only observations before the event peak are assimilated. In re-analysis mode, the soil moisture content was initialized by an S calibrated for the simulation forced by MFB corrected rainfall. In prevision mode, the soil moisture deficit was initialized using the Hu2 indicator, modeled remotely by M�t�o-France. The Kalman Filter algorithm was used to assimilate discharge observations for the correction of model inputs. The study resulted in two main findings: 1) simulations using radar rainfall corrected by ?, calculated by data assimilation in re-analysis mode showed an improved Nash criterion when compared to simulations forced by MFB corrected rainfall and 2) simulations using radar rainfall data corrected by data assimilation in prevision mode showed, on average, improved results over the initial simulation. The re-analysis results provide an important validation of the model, demonstrating that the assimilation of discharge data provides information about the system not available with corrections based solely on rain gauge data. The second result demonstrates the ability of data assimilation to render radar data useable for flood prediction. This finding is especially pertinent for the next step of this study which is the use of modeled future rainfall data to extend lead times; these rainfalls are expected to be subject to high levels of uncertainty.
Harader, E. B.; Estupina-Borrell, V.; Ricci, S. M.; Coustau, M.; Thual, O.; Bouvier, C.
Dynamic model for space-time weather radar observation and nowcasting
NASA Astrophysics Data System (ADS)
A general framework of the dynamic model for space-time radar observations has been developed in the current research. There exist three difficulties in modeling space-time radar observations: (1) high dimensionality due to the high-resolution radar measurements over a large area, (2) non-stationarity due to the storm motion, and (3) nonstationarity due to evolution (growth and decay). These difficulties are addressed in this research. To deal with the storm motion, an efficient radar storm tracking algorithm is developed in the spectral domain. Based on this new technique, the Dynamic and Adaptive Radar Tracking of Storms (DARTS) is developed and evaluated using the synthesized and the observed radar reflectivity. To tackle the high dimensionality and model the spatial variability of radar observations, a general modeling framework is formulated and the singular value decomposition (SVD) is used for dimension reduction. To deal with the dynamic evolution and model the temporal variability of radar observations, the motion-compensated temporal alignment (MCTA) transformation is developed. In this analysis the evolution of radar storm fields is modeled by the linear dynamic system (LDS) in the low-dimensional subspace. The applications of the dynamic model for space-time radar observations are further demonstrated. Spatial and dynamic characteristics are obtained based on the estimated model parameters using three months of radar observations. The characteristic temporal scales are quantified for this dataset. The correlation between the temporal characterization and the spatial characterization of observed radar fields are explored. The simulation capability of different spatiotemporal radar reflectivity fields is demonstrated. Evaluation of the space time variability is particularly important in the context of adaptive scanning of storm systems. The short-term prediction of radar reflectivity fields based on the space-time dynamic model is evaluated using observed radar data. The simulations of the DARTS for real-time applications are also conducted and evaluated.
Xu, Gang
Model-based iterative approach to polarimetric radar rainfall estimation in presence of path attenuation
NASA Astrophysics Data System (ADS)
A new model-based iterative technique to correct for attenuation and differential attenuation and retrieve rain rate, based on a neural-network scheme and a differential phase constraint, is presented. Numerical simulations are used to investigate the efficiency and accuracy of this approach named NIPPER. The simulator is based on a T-matrix solution technique, while precipitation is characterized with respect to shape, raindrop size distribution and orientation. A sensitivity analysis is performed in order to evaluate the expected errors of this method. The performance of the proposed methodology on radar measurements is evaluated by using one-dimensional Gaussian shaped rain cell models and synthetic radar data derived from disdrometer measurements. Numerical results are discussed in order to evaluate the robustness of the proposed technique.
Vulpiani, G.; Marzano, F. S.; Chandrasekar, V.; Uijlenhoet, R.
NSDL National Science Digital Library
You will learn how to describe and observe changes in weather patterns by completing the following activities. The students will record and report changes in weather on their data sheet. The Process: Read the information on How Air Pressure Affects You. In this article you will see the term barometer. Write its definition. Now look over Weather Facts. Now go to Investigate Climate Conditions and use the weather maker to observe the effects of certain changes. Answer the questions: How much of a change in temperature is needed to make it ...
Lauren, Ms.
The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network
NASA Astrophysics Data System (ADS)
Using measurements from the national network of 12 weather radar stations for the 11-year period 2000-2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate- to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.
Devasthale, A.; Norin, L.
The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network
NASA Astrophysics Data System (ADS)
Using measurements from the national network of 12 weather radar stations for the last decade (2000-2010), we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects namely, the diurnal cycle of precipitation and its seasonality, the dominant time scale (diurnal vs. seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate to high intensity events (precipitation > 0.34 mm (3 h)-1) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high intensity events (precipitation > 1.7mm (3 h)-1) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.
Devasthale, A.; Norin, L.
Potential use of radar QPE for hydrological design
NASA Astrophysics Data System (ADS)
Intensity-duration-frequency (IDF) curves are commonly used for flood management design, and are identified from rainfall records analyzing maximum intensity values for a set of given durations. This approach applies to raingauge measurements even if usual design applications would prefer catchment scale curves. Weather radar provides distributed rainfall estimates with high spatial and temporal resolutions; in this way it is able to exploit the dynamics and variability of extreme rainfall events over wide areas. Two main objections usually restrain this approach: the length of radar data records and the reliability of radar quantitative precipitation estimations (QPE). This work aims to explore the feasibility of using radar QPE for the identification of IDF curves by means of a long length radar data archive and a combined physical- and quantitative- adjustment of radar rainfall estimates. Two C-Band weather radars are located in the eastern Mediterranean area (Tel Aviv, Israel) and are operational since 1990 and 1997 respectively, providing relatively long-term records. Radar measurements are elaborated using physically-based correction algorithms and are then adjusted by removing the mean field bias with respect to ground observations. Accuracy of radar QPE is assessed by comparison with raingauge measurements using a bootstrap technique. IDF curves are calculated for a set of reference raingauges using different sources of rainfall information: i) raingauge data record ("true" IDF), ii) data record of the closest raingauge and iii) radar QPE obtained excluding the examined raingauge from the adjustment procedure. Accuracy of radar-based IDF compared to close by-raingauge IDF is assessed. Results of this on-going study will be presented leading to conclusions on the potential use of radar QPE for IDF estimation.
Marra, Francesco; Morin, Efrat
Observations of Hurricane Bonnie in spaceborne synthetic aperture radar (SAR) and next-generation Doppler weather radar (NEXRAD)
Atmospheric circulation systems have being shown to produce observable signatures on spaceborne synthetic aperture radar (SAR) imagery of the ocean surface. Capillary and small gravity ocean waves of roughly the scale of the SAR electromagnetic wavelength, the so-called Bragg waves, provide the surface roughness that allows for SAR mapping of both ocean and atmospheric mesoscale features. Two RADARSAT SAR images
Pablo Clemente-Colon; Peter C. Manousos; William G. Pichel; Karen Friedman
Observation of Sea Breeze Front and its Induced Convection over Chennai in Southern Peninsular India Using Doppler Weather Radar
NASA Astrophysics Data System (ADS)
Sea breeze, the onshore wind over a coastal belt during daytime, is a welcoming weather phenomenon as it modulates the weather condition by moderating the scorching temperature and acts as a favourable mechanism to trigger convection and induce precipitation over coastal and interior locations. Sea breeze aids dispersal of pollutants as well. Observational studies about its onset, depth of circulation and induced precipitation have been carried out in this paper for the period April to September, 2004 2005 using a S-band Doppler Weather Radar functioning at Cyclone Detection Radar Station, India Meteorological Department, Chennai, India. The onset of sea breeze has been observed to be between 0900 and 1000 UTC with the earliest onset at 0508 UTC and late onset at 1138 UTC. The frequency is greater during the southwest monsoon season, viz., June September and the frequency of initial onset is greater in north Chennai. The modal length of sea breeze is between 20 and 50 km with extreme length as high as 100 km also having been observed. Though the inland penetration is on average 10 to 20 km, penetration reaching 100 km was also observed on a number of cases. The induced convection could be seen in the range 50 100 km in more than 53% of the cases. The mean depth of sea breeze circulation is 300 600 m but may go well beyond 1000 m on conducive atmospheric conditions.
Suresh, R.
By Air and Land: Estimating Post-Fire Debris-Flow Susceptibility through High-Resolution Radar Reflectivity and Tipping-Bucket Gage Rainfall
NASA Astrophysics Data System (ADS)
Wildfires often increase the occurrence of post-fire hazardous flash floods and debris flows from steeplands during intense rainfall. Rainfall intensity-duration thresholds have been used to forecast when this hazard increases rapidly; one threshold for Southern California is 15 mm/hr. However, such thresholds are usually developed with point measurements that only capture a small portion of the landscape. In an attempt to limit potential loss of life, the USGS is collaborating with NOAA on a demonstration early-warning system. To address the lack of spatial rainfall coverage, NOAA deployed a small mobile radar truck (SMART-R) to the Day fire in the western Transverse Range during the 2006-07 winter, and to the Canyon and Corral fires in the Santa Monica Mountains near Malibu during the 2007-08 winter. The SMART-R's C-band Doppler radar can be used to estimate rainfall rates over entire burned areas. On topography susceptible to debris flows within these 3 fires, the USGS installed a dense array of ground-based instruments, including 8 tipping- bucket rain gages in the Day fire, and 3 each in the Canyon and Corral fires. After converting hourly time- step grids of SMART-R reflectivity (150 m node spacing) into precipitation estimates, we compared the gage data to its spatially coincident SMART-R cell.Results from the Day fire indicate that SMART-R derived seasonal and event-based rainfall totals were typically greater than gage totals during the 2006-07 winter of record-low rainfall. Both data sets, however, reflected similar spatial patterns of rainfall intensity. In contrast, for the Malibu fires there is no systematic agreement in spatial pattern or rainfall mismatch; the difference between the two data sets. Of the 9 storms recorded during this 2007-08 winter, SMART-R estimates of rainfall totals exceeded the gage totals for only 3, underestimating totals for the remaining 6. The mismatch magnitudes also exceed that of the previous winter recorded at the Day fire, and, for the largest storm of the season, was 129 mm less than a rain gage total.These discrepancies reduce the reliability of a potential SMART-R-advised warning system, assuming truth from ground-based gages. During the 2007-08 winter near Malibu the rain gages recorded that the 15 mm/hr warning threshold was exceeded during only one storm, and only at one gage in the Corral fire. This event transported large amounts of sediment that resulted in road closures, and it produced at least one "firehose" debris flow generated by runoff from steep, exposed bedrock. In contrast, SMART-R derived rainfall intensities exceeded this threshold at all gage locations for 2 of the 3 storms with overestimated rainfall intensities. It underestimated rainfall intensities for the 6 remaining storms; such underestimates could have led to potential false negatives, which are of concern for preserving human life.It is not yet clear which storms are amenable to the use of SMART-R technology for capturing spatial estimates of rainfall intensity, but results from the Day fire showing topographically forced rainfall patterns support validity of the system. Future work needs to address discrepancies arising from comparing spatially continuous atmospheric radar measurements with terrestrial point measurements. One effort to mitigate some interpretation complexities could include the installation of a disdrometer along with the rain gages, to measure rain drop-size distributions to calibrate in near real-time the relation between measured reflectivity and inferred rainfall.
Hanshaw, M. N.; Schmidt, K. M.; Jorgensen, D. P.; Stock, J. D.
Analysis of airborne Doppler lidar, Doppler radar and tall tower measurements of atmospheric flows in quiescent and stormy weather
NASA Technical Reports Server (NTRS)
The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments.
Bluestein, H. B.; Doviak, R. J.; Eilts, M. D.; Mccaul, E. W.; Rabin, R.; Sundara-Rajan, A.; Zrnic, D. S.
Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set
NASA Technical Reports Server (NTRS)
The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.
Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.
ERIC Educational Resources Information Center
This subject guide to weather resources includes Web sites, CD-ROMs and software, videos, books, audios, magazines, and professional resources. Related disciplines are indicated, age levels are specified, and a student activity is included. (LRW)
Web Feet K-8, 2000
In the natural environment, weathering and breakdown of stone is an accepted part of long-term landscape development but the\\u000a same acceptance of change and deterioration is not extended to stone used in construction especially when such deterioration\\u000a affects historically and\\/or culturally important structures. The value of an integrative approach to improve understanding\\u000a of weathering and failure of building stone is
P. A. Warke; J. McKinley; B. J. Smith
On the Tropical Rainfall Measuring Mission (TRMM): Bringing NASA's Earth System Science Program to the Classroom
NASA Technical Reports Server (NTRS)
The Tropical Rainfall Measuring Mission is the first mission dedicated to measuring tropical and subtropical rainfall using a variety of remote sensing instrumentation, including the first spaceborne rain-measuring radar. Since the energy released when tropical rainfall occurs is a primary "fuel" supply for the weather and climate "engine"; improvements in computer models which predict future weather and climate states may depend on better measurements of global tropical rainfall and its energy. In support of the STANYS conference theme of Education and Space, this presentation focuses on one aspect of NASA's Earth Systems Science Program. We seek to present an overview of the TRMM mission. This overview will discuss the scientific motivation for TRMM, the TRMM instrument package, and recent images from tropical rainfall systems and hurricanes. The presentation also targets educational components of the TRMM mission in the areas of weather, mathematics, technology, and geography that can be used by secondary school/high school educators in the classroom.
Shepherd, J. Marshall
High-Resolution Rainfall From Radar Reflectivity and Terrestrial Rain Gages for use in Estimating Debris-Flow Susceptibility in the Day Fire, California
NASA Astrophysics Data System (ADS)
Constraining the distribution of rainfall is essential to evaluating the post-fire mass-wasting response of steep soil-mantled landscapes. As part of a pilot early-warning project for flash floods and debris flows, NOAA deployed a portable truck-mounted Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) to the 2006 Day fire in the Transverse Ranges of Southern California. In conjunction with a dense array of ground- based instruments, including 8 tipping-bucket rain gages located within an area of 170 km2, this C-band mobile Doppler radar provided 200-m grid cell estimates of precipitation data at fine temporal and spatial scales in burned steeplands at risk from hazardous flash floods and debris flows. To assess the utility of using this data in process models for flood and debris flow initiation, we converted grids of radar reflectivity to hourly time-steps of precipitation using an empirical relationship for convective storms, sampling the radar data at the locations of each rain gage as determined by GPS. The SMART-R was located 14 km from the farthest rain gage, but <10 km away from our intensive research area, where 5 gages are located within <1-2 km of each other. Analyses of the nine storms imaged by radar throughout the 2006/2007 winter produced similar cumulative rainfall totals between the gages and their SMART-R grid location over the entire season which correlate well on the high side, with gages recording the most precipitation agreeing to within 11% of the SMART-R. In contrast, on the low rainfall side, totals between the two recording systems are more variable, with a 62% variance between the minimums. In addition, at the scale of individual storms, a correlation between ground-based rainfall measurements and radar-based rainfall estimates is less evident, with storm totals between the gages and the SMART-R varying between 7 and 88%, a possible result of these being relatively small, fast-moving storms in an unusually dry winter. The SMART-R also recorded higher seasonal cumulative rainfall than the terrestrial gages, perhaps indicating that not all precipitation reached the ground. For one storm in particular, time-lapse photographs of the ground document snow. This could explain, in part, the discrepancy between storm-specific totals when the rain gages recorded significantly lower totals than the SMART-R. For example, during the storm where snow was observed, the SMART-R recorded a maximum of 66% higher rainfall than the maximum recorded by the gages. Unexpectedly, the highest elevation gage, located in a pre-fire coniferous vegetation community, consistently recorded the lowest precipitation, whereas gages in the lower elevation pre- fire chaparral community recorded the highest totals. The spatial locations of the maximum rainfall inferred by the SMART-R and the terrestrial gages are also offset by 1.6 km, with terrestrial values shifted easterly. The observation that the SMART-R images high rainfall intensities recorded by rain gages suggests that this technology has the ability to quantitatively estimate the spatial distribution over larger areas at a high resolution. Discrepancies on the storm scale, however, need to be investigated further, but we are optimistic that such high resolution data from the SMART-R and the terrestrial gages may lead to the effective application of a prototype debris-flow warning system where such processes put lives at risk.
Hanshaw, M. N.; Schmidt, K. M.; Jorgensen, D. P.; Stock, J. D.
Simultaneous ocean cross-section and rainfall measurements from space with a nadir-pointing radar
NASA Technical Reports Server (NTRS)
A method to determine simultaneously the rainfall rate and the normalized backscattering cross section of the surface was evaluated. The method is based on the mirror reflected power, p sub m which corresponds to the portion of the incident power scattered from the surface to the precipitation, intercepted by the precipitation, and again returned to the surface where it is scattered a final time back to the antenna. Two approximations are obtained for P sub m depending on whether the field of view at the surface is either much greater or much less than the height of the reflection layer. Since the dependence of P sub m on the backscattering cross section of the surface differs in the two cases, two algorithms are given by which the path averaged rain rate and normalized cross section are deduced. The detectability of P sub m, the relative strength of other contributions to the return power arriving simultaneous with P sub m, and the validity of the approximations used in deriving P sub m are discussed.
Meneghini, R.; Atlas, D.
Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds
Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73�97% of the total TSS load and 64�88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.
Danz, Mari E.;Corsi, Steven;Brooks, Wesley R.; Bannerman, Roger T.
Polarimetric X-band weather radar measurements in the tropics: radome and rain attenuation correction
NASA Astrophysics Data System (ADS)
A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with three additional laser disdrometers. The disdrometers are capable of measuring the raindrop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This set-up allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. For the campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps was analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured at a distance of 20 km from the radar. Radome attenuation reached values up to 14 dB which was found to be consistent with an empirical radome attenuation vs. rain intensity relation that was previously developed for the same radar type. In contrast to previous work, our results suggest that radome attenuation should be estimated individually for every view direction of the radar in order to obtain homogenous reflectivity fields.
Schneebeli, M.; Sakuragi, J.; Biscaro, T.; Angelis, C. F.; Carvalho da Costa, I.; Morales, C.; Baldini, L.; Machado, L. A. T.
High resolution fire danger modeling : integration of quantitative precipitation amount estimates derived from weather radars as an input of FWI
NASA Astrophysics Data System (ADS)
Fire meteo indices provide efficient guidance tools for the prevention, early warning and surveillance of forest fires. The indices are based on meteorological input data. The underlying approach is to exploit meteorological information as fully as possible to model the soil water content, biomass condition and fire danger. Fire meteorological danger is estimated by M�t�o-France at national level through the use of Fire Weather Index. The fire index services developed within the PREVIEW project (2005-2008) offer for the first time very high resolution mapping of forest fire risk. The high resolution FWI has been implemented in France complementary to the existing EFFIS operated by the Joint Research Center. A new method (ANTILOPE method) of combining precipitation data originating from different sources like rain gauges and weather radar measurements has been applied in the new service. Some of the advantages of this new service are: � Improved detection of local features of fire risk � More accurate analysis of meteorological input data used in forest fire index models providing added value for forest fire risk forecasts � Use of radar precipitation data "as is� utilizing the higher resolution, i.e. avoiding averaging operations The improved accuracy and spatial resolution of the indices provide a powerful early warning tool for national and regional civil protection and fire fighting authorities to alert and initiate forest fire fighting actions and measures.
Cloppet, E.; Regimbeau, M.
Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear
NASA Technical Reports Server (NTRS)
An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.
Keel, Byron M.
Radar data assimilation for the simulation of mesoscale convective systems
NASA Astrophysics Data System (ADS)
A heavy rainfall case related to Mesoscale Convective Systems (MCSs) over the Korean Peninsula was selected to investigate the impact of radar data assimilation on a heavy rainfall forecast. The Weather Research and Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation system with tuning of the length scale of the background error covariance and observation error parameters was used to assimilate radar radial velocity and reflectivity data. The radar data used in the assimilation experiments were preprocessed using quality-control procedures and interpolated/thinned into Cartesian coordinates by the SPRINT/CEDRIC packages. Sensitivity experiments were carried out in order to determine the optimal values of the assimilation window length and the update frequency used for the rapid update cycle and incremental analysis update experiments. The assimilation of radar data has a positive influence on the heavy rainfall forecast. Quantitative features of the heavy rainfall case, such as the maximum rainfall amount and Root Mean Squared Differences (RMSDs) of zonal/meridional wind components, were improved by tuning of the length scale and observation error parameters. Qualitative features of the case, such as the maximum rainfall position and time series of hourly rainfall, were enhanced by an incremental analysis update technique. The positive effects of the radar data assimilation and the tuning of the length scale and observation error parameters were clearly shown by the 3DVAR increment.
Lee, Jo-Han; Lee, Hyun-Ha; Choi, Yonghan; Kim, Hyung-Woo; Lee, Dong-Kyou
A seamless flash-flood early warning tool based on IDF-curves and coupling of weather-radar with numerical weather predictions
NASA Astrophysics Data System (ADS)
A flash-flood is a flood that develops rapidly after a heavy precipitation event. Flash-flood forecasting is an important field of research because flash floods cause a lot of fatalities and damage. A flash-flood early warning tool is developed based on precipitation statistics. Our target areas are small ungauged areas of southern-Switzerland. A total of 759 sub-cathcments was considered. In a first intensity-duration-frequency (IDF) curves for each catchment have been calculated basin on: A) Gridded precipitation products for the period 1961 to 2012 and B) gridded reforecast of the COSMO-LEPS NWP for the period 1971-2000. These different IDF-curves at the catchment level in combination with precipitation forecasts are the basis for the flash-flood early warning tool. The forecast models used are COSMO-2 (deterministic, updated every three hours and with a lead time of 24 hours) and COSMO-LEPS (probabilistic, 16 member and with a lead time of five days). In operational mode COSMO-2 is nudged to real-time data of a weather-radar precipitation obtained by blending the radar qpe with information from a national network of precipitation data. This product is called COMBIPRECIP. The flash-flood early warning tool has been evaluated against observed events. These events are either discharge peaks in gauged sub-areas or reports of damages caused by flash-flood events. The hypothesis that it is possible to detect hydrological events with the flash-flood early warning tool can be partly confirmed. The highest skill is obtained if the return-period of weather radar QPE is assessed at hourly time scale. With this it was possible to confirm most of the damage events occurred in 2010 and 2011. The prototype tool is affected by several false alarms. This is because initial conditions of the soils are not considered. Further steps will be therefore focussed on the addition of real-time hydrological information as obtained from the application of high resolution distributed models.
Liechti, Kaethi; Knechtl, Valentin; Andres, Norina; Sideris, Ioannis; Zappa, Massimiliano
Flash flood warning in mountaineous areas using X-band weather radars and the AIGA method in the framework of the RHYTMME project
NASA Astrophysics Data System (ADS)
The knowledge of precipitations still remains a tricky issue in mountaineous areas: the available rain-gauges are in a limited number and most often located in the valleys, and the radar rainfall estimates have to deal with a lot of problems due to the relief and the difficulty to distinguish the different types of hydrometeors (snow, hail, rain). In this context, the "RHYTMME" project deals with two main issues: - Providing an accurate radar rainfall information in mountainous areas. - Developing a real-time hazards warning system based on this information. To answer to the first issue, a X-band doppler dual polarized radar network is currently implemented in the French South Alps. At the end of the project (2013), three new radars will be installed, completing a pre-existing radar already installed on the Mont Vial top since 2008 (Hydrix� technology developed by the Novimet company, and tested in a previous project). The present communication focuses on the flash flood warning issue. It presents some results obtained by coupling the radar estimates to a simple distributed hydrological model (the AIGA method). Results are compared on damages observed by end-users, which were strongly involved into the project. The RHYTMME project is co-piloted by Meteo-France and the Cemagref and has the financial support of the European Union, the Provence-Alpes-C�te d'Azur Region and the French Ministry in charge of Ecology.
Javelle, Pierre; Defrance, Dimitri; Ecrepont, St�phane; Fouchier, Catherine; M�riaux, Patrice; Tolsa, Mathieu; Westrelin, Samuel
MicroRadarNet: a Network of Integrated High-Resolution Weather Micro Radars to Service Tracking and Forecasting of Local Precipitation Patterns
NASA Astrophysics Data System (ADS)
MicroRadarNet (MRN) is a network of high-resolution, low-cost, low-power consumption micro radars for continuous, unattended meteorological monitoring. The MRN project started in the framework of the European INTERREG IIIB Alpine Space Programme (within the FORALPS project) since 2004 and was developed and operated by the Remote Sensing Group at the Politecnico di Torino from its early design stages. MRN is currently under its release and operational validation phase, cooperating with professional weather operators (e.g. civil protection offices) to run extensive on-field tests. The key aspects of MRN are a short range strategy (about thirty kilometers) and the implementation of an effective sensor network approach. Raw spatial and temporal data is processed on-board in real-time, yielding a consistent evaluation of the information from the sensor and compressing the data to be transmitted. Network servers receive and merge the data sets coming from each unit yielding a synthetic, high-resolution plot of meteorological events (updated every minute). This networked approach implies in turn a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range C-band approach. An ever-growing database of meteorological events is being collected, thus providing a real-data test bench to refine assessment and data enhancement algorithms. Assessment techniques have been adopted for the estimation of precipitation, based on systematic rain gauges comparisons. Efforts were also devoted to the design and implementation of specific decluttering algorithms. New techniques to mitigate the effect of co-channel interference sources are also under testing. It is shown how these enhancement algorithms further improve the assessment process raising the overall data quality. Furthermore, new data analysis modules for the identification of precipitation patterns are being evaluating, including tracking routines for the short term prediction of meteorological cells motion and morphing. We strongly expect that these enhancements will be of some interest to the final users, contributing to the relevance of the provided weather information. Finally, particular attention has been devoted to set up efficient data availability and presentation mechanisms in other to ease weather services access for a broad range of purposes. Up-to-date Web techniques have been implemented accordingly. A consistent amount of case studies clearly shows that MicroRadarNet has enough potentialities to act as a fast-reacting weather monitoring tool. The proposed strategy, based on a network of short range radars, shall effectively collect high-resolution quality datasets while lowering the overall operational costs. This could prevent, by design, the volumetric resolution loss at higher ranges, as well as the need for atmospheric corrections and the shielding shortcomings which typically occur in orographically complex areas.
Turso, S.; Terzo, O.; Gabella, M.; Perona, G.
All-weather perception for man-portable robots using ultra-wideband radar
Autonomous man-portable robots have the potential to provide a wide range of new capabilities for both military and civilian applications. Previous research in autonomy for small robots has focused on vision, LIDAR, and sonar sensors. While vision and LIDAR work well in clear weather, they are seriously impaired by rain, snow, fog, and smoke. Sonar can penetrate adverse weather, but
Brian Yamauchi
Radar data bias correction implementing quantile mapping and investigation of its influence in a hydrological model
NASA Astrophysics Data System (ADS)
Weather radar is an important source of data for estimating rainfall rate with relatively high temporal and spatial resolution covering large areas. Although weather radar provides fine temporal and spatial resolution data, it is subject to different sources of error. Beside casual problems associated with radar, e.g. clutter and attenuation, weather radar either underestimates or overestimates the rainfall amount. Additionally, time steps with strangely high values result in destroying the structure of time series derived from radar data. In order to estimate areal precipitation for hydrological analyses, radar data could be merged with rain gauge network data. The merging product quality is strongly dependent on radar data quality. The main purpose of this study is to illustrate a method for improving radar data quality and to investigate the influence of radar data quality on merging products by means of cross validation. Quantile mapping on the two sources of data, the radar and rain gauge network, is implemented in this study to improve the radar data quality. After correcting the radar data, considering rain gauge data as the truth, the data is implemented into a hydrological model, HBV-IWW, to investigate the influence of the different input sources regarding model performance. It has been observed that implementing quantile mapping improves radar data quality significantly. On the other hand, using radar data after correction not only improves interpolation performances but also reveals other possible applications like disaggregation of daily rainfall data into finer temporal resolutions. Beside radar data quality, there are other factors influencing the model performance like network density and the applied interpolation technique. The study area is a mesoscale catchment located in Lower Saxony, northern Germany.
Rabiei, Ehsan; Wallner, Markus; Haberlandt, Uwe
A Reduction in Rainfall Associated with Smoke from SugarCane Fires--An Inadvertent Weather Modification?
An examination of 60 years of rainfall during three months of the cane-harvesting season has shown a reduction of rainfall at inland stations coinciding with increasing cane production; no such reduction occurred at a `control' station upwind of smoke from the cane fires. The reduction is consistent with the hypothesis that through their activity as condensation nuclei the smoke particles
J. Warner
Rain gauge - radar rainfall reanalysis of operational and research data in the C�vennes-Vivarais region, France, estimation error analysis over a wide range of scales.
NASA Astrophysics Data System (ADS)
In the C�vennes -Vivarais region in France, flash-flood events can occur due to high intensity precipitation events. These events are described in a detailed quantitative precipitation estimates, to be able to better characterize the hydrological response to these rain events in a number of small-scale nested watersheds (<100 km� typically), sampling various landscapes of the Mediterranean region. Radar - rain gauge merging methods described by Delrieu et al (2013) are applied to the 9 events of the autumn of 2012. Rainfall data is merged for both the operational networks in the C�vennes-Vivarais region in France on a 160 x 200 km window, as well as a research network, in the same region on a window of 15x30 km. The radar and rain gauge data of the operational network are collected from three organisms (M�t�o-France, Service de Pr�vision des Crues du Grand Delta and EdF/DTG). The research network contains high resolution data are from research rainfall observation systems deployed within the Enhanced Observation Period (autumn 2012-2015) of the HyMeX project (www.hymex.org). This project aims at studying the hydrological cycle in the Mediterranean with emphases on the hydro-meteorological extremes and their evolution in the coming decades. Rain gauge radar merging is performed using a kriging with external drift (KED) technique, and compared to the ordinary kriging (OK) of the rain gauges and the radar products on the same time scale using a cross-validation technique. Also a method is applied to quantify kriging estimation variances for both kriging techniques at the two spatial scales, in order to analyse the error characteristics of the interpolation methods at a scale range of 0.1 - 100 km� and 0.2 - 12 h. The combined information of the reanalysis of the data of the operational network and the research network gives a view on the error structure of rainfall estimations over several orders of magnitudes in spatial scale. This allows understanding of the error structure of these rain events, their relation to availability of data, and gives insight in the added value of detailed rainfall data on the understanding of the rainfall structure on very small, 'missing', scales (smaller than 1km2 and 1 hour time steps).
Wijbrans, Annette; Delrieu, Guy; Nord, Guillaume; Boudevillain, Brice; Berne, Alexis; Grazioli, Jacopo; Confoland, Audrey
NSDL National Science Digital Library
In the project you will learn about thunderstorms and tornadoes and play a weather matching game. What exactly are thunderstorms and tornadoes? Use your T- chart to explain some facts about a thunderstorm and a tornado as we review each. T-Chart Begin by reviewing what a thunderstorm is and how they form. Thunderstorm information What is a thunderstorm? What are thunderstorms most likely to occur? What causes thunder? Next review what a tornado ...
Caitlin, Ms.
Methods of Attenuation Correction for Dual-Wavelength and Dual-Polarization Weather Radar Data
NASA Technical Reports Server (NTRS)
In writing the integral equations for the median mass diameter and number concentration, or comparable parameters of the raindrop size distribution, it is apparent that the forms of the equations for dual-polarization and dual-wavelength radar data are identical when attenuation effects are included. The differential backscattering and extinction coefficients appear in both sets of equations: for the dual-polarization equations, the differences are taken with respect to polarization at a fixed frequency while for the dual-wavelength equations, the differences are taken with respect to frequency at a fixed polarization. An alternative to the integral equation formulation is that based on the k-Z (attenuation coefficient-radar reflectivity factor) parameterization. This-technique was originally developed for attenuating single-wavelength radars, a variation of which has been applied to the TRMM Precipitation Radar data (PR). Extensions of this method have also been applied to dual-polarization data. In fact, it is not difficult to show that nearly identical equations are applicable as well to dualwavelength radar data. In this case, the equations for median mass diameter and number concentration take the form of coupled, but non-integral equations. Differences between this and the integral equation formulation are a consequence of the different ways in which attenuation correction is performed under the two formulations. For both techniques, the equations can be solved either forward from the radar outward or backward from the final range gate toward the radar. Although the forward-going solutions tend to be unstable as the attenuation out to the range of interest becomes large in some sense, an independent estimate of path attenuation is not required. This is analogous to the case of an attenuating single-wavelength radar where the forward solution to the Hitschfeld-Bordan equation becomes unstable as the attenuation increases. To circumvent this problem, the equations can be expressed in the form of a final-value problem so that the recursion begins at the far range gate and proceeds inward towards the radar. Solving the problem in this way traditionally requires estimates of path attenuation to the final gate: in the case of orthogonal linear polarizations, the attenuations at horizontal and vertical polarizations (same frequency) are required while in the dual-wavelength case, attenuations at the two frequencies (same polarization) are required.
Meneghini, R.; Liao, L.
Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida
NASA Technical Reports Server (NTRS)
Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are discussed.
Crosson, William L.; Duchon, Claude E.; Raghavan, Ravikumar; Goodman, Steven J.
Considerations for the Design of Ground Clutter Cancelers for Weather Radar.
National Technical Information Service (NTIS)
Effects of the ground clutter ring in the second trip area for velocity estimation are investigated. Besides unfavorable effects on weather signal due to range square advantage, the clutter poses a new problem when interlaced samples for assigning correct...
A. Zahrai D. S. Zrnic' S. Hamidi
Microradarnet: AN Innovative High-Resolution Low-Cost X-Band Weather Radar Network
NASA Astrophysics Data System (ADS)
In this paper, an innovative micro radar network for meteorological purposes has been presented. The key aspects of this network, named MicroRadarNet (MRN), are a short range strategy (about thirty kilometers) and the implementation of effective enhancing techniques. High resolution spatial and temporal data is processed in real-time, yielding a synthetic and consistent evaluation of the information coming from the sensor network. This approach implies in turn a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range C-band approach.
Turso, S.; Zambotto, M.; Gabella, M.; Orione, F.; Notarpietro, R.; Perona, G.
High-resolution summer rainfall prediction in the JHWC real-time WRF system
NASA Astrophysics Data System (ADS)
The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr-1.
Lee, Dong-Kyou; Eom, Dae-Yong; Kim, Joo-Wan; Lee, Jae-Bok
Frequency diversity wideband digital receiver and signal processor for solid-state dual-polarimetric weather radars
NASA Astrophysics Data System (ADS)
The recent spate in the use of solid-state transmitters for weather radar systems has unexceptionably revolutionized the research in meteorology. The solid-state transmitters allow transmission of low peak powers without losing the radar range resolution by allowing the use of pulse compression waveforms. In this research, a novel frequency-diversity wideband waveform is proposed and realized to extenuate the low sensitivity of solid-state radars and mitigate the blind range problem tied with the longer pulse compression waveforms. The latest developments in the computing landscape have permitted the design of wideband digital receivers which can process this novel waveform on Field Programmable Gate Array (FPGA) chips. In terms of signal processing, wideband systems are generally characterized by the fact that the bandwidth of the signal of interest is comparable to the sampled bandwidth; that is, a band of frequencies must be selected and filtered out from a comparable spectral window in which the signal might occur. The development of such a wideband digital receiver opens a window for exciting research opportunities for improved estimation of precipitation measurements for higher frequency systems such as X, Ku and Ka bands, satellite-borne radars and other solid-state ground-based radars. This research describes various unique challenges associated with the design of a multi-channel wideband receiver. The receiver consists of twelve channels which simultaneously downconvert and filter the digitized intermediate-frequency (IF) signal for radar data processing. The product processing for the multi-channel digital receiver mandates a software and network architecture which provides for generating and archiving a single meteorological product profile culled from multi-pulse profiles at an increased data date. The multi-channel digital receiver also continuously samples the transmit pulse for calibration of radar receiver gain and transmit power. The multi-channel digital receiver has been successfully deployed as a key component in the recently developed National Aeronautical and Space Administration (NASA) Global Precipitation Measurement (GPM) Dual-Frequency Dual-Polarization Doppler Radar (D3R). The D3R is the principal ground validation instrument for the precipitation measurements of the Dual Precipitation Radar (DPR) onboard the GPM Core Observatory satellite scheduled for launch in 2014. The D3R system employs two broadly separated frequencies at Ku- and Ka-bands that together make measurements for precipitation types which need higher sensitivity such as light rain, drizzle and snow. This research describes unique design space to configure the digital receiver for D3R at several processing levels. At length, this research presents analysis and results obtained by employing the multi-carrier waveforms for D3R during the 2012 GPM Cold-Season Precipitation Experiment (GCPEx) campaign in Canada.
Mishra, Kumar Vijay
Over 1,000,000 km2 of the equatorial surface of Mars west of the Arsia Mons volcano displays no 3.5-cm radar echo to the very low level of the radar system noise for the Very Large Array; the area displaying this unique property has been terms \\
James R. Zimbelman; Kenneth S. Edgett
The Use of a Vertically Pointing Pulsed Doppler Radar in Cloud Physics and Weather Modification Studies
It is shown that Doppler radar measurements of the changes with height of the average fallspeeds of solid precipitation particles can be used together with radiosonde data to distinguish between growth of ice particles by riming and growth by deposition from the vapor phase. Under some conditions this information can be deduced from real-time observations, but generally spectral broadening by
Richard R. Weiss; Peter V. Hobbs
Report to the Chairman and Ranking Minority Member, Committee on Science, House of Representatives. Weather Forecasting: Radar Availability Requirement Not Being Met.
National Technical Information Service (NTIS)
The status of the Next Generation Weather Radar (NEXRAD) project is reported. The reasons why some of the NEXRAD units were dropped from the original deployment plan are investigated, along with the feasibility and estimated cost of extending the NEXRAD c...
An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar
NASA Astrophysics Data System (ADS)
By using a Doppler Weather Radar (DWR) at Shriharikota (13.66�N & 80.23�E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34-18% and 17-3% respectively, compared to Z- R approach.
Dutta, Devajyoti; Sharma, Sanjay; Sen, G. K.; Kannan, B. A. M.; Venketswarlu, S.; Gairola, R. M.; Das, J.; Viswanathan, G.
The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system
NASA Technical Reports Server (NTRS)
The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.
Hermes, Laurie G.; Witt, Arthur; Smith, Steven D.; Klingle-Wilson, Diana; Morris, Dale; Stumpf, Gregory J.; Eilts, Michael D.
Using X-band weather radar measurements to monitor the integrity of digital elevation models for synthetic vision systems
NASA Astrophysics Data System (ADS)
Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data representing terrain, obstacles, and cultural features. As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. Futher, updates to the databases may not be provided as changes occur. These issues limit the certification level and constrain the operational context of SVS for civil aviation. Previous work demonstrated the feasibility of using a real-time monitor to bound the integrity of Digital Elevation Models (DEMs) by using radar altimeter measurements during flight. This paper describes an extension of this concept to include X-band Weather Radar (WxR) measurements. This enables the monitor to detect additional classes of DEM errors and to reduce the exposure time associated with integrity threats. Feature extraction techniques are used along with a statistical assessment of similarity measures between the sensed and stored features that are detected. Recent flight-testing in the area around Juneau, Alaska Airport (JNU) has resulted in a comprehensive set of sensor data that is being used to assess the feasibility of the proposed monitor technology. Initial results of this assessment are presented.
Young, Steven D.; Uijt de Haag, Maarten; Sayre, Jonathon
Assessment of the Doppler Radar for Airport Weather (DRAW) System in Japan as a Research Tool for Studying Typhoon
NASA Astrophysics Data System (ADS)
The purpose of this study is to demonstrate the usefulness of the Doppler Radar for Airport Weather (DRAW) system as a research tool for studying typhoon. I particularly aim at assessing opportunity for detecting typhoon inner core circulations and precipitations with the DRAW. For centers of typhoons, which correspond to positions of the inner cores, it is estimated that 322 hours of data (61cases) had been collected with the eight DRAWs over past 30 typhoons (1995-2005). On average, about one typhoon will be observed with each DRAW site. The Naha DRAW (the southernmost DRAW site) will provide the most frequent observations and each observed center would remain in radar range for periods between 4 and 11 hours. In this study, it is shown that many typhoon inner core cases will be collected with DRAW and suggested new opportunities for further research and development these phenomena. DRAWs will play an increasing role to understand detailed typhoon structures and life cycles (e.g., polygonal eyewall, mesovorticies, landfall processes, and asymmetric structure), and in the future, to improve typhoon intensity forecasts.
Kusunoki, Kenichi
NSDL National Science Digital Library
This website, supplied by Annenberg / CPB, discusses weather satellites, Doppler radar, and additional tools forecasters use to predict the weather. Students can find a wind chill calculator along with a brief discussion of the history of forecasting and weather lore. Once you have a firm grasp on the science of weather forecasting, be sure to check out the other sections of this site, which include: "ice and snow," "our changing climate," "the water cycle," and "powerful storms."
Correlation between ground weather radar and satellite observations at microwaves for the Gr�msv�tn volcanic eruption on May 2011
NASA Astrophysics Data System (ADS)
The potential use of passive and active microwaves sensors to provide quantitative information about near-source volcanic ash cloud parameters during an eruptive event is analyzed in this work from an experimental point of view. To this aim ground-based microwave (MW) weather radar and satellite MW radiometer observations are used together. The target area where the collected measurements are compared is the Icelandic subglacial volcanic region and the analyzed case study is that of the Gr�msv�tn eruption on May 2011. The analyzed weather radar data include those of the Keflav�k (Iceland) site (260 km far from the volcano vent) operating at single polarization and working at the frequency of 5.6 GHz with a range resolution of 2 km and that of a portable radar system positioned 70 km far from the volcano vent with polarimetry capabilities (i.e. able to measure signals from both the orthogonal polarizations of the backscattered power as well as the phase shift returns) and working at the frequency of 10 GHz with a range spatial resolution of 0.25 km. On the other hand, the measurements from the satellite passive radiometer are derived from the Special Sensor Microwave Imager/Sounder (SSMIS) in terms of brightness temperature. SSMIS is a conically scanning passive microwave radiometer aboard of a low-earth- orbit platform with several channels (from about 19 GHz to 189 GHz) and with a ground resolution variable from 12.5 and 25 km depending from the frequency channel used. The diversity in terms of spatial scale, frequency, polarization and observation point of view of the collected data gives an original contribution to the characterization of the near source parameters of the Gr�msv�tn eruption in May 2011 highlighting the advantages and drawbacks of microwave sensors used for volcanic purposes. Traditionally, the monitoring of ash plumes is performed exploiting thermal infrared (TIR) and optical channels of spaceborne radiometers. These measurements can be obtained from sensors aboard geosynchronous-earth-orbit (GEO) and low-earth- orbit (LEO) satellites, thus offering different spatial and temporal resolutions for ash cloud remote sensing. For GEO platforms the advantage of rapid sampling of the earth scene is paid with lower resolution (typically larger than few kilometers), whereas for LEO the revisit time may be even longer than 12 hours. Moreover, TIR and optical channels may suffer from strong ash cloud opacity (very often mixed with water cloud) due to the significant radiation extinction especially in the proximity of the volcanic source. In this respect, the exploitation of the microwave (MW) passive sensors may represent a good opportunity due to their capability to sound the ash cloud, though with some inherent limitations. The results of this work will be shown in terms of correlation between the passive satellite-based brightness temperatures and active ground based retrievals of ash content. The latter is obtained applying the Volcanic Ash Radar Retrieval (VARR) technique both on single and dual polarization mode. The advantage of using the ground based radar orthogonal-polarization measurements will be preliminarily discussed.
Montopoli, Mario; Cimini, Domenico; Vulpiani, Gianfranco; Marzano, Frank S.
Evaluation of the RadEst and ClimGen Stochastic Weather Generators for Low-Medium Rainfall Regions
NASA Astrophysics Data System (ADS)
The aim of this study is to generate the daily weather values for maximum and minimum air temperatures and solar radiation. Two well known weather generators are evaluated here. Data from the five Iranian synoptic stations having long-term weather records and dry climates have been used to compare the actual data sets with generated one. The accuracy of the different weather generators models was evaluated by means of three widely used statistics: Correlation coefficient (R), Root Mean Square Error (RMSE) and Mean Bias Error (MBE). For maximum and minimum temperatures, Bushehr`s data show the lowest RMSE and Esfahan`s data show the highest RMSE. For radiation data, RMSEs of all of the stations are very high, except for Esfahan station. In general, the computed values of temperature are in good agreement with the data derived by the observation, but the computed values for radiation do not indicate a good agreement with the measured data.
Moradi, Isaac; Nosrati, Kazem; Eslamian, Saeid
Rainfall generator for the Rhine basin: multi-site simulation of daily weather variables by nearest-neighbour resampling
Nearest-neighbour resampling is used here for the joint simulation of daily rainfall and temperature at 36 stations in Germany, Luxemburg, France and Switzerland all situated in the Rhine basin. The daily temperatures are used to determine snow accumulation and melt in winter. A major advantage of a non-parametric resampling technique is that it preserves both the spatial association of daily
Jules J. Beersma; T. Adri Buishand
Shuttle imaging radar-B (SIR-B) data analysis for identifying rainfall event occurrence and intensity
NASA Technical Reports Server (NTRS)
The utility of SIR-B data were evaluated for the detection and measurement of rainfall events, and applications of SIR-B data were developed to the improvement of existing rainfall models. During the SIR-B mission, EarthSat monitored rainfall events occurring within the conterminous United States. The GOES scenes form showed rainfall activity within the conterminous U.S. during the SIR-B mission. Swaths of the actual SIR-B data taken were plotted onto the GOES satellite scenes most closely representing the time of the Shuttle overpass. The JPL provided EarthSat with available SIR-B imagery in paper print form representing the appropriate requested data takes. EarthSat identified the collateral data required for site characterization during subsequent SIR-B contracts with JPL.
The TRMM Precipitation Radar: Opportunities and Challenges
NASA Technical Reports Server (NTRS)
Although studies on the feasibility of spaceborne weather radar date back to the 1960's, it was only with the launch of the Tropical Rainfall Measuring Mission (TRMM) Satellite in November 1997 that the first weather radar was placed into low earth orbit. The long delay between the initial concept and implementation was caused not only by the demanding requirements of active sensors such as mass, power, and reliability, but because of scientific and technological challenges. For example, the demand for adequate spatial resolution arises from the need to resolve the horizontal structure of convective storm cells and to avoid surface contamination of the rain return at off-nadir angles. To achieve a horizontal resolution on the order of 4 km from low earth orbit with a modest antenna size of 2 m requires the use of a much higher frequency (Ku-band) than those typically used for ground-based weather radars (S- and C-band). Higher frequencies are subject to higher attenuation. As Hitschfeld and Bordan (1954) showed in their classic paper, attenuation correction with a single-wavelength radar is inherently unstable at high attenuations unless the drop size distribution and the radar constant are known precisely. Since these conditions are seldom met, much work over the last decade has been devoted to formulating and testing alternative methods of attenuation correction. The operational method used in the TRMM radar processing is discussed in section 3 of the paper.
Meneghini, R.; Kozu, T.; Kawanishi, T.; Kuroiwa, H.; Okamoto, K.; Atlas, D.
Spaced-antenna wind estimation using an X-band active phased-array weather radar
NASA Astrophysics Data System (ADS)
Over the past few decades, several single radar methods have been developed to probe the kinematic structure of storms. All these methods trade angular-resolution to retrieve the wind-field. To date, the spaced-antenna method has been employed for profiling the ionosphere and the precipitation free lower atmosphere. This work focuses on applying the spaced-antenna method on an X-band active phased-array radar for high resolution horizontal wind-field retrieval from precipitation echoes. The ability to segment the array face into multiple displaced apertures allows for flexible spaced-antenna implementations. The methodology employed herein comprises of Monte-Carlo simulations to optimize the spaced-antenna system design and analysis of real data collected with the designed phased-array system. The contribution that underpins this dissertation is the demonstration of qualitative agreement between spaced-antenna and Doppler beam swinging retrievals based on real data. First, simulations of backscattered electric fields at the antenna array elements are validated using theoretical expressions. Based on the simulations, the degrees of freedom in the spaced-antenna system design are optimized for retrieval of mean baseline wind. We show that the designed X-band spaced-antenna system has lower retrieval uncertainty than the existing S-band spaced-antenna implementation on the NWRT. This is because of the flexibility to synthesize small overlapping apertures and the ability to obtain statistically independent samples at a faster rate at X-band. We then demonstrate a technique to make relative phase-center displacement measurements based on simulations and real data from the phased-array spaced-antenna system. This simple method uses statistics of precipitation echoes and apriori beamwidth measurements to make field repeatable phase-center displacement measurements. Finally, we test the hypothesis that wind-field curvature effects are common to both the spaced-antenna and Doppler beam swinging methods. Based on a close-range winter storm data set, we find that the spaced-antenna and fine-resolution Doppler beam swinging retrievals are in qualitative agreement. The correlation between the spaced-antenna and fine-resolution Doppler beam swinging retrievals was 0.57. The lowered correlation coefficient was, in part, due to the high standard deviation of the DBS retrievals. At high wind-speeds, the spaced-antenna retrievals significantly departed from variational retrievals of mean baseline wind.
Venkatesh, Vijay
Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar
NASA Technical Reports Server (NTRS)
Ground clutter interference is a major problem for airborne pulse Doppler radar operating at low altitudes in a look-down mode. With Doppler zero set at the aircraft ground speed, ground clutter rejection filtering is typically accomplished using a high-pass filter with real valued coefficients and a stopband notch centered at zero Doppler. Clutter spectra from the NASA Wind Shear Flight Experiments of l991-1992 show that the dominant clutter mode can be located away from zero Doppler, particularly at short ranges dominated by sidelobe returns. Use of digital notch filters with complex valued coefficients so that the stopband notch can be located at any Doppler frequency is investigated. Several clutter mode tracking algorithms are considered to estimate the Doppler frequency location of the dominant clutter mode. From the examination of night data, when a dominant clutter mode away from zero Doppler is present, complex filtering is able to significantly increase clutter rejection over use of a notch filter centered at zero Doppler.
Jamora, Dennis A.
Airborne derivation of microburst alerts from ground-based Terminal Doppler Weather Radar information: A flight evaluation
NASA Technical Reports Server (NTRS)
An element of the NASA/FAA windshear program is the integration of ground-based microburst information on the flight deck, to support airborne windshear alerting and microburst avoidance. NASA conducted a windshear flight test program in the summer of 1991 during which airborne processing of Terminal Doppler Weather Radar (TDWR) data was used to derive microburst alerts. Microburst information was extracted from TDWR, transmitted to a NASA Boeing 737 in flight via data link, and processed to estimate the windshear hazard level (F-factor) that would be experienced by the aircraft in each microburst. The microburst location and F-factor were used to derive a situation display and alerts. The situation display was successfully used to maneuver the aircraft for microburst penetrations, during which atmospheric 'truth' measurements were made. A total of 19 penetrations were made of TDWR-reported microburst locations, resulting in 18 airborne microburst alerts from the TDWR data and two microburst alerts from the airborne reactive windshear detection system. The primary factors affecting alerting performance were spatial offset of the flight path from the region of strongest shear, differences in TDWR measurement altitude and airplane penetration altitude, and variations in microburst outflow profiles. Predicted and measured F-factors agreed well in penetrations near microburst cores. Although improvements in airborne and ground processing of the TDWR measurements would be required to support an airborne executive-level alerting protocol, the practicality of airborne utilization of TDWR data link data has been demonstrated.
Hinton, David A.
Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation
NASA Astrophysics Data System (ADS)
The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.
Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.
Quasi-global extreme rainfall intensity derived from the Tropical Rainfall Measurement Mission
NASA Astrophysics Data System (ADS)
The frequency, magnitude and duration of precipitation extremes are closely dependent on climate change and variability. While recent works suggest an ongoing increase of extreme climate events, a comparison between past and actual maxima rainfall intensities across the world is necessary. Previous compilations of the world's greatest rainfall depths are based on rain gauges sparsely located on the global terrestrial surface with significant gaps in remote continental regions and oceans. Unlike rain gauges and weather radars which provide extreme precipitation estimates at the micro- and mesoscale respectively, new remote sensing techniques offer now the possibility of monitoring precipitation over tropical and temperate regions across the world. Also, for the first time, such tools allow to detect rainfall extreme values over oceanic regions. This work provides a comparison between the world's greatest rainfall depths from point measurements in climatological stations during the 20th century (WMO, 1994) and those derived by the Tropical Rainfall Measurement Mission (TRMM) satellite with a 0.25� x 0.25� resolution grid from 1998 until 2013. During this 15 year observational period, global maxima rainfall depths associated to durations ranging between 3 hours and 2 years were estimated. A scaling law and functional form of maxima rainfall over continents and oceans provided for the first time a quasi-global assessment of the temporal and spatial distribution of the most intense rainfall events. In particular, the results show that (1) all the rain gauge-based measurements over the past century exceed the satellite-based values during last 15 years, and (2) the majority of hotspots with maximum rainfall intensity are located in the oceans.
Brena-Naranjo, Agustin; Matamoros-Casanova, Alberto; Pedrozo-Acu�a, Adrian
Diagnostic analysis of a heavy rainfall event over Beijing on July 21-22, 2012
NASA Astrophysics Data System (ADS)
The eastward moving low vortex over the North China plain induced the heaviest rainfall in 61 years over Beijing on July 21-22, 2012. This record-breaking heavy rainfall is characterized by its great rainfall amount and intensity, wide range, and high impact, causing dozens of deaths and extensive damage. In this paper, using a set of measurements and the NCEP 1��1� reanalysis data, the synoptic and mesoscale conditions of the heavy rainfall are firstly diagnosed. The measurements include the intensive surface observations, the observations of the operational sounding station and microwave radiometer, as well as the products of Doppler radar and satellite. Preliminary analysis shows that the eastward moving cold front encounters the warm moist southwest flow around Subtropical High, providing a favorable circulation condition for strong convective weather in this East Asian monsoon region. Meanwhile, the conditions of sustained water vapor, strong vertical ascent of air and unstable stratification are suitable for the formation of a heavy rainfall over Beijing. The mesoscale convective systems (MCSs) which produced the most severe rainfall in Fang Shan area are then analyzed, and the radar and satellite data with mesoscale model forecasts are used to further examine the features of the MCSs evolution. Moreover, the effects of topography and urban heat island which may contribute to the heavy rainfall are also discussed.; Heavy rainfall in Beijing on July 21, 2012 ; The distribution of precipitation (mm) over Beijing during 0200UTC to 2200UTC, July 21
Jiang, X.; Yuan, H.
Comparison of Spatial and Temporal Rainfall Characteristics in WRF-Simulated Precipitation to Gauge and Radar Observations
Weather Research and Forecasting (WRF) meteorological data are used for USEPA multimedia air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hi...
Observed and NWP simulated rainfall uncertainty cascading into rainfall-runoff and flood inundation impact models
NASA Astrophysics Data System (ADS)
Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade is still poorly understood. Such a project requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and hydraulic flood wave propagation based on the runoff predictions. Accounting for uncertainty in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures as part of the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions which are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products for real forecasting situations.
Souvignet, M.; Freer, J. E.; de Almeida, G. A.; Coxon, G.; Neal, J. C.; Champion, A.; Cloke, H. L.; Bates, P. D.
The response of the high-latitude ionosphere to the coronal mass ejection event of April 6, 2000: A practical demonstration of space weather nowcasting with the Super Dual Auroral Radar Network HF radars
NASA Astrophysics Data System (ADS)
The ionosphere at high latitudes is the site of important effects in space weather. These include strong electrical currents that may disrupt power systems through induced currents and density irregularities that can degrade HF and satellite communication links. With the impetus provided by the National Space Weather Program, the radars of the Super Dual Auroral Radar Network have been applied to the real-time specification (``nowcasting'') of conditions in the high-latitude ionosphere. A map of the plasma convection in the northern high-latitude ionosphere is continually generated at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) SuperDARN web site using data downloaded in real time from the radars via Internet connections. Other nowcast items include information on the conditions of HF propagation, the spatial extent of auroral effects, and the total cross polar cap potential variation. Time series of various parameters and an animated replay of the last 2 hours of convection patterns are also available for review. By comparing with simultaneous measurements from an upstream satellite, it is possible to infer the effective delay from the detection of changes in the solar wind at the satellite to the arrival of related effects in the high-latitude ionosphere. We discuss the space weather products available from the JHU/APL SuperDARN web site and their uses by simulating a nowcast of the ionosphere on April 6, 2000, during the arrival of a coronal mass ejection (CME) -related shock. The nowcast convection pattern in particular satisfies a critical need for timely, comprehensive information on ionospheric electric fields.
Ruohoniemi, J. M.; Barnes, R. J.; Greenwald, R. A.; Shepherd, S. G.
NSDL National Science Digital Library
This website provides real-time and forecast weather maps and data for the United States. The Satellite section contains satellite weather images from the GOES 8 and GOES 10 satellites, the Radar section contains radar weather images from NEXRAD radars, the Surface Data section contains plots of various weather conditions (temperatures, winds, pressure, precipitation), and the Upper Air section plots winds and temperatures across the United States.
Linking the Annual Variation of Snow Radar-derived Accumulation in West Antarctica to Long-term Automatic Weather Station Measurements
NASA Astrophysics Data System (ADS)
Understanding the snow accumulation rate on polar ice sheets is important in assessing mass balance and ice sheet contribution to sea level rise. Measuring annual accumulation on a regional scale and extending back in time several decades has been accomplished using the Center for Remote Sensing of Ice Sheets (CReSIS) Snow Radar on the NASA DC-8 that is part of NASA's Ice-Bridge project. The Snow Radar detects and maps near-surface internal layers in polar firn, operating from 2- 6 GHz and providing a depth resolution of ~4 cm. During November 2011, Snow Radar data were obtained for large areas of West Antarctica, including a flight segment that passed within ~70 km of Byrd Station (80�S, 119�W). Byrd Station has a very long automatic weather station (AWS) record, extending from present to 1980, with 3 relatively brief gaps in the record. The AWS data for Byrd Station were obtained from the Antarctic Meteorological Research Center (AMRC) at the University of Wisconsin. The L1B Snow Radar data products, available from the National Snow and Ice Data Center (NSIDC), were analyzed using layer picking software to obtain the depth of reflectors in the firn that are detected by the radar. These reflectors correspond to annual markers in the firn, and allow annual accumulation to be determined. Using the distance between the reflectors and available density profiles from ice cores, water equivalent accumulation for each annual layer back to 1980 is obtained. We are analyzing spatial variations of accumulation along flight lines, as well as variations in the time series of annual accumulation. We are also analyzing links between annual accumulation and surface weather observations from the Byrd Station AWS. Our analyses of surface weather observations have focused on annual temperature, atmospheric pressure and wind extremes (e.g. 5th and 95th percentiles) and links to annual snow accumulation. We are also examining satellite-derived sea ice extent records for the Bellingshausen and Amundsen seas sector (60�W-120�W) over the same 31-year time period and comparing results to annual snow accumulation. Results from this work will be presented at the meeting.
Feng, B.; Braaten, D. A.; Gogineni, P.; Paden, J. D.; Leuschen, C.; Purdon, K.
NETWORKED WAVEFORM SYSTEM FOR A WEATHER RADAR NETWORK Nitin Bharadwaj and V. Chandrasekar Colorado State Univeristy, Fort Collins, CO 80523
A networked waveform system is developed to overcome the fundamental limitation of a single pulsed Doppler radar in re- solving ambiguities. The networked radar system uses the principle that the underlying intrinsic properties of the pre- cipitation medium remain consistent in a network. The am- biguity in range and velocity is resolved by jointly process- ing the measurements from all
Nitin Bharadwaj
Engineering Evaluation and Calibration of Iowa X-Band Polarimetric Radars
NASA Astrophysics Data System (ADS)
The detailed knowledge and extensive monitoring of the precipitation structure at smaller temporal and spatial scales are critical to the scientific understanding of the hydrological cycle and associated processes. The hydrometeorological information at smaller scales is usually not available with the current weather radar systems which operate at lower frequencies such as S- and C-bands. This has necessitated the use of higher frequency (X-band) weather radars to obtain rainfall data at improved accuracy and near-ground coverage at shorter ranges. The University of Iowa has acquired four scanning, mobile, X-band polarimetric (XPOL) Doppler weather radars with the objective of accurate quantitative estimation of the rainfall at a high temporal and spatial resolution. These four XPOL radars will be deployed for short-range multiple-view observations of the same weather event thus reducing uncertainties introduced by the signal attenuation and instrument-wide errors. This network of radars is intended to serve multiple areas of hydrological research including uncertainty modelling, urban hydrology, flood and flash-flood prediction, and soil erosion. Compared to the existing networks of X-band weather radars, several features place the XPOL radar systems in a distinctly attractive position for the scientific community. Firstly, the Iowa XPOL radars are mounted on mobile platforms, and consequently, are deployed at any location of interest. Secondly, these systems are capable of acquiring data at a programmable range sampling which can be as low as 30m. Thirdly, the use of dual-polarization provides additional information about the hydrometeors at smaller scales. The radars can operate in staggered PRT and dual-PRF pulsing modes and can process data using either standard pulse-pair or spectral mode techniques. The Iowa XPOL radar systems are currently being evaluated and calibrated to participate in their first field campaigns in the upcoming NASA IFloodS (Iowa Flood Studies) field experiment during Spring-Summer 2013. This paper will present results obtained through extensive system-level tests conducted on the transmitter-receiver unit and carried out largely in conformity with the NASA Global Precipitation Measurement - Ground Validation (GPM-GV) standards. This includes scrutinizing the temporal stability of the some of the performance parameters. The radar systems will also be calibrated against existing standard weather radar systems during the campaign. The experimental observations of the individual XPOL radar units with respect to the reference ground and weather targets will also be analysed. The paper will also present an inter-XPOL comparison of the findings of these experiments.
Vijay Mishra, Kumar; Kruger, Anton; Krajewski, Witold
NSDL National Science Digital Library
This Topic in Depth discusses the variety of instruments used to collect climate and weather data. The first two websites provide simple introductions to the many weather instruments. Bethune Academy's Weather Center (1) discusses the functions of psychrometers, anemometers, weather balloons, thermometers, and barometers. The Illinois State Water Survey (2) furnishes many images of various instruments that collect data daily for legal issues, farmers, educators, students, and researchers. The third website (3), created by the Center for Improving Engineering and Science Education (CIESE), provides a classroom activity to educate users on how to build and use weather instruments. By the end of the group project, students should know all about wind vanes, rain gauges, anemometers, and thermometers. Next, the Miami Museum of Science provides a variety of activities to help students learn about the many weather instruments including wind scales and wind chimes (4). Students can learn about the wind, air pressure, moisture, and temperature. At the fifth website, the Tyson Research Center at Washington University describes the devices it uses in its research (5). At the various links, users can find out the center's many projects that utilize meteorological data such as acid rain monitoring. The sixth website, a pdf document created by Dr. John Guyton at the Mississippi State University Extension Service, provides guidance to teachers about the education of weather patterns and instruments (6). Users can find helpful information on pressure systems, humidity, cloud patterns, and much more. Next, the University of Richmond discusses the tools meteorologists use to learn about the weather (7). While providing materials about the basic tools discussed in the other websites, this site also offers information about weather satellites, radar, and computer models. After discovering the many weather instruments, users can learn about weather data output and analysis at the Next Generation Weather Lab website (8). This expansive website provides an abundance of surface data and upper air data as well as satellite and radar images for the United States.
Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina
Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfa
Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul A.; Bradley, Paul M.
Flood Monitoring using X-band Dual-polarization Radar Network
NASA Astrophysics Data System (ADS)
A dense weather radar network is an emerging concept advanced by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). Using multiple radars observing over a common will create different data outcomes depending on the characteristics of the radar units employed and the network topology. To define this a general framework is developed to describe the radar network space, and formulations are obtained that can be used for weather radar network characterization. Current weather radar surveillance networks are based upon conventional sensing paradigm of widely-separated, standalone sensing systems using long range radars that operate at wavelengths in 5-10 cm range. Such configuration has limited capability to observe close to the surface of the earth because of the earth's curvature but also has poorer resolution at far ranges. The dense network radar system, observes and measures weather phenomenon such as rainfall and severe weather close to the ground at higher spatial and temporal resolution compared to the current paradigm. In addition the dense network paradigm also is easily adaptable to complex terrain. Flooding is one of the most common natural hazards in the world. Especially, excessive development decreases the response time of urban watersheds and complex terrain to rainfall and increases the chance of localized flooding events over a small spatial domain. Successful monitoring of urban floods requires high spatiotemporal resolution, accurate precipitation estimation because of the rapid flood response as well as the complex hydrologic and hydraulic characteristics in an urban environment. This paper reviews various aspects in radar rainfall mapping in urban coverage using dense X-band dual-polarization radar networks. By reducing the maximum range and operating at X-band, one can ensure good azimuthal resolution with a small-size antenna and keep the radar beam closer to the ground. The networked topology helps to achieve satisfactory sensitivity and fast temporal update across the coverage. Strong clutter is expected from buildings in the neighborhood which act as perfect reflectors. The reduction in radar size enables flexible deployment, such as rooftop installation, with small infrastructure requirement, which is critical in a metropolitan region. Dual-polarization based technologies can be implemented for real-time mitigation of rain attenuations and accurate estimation of rainfall. The NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is developing the technologies and the systems for network centric weather observation. The Differential propagation phase (Kdp) has higher sensitivity at X-band compared to S and C band. It is attractive to use Kdp to derive Quantitative Precipitation Estimation (QPE) because it is immune to rain attenuation, calibration biases, partial beam blockage, and hail contamination. Despite the advantage of Kdp for radar QPE, the estimation of Kdp itself is a challenge as the range derivative of the differential propagation phase profiles. An adaptive Kdp algorithm was implemented in the CASA IP1 testbed that substantially reduces the fluctuation in light rain and the bias at heavy rain. The Kdp estimation also benefits from the higher resolution in the IP1 radar network. The performance of the IP1 QPE product was evaluated for all major rain events against the USDA Agriculture Research Service's gauge network (MicroNet) in the Little Washita watershed, which comprises 20 weather stations in the center of the test bed. The cross-comparison with gauge measurements shows excellent agreement for the storm events during the Spring Experiments of 2007 and 2008. The hourly rainfall estimates compared to the gauge measurements have a very small bias of few percent and a normalized standard error of 21%. The IP1 testbed was designed with overlapping coverage among its radar nodes. The study area is covered by multiple radars and the aspect of network composition is also evaluated. The independence of Kdp on the radar calibration e
Chandrasekar, V.; Wang, Y.; Maki, M.; Nakane, K.
Correction of Sampling Errors in Ocean Surface Cross-Sectional Estimates from Nadir-Looking Weather Radar
NASA Technical Reports Server (NTRS)
The return from the ocean surface has a number of uses for airborne meteorological radar. The normalized surface cross section has been used for radar system calibration, estimation of surface winds, and in algorithms for estimating the path-integrated attenuation in rain. However, meteorological radars are normally optimized for observation of distributed targets that fill the resolution volume, and so a point target such as the surface can be poorly sampled, particularly at near-nadir look angles. Sampling the nadir surface return at an insufficient rate results in a negative bias of the estimated cross section. This error is found to be as large as 4 dB using observations from a high-altitude airborne radar. An algorithm for mitigating the error is developed that is based upon the shape of the surface echo and uses the returned signal at the three range gates nearest the peak surface echo.
Caylor, I. Jeff; Meneghini, R.; Miller, L. S.; Heymsfield, G. M.
NASA Satellite Reveals Heavy Rainfall Patterns in California
NSDL National Science Digital Library
The collision of a flow of moisture from Hawaii known as a "Pineapple Express" and a persistent low pressure system are wreaking havoc on California weather. This movie shows rain accumulation in San Diego from Jan. 6 through Jan. 11 based on data from the Tropical Rainfall Measuring Mission (TRMM)-based Multisatellite Precipitation Analysis. The accumulation is shown in colors ranging from green (less than 50 mm of rain) through red (200 mm or more). The TRMM satellite, using the worlds only spaceborne rain radar and other microwave instruments, measures rainfall over the ocean. In this case instruments were able to reveal rainfall structure resulting from storms "riding" the actual Pineapple Express extending toward Hawaii, which is beyond the range of conventional land-based National Weather Service radars. In early 1995, a Pineapple Express hit California, contributing to a season of winter storms that killed 27 people and did $3 billion in damages and costs. A Pineapple Express in mid-October 2003 wreaked havoc from south of Seattle to north of Vancouver Island. Flooding forced more than 3,000 people from their homes.
Perkins, Lori; Shirah, Greg; Halverson, Jeff
Climatology of daily rainfall semivariance in The Netherlands
NASA Astrophysics Data System (ADS)
Rain gauges can offer high quality rainfall measurements at their location. Networks of rain gauges can offer better insight into the space-time variability of rainfall, but they tend to be too widely spaced for accurate estimates between points. While remote sensing systems, such as radars and networks of microwave links, can offer good insight in the spatial variability of rainfall they tend to have more problems in identifying the correct rain amounts at the ground. A way to estimate the variability of rainfall between gauge points is to interpolate between them using fitted variograms. If a dense rain gauge network is lacking it is difficult to estimate accurate variograms. In this paper a 30-year dataset of daily rain accumulations gathered at 29 automatic weather stations operated by KNMI and a one-year dataset of 10 gauges in a network with a radius of 5 km around CESAR (Cabauw Experimental Site for Atmospheric Research) are employed to estimate variograms. Fitted variogram parameters are shown to vary according to season, closely following simple cosine functions allowing for applications in catchment hydrology and rainfall field generation. Semivariances at short ranges during winter and spring tend to be underestimated, but summer and autumn are well predicted. This climatological semivariance can be employed to estimate the accuracy of the rainfall input to a hydrological model even with only few gauges in a given catchment area.
van de Beek, C. Z.; Leijnse, H.; Torfs, P. J. J. F.; Uijlenhoet, R.
Rainfall Modification by Urban Areas: New Perspectives from TRMM
NASA Technical Reports Server (NTRS)
Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.
Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew
Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities
NASA Technical Reports Server (NTRS)
Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed.
Chandrasekar, V.; Hou, Arthur; Smith, Eric; Bringi, V. N.; Rutledge, S. A.; Gorgucci, E.; Petersen, W. A.; SkofronickJackson, Gail
a Statistical Description of Storm Cells: Analysis of Film Records of the Binghamton, New York WSR-57 PPI Weather Radar.
NASA Astrophysics Data System (ADS)
Considerable effort has been expended recently to mathematically model convective rainstorms. Parameter estimation has lagged behind theoretical work. This investigation utilizes digitized radar imagery to estimate the duration and areal extent of convective cells. The parameters were chosen based on a mathematical model proposed by Rodriguez -Iturbe-Eagelson. Three thunderstorms in the area scanned by the Broome County, New York radar were chosen. The film images of the radar scope taken at 5-minute intervals were digitized. Data were extracted from the digitized image concerning the spatial and temporal characteristics of convective cells. The cells were found to have durations of 20 to 30 minutes, with an exponential distribution. Mean cell area was found to be 15 km^2 and best described by a log-normal distribution. Preliminary data descriptions of relative cell precipitation, cell velocity and growth-life-decay cycle were given.
Kirby, Cynthia Brower
Observation of Sea Breeze Front and its Induced Convection over Chennai in Southern Peninsular India Using Doppler Weather Radar
Sea breeze, the onshore wind over a coastal belt during daytime, is a welcoming weather phenomenon as it modulates the weather\\u000a condition by moderating the scorching temperature and acts as a favourable mechanism to trigger convection and induce precipitation\\u000a over coastal and interior locations. Sea breeze aids dispersal of pollutants as well. Observational studies about its onset,\\u000a depth of circulation
R. Suresh
Observation of Sea Breeze Front and its Induced Convection over Chennai in Southern Peninsular India Using Doppler Weather Radar
Sea breeze, the onshore wind over a coastal belt during daytime, is a welcoming weather phenomenon as it modulates the weather\\u000a condition by moderating the scorching temperature and acts as a favourable mechanism to trigger convection and induce precipitation\\u000a over coastal and interior locations. Sea breeze aids dispersal of pollutants as well. Observational studies about its onset,\\u000a depth of circulation
R. Suresh
Comparison of short-term rainfall forecasts for model-based flow prediction in urban drainage systems.
Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real-time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 h. The best performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times. PMID:23863443
Thorndahl, S�ren; Poulsen, Troels Sander; B�vith, Thomas; Borup, Morten; Ahm, Malte; Nielsen, Jesper Ellerb�k; Grum, Morten; Rasmussen, Michael R; Gill, Rasphall; Mikkelsen, Peter Steen
The study and real-time implementation of attenuation correction for X-band dual-polarization weather radars
NASA Astrophysics Data System (ADS)
Attenuation of electromagnetic radiation due to rain or other wet hydrometeors along the propagation path has been studied extensively in the radar meteorology community. Recently, use of short range dual-polarization X-band radar systems has gained momentum due to lower system cost compared with the much more expensive S-band systems. Advances in dual-polarization radar research have shown that the specific attenuation and differential attenuation between horizontal and vertical polarized waves caused by oblate, highly oriented raindrops can be estimated using the specific differential phase. This advance leads to correction of the measured reflectivity (Zh) and the differential reflectivity (Zdr) due to path attenuation. This thesis addresses via theory, simulations and data analyses the accuracy and optimal estimation of attenuation-correction procedures at X-band frequency. Real-time implementation of the correction algorithm was developed for the first generation of X-band dual-polarized Doppler radar network (Integration Project 1, IP1) operated by the NSF Center for Collaborate Adaptive Sensing of the Atmosphere (CASA). We evaluate the algorithm for correcting the Zh, and the Zdr for rain attenuation using simulations and X-band radar data under ideal and noisy situations. Our algorithm is able to adjust the parameters according to the changes in temperature, drop shapes, and a certain class of drop size distributions (DSD) with very fast convergence. The X-band radar data were obtained from the National Institute of Earth Science and Disaster Prevention (NIED), Japan, and from CASA IP1. The algorithm accurately corrects NIED's data when compared with ground truth calculated from in situ disdrometer-based DSD measurements for a Typhoon event. We have implemented, in real-time, the algorithm in all the CASA IP1 radar nodes. We also evaluate our preliminary method that separately estimates rain and wet ice attenuation using microphysical outputs from a previous supercell simulation using the CSU-RAMS (Regional Atmospheric Modeling System). The retrieved rain and wet ice specific attenuation fields were found to be in close correspondence to the 'true' fields calculated from the simulation. The concept to correct rain and wet ice attenuation separately can be also applied to the CASA IP1 network with additional constraint information possibly provided by the WSR-88D network.
Liu, Yuxiang
A coupled stochastic space-time intermittent random cascade model for rainfall downscaling
NASA Astrophysics Data System (ADS)
Analysis of Next Generation Weather Radar rainfall data indicates that for the central United States, rainfall exhibits a composite behavior with respect to its spatial and temporal scaling characteristics. Our data analysis shows that rainfall fluctuations at spatial scales smaller than a reference scale exhibit self-similarity and that at scales larger than the reference scale, rainfall fluctuations are scale dependent. Accordingly, we present a new methodology for downscaling large-scale rainfall consistent with this composite character of rainfall variability. The new downscaling model is a composite of a stochastic space-time submodel that preserves the spatial and temporal dependency characteristics at scales larger than the reference scale and an intermittent random cascade submodel that preserves the statistical self-similarity and spatial intermittency at scales smaller than the reference scale. The new model is applied to downscale summer daily rainfall for the central United States from a scale of 256 km to a scale of 2 km. We show that the new model reproduces quite well the intermittency and self-similarity features and the interscale and across-scale correlation structures of observed rainfall with a relatively low computational burden.
Kang, Boosik; Ram�Rez, Jorge A.
Probing the Architecture of the Weathering Zone in a Tropical System in the Rio Icacos Watershed (Puerto Rico) With Drilling and Ground Penetrating Radar (GPR)
NASA Astrophysics Data System (ADS)
Weathering processes in rapidly eroding systems such as humid tropical environments are complex and not well understood. The interface between weathered material (regolith) and non-weathered material (bedrock) is particularly important in these systems as it influences water infiltration and groundwater flow paths and movement. Furthermore, the spatial distribution of this interface is highly heterogeneous and difficult to image with conventional techniques such as direct coring and drilling. In this work we present results from a preliminary geophysical study in the Luquillo Critical Zone Observatory (LCZO) located in the rain forest in the Luquillo Mountains of northeastern Puerto Rico. The Luquillo Mountains are composed of volcaniclastic rocks which have been uplifted and metamorphosed by the Tertiary Rio Blanco quartz diorite intrusion. The Rio Blanco quartz diorite weathers spheroidally, creating corestones of relatively unweathered material that are surrounded by weathered rinds. A number of boreholes were drilled near the top of the Rio Icacos watershed, where the corestones are thought to be in the primary stages of formation, to constrain the regolith/bedrock interface and to provide an understanding of the depth to which corestones form. The depth of the water table was also a target goal in the project. Drilling reveals that corestones are forming in place, separated by fractures, even to depths of 10s of meters below ground surface. One borehole was drilled to a depth of about 25 meters and intersected up to 7 bedrock blocks (inferred to be incipient corestones) and the water table was measured at about 15 meters. Ground Penetrating Radar surveys were conducted in the same location to determine if GPR images variable thicknesses of saprolite overlying corestones. GPR common offset measurements and common midpoint surveys with 50, 100, and 200 MHz antenna frequencies were combined with borehole drillings in order to constrain geophysical results. We will compare drilling observations to GPR data to understand: 1) the lateral extent of the regolith-bedrock interface; 2) distribution of rindlets or spheroidal fracturing around corestones; and 3) presence and extent of corestones. This work has implications for understanding the rate of weathering advance and changes in permeability across rapidly eroding watersheds.
Orlando, J.; Comas, X.; Mount, G. J.; Brantley, S. L.
Use of past precipitation data for regionalisation of hourly rainfall in the low mountain ranges of Saxony, Germany
Within the context of flood forecasting we deal with the improvement of regionalisation methods for the generation of highly resolved (1 h, 1�1km2) precipitation fields, which can be used as input for rainfall-runoff models or for verification of weather forecasts. Although radar observations of precipitation are available in many regions, it might be necessary to apply regionalisation methods near real-time
T. Pluntke; N. Jatho; C. Kurbjuhn; J. Dietrich; C. Bernhofer
Cascading rainfall uncertainty into flood inundation impact models
NASA Astrophysics Data System (ADS)
Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade, and how best to approach this, is still poorly understood. This requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and finally the hydraulic flood wave propagation based on the runoff predictions. Improving the characterisation of uncertainty, and what is important to include, in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures using the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions that are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products used for real forecasting situations.
Souvignet, Maxime; Freer, Jim E.; de Almeida, Gustavo A. M.; Coxon, Gemma; Neal, Jeffrey C.; Champion, Adrian J.; Cloke, Hannah L.; Bates, Paul D.
Rainfall retrieval in urban areas using commercial microwave links from mobile networks: A modelling feasibility study
NASA Astrophysics Data System (ADS)
Rainfall is usually measured by networks of rain gauges and weather radars. Many cities worldwide are not supplied with these devices; however, they are generally equipped with mobile telecommunication networks. Mobile networks use atmospheric Hyper-Frequency (HF) links whose transmitted signal power is attenuated by rainfall. Measuring that signal attenuation along each link could allow the measurement of path-averaged rainfall [Leijnse et al 2007, Overeem et al 2013, Messer et al 2006, Guili et al 1991, Zinevich et al 2008, Cuccoli et al 2011]. As HF links are concentrated in cities, these networks could constitute a self-sufficient approach to monitoring rainfall in urban areas. We adopt a simulation approach in order to study the feasibility of mapping rainfall fields at the city scale by means of existing HF links. Our domain of study is the central part of the city of Nantes, France, where the density of cellular networks is greatest. As a basis, we use a data set consisting of hundreds of weather radar images recorded by the M�t�o-France C band weather radar at high spatial (250m x 250m) and temporal (5 minute) resolutions located about 10 km north of the center of Nantes. We convert these images into rainfall maps using the Z-R relation and consider them as reference rainfall fields. The simulation is performed as follows. First, we simulate the measurement of total attenuation along each HF link using a rain-attenuation model based on Mie theory and a known drop size distribution in a continental temperate climate. This procedure is applied for 256 real radio links operating at different frequencies (18, 23, 38 GHz) with lengths ranging from 0.4 to 16 km. This helps us to substitute the attenuation data for the signal power received from microwave links. Error sources affecting measurement accuracy are introduced as a zero-mean Gaussian distributed random variable with variance of 10% of total attenuation. The retrieval of the rainfield is performed by a nonlinear algorithm [Tarantola and Valette 1982] based on the general nonlinear least square criterion. The a priori knowledge used to initialize the algorithm heavily influences the model outcome if the stated problem is underdetermined. In order to evaluate the performance of our model, we carry out a series of rainfall retrieval tests for various rain events (convective and stratiform) with different time intervals. We evaluate retrieval efficiency by comparing observed rain fields with retrieved ones. We perform a sensitivity analysis to define the model's limitations and capabilities by considering essential factors, namely spatial and temporal rainfall structure, the geometry of HF link networks, the choice of a priori information and associated errors.
Zohidov, Bahtiyor; Andrieu, Herv�; Servi�res, Myriam; Normand, Nicolas
NSDL National Science Digital Library
This site offers links to a variety of weather information, including national, international and local weather maps and forecasts, satellite and radar imagery, and severe weather warnings. There are also links to diverse resources such as fire maps, glacier inventories, snow depths, storm surges and tropical storms. There are reports and advisories about El Nino and La Nina. The site also has a glossary of weather terms and conversion charts for temperature, wind speed and atmospheric pressure.
Convective rain cells: spatio-temporal characteristics, synoptic patterns and a high resolution synoptically conditioned weather generator
NASA Astrophysics Data System (ADS)
Information on rain cell features was extracted from high-resolution weather radar data for a total of 191,586 radar volume scans from 12 hydrological years. The convective rain cell features (i.e., cell area, rainfall intensity and cell orientation) were obtained using cell segmentation technique and cell tracking algorithm was used to analyze the changes of those features over time. Three synoptic types were defined for the study area (northen Israel), two extratropical winter lows: deep Cyprus low and a shallow low, and a tropical intrusion: Active Red Sea Trough. Empirical distributions were computed to describe the spatiotemporal characteristics of convective rain cells for these synoptic systems. Those empirical distributions were used for the development of the HiReS-WG (high-resolution synoptically conditioned weather generator). This weather generator is a stochastic model that generates high resolution rainfall fields (5 min and 0.25 km2). The WG is composed of four modules: the synoptic generator, the motion vector generator, the convective rain cell generator and the low-intensity rainfall generator. The weather generator was evaluated for annual rain depth, season timing, wet-/dry-period duration, rain-intensity distributions and spatial correlations using 300 years of simulated rainfall data. It was found that the weather generator well-represented the above properties compared to radar and rain-gauge observations from the studied region. The HiReS-WG is a good tool to study catchments' hydrological responses to variations in rainfall, especially small- to medium-s