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Office of Scientific and Technical Information
MAP D-PHASE: Real-Time Demonstration of Weather Forecast Quality in the Alpine Region
Science Conference Proceedings (OSTI)
Demonstration of probabilistic hydrological and atmospheric simulation of flood events in the Alpine region (D-PHASE) is made by the Forecast Demonstration Project in connection with the Mesoscale Alpine Programme (MAP). Its focus lies in the end-...
Mathias W. Rotach; Paolo Ambrosetti; Christof Appenzeller; Marco Arpagaus; Lionel Fontannaz; Felix Fundel; Urs Germann; Alessandro Hering; Mark A. Liniger; Marco Stoll; Andre Walser; Felix Ament; Hans-Stefan Bauer; Andreas Behrendt; Volker Wulfmeyer; Fran�ois Bouttier; Yann Seity; Andrea Buzzi; Silvio Davolio; Matteo Corazza; Michael Denhard; Manfred Dorninger; Theresa Gorgas; Jacqueline Frick; Christoph Hegg; Massimiliano Zappa; Christian Keil; Hans Volkert; Chiara Marsigli; Andrea Montaini; Ron McTaggart-Cowan; Ken Mylne; Roberto Ranzi; Evelyne Richard; Andrea Rossa; Daniel Santos-Mu�oz; Christoph Sch�r; Michael Staudinger; Yong Wang; Johannes Werhahn
Urban traffic flow forecasting using Gauss-SVR with cat mapping, cloud model and PSO hybrid algorithm
In order to improve forecasting accuracy of urban traffic flow, this paper applies support vector regression (SVR) model with Gauss loss function (namely Gauss-SVR) to forecast urban traffic flow. By using the input historical flow data as the validation ... Keywords: Cat mapping, Chaos theory, Cloud model, Particle Swarm Optimization, Support vector regression, Traffic flow forecasting
Ming-Wei Li; Wei-Chiang Hong; Hai-Gui Kang
Eta Model Precipitation Forecasts for a Period Including Tropical Storm Allison
A step-mountain (eta) coordinate limited-area model is being developed at the National Meteorological Center (NMC) to improve forecasts of severe weather and other mesoscale phenomena. Precipitation forecasts are reviewed for the 20-day period 16 ...
Fedor Mesinger; Thomas L. Black; David W. Plummer; John H. Ward
Wholesale power price maps reflect real-time constraints ...
U.S. Energy Information Administration (EIA)
U.S. States. State energy information, detailed and overviews. Maps. Maps by energy source and topic, includes forecast maps. Countries. Country ...
An Evaluation of Precipitation Forecasts from Operational Models and Reanalyses Including Precipitation Variations Associated with MJO Activity
In this paper, the results of an examination of precipitation forecasts for 1�30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ...
John E. Janowiak; Peter Bauer; Wanqiu Wang; Phillip A. Arkin; Jon Gottschalck
A hybrid model of self-organizing maps (SOM) and least square support vector machine (LSSVM) for time-series forecasting
Support vector machine is a new tool from Artificial Intelligence (AI) field has been successfully applied for a wide variety of problem especially in time-series forecasting. In this paper, least square support vector machine (LSSVM) is an improved ... Keywords: Forecasting, Least square support vector machine, Self-organizing maps, Time series
Shuhaida Ismail; Ani Shabri; Ruhaidah Samsudin
U.S. States - Maps - U.S. Energy Information Administration (EIA)
Natural Gas. Exploration and reserves, storage, imports and exports, production, prices, sales. ... Maps by energy source and topic, includes forecast maps.
Another Approach to Forecasting Forecast Skill
The skill of a medium-range numerical forecast can fluctuate widely from day to day. Providing an a priori estimate of the skill of the forecast is therefore important. Existing approaches include Monte Carlo Forecasting and Lagged Average ...
W. Y. Chen
Classifying Proximity Soundings with Self-Organizing Maps toward Improving Supercell and Tornado Forecasting
The self-organizing map (SOM) statistical technique is applied to vertical profiles of thermodynamic and kinematic parameters from a Rapid Update Cycle-2 (RUC-2) proximity sounding dataset with the goal of better distinguishing and predicting ...
Christopher J. Nowotarski; Anders A. Jensen
Forecast Correlation Coefficient Matrix of Stock Returns in Portfolio Analysis
E-Print Network (OSTI)
Unadjusted Forecasts . . . . . . . . . . . . . . . .Forecasts . . . . . . . . . . . . . . . . . . . . . . . . . .Unadjusted Forecasts . . . . . . . . . . . . . . . . . . .
Zhao, Feng
Forecast Technical Document Forecast Types
Forecast Technical Document Forecast Types A document describing how different forecast types are implemented in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 Forecast Types Background Different `types' of forecast are possible for a specified area
The Influence of Variations in Surface Treatment on 24-Hour Forecasts with a Limited Area Model, Including a Comparison of Modeled and Satellite-Measured Surface Temperatures
The effect of variations in surface parameters on 24-hour limited area forecasts has been examined on a day in July 1981. The vehicle for the study is a ten-level primitive equation model covering most of the continental United States. Variations ...
George Diak; Stacey Heikkinen; John Rates
RACORO Forecasting
NLE Websites -- All DOE Office Websites (Extended Search)
Weather Briefings Observed Weather Cloud forecasting models BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated...
1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.
This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.
United States. Bonneville Power Administration.
Business forecasting methods
Forecasting is a common statistical task in business, where it helps inform decisions about scheduling of production, transportation and personnel, and provides a guide to long-term strategic planning. However, business forecasting is often done poorly and is frequently confused with planning and goals. They are three different things. Forecasting is about predicting the future as accurately as possible, given all the information available including historical data and knowledge of any future events that might impact the forecasts. Goals are what you would like to happen. Goals should be linked to forecasts and plans, but this does not always occur. Too often, goals are set without any plan for how to achieve them, and no forecasts for whether they are realistic. Planning is a response to forecasts and goals. Planning involves determining the appropriate actions that are required to make your forecasts match your goals. Forecasting should be an integral part of the decision-making activities of management, as it can play an important role in many areas of a company. Modern organizations require short-, medium- and long-term forecasts, depending on the specific application.
Rob J Hyndman
Forecasting Forecast Skill
We have shown that it is possible to predict the skill of numerical weather forecasts�a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average ...
Eugenia Kalnay; Amnon Dalcher
A Short-Range Forecasting Experiment Conducted during the Canadian Atlantic Storms Program
During the Canadian Atlantic Storms Program (CASP), a dedicated forecast center conducted experiments in mesoscale forecasting. Several forecast products, including a marine forecast and a site-specific public forecast, were written every 3 h. ...
K. A. Macdonald; M. Danks; J. D. Abraham
Forecast Combinations
Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this chapter we analyze theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models� forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where thenumbersofmodelsislargerelativetothe available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts. Key words: Forecast combinations; pooling and trimming; shrinkage methods; model misspecification, diversification gains
Allan Timmermann; Jel Codes C
Forecast Technical Document Tree Species
Forecast Technical Document Tree Species A document listing the tree species included in the 2011 Production Forecast Tom Jenkins Justin Gilbert Ewan Mackie Robert Matthews #12;PF2011 List of tree species The following is the list of species used within the Forecast System. Species are ordered alphabetically
Forecasting overview
Forecasting is required in many situations: deciding whether to build another power generation plant in the next five years requires forecasts of future demand; scheduling staff in a call centre next week requires forecasts of call volume; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. Some things are easier to forecast than others. The time of the sunrise tomorrow morning can be forecast very precisely. On the other hand, currency exchange rates are very difficult to forecast with any accuracy. The predictability of an event or a quantity depends on how well we understand the factors that contribute to it, and how much unexplained variability is involved. Forecasting situations vary widely in their time horizons, factors determining actual outcomes, types of data patterns, and many other aspects. Forecasting methods can be very simple such as using the most recent observation as a forecast (which is called the �na�ve method�), or highly complex such as neural nets and econometric systems of simultaneous equations. The
U.S. Regional Demand Forecasts Using NEMS and GIS
Forecasts Using NEMS and GIS National Climatic Data Center.with Changing Boundaries." Use of GIS to Understand Socio-Forecasts Using NEMS and GIS Appendix A. Map Results Gallery
Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris
An Alternative Tropical Cyclone Intensity Forecast Verification Technique
The National Hurricane Center (NHC) does not verify official or model forecasts if those forecasts call for a tropical cyclone to dissipate or if the real tropical cyclone dissipates. A new technique in which these forecasts are included in a ...
Sim D. Aberson
Maps Maps Maps Los Alamos is located in Northern New Mexico about 35 miles (about 40 minutes drive) northwest of Santa Fe and 1 hour and 45 minutes drive from Albuquerque. Contact LANL Directory 667-5061 Badge Office (505) 667-6901 Email Institutional Visits and Events (505) 667-2222 Location and directions How to get to LANL Los Alamos is located in Northern New Mexico about 35 miles (about 40 minutes drive) northwest of Santa Fe and 1 hour and 45 minutes drive from Albuquerque. Laboratory facilities can be found in 50 different work areas that are spread across 36 square miles. Below is the general location of the Otowi Building, Badge Office, cafeteria, and Research Library. V Screen reader users: click here for plain HTML Go to Google Maps Home Casa Grande Drive, Los Alamos, NM
Load Forecasting for Modern Distribution Systems
Load forecasting is a fundamental activity for numerous organizations and activities within a utility, including planning, operations, and control. Transmission and Distribution (T&D) planning and design engineers use the load forecast to determine whether any changes and additions are needed to the electric system to satisfy the anticipated load. Other load forecast users include system operations, financial ...
Performance of Recent Multimodel ENSO Forecasts
The performance of the International Research Institute for Climate and Society �ENSO forecast plume� during the 2002�11 period is evaluated using deterministic and probabilistic verification measures. The plume includes multiple model forecasts ...
Michael K. Tippett; Anthony G. Barnston; Shuhua Li
Solar forecasting review
of Solar Forecasting . . . . . . . . . 2.4.1 Solarbudget at the foundation of satellite based forecastingWeather Research and Forecasting (WRF) Model 7.1 Global
Inman, Richard Headen
NFI Forecasts Methodology NFI Forecasts Methodology
NFI Forecasts Methodology NFI Forecasts Methodology Overview Issued by: National Forest firstname.lastname@example.com Website: www.forestry.gov.uk/inventory 1 NFI Softwood Forecasts Methodology Overview #12;NFI Forecasts ........................................................................................................4 Rationale behind the new approach to the GB Private sector production forecast ........4 Volume
Forecast Technical Document Restocking in the Forecast
Forecast Technical Document Restocking in the Forecast A document describing how restocking of felled areas is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the forecast Background During the period of a production forecast it is assumed that, as forest sub
> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS BRISBANE FORECAST IMPROVEMENTS The Bureau of Meteorology is progressively upgrading its forecast system to provide more detailed forecasts across Australia. From October 2013 new and improved 7 day forecasts will be introduced for Brisbane, Gold Coast
Greenslade, Diana
NOS Point Forecast Guidance to Weather and Ocean Conditions ...
NOS Point Forecast Guidance to Weather and Ocean Conditions Ocean Data Tools Technical Guide Map Gallery Regional Planning Feedback Ocean You are here Data.gov Communities ...
Point Forecast Guidance to Weather and Ocean Conditions Ocean Data Tools Technical Guide Map Gallery Regional Planning Feedback Ocean You are here Data.gov Communities Ocean...
Forecast Energy | Open Energy Information
Open Energy Info (EERE)
Forecast Energy Forecast Energy Jump to: navigation, search Name Forecast Energy Address 2320 Marinship Way, Suite 300 Place Sausalito, California Zip 94965 Sector Services Product Intelligent Monitoring and Forecasting Services Year founded 2010 Number of employees 11-50 Company Type For profit Website http://www.forecastenergy.net Coordinates 37.865647°, -122.496315° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.865647,"lon":-122.496315,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}
Evaluating Density Forecasts: Forecast Combinations, Model Mixtures, Calibration and Sharpness
In a recent article Gneiting, Balabdaoui and Raftery (JRSSB, 2007) propose the criterion of sharpness for the evaluation of predictive distributions or density forecasts. They motivate their proposal by an example in which standard evaluation procedures based on probability integral transforms cannot distinguish between the ideal forecast and several competing forecasts. In this paper we show that their example has some unrealistic features from the perspective of the time-series forecasting literature, hence it is an insecure foundation for their argument that existing calibration procedures are inadequate in practice. We present an alternative, more realistic example in which relevant statistical methods, including information-based methods, provide the required discrimination between competing forecasts. We conclude that there is no need for a subsidiary criterion of sharpness.
James Mitchell; Kenneth F. Wallis
Annual Energy Outlook Forecast Evaluation
Gasoline and Diesel Fuel Update (EIA)
Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation by Susan H. Holte In this paper, the Office of Integrated Analysis and Forecasting (OIAF) of the Energy Information Administration (EIA) evaluates the projections published in the Annual Energy Outlook (AEO), (1) by comparing the projections from the Annual Energy Outlook 1982 through the Annual Energy Outlook 2001 with actual historical values. A set of major consumption, production, net import, price, economic, and carbon dioxide emissions variables are included in the evaluation, updating similar papers from previous years. These evaluations also present the reasons and rationales for significant differences. The Office of Integrated Analysis and Forecasting has been providing an
Fuzzy forecasting with DNA computing
There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard ...
Don Jyh-Fu Jeng; Junzo Watada; Berlin Wu; Jui-Yu Wu
Update On The Wholesale Electricity Price Forecast & Modeling Results
Forecast Base Case includes § Medium Demand Forecast § Medium Natural Gas Price Forecast § Federal CO2 Rathdrum Power LLC-ID 4) CO2 Emissions - 2009 Selected Natural Gas Plants Plant level, emission percentage § Significantly lower electricity prices than 6th Plan Forecast, due to lower demand, lower gas prices, deferred
CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons
SolarAnywhere forecast (Perez & Hoff) This chapter describes, and presents an evaluation of, the forecast models imbedded in the
SolarAnywhere forecast (Perez & Hoff) ABSTRACT This chapter describes, and presents an evaluation of, the forecast models imbedded in the SolarAnywhere platform. The models include satellite derived cloud motion based forecasts for the short to medium horizon (1 5 hours) and forecasts derived from NOAA
Perez, Richard R.
The Forecast Gap: Linking Forwards and Forecasts
This report addresses a common problem in price forecasting: What to do when confronted with a persistent gap between results obtained from a structural forecast model and actual forward or spot prices? The report examines examples taken from natural gas and electric power forecasts and presents a novel approach to closing this �forecast gap.� Inspection reveals that the ratio of actual prices to forecast prices often exhibits stochastic movements that resemble those of commodity price movements. By usin...
Forecast Prices
Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon
MSSM Forecast for the LHC
We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered, the preferred region (for $\\mu>0$) is well inside the LHC scope. We also perform a Bayesian comparison of the positive- and negative-$\\mu$ possibilities.
Maria Eugenia Cabrera; Alberto Casas; Roberto Ruiz de Austri
Forecasting in Meteorology
Public weather forecasting heralded the beginning of modern meteorology less than 150 years ago. Since then, meteorology has been largely a forecasting discipline. Thus, forecasting could have easily been used to test and develop hypotheses, ...
C. S. Ramage
Spatial Forecasts of Maximum Hail Size Using Prognostic Model Soundings and HAILCAST
Forecasting the occurrence of hail and the maximum hail size is a challenging problem. This paper investigates the feasibility of producing maps of the forecast maximum hail size over the Canadian prairies using 12-h prognostic soundings from an ...
Julian C. Brimelow; Gerhard W. Reuter; Ron Goodson; Terrence W. Krauss
Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1
Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range
Operations of the National Severe Storms Forecast Center
The National Severe Storms Forecast Center in Kansas City, Missouri, is composed of several operational forecasting units, all national in scope. It includes the Severe Local Storms Unit (SELS), the National Aviation Weather Advisory Unit (NAWAU),...
Frederick P. Ostby
Forecasts, Meteorology Services, Environmental Sciences Department
Forecasts Short Term Forecast Suffolk County Northern Nassau Southern Nassau Area Forecast Discussion - OKX Area Forecast Discussion - NYS Area Forecast Discussion Mount Holly Area...
A RELM earthquake forecast based on pattern informatics
We present a RELM forecast of future earthquakes in California that is primarily based on the pattern informatics (PI) method. This method identifies regions that have systematic fluctuations in seismicity, and it has been demonstrated to be successful. A PI forecast map originally published on 19 February 2002 for southern California successfully forecast the locations of sixteen of eighteen M>5 earthquakes during the past three years. The method has also been successfully applied to Japan and on a worldwide basis. An alternative approach to earthquake forecasting is the relative intensity (RI) method. The RI forecast map is based on recent levels of seismic activity of small earthquakes. Recent advances in the PI method show considerable improvement, particularly when compared with the RI method using relative operating characteristic (ROC) diagrams for binary forecasts. The RELM application requires a probability for each location for a number of magnitude bins over a five year period. We have therefore co...
Holliday, J R; Donnelan, A; Rundle, J B; Tiampo, K F; Turcotte, D L; Chen, Chien-chih; Donnelan, Andrea; Holliday, James R.; Rundle, John B.; Tiampo, Kristy F.; Turcotte, Donald L.
Does Money Matter in Inflation Forecasting? JM Binner 1
1 Does Money Matter in Inflation Forecasting? JM Binner 1 P Tino 2 J Tepper 3 R Anderson4 B Jones 5 or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide collections of included monetary assets. In our forecasting experiment we use two non-linear techniques
Tino, Peter
Verifying Forecasts Spatially
Numerous new methods have been proposed for using spatial information to better quantify and diagnose forecast performance when forecasts and observations are both available on the same grid. The majority of the new spatial verification methods can be ...
Eric Gilleland; David A. Ahijevych; Barbara G. Brown; Elizabeth E. Ebert
Forecasting of Supercooled Clouds
Using parameterizations of cloud microphysics, a technique to forecast supercooled cloud events is suggested. This technique can be coupled on the mesoscale with a prognostic equation for cloud water to improve aircraft icing forecasts. The ...
Andr� Tremblay; Anna Glazer; Wanda Szyrmer; George Isaac; Isztar Zawadzki
A Lightning Data Assimilation Technique for Mesoscale Forecast Models
Lightning observations have been assimilated into a mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network (cloud-to-ground lightning detection) and a Lightning Mapping Array (...
Edward R. Mansell; Conrad L. Ziegler; Donald R. MacGorman
Time Series and Forecasting
Time Series and Forecasting. Leigh, Stefan and Perlman, S. (1991). "An Index for Comovement of Time Sequences With ...
Forecast Technical Document Volume Increment
Forecast Technical Document Volume Increment Forecasts A document describing how volume increment is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 Volume increment forecasts Background A volume increment forecast is a fundamental output of the forecast
Maps and Shuttle - TMS
TMS 2008 Conference Maps and Shuttle Information. Ernest N. Morial Convention Center Maps All conference events, including registration, technical sessions�...
The Strategy of Professional Forecasting
This paper develops and compares two theories of strategic behavior of professional forecasters. The first theory posits that forecasters compete in a forecasting contest with pre-specified rules. In equilibrium of a winner-take-all contest, forecasts are excessively differentiated. According to the alternative reputational cheap talk theory, forecasters aim at convincing the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the realized state. If the market expects forecaster honesty, forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded.
Marco Ottaviani; Peter Norman S�rensen
5.5 ENSEMBLE RE-FORECASTING : IMPROVING MEDIUM-RANGE FORECAST SKILL USING RETROSPECTIVE FORECASTS, Colorado 1. INTRODUCTION Improving weather forecasts is a primary goal of the U.S. National Oceanic predictions has been to improve the accuracy of the numerical forecast models. Much effort has been expended
Hamill, Tom
Today's Forecast: Improved Wind Predictions | Department of Energy
in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar --...
1993 Solid Waste Reference Forecast Summary
SciTech Connect
This report, which updates WHC-EP-0567, 1992 Solid Waste Reference Forecast Summary, (WHC 1992) forecasts the volumes of solid wastes to be generated or received at the US Department of Energy Hanford Site during the 30-year period from FY 1993 through FY 2022. The data used in this document were collected from Westinghouse Hanford Company forecasts as well as from surveys of waste generators at other US Department of Energy sites who are now shipping or plan to ship solid wastes to the Hanford Site for disposal. These wastes include low-level and low-level mixed waste, transuranic and transuranic mixed waste, and nonradioactive hazardous waste.
Valero, O.J.; Blackburn, C.L. [Westinghouse Hanford Co., Richland, WA (United States); Kaae, P.S.; Armacost, L.L.; Garrett, S.M.K. [Pacific Northwest Lab., Richland, WA (United States)
Evaluation Evaluation Annual Energy Outlook Forecast Evaluation by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the impacts were not incorporated in the AEO projections until their enactment or effective dates in accordance with EIA's requirement to remain policy neutral and include only current laws and regulations in the AEO reference case projections.
ORNL integrated forecasting system
This paper describes the integrated system for forecasting electric energy and load. In the system, service area models of electrical energy (kWh) and load distribution (minimum and maximum loads and load duration curve) are linked to a state-level model of electrical energy (kWh). Thus, the service area forecasts are conditional upon the state-level forecasts. Such a linkage reduces considerably the data requirements for modeling service area electricity demand.
Rizy, C.G.
Probabilistic Forecasts from the National Digital Forecast Database
The Bayesian processor of forecast (BPF) is developed for a continuous predictand. Its purpose is to process a deterministic forecast (a point estimate of the predictand) into a probabilistic forecast (a distribution function, a density function, ...
Roman Krzysztofowicz; W. Britt Evans
2.1.2 European Solar Radiation Atlas (ESRA)2.4 Evaluation of Solar Forecasting . . . . . . . . .2.4.1 Solar Variability . . . . . . . . . . . . .
forecast | OpenEI
Browse Upload data GDR Community Login | Sign Up Search Facebook icon Twitter icon forecast Dataset Summary Description The EIA's annual energy outlook (AEO) contains yearly...
Seasonal tropical cyclone forecasts
Seasonal forecasts of tropical cyclone activity in various regions have been developed since the first attempts in the early 1980s by Neville
Suzana J. Camargo; Anthony G. Barnston; Philip J. Klotzbach; Christopher W. Landsea
Online 24-h solar power forecasting based on weather typeweather observations at blue hill massachusetts,� Solarof weather patterns on the intensity of solar irradiance;
Forecasting future volatility from option prices, Working
Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information � including all information contained in the history of past prices � about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.
Allen M. Poteshman
Forecasting the demand for commercial telecommunications satellites
This paper summarizes the key elements of a forecast methodology for predicting demand for commercial satellite services and the resulting demand for satellite hardware and launches. The paper discusses the characterization of satellite services into more than a dozen applications (including emerging satellite Internet applications) used by Futron Corporation in its forecasts. The paper discusses the relationship between demand for satellite services and demand for satellite hardware
Carissa Bryce Christensen; Carie A. Mullins; Linda A. Williams
Arnold Schwarzenegger INTEGRATED FORECAST AND
Arnold Schwarzenegger Governor INTEGRATED FORECAST AND RESERVOIR MANAGEMENT (INFORM) FOR NORTHERN; the former with primary contributions in the areas of climate and hydrologic forecasting and the latter Service (NWS) California Nevada River Forecast Center (CNRFC), the California Department of Water
CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy
Does the term structure forecast
provides more accurate forecasts of real consumption growth14. Harvey, C.R. (1989): \\Forecasts of economic growth fromC.R. (1993): \\Term structure forecasts economic growth", Fi-
Berardi, Andrea; Torous, Walter
Global and Local Skill Forecasts
A skill forecast gives the probability distribution for the error in a forecast. Statistically, Well-founded skill forecasting methods have so far only been applied within the context of simple models. In this paper, the growth of analysis errors ...
P. L. Houtekamer
Distortion Representation of Forecast Errors
Forecast error is decomposed into three components, termed displacement error, amplitude error, mid residual error, respectively. Displacement error measures how much of the forecast error can be accounted for by moving the forecast to best fit ...
Ross N. Hoffman; Zheng Liu; Jean-Francois Louis; Christopher Grassoti
Composite forecasting in commodity systems
Paper No. COMPOSI1E FORECASTING IN CO/Yt.flDITI SYSTfu\\1S1980 .i CfIAPTER COMPOSITE FORECASTING IN COMMOOITY SYSTEMS*to utilizeeconometric .modelsfor forecasting ! ,urposes. The
Johnson, Stanley R; Rausser, Gordon C.
Evaluating Point Forecasts
Typically, point forecasting methods are compared and assessed by means of an error measure or scoring function, such as the absolute error or the squared error. The individual scores are then averaged over forecast cases, to result in a summary measure of the predictive performance, such as the mean absolute error or the (root) mean squared error. I demonstrate that this common practice can lead to grossly misguided inferences, unless the scoring function and the forecasting task are carefully matched. Effective point forecasting requires that the scoring function be specified ex ante, or that the forecaster receives a directive in the form of a statistical functional, such as the mean or a quantile of the predictive distribution. If the scoring function is specified ex ante, the forecaster can issue the optimal point forecast, namely, the Bayes rule. If the forecaster receives a directive in the form of a functional, it is critical that the scoring function be consistent for it, in the sense that the expect...
Gneiting, Tilmann
Forecasters � Objectives and Strategies ?
This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive literature on analysts, we review the empirical evidence on strategic forecasting and illustrate how our model can be structurally estimated.
Iv�n Marinovic; Marco Ottaviani; Peter Norman S�rensen
Coefficients for Debiasing Forecasts
Skill-score decompositions can be used to analyze the effects of bias on forecasting skill. However, since bias terms are typically squared, and bias is measured in skill-score units rather than in units of the forecasts, such decompositions only ...
Thomas R. Stewart; Patricia Reagan-Cirincione
Getting the Most out of Ensemble Forecasts: A Valuation Model Based on User�Forecast Interactions
A flexible theoretical model of perceived forecast value is proposed that explicitly includes the effects of user and ensemble characteristics and their interactions. The model can be applied to arbitrary decision problems and is sensitive to a ...
Antony Millner
A New Verification Score for Public Forecasts
CREF, a new verification score for public forecasts, is introduced. This verification score rewards a forecaster who forecasts a rare event accurately. CREF was used to verify local forecasts at the Weather Service Forecast Office (WSFO) in ...
Dean P. Gulezian
· NATIONAL AND GLOBAL FORECASTS · WEST VIRGINIA PROFILES AND FORECASTS · ENERGY · HEALTHCARE Industry Insight: West Virginia Fiscal Forecast 34 CHAPTER 4: WEST ViRGiNiA'S 35 COUNTiES AND MSAs West Forecast Summary 2 CHAPTER 1: THE UNiTED STATES ECONOMY Figure 1.1: United States Real GDP Growth 3 Figure
Mohaghegh, Shahab
1 APPLICATION OF PROBABILISTIC FORECASTS: DECISION MAKING WITH FORECAST UNCERTAINTY Rick Katz.isse.ucar.edu/HP_rick/dmuu.pdf #12;2 QUOTES ON USE OF PROBABILITY FORECASTS · Lao Tzu (Chinese Philosopher) "He who knows does and Value of Probability Forecasts (4) Cost-Loss Decision-Making Model (5) Simulation Example (6) Economic
Katz, Richard
Why are survey forecasts superior to model forecasts?
We investigate two characteristics of survey forecasts that are shown to contribute to their superiority over purely model-based forecasts. These are that the consensus forecasts incorporate the effects of perceived changes in the long-run outlook, as well as embodying departures from the path toward the long-run expectation. Both characteristics on average tend to enhance forecast accuracy. At the level of the individual forecasts, there is scant evidence that the second characteristic enhances forecast accuracy, and the average accuracy of the individual forecasts can be improved by applying a mechanical correction.
Michael P. Clements; Michael P. Clements
Essays on macroeconomics and forecasting
This dissertation consists of three essays. Chapter II uses the method of structural factor analysis to study the effects of monetary policy on key macroeconomic variables in a data rich environment. I propose two structural factor models. One is the structural factor augmented vector autoregressive (SFAVAR) model and the other is the structural factor vector autoregressive (SFVAR) model. Compared to the traditional vector autogression (VAR) model, both models incorporate far more information from hundreds of data series, series that can be and are monitored by the Central Bank. Moreover, the factors used are structurally meaningful, a feature that adds to the understanding of the ��?black box� of the monetary transmission mechanism. Both models generate qualitatively reasonable impulse response functions. Using the SFVAR model, both the ��?price puzzle� and the ��?liquidity puzzle� are eliminated. Chapter III employs the method of structural factor analysis to conduct a forecasting exercise in a data rich environment. I simulate out-of-sample real time forecasting using a structural dynamic factor forecasting model and its variations. I use several structural factors to summarize the information from a large set of candidate explanatory variables. Compared to Stock and Watson (2002)��?s models, the models proposed in this chapter can further allow me to select the factors structurally for each variable to be forecasted. I find advantages to using the structural dynamic factor forecasting models compared to alternatives that include univariate autoregression (AR) model, the VAR model and Stock and Watson��?s (2002) models, especially when forecasting real variables. In chapter IV, we measure U.S. technology shocks by implementing a dual approach, which is based on more reliable price data instead of aggregate quantity data. By doing so, we find the relative volatility of technology shocks and the correlation between output fluctuation and technology shocks to be much smaller than those revealed in most real-business-cycle (RBC) studies. Our results support the findings of Burnside, Eichenbaum and Rebelo (1996), who showed that the correlation between technology shocks and output is exaggerated in the RBC literature. This suggests that one should examine other sources of fluctuations for a better understanding of the business cycle phenomena.
Liu, Dandan
Demand Forecast INTRODUCTION AND SUMMARY
Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast
LOAD FORECASTING Eugene A. Feinberg
's electricity price forecasting model, produces forecast of gas demand consistent with electric load. #12Gas demand Council's Market Price of Electricity Forecast Natural GasDemand Electric Load Aggregating Natural between the natural gas and electricity and new uses of natural gas emerge. T natural gas forecasts
Feinberg, Eugene A.
Air Quality Forecasts in the Mid-Atlantic Region: Current Practice and Benchmark Skill
Air quality forecasts for the mid-Atlantic region (including the metropolitan areas of Baltimore, Washington, D.C., and Philadelphia) began in 1992. These forecasts were issued to the public beginning in 1995 and predict daily peak O3 ...
William F. Ryan; Charles A. Piety; Eric D. Luebehusen
Hydrometeorological Short-Range Ensemble Forecasts in Complex Terrain. Part I: Meteorological Evaluation
This paper addresses the question of whether it is better to include lower-resolution members of a nested suite of numerical precipitation forecasts to increase ensemble size, or to utilize high-resolution members only to maximize forecast ...
Doug McCollor; Roland Stull
Nambe Pueblo Water Budget and Forecasting model.
This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.
Brainard, James Robert
RAINSAT. A One Year Evaluation of a Bispectral Method for the Analysis and Short-Range Forecasting of Precipitation Areas
RAINSAT uses under data to calibrate GOES visible and infra data in terms of probability of rain. It produces probability of rain maps and 3 h forecast probability of rain maps by extrapolation.
Patrick King; Tsoi-Ching Yip; J. David Steenbergen
Factors Driving Prices & Forecast
This spread is a function of the balance between demand and fresh supply (production and net imports). Finally I will discuss the current forecast for distillate prices this winter...
Modeling and Forecasting Aurora
Modeling the physical processes needed for forecasting space-weather events requires multiscale modeling. This article discusses several modelsresearchers use to treat the various auroral processes that influence space weather.
Dirk Lummerzheim
Valuing Climate Forecast Information
The article describes research opportunities associated with evaluating the characteristics of climate forecasts in settings where sequential decisions are made. Illustrative results are provided for corn production in east central Illinois. ...
Steven T. Sonka; James W. Mjelde; Peter J. Lamb; Steven E. Hollinger; Bruce L. Dixon
Energy.gov (U.S. Department of Energy (DOE)) Indexed Site
Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.
Short-Term Wind Speed Forecasting for Power System Operations
Global large scale penetration of wind energy is accompanied by significant challenges due to the intermittent and unstable nature of wind. High quality short-term wind speed forecasting is critical to reliable and secure power system operations. This paper gives an overview of the current status of worldwide wind power developments and future trends, and reviews some statistical short-term wind speed forecasting models, including traditional time series models and advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented.
Xinxin Zhu; Marc G. Genton
Multivariate Forecast Evaluation And Rationality Testing
1062�1088. MULTIVARIATE FORECASTS Chaudhuri, P. (1996): �OnKingdom. MULTIVARIATE FORECASTS Kirchg�ssner, G. , and U. K.2005): �Estimation and Testing of Forecast Rationality under
Komunjer, Ivana; OWYANG, MICHAEL
Forecasting in the Presence of Level Shifts
accuracy. Journal of Forecasting 19 : 537-560. Hamilton JD.430. Harvey AC. 1989. Forecasting, structural time seriesMH, Timmermann A. 1994. Forecasting stock returns: An
Smith, Aaron
On Modeling and Forecasting Time Series of Smooth Curves
/fertility rate curves (Hyndman and Ullah, 2007; Erbas et al., 2007). Other examples include electricity system the rates are unobservable; hence one needs to forecast future rate profiles based on historical call of telephone customer service centers, where forecasts of daily call arrival rate profiles are needed
Shen, Haipeng
We examine the accuracy and bias of intrinsic equity prices estimated from three accounting-based valuation models using analyst�s earnings forecasts over a four-year horizon. The models are: (a) the earnings capitalization model, (b) the residual income model without a terminal value, and (c) the residual income model with a terminal value that assumes residual income will grow beyond the horizon at a constant rate determined from the expected residual income growth rate over the forecast horizon. Our analysis is based on valuation errors that are calculated by comparing estimated prices to actual prices. We contribute to the literature by examining whether: (i) the analysts � earnings forecasts convey information about value beyond that conveyed by current earnings, book value and dividends, (ii) the use of firm specific growth rates in terminal value calculations results in more unbiased and accurate valuations than the use of constant growth rates, and (iii) different models perform better under different ex-ante conditions. We find that analysts � earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Each of the models that we used has valuation errors that decline monotonically as the horizon increases implying that earnings forecasts at each horizon convey new value relevant information. We cannot find a clear advantage to using firm specific growth rates instead of a constant rate of 4 % across all sample
Theodore Sougiannis; Takashi Yaekura
Solar Wind Forecasting with Coronal Holes
An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.
S. Robbins; C. J. Henney; J. W. Harvey
1 THE PITTSBURGH REMI MODEL: LONG-TERM REMI MODEL FORECAST FOR ALLEGHENY COUNTY AND THE PITTSBURGH made. REMI LONG-TERM FORECAST AND BEA PROJECTIONS This report includes UCSUR's 1998 economic and population projections for the Pittsburgh Region. The purpose of UCSUR's long-term regional forecasts
Sibille, Etienne
CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast
Statistical Recalibration of GCM Forecasts over Southern Africa Using Model Output Statistics
A technique for producing regional rainfall forecasts for southern Africa is developed that statistically maps or �recalibrates� large-scale circulation features produced by the ECHAM3.6 general circulation model (GCM) to observed regional ...
Willem A. Landman; Lisa Goddard
Revised Draft Forecast of Electricity Demand
. Forecasts of higher electricity and natural gas prices will fundamentally challenge energy intensive. These include the reduced growth in natural gas supplies in spite of significant drilling activity and #12;DRAFT the medium-high case, while paper and allied products has been below the medium-low. Future natural gas
New Concepts in Wind Power Forecasting Models
of the motivations behind the project led by ANL Argonne National Laboratory, together with INESC Porto from a manageable procedure to compute the solution. IV. ENTROPY AND PARZEN WINDOW PDF ESTIMATION The most well into the substation connecting it to the electric power network. Other model's input variables include forecasts
Kemner, Ken
Issues in midterm analysis and forecasting, 1996
This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.
CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW
Forecast Technical Document Technical Glossary
Forecast Technical Document Technical Glossary A document defining some of the terms used in the 2011 Production Forecast technical documentation. Tom Jenkins Robert Matthews Ewan Mackie Lesley in the Forecast documentation. In some cases, the terms and the descriptions are "industry standard", in others
3, 21452173, 2006 Probabilistic forecast
HESSD 3, 21452173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page for probabilistic forecasts of continuous hydrological variables F. Laio and S. Tamea DITIC Department2173, 2006 Probabilistic forecast verification F. Laio and S. Tamea Title Page Abstract Introduction
Paris-Sud XI, Université de
4, 189212, 2007 Forecast and
OSD 4, 189212, 2007 Forecast and analysis assessment through skill scores M. Tonani et al. Title Science Forecast and analysis assessment through skill scores M. Tonani 1 , N. Pinardi 2 , C. Fratianni 1 Forecast and analysis assessment through skill scores M. Tonani et al. Title Page Abstract Introduction
predecessors to forecast stock prices and manage portfolios for approximately 3 years.) We examineFINANCIAL FORECASTING USING GENETIC ALGORITHMS SAM MAHFOUD and GANESH MANI LBS Capital Management entitled Genetic Algorithms for Inductive Learning). Time-series forecasting is a special type
Boetticher, Gary D.
Consensus Coal Production Forecast for
Consensus Coal Production Forecast for West Virginia 2009-2030 Prepared for the West Virginia Summary 1 Recent Developments 2 Consensus Coal Production Forecast for West Virginia 10 Risks References 27 #12;W.Va. Consensus Coal Forecast Update 2009 iii List of Tables 1. W.Va. Coal Production
Annual Energy Outlook Forecast Evaluation - Tables
Annual Energy Outlook Forecast Evaluation Table 2. Total Energy Consumption, Actual vs. Forecasts Table 3. Total Petroleum Consumption, Actual vs. Forecasts Table 4. Total Natural Gas Consumption, Actual vs. Forecasts Table 5. Total Coal Consumption, Actual vs. Forecasts Table 6. Total Electricity Sales, Actual vs. Forecasts Table 7. Crude Oil Production, Actual vs. Forecasts Table 8. Natural Gas Production, Actual vs. Forecasts Table 9. Coal Production, Actual vs. Forecasts Table 10. Net Petroleum Imports, Actual vs. Forecasts Table 11. Net Natural Gas Imports, Actual vs. Forecasts Table 12. Net Coal Exports, Actual vs. Forecasts Table 13. World Oil Prices, Actual vs. Forecasts Table 14. Natural Gas Wellhead Prices, Actual vs. Forecasts Table 15. Coal Prices to Electric Utilities, Actual vs. Forecasts
Forecast of auroral activity
A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting
A. T. Y. Lui
Diagnosing Sources of U.S. Seasonal Forecast Skill
In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ...
X. Quan; M. Hoerling; J. Whitaker; G. Bates; T. Xu
Recently released EIA report presents international forecasting data
This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.
by Esmeralda Sánchez The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors,
Forecasting Dangerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures
Forecasting Dangerous Inmate Misconduct: An Applications ofidentify with useful forecasting skill the very few inmatescontribute substantially to forecasting skill necessarily
Berk, Richard; Kriegler, Brian; Baek, Jong-Ho
Information and Inference in Econometrics: Estimation, Testing and Forecasting
Application: Forecasting Equity Premium . . . . . . . . . .2.6.1 Forecasting4 Forecasting Using Supervised Factor Models 4.1
Tu, Yundong
Richard A. Berk; Brian Kriegler; Jong-Ho Baek
by Esmeralda Sanchez by Esmeralda Sanchez Errata -(7/14/04) The Office of Integrated Analysis and Forecasting has produced an annual evaluation of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and the most recent historical year of data. The Forecast Evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute forecast errors for each of the major variables for AEO82 through AEO2003. The average absolute forecast error, which for the purpose of this report will also be referred to simply as "average error" or "forecast error", is computed as the simple mean, or average, of all the absolute values of the percent errors, expressed as the percentage difference between the Reference Case projection and actual historic value, shown for every AEO and for each year in the forecast horizon (for a given variable). The historical data are typically taken from the Annual Energy Review (AER). The last column of Table 1 provides a summary of the most recent average absolute forecast errors. The calculation of the forecast error is shown in more detail in Tables 2 through 18. Because data for coal prices to electric generating plants were not available from the AER, data from the Monthly Energy Review (MER), July 2003 were used.
Management Earnings Forecasts and Value of Analyst Forecast Revisions
Prior studies evaluate the relative importance of the sources of value that financial analysts bring to the market based on the price impact of forecast revisions over the event time. We find that management earnings forecasts influence the timing and precision of analyst forecasts. More importantly, evidence suggests that prior studies � finding of weaker (stronger) stock-price responses to forecast revisions in the period immediately after (before) the prior-quarter earnings announcement is likely to be the artifact of a temporal pattern of management earnings forecasts over the event time. To the extent that management earnings forecasts are public disclosures, our results suggest that the relative importance of analysts ' information discovery role documented in prior studies is likely to be overstated.
Yongtae Kim; Minsup Song
Viability, Development, and Reliability Assessment of Coupled Coastal Forecasting Systems
Real-time wave forecasts are critical to a variety of coastal and offshore opera- tions. NOAA�s global wave forecasts, at present, do not extend into many coastal regions of interest. Even after more than two decades of the historical Exxon Valdez disaster, Cook Inlet (CI) and Prince William Sound (PWS) are regions that suffer from a lack of accurate wave forecast information. This dissertation develops high- resolution integrated wave forecasting schemes for these regions in order to meet the critical requirements associated with shipping, commercial and sport fishing vessel safety, and oil spill response. This dissertation also performs a detailed qualitative and quantitative assessment of the impact of various forcing functions on wave pre- dictions, and develops maps showing extreme variations in significant wave heights (SWHs). For instance, it is found that the SWH could vary by as much as 1 m in the northern CI region in the presence of currents (hence justifying the need for integration of the wave model with a circulation model). Such maps can be useful for several engineering operations, and could also serve as guidance tool as to what can be expected in certain regions. Aside from the system development, the issue of forecast reliability is also addressed for PWS region in the context of the associated uncertainty which confronts the manager of engineering operations or other planners. For this purpose, high-resolution 36-h daily forecasts of SWHs are compared with measurements from buoys and satellites for about a year. The results show that 70% of the peak SWHs in the range 5-8 m were predicted with an accuracy of 15% or less for a forecast lead time of 9 h. On average, results indicate 70% or greater likelihood of the prediction falling within a tolerance of �(1*RMSE) for all lead times. This analysis could not be performed for CI due to lack of data sources.
Singhal, Gaurav
Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets
against the risk of energy price fluctuations. In theory,The poor track record of energy price forecasting models hasof information about future energy prices, including most
Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex
Chapter 11 Forecasting breaks and forecasting during breaks
Success in accurately forecasting breaks requires that they are predictable from relevant information available at the forecast origin using an appropriate model form, which can be selected and estimated before the break. To clarify the roles of these six necessary conditions, we distinguish between the information set for �normal forces � and the one for �break drivers�, then outline sources of potential information. Relevant non-linear, dynamic models facing multiple breaks can have more candidate variables than observations, so we discuss automatic model selection. As a failure to accurately forecast breaks remains likely, we augment our strategy by modelling breaks during their progress, and consider robust forecasting devices.
Jennifer L. Castle; Nicholas W. P. Fawcett; David F. Hendry
Forecasting Uncertain Hotel Room Demand
Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...
Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister
Forecast Technical Document Growing Stock Volume
Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 Growing stock volume forecasts Background A forecast of standing volume (or
Issues in midterm analysis and forecasting 1998
Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.
This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.
Aviation forecasting and systems analyses
The 9 papers in this report deal with the following areas: method of allocating airport runway slots; method for forecasting general aviation activity; air traffic control network-planning model based on second-order Markov chains; analyzing ticket-choice decisions of air travelers; assessing the safety and risk of air traffic control systems: risk estimation from rare events; forecasts of aviation fuel consumption in Virginia; estimating the market share of international air carriers; forecasts of passenger and air-cargo activity at Logan International Airport; and forecasting method for general aviation aircraft and their activity.
Geisinger, K.E.; Brander, J.R.G.; Wilson, F.R.; Kohn, H.M.; Polhemus, N.W.
Studies of inflation and forecasting.
??This dissertation contains five research papers in the area of applied econometrics. The two broad themes of the research are inflation and forecasting. The first� (more)
Bermingham, Colin
UWIG Forecasting Workshop -- Albany (Presentation)
This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.
Lew, D.
Density Forecasting for Long-Term Peak Electricity Demand
Long-term electricity demand forecasting plays an important role in planning for future generation facilities and transmission augmentation. In a long-term context, planners must adopt a probabilistic view of potential peak demand levels. Therefore density forecasts (providing estimates of the full probability distributions of the possible future values of the demand) are more helpful than point forecasts, and are necessary for utilities to evaluate and hedge the financial risk accrued by demand variability and forecasting uncertainty. This paper proposes a new methodology to forecast the density of long-term peak electricity demand. Peak electricity demand in a given season is subject to a range of uncertainties, including underlying population growth, changing technology, economic conditions, prevailing weather conditions (and the timing of those conditions), as well as the general randomness inherent in individual usage. It is also subject to some known calendar effects due to the time of day, day of week, time of year, and public holidays. A comprehensive forecasting solution is described in this paper. First, semi-parametric additive models are used to estimate the relationships between demand and the driver variables, including temperatures, calendar effects and some demographic and economic variables. Then the demand distributions are forecasted by using a mixture of temperature simulation, assumed future economic scenarios, and residual bootstrapping. The temperature simulation is implemented through a new seasonal bootstrapping method with variable blocks. The proposed methodology has been used to forecast the probability distribution of annual and weekly peak electricity demand for South Australia since 2007. The performance of the methodology is evaluated by comparing the forecast results with the actual demand of the summer 2007�2008.
Rob J. Hyndman; Shu Fan
A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty
This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.
Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.
Lagged Ensembles, Forecast Configuration, and Seasonal Predictions
An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...
Mingyue Chen; Wanqiu Wang; Arun Kumar
Probabilistic Verification of Monthly Temperature Forecasts
Monthly forecasting bridges the gap between medium-range weather forecasting and seasonal predictions. While such forecasts in the prediction range of 1�4 weeks are vital to many applications in the context of weather and climate risk management, ...
Andreas P. Weigel; Daniel Baggenstos; Mark A. Liniger; Fr�d�ric Vitart; Christof Appenzeller
CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad
CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare
A Forecast for the California Labor Market
issue for the state. A Forecast for the California Laborto Go? � The UCLA Anderson Forecast for the Nation andAngeles: UCLA Anderson Forecast: Nation 1.1 � 1.9. Dhawan,
Mitchell, Daniel J. B.
CALIFORNIA ENERGY COMMISSION STAFF FORECAST OF 2007 PEAK DEMAND STAFFREPORT June 2006 CEC-400.................................................................................. 9 Sources of Forecast Error....................................................................... .................11 Tables Table 1: Revised versus September 2005 Peak Demand Forecast ......................... 2
Operational Forecaster Uncertainty Needs and Future Roles
Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are ...
David R. Novak; David R. Bright; Michael J. Brennan
Calibration of Probabilistic Forecasts of Binary Events
Probabilistic forecasts of atmospheric variables are often given as relative frequencies obtained from ensembles of deterministic forecasts. The detrimental effects of imperfect models and initial conditions on the quality of such forecasts can ...
Cristina Primo; Christopher A. T. Ferro; Ian T. Jolliffe; David B. Stephenson
1 CORPORATE GOVERNANCE AND MANAGEMENT EARNINGS FORECAST QUALITY: EVIDENCE FROM FRENCH IPOS Anis attributes, ownership retained, auditor quality, and underwriter reputation and management earnings forecast quality measured by management earnings forecast accuracy and bias. Using 117 French IPOs, we find
Forecasting women's apparel sales using mathematical
Forecasting women's apparel sales using mathematical modeling Celia Frank and Ashish Garg, USA Les Sztandera Philadelphia University, Philadelphia, PA, USA Keywords Apparel, Forecasting average (MA), auto- regression (AR), or combinations of them are used for forecasting sales. Since
Raheja, Amar
On the Prediction of Forecast Skill
Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The first, giving the consistency between adjacent forecasts, ...
T. N. Palmer; S. Tibaldi
Equitable Skill Scores for Categorical Forecasts
Many skill scores used to evaluate categorical forecasts of discrete variables are inequitable, in the sense that constant forecasts of some events lead to better scores than constant forecasts of other events. Inequitable skill scores may ...
Lev S. Gandin; Allan H. Murphy
Forecasting Electric Vehicle Costs with Experience Curves
April, 5. R 2~1. Dino. "Forecasting the Price Evolution of 1ElectromcProducts," Ioumal of Forecasting, �oL4, No I, 1985.costs and a set of forecasting tools that can be refined as
Lipman, Timonthy E.; Sperling, Daniel
Calibration of Probabilistic Quantitative Precipitation Forecasts
From 1 August 1990 to 31 July 1995, the Weather Service Forecast Office in Pittsburgh prepared 6159 probabilistic quantitative precipitation forecasts. Forecasts were made twice a day for 24-h periods beginning at 0000 and 1200 UTC for two river ...
Roman Krzysztofowicz; Ashley A. Sigrest
Evaluating Probabilistic Forecasts Using Information Theory
The problem of assessing the quality of an operational forecasting system that produces probabilistic forecasts is addressed using information theory. A measure of the quality of the forecasting scheme, based on the amount of a data compression ...
Mark S. Roulston; Leonard A. Smith
Diagnosing Forecast Errors in Tropical Cyclone Motion
This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend ...
Thomas J. Galarneau Jr.; Christopher A. Davis
Improving Forecast Communication: Linguistic and Cultural Considerations
One goal of weather and climate forecasting is to inform decision making. Effective communication of forecasts to various sectors of the public is essential for meeting that goal, yet studies repeatedly show that forecasts are not well understood ...
Karen Pennesi
Ensemble Cloud Model Applications to Forecasting Thunderstorms
A cloud model ensemble forecasting approach is developed to create forecasts that describe the range and distribution of thunderstorm lifetimes that may be expected to occur on a particular day. Such forecasts are crucial for anticipating severe ...
Kimberly L. Elmore; David J. Stensrud; Kenneth C. Crawford
Evaluation of errors in national energy forecasts.
??Energy forecasts are widely used by the U.S. government, politicians, think tanks, and utility companies. While short-term forecasts were reasonably accurate, medium and long-range forecasts� (more)
Sakva, Denys
What Is the True Value of Forecasts?
Understanding the economic value of weather and climate forecasts is of tremendous practical importance. Traditional models that have attempted to gauge forecast value have focused on a best-case scenario, in which forecast users are assumed to ...
Whither the Weather Analysis and Forecasting Process?
An argument is made that if human forecasters are to continue to maintain a skill advantage over steadily improving model and guidance forecasts, then ways have to be found to prevent the deterioration of forecaster skills through disuse. The ...
Lance F. Bosart
An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2) is presented. The focus of the analysis is on the construction of lagged ensemble forecasts ...
Virtual Floe Ice Drift Forecast Model Intercomparison
Both sea ice forecast models and methods to measure their skill are needed for operational sea ice forecasting. Two simple sea ice models are described and tested here. Four different measures of skill are also tested. The forecasts from the ...
Robert W. Grumbine
We validated one year of Global Forecast System (GFS) predictions of surface meteorological variables (wind speed, air temperature, dewpoint temperature, air pressure) over the entire planet for forecasts extending from zero hours into the future (an analysis) to 36 hours. Approximately 12,000 surface stations world-wide were included in this analysis. Root-Mean-Square- Errors (RMSE) increased as the forecast period increased from zero to 36 hours, but the initial RMSE were almost as large as the 36 hour forecast RMSE for all variables. Typical RMSE were 3 C for air temperature, 2-3mb for sea-level pressure, 3.5 C for dewpoint temperature and 2.5 m/s for wind speed. Approximately 20-40% of the GFS errors can be attributed to a lack of resolution of local features. We attribute the large initial RMSE for the zero hour forecasts to the inability of the GFS to resolve local terrain features that often dominate local weather conditions, e.g., mountain- valley circulations and sea and land breezes. Since the horizontal resolution of the GFS (about 1{sup o} of latitude and longitude) prevents it from simulating these locally-driven circulations, its performance will not improve until model resolution increases by a factor of 10 or more (from about 100 km to less than 10 km). Since this will not happen in the near future, an alternative for the near term to improve surface weather analyses and predictions for specific points in space and time would be implementation of a high-resolution, limited-area mesoscale atmospheric prediction model in regions of interest.
Werth, D.; Garrett, A.
The evolution of consensus in macroeconomic forecasting
When professional forecasters repeatedly forecast macroeconomic variables, their forecasts may converge over time towards a consensus. The evolution of consensus is analyzed with Blue Chip data under a parametric polynomial decay function that permits flexibility in the decay path. For the most part, this specification fits the data. We test whether forecast differences decay to zero at the same point in time for a panel of forecasters, and discuss possible explanations for this, along with its implications for studies using panels of forecasters.
Allan W. Gregory; James Yetman; Jel Codes C E; Robert Eggert; Fred Joutz
Improving Forecasting: A plea for historical retrospectives
Improving Forecasting: A plea for historical retrospectives Title Improving Forecasting: A plea for historical retrospectives Publication Type Journal Article Year of Publication...
Electricity price forecasting in a grid environment.
??Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. Market participants rely on price forecasts to decide their bidding strategies, allocate� (more)
Li, Guang, 1974-
Background pollution forecast over bulgaria
Both, the current level of air pollution studies and social needs in the country, are in a stage mature enough for creating Bulgarian Chemical Weather Forecasting and Information System The system is foreseen to provide in real time forecast of the spatial/temporal ...
D. Syrakov; K. Ganev; M. Prodanova; N. Miloshev; G. Jordanov; E. Katragkou; D. Melas; A. Poupkou; K. Markakis
Frequency Dependence in Forecast Skill
A method is proposed to calculate measures of forecast skill for high, medium and low temporal frequency variations in the atmosphere. This method is applied to a series of 128 consecutive 1 to 10-day forecasts produced at NMC with their ...
H. M. van Den Dool; Suranjana Saha
Radiation fog forecasting using a 1-dimensional model
The importance of fog forecasting to the aviation community, to road transportation and to the public at large is irrefutable. The deadliest aviation accident in history was in fact partly a result of fog back on 27 March 1977. This has, along with numerous less dramatic examples, helped focus many meteorological efforts into trying to forecast this phenomenon as accurately as possible. Until recently, methods of fog forecasting have relied primarily on the forecaster's ability to recognize surface weather patterns known to be favorable for producing fog and once it has formed, to state that it will persist unless the pattern changes. Unfortunately, while such methods have shown some success, many times they have led weather forecasters astray with regards to the onset and dissipation of the phenomenon. Fortunately, now with computers becoming ever-increasingly powerful, numerical models have been utilized to attempt to more accurately deal with the fog forecasting problem. This study uses a 1 dimensional model called COBEL to simulate several past fog cases in the hopes of mimicking its actual occurrence and determining what weather parameters the fog is most sensitive to. The goal is to create a technique where the weather forecaster will be able to run several fog forecasts with the model each time with different initial conditions representing the uncertain weather conditions. In this way, the forecaster will be able to use his expertise to choose the most likely scenario. Results indicate that COBEL is able to simulate the fog cases quite well. Issues remain with the model's handling of the gravitational settling rate, the fact that it currently does not include any vegetation, and its coupling process with the soil model. Nevertheless, simulations and sensitivity tests indicate that soil temperature, soil moisture, low-level winds, initial relative humidity, dew deposition and surface emissivity are the weather parameters that affect fog the most. These parameters will be prime candidates for the 1 dimensional ensemble (ODEP) technique described above.
Peyraud, Lionel
Ensemble-Based Exigent Analysis. Part I: Estimating Worst-Case Weather-Related Forecast Damage Scenarios
Exigent analysis supplements an ensemble forecast of weather-related damage with a map of the worst-case scenario (WCS), a multivariate confidence bound of the damage. For multivariate Gaussian ensembles, ensemble-based exigent analysis uses a ...
Daniel Gombos; Ross N. Hoffman
Title of Paper Annual Energy Outlook Forecast Evaluation Title of Paper Annual Energy Outlook Forecast Evaluation by Susan H. Holte OIAF has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: Natural gas has generally been the fuel with the least accurate forecasts of consumption, production, and prices. Natural gas was the last fossil fuel to be deregulated following the strong regulation of energy markets in the 1970s and early 1980s. Even after deregulation, the behavior
Regional Maps
Annual Energy Outlook 2012 (EIA)
United States Census Divisions Figure 2.Electricity Market Module (EMM)Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting Figure...
Development and testing of improved statistical wind power forecasting methods.
DOE Green Energy (OSTI)
Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.
Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)
Short-Termed Integrated Forecasting System: 1993 Model documentation report
The purpose of this report is to define the Short-Term Integrated Forecasting System (STIFS) and describe its basic properties. The Energy Information Administration (EIA) of the US Energy Department (DOE) developed the STIFS model to generate short-term (up to 8 quarters), monthly forecasts of US supplies, demands, imports exports, stocks, and prices of various forms of energy. The models that constitute STIFS generate forecasts for a wide range of possible scenarios, including the following ones done routinely on a quarterly basis: A base (mid) world oil price and medium economic growth. A low world oil price and high economic growth. A high world oil price and low economic growth. This report is written for persons who want to know how short-term energy markets forecasts are produced by EIA. The report is intended as a reference document for model analysts, users, and the public.
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Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast
Forecast Introduction................................................................... 16 The Base Case Forecast..................................................................... 16 Base Case Price Forecast
Comparison of Ensemble Kalman Filter�Based Forecasts to Traditional Ensemble and Deterministic Forecasts for a Case Study of Banded Snow
The ensemble Kalman filter (EnKF) technique is compared to other modeling approaches for a case study of banded snow. The forecasts include a 12- and 3-km grid-spaced deterministic forecast (D12 and D3), a 12-km 30-member ensemble (E12), and a 12-...
Astrid Suarez; Heather Dawn Reeves; Dustan Wheatley; Michael Coniglio
Quantitative Precipitation Forecast Techniques for Use in Hydrologic Forecasting
Quantitative hydrologic forecasting usually requires knowledge of the spatial and temporal distribution of precipitation. First, it is important to accurately measure the precipitation falling over a particular watershed of interest. Second, ...
Konstantine P. Georgakakos; Michael D. Hudlow
Bayesian Study and Naturalness in MSSM Forecast for the LHC
We perform a forecast of the CMSSM for the LHC based in an improved Bayesian analysis taking into account the present theoretical and experimental wisdom about the model. In this way we obtain a map of the preferred regions of the CMSSM parameter space and show that fine-tuning penalization arises from the Bayesian analysis itself when the experimental value of Mz is considered. The results are remarkable stable when using different priors
Maria Eugenia Cabrera
Load Forecast For use in Resource Adequacy
Load Forecast 2019 For use in Resource Adequacy Massoud Jourabchi #12;In today's presentation d l Load forecast methodology Drivers of the forecast f i Treatment of conservation Incorporating impact of weather Forecast for 2019 #12;Regional Loads (MWA and MW)Regional Loads (MWA and MW
Forecast Technical Document Felling and Removals
Forecast Technical Document Felling and Removals Forecasts A document describing how volume fellings and removals are handled in the 2011 Production Forecast system. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 Felling and removals forecasts Background A fellings and removals
CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia
Combining forecast weights: Why and how?
This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions
Yip Chee Yin; Ng Kok-Haur; Lim Hock-Eam
PROBLEMS OF FORECAST1 Dmitry KUCHARAVY
1 PROBLEMS OF FORECAST1 Dmitry KUCHARAVY email@example.com Roland DE GUIO roland for the purpose of Innovative Design. First, a brief analysis of problems for existing forecasting methods of the forecast errors. Second, using a contradiction analysis, a set of problems related to technology forecast
Using reforecasts for probabilistic forecast calibration
1 Using reforecasts for probabilistic forecast calibration Tom Hamill NOAA Earth System Research that is currently operational. #12;3 Why compute reforecasts? · For many forecast problems, such as long-lead forecasts or high-precipitation events, a few past forecasts may be insufficient for calibrating
Assessing Forecast Accuracy Measures Department of Economics
Assessing Forecast Accuracy Measures Zhuo Chen Department of Economics Heady Hall 260 Iowa State forecast accuracy measures. In the theoretical direction, for comparing two forecasters, only when the errors are stochastically ordered, the ranking of the forecasts is basically independent of the form
Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model
1 1 Current status of ForecastCurrent status of Forecast 2005 EPACT is in the model 2007 Federal prices are being inputted into the model 2 Sales forecast Select yearsSales forecast Select years --Draft 0.53% Irrigation 2.76% Annual Growth Rates Preliminary Electricity ForecastAnnual Growth Rates
Can earnings forecasts be improved by taking into account the forecast bias?
Can earnings forecasts be improved by taking into account the forecast bias? François DOSSOU allow the calculation of earnings adjusted forecasts, for horizons from 1 to 24 months. We explain variables. From the forecast evaluation statistics viewpoints, the adjusted forecasts make it possible quasi
Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model
An important determinant of our energy future is the rate at which energy conservation technologies, once developed, are put into use. At Synergic Resources Corporation, we have adapted and applied a methodology to forecast the use of conservation technologies. This paper briefly discusses the observed patterns of the diffusion of new' technologies and the determinants (both sociological and economic) which have been proposed to explain the variation in the diffusion rates. Existing market penetration models are reviewed and their capability to forecast the use of conservation technologies is assessed using a set of criteria developed for this purpose. The reasoning behind the choice of criteria is discussed. The criteria includes the range of hypothesized influences to market penetration that are incorporated into the models and the applicability of the available parameter estimates. The attributes of our methodology and forecasting model choice (a behavioral lag equation developed by Mathtech, Inc.), are displayed using a list of the judgment criteria. This method was used to forecast the use of electricity conservation technologies in industries located in the Pacific Northwest for the Bonneville Power Administration.
Lang, K.
Application of DSM evaluation studies to utility forecasting and planning
Utilities and their customers have made substantial investments in utility demand-side management (DSM) programs. These DSM programs also represent a substantial electricity resource. DSM program performance has been studied more systematically in recent years than over any previous period. DSM program evaluations are traditionally targeted to meet the program manager`s need for information on program costs and performance and, more recently, to verify savings to regulators for incentive awards and lost revenue recovery. Yet evaluations may also be used to produce results relevant to utility forecasting and planning. Applying evaluation results is especially important for utilities with substantial current and future commitments to acquiring demand-side resources. This report discusses the application of evaluation results to utility forecasting and planning. The report has three objectives. First, we identify what demand forecasters, DSM forecasters, and resource planners want to learn from evaluations. Second, we identify and describe the major obstacles and problems associated with applying evaluation results and illustrate many of these issues through a specific evaluation application exercise. Finally, we suggest approaches for addressing these major problems. The report summarizes results from interviews with utilities, regulators, and consultants to determine how the industry currently applies evaluation results in forecasting and planning. The report also includes results from case studies of Sacramento Municipal Utility District and Southern California Edison Company, utilities with large DSM programs and active evaluation efforts. Finally, we draw on a specific application exercise in which we used a set of impact evaluations to revise a utility DSM forecast.
Baxter, L.W.
Downscaling Extended Weather Forecasts for Hydrologic Prediction
Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.
Leung, Lai-Yung R.; Qian, Yun
Sampling Errors in Seasonal Forecasting
The limited numbers of start dates and ensemble sizes in seasonal forecasts lead to sampling errors in predictions. Defining the magnitude of these sampling errors would be useful for end users as well as informing decisions on resource ...
Stephen Cusack; Alberto Arribas
Scoring Rules for Forecast Verification
The problem of probabilistic forecast verification is approached from a theoretical point of view starting from three basic desiderata: additivity, exclusive dependence on physical observations (�locality�), and strictly proper behavior. By ...
Riccardo Benedetti
Wavelets and Field Forecast Verification
Current field forecast verification measures are inadequate, primarily because they compress the comparison between two complex spatial field processes into one number. Discrete wavelet transforms (DWTs) applied to analysis and contemporaneous ...
William M. Briggs; Richard A. Levine
Value of Wind Power Forecasting
This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.
Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.
Richardson's Barotropic Forecast: A Reappraisal
To elucidate his numerical technique and to examine the effectiveness of geostrophic initial winds, Lewis Fry Richardson carried out an idealized forecast using the linear shallow-water equations and simple analytical pressure and velocity ...
Peter Lynch
Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts
An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near�real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from ...
Charles R. Sampson; Paul A. Wittmann; Efren A. Serra; Hendrik L. Tolman; Jessica Schauer; Timothy Marchok
Weather forecasting : the next generation : the potential use and implementation of ensemble forecasting
This thesis discusses ensemble forecasting, a promising new weather forecasting technique, from various viewpoints relating not only to its meteorological aspects but also to its user and policy aspects. Ensemble forecasting ...
Goto, Susumu
Ability to Forecast Regional Soil Moisture with a Distributed Hydrological Model Using ECMWF Rainfall Forecasts
This study mimics an online forecast system to provide nine day-ahead forecasts of regional soil moisture. It uses modified ensemble rainfall forecasts from the numerical weather prediction model of the European Centre for Medium-Range Weather ...
J. M. Schuurmans; M. F. P. Bierkens
Spatial Structure, Forecast Errors, and Predictability of the South Asian Monsoon in CFS Monthly Retrospective Forecasts
The spatial structure of the boreal summer South Asian monsoon in the ensemble mean of monthly retrospective forecasts by the Climate Forecast System of the National Centers for Environmental Prediction is examined. The forecast errors and ...
Hae-Kyung Lee Drbohlav; V. Krishnamurthy
What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting
Differences of opinion exist among forecasters�and between forecasters and users�regarding the meaning of the phrase �good (bad) weather forecasts.� These differences of opinion are fueled by a lack of clarity and/or understanding concerning the ...
Allan H. Murphy
The Potential Impact of Using Persistence as a Reference Forecast on Perceived Forecast Skill
Skill is defined as actual forecast performance relative to the performance of a reference forecast. It is shown that the choice of reference (e.g., random or persistence) can affect the perceived performance of the forecast system. Two scores, ...
Marion P. Mittermaier
Quantification of Uncertainity in Fire-Weather Forecasts: Some Results of Operational and Experimental Forecasting Programs
Fire-weather forecasts (FWFs) prepared by National Weather Service (NWS) forecasters on an operational basis are traditionally expressed in categorical terms. However, to make rational and optimal use of such forecasts, fire managers need ...
Barbara G. Brown; Allan H. Murphy
The Complex Relationship between Forecast Skill and Forecast Value: A Real-World Analysis
For routine forecasts of temperature and precipitation, the relative skill advantage of human forecasters with respect to the numerical�statistical guidance is small (and diminishing). Since the relationship between forecast skill and the value ...
Paul J. Roebber; Lance F. Bosart
Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012
AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.
Pennock, K.
Light truck forecasts
The recent dramatic increase in the number of light trucks (109% between 1963 and 1974) has prompted concern about the energy consequences of the growing popularity of the light truck. An estimate of the future number of light trucks is considered to be a reasonable first step in assessing the energy impact of these vehicles. The monograph contains forecasts based on two models and six scenarios. The coefficients for the models have been derived by ordinary least squares regression of national level time series data. The first model is a two stage model. The first stage estimates the number of light trucks and cars (together), and the second stage applies a share's submodel to determine the number of light trucks. The second model is a simultaneous equation model. The two models track one another remarkably well, within about 2%. The scenarios were chosen to be consistent with those used in the Lindsey-Kaufman study Projection of Light Truck Population to Year 2025. Except in the case of the most dismal economic scenario, the number of light trucks is expected to increase from the 1974 level of 0.09 light truck per person to about 0.12 light truck per person in 1995.
Liepins, G.E.
Annual Energy Outlook Forecast Evaluation-Table 1
Annual Energy Outlook Forecast Evaluation > Table 1 Annual Energy Outlook Forecast Evaluation Table 1. Comparison of Absolute Percent Errors for AEO Forecast Evaluation, 1996 to...
CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts
Forecasting new product penetration with flexible substitution patterns
choice model for forecasting demand for alternative-fuel7511, Urban Travel Demand Forecasting Project, Institute of89 (1999) 109�129 Forecasting new product penetration with ?
Brownstone, David; Train, Kenneth
Overestimation Reduction in Forecasting Telecommuting as a TDM Policy
M. , Ethics and advocacy in forecasting for public policy.change and social forecasting: the case of telecommuting asOverestimation Reduction in Forecasting Telecommuting as a
Tal, Gil
Forecasting US CO2 Emissions Using State-Level Data
F. Hendry (eds), Economic Forecasting, Blackwell Publishing,W. : 2002, Macroeconomic forecasting using di?usion indexes,2003, Macroeconomic forecasting in the euro area: Country
Steinhauser, Ralf; Auffhammer, Maximilian
NoVaS Transformations: Flexible Inference for Volatility Forecasting
and Correlation Forecasting� in G. Elliott, C.W.J.Handbook of Economic Forecasting, Amsterdam: North-Holland,Transformations�, forthcoming in Forecasting in the Presence
Politis, Dimitris N; Thomakos, Dimitrios D
7511, Urban Travel Demand Forecasting Project, Institute ofchoice model for forecasting demand for alternative-fuel89 (1999) 109�129 Forecasting new product penetration with
Earthquake Forecasting in Diverse Tectonic Zones of the Globe
Long-term probabilistic forecasting of earthquakes, J.2000), Probabilistic forecasting of earthquakes, Geophys. J.F.F. (2006), The EEPAS forecasting model and the probability
Kagan, Y. Y.; Jackson, D. D.
Ensemble-based methods for forecasting census in hospital units
P, Fitzgerald G: Regression forecasting of patient admissionapproach to modeling and forecasting demand in the emergencySJ, Haug PJ, Snow GL: Forecasting daily patient volumes in
Koestler, Devin C; Ombao, Hernando; Bender, Jesse
Forecasting Danerous Inmate Misconduct: An Applications of Ensemble Statistical Procedures
costs could alter forecasting skill and the predictors thatForecasting Dangerous Inmate Misconduct: An Applications ofOn-Line Working Paper Series Forecasting Dangerous Inmate
Berk, Richard A.; Kriegler, Brian; Baek, John-Ho
Developing a Practical Forecasting Screener for Domestic Violence Incidents
Developing a Practical Forecasting Screener for Domesticcomplicated did not improve forecasting skill. Taking thethe local costs of forecasting errors. It is also feasible
Richard A. Berk; Susan B. Sorenson; Yan He
Forecasting with Dynamic Microsimulation: Design, Implementation, and Demonstration
Goulias Page 84 Forecasting with Dynamic Microsimulation:Goulias Page 80 Forecasting with Dynamic Microsimulation:L. Demographic Forecasting with a Dynamic Stochastic
Ravulaparthy, Srinath; Goulias, Konstadinos G.
Base Resource Forecasts - Power Marketing - Sierra Nevada Region...
Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...
Technology data characterizing space conditioning in commercial buildings: Application to end-use forecasting with COMMEND 4.0
In the US, energy consumption is increasing most rapidly in the commercial sector. Consequently, the commercial sector is becoming an increasingly important target for state and federal energy policies and also for utility-sponsored demand side management (DSM) programs. The rapid growth in commercial-sector energy consumption also makes it important for analysts working on energy policy and DSM issues to have access to energy end-use forecasting models that include more detailed representations of energy-using technologies in the commercial sector. These new forecasting models disaggregate energy consumption not only by fuel type, end use, and building type, but also by specific technology. The disaggregation of space conditioning end uses in terms of specific technologies is complicated by several factors. First, the number of configurations of heating, ventilating, and air conditioning (HVAC) systems and heating and cooling plants is very large. Second, the properties of the building envelope are an integral part of a building`s HVAC energy consumption characteristics. Third, the characteristics of commercial buildings vary greatly by building type. The Electric Power Research Institute`s (EPRI`s) Commercial End-Use Planning System (COMMEND 4.0) and the associated data development presented in this report attempt to address the above complications and create a consistent forecasting framework. This report describes the process by which the authors collected space-conditioning technology data and then mapped it into the COMMEND 4.0 input format. The data are also generally applicable to other end-use forecasting frameworks for the commercial sector.
Sezgen, O.; Franconi, E.M.; Koomey, J.G.; Greenberg, S.E.; Afzal, A.; Shown, L.
Impact of a New Radiation Package, McRad, in the ECMWF Integrated Forecasting System
A new radiation package, �McRad,� has become operational with cycle 32R2 of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). McRad includes an improved description of the land surface ...
J-J. Morcrette; H. W. Barker; J. N. S. Cole; M. J. Iacono; R. Pincus
Current Forecast for Sunspot Cycle 24 Parameters
Our prediction for the development of sunspot cycle 23 activity came true; one of the very few to have attained this status. We use the 3?cycle quasi?periodicity observed in the planetary index Ap. We improve our method by including data for 150 years and draw inferences as to what to expect for the development phase of cycle 24. Our forecast for the smoothed sunspot number at cycle 24 peak 78�5 in June 2013; the possibility that next three cycles may be progressively less active cannot be ruled out; the trend may possibly continue for the rest of the 21st century.
H. S. Ahluwalia; R. C. Ygbuhay
Solar Energy Market Forecast | Open Energy Information
Solar Energy Market Forecast Solar Energy Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast Agency/Company /Organization: United States Department of Energy Sector: Energy Focus Area: Solar Topics: Market analysis, Technology characterizations Resource Type: Publications Website: giffords.house.gov/DOE%20Perspective%20on%20Solar%20Market%20Evolution References: Solar Energy Market Forecast[1] Summary " Energy markets / forecasts DOE Solar America Initiative overview Capital market investments in solar Solar photovoltaic (PV) sector overview PV prices and costs PV market evolution Market evolution considerations Balance of system costs Silicon 'normalization' Solar system value drivers Solar market forecast Additional resources"
Comparison of Energy Information Administration and Bonneville Power Administration load forecasts
Comparisons of the modeling methodologies underlying the project Independence Evaluation System (PIES) and the Bonneville Power Administration forecasts are discussed in this paper. This Technical Memorandum is presented in order to reconcile apparent inconsistencies between the forecasts. These represent different purposes for the modeling effort as well as different forecasts. Nonetheless, both are appropriate within the context that they are intended. The BPA forecasts are site-specific, detailed, micro-level, yearly forecasts of the demand for electricity. PIES develops regional, macro forecasts and does not contain estimates of the timing of the completion of plants within the period of the forecast. The BPA forecast is intended to be utilized in analyzing a sub-regional capacity expansion program. PIES is a regional energy market-clearing, non-normative model which allows different scenarios to be compared by changing input variables. Clearly, both forecasts are dependent upon the accuracy of the assumptions and input variables included. However, the differing levels of aggregation and objectives require different types of input variables.
Reed, H.J.
Using Customers' Reported Forecasts to Predict Future Sales
Using Customers' Reported Forecasts to Predict Future Sales Nihat Altintas , Alan Montgomery orders using forecasts provided by their customers. Our goal is to improve the supplier's operations through a better un- derstanding of the customers's forecast behavior. Unfortunately, customer forecasts
Murphy, Robert F.
Short-Range Ensemble Forecasts of Precipitation Type
Short-range ensemble forecasting is extended to a critical winter weather problem: forecasting precipitation type. Forecast soundings from the operational NCEP Short-Range Ensemble Forecast system are combined with five precipitation-type ...
Matthew S. Wandishin; Michael E. Baldwin; Steven L. Mullen; John V. Cortinas Jr.
A Review of Numerical Forecast Guidance for Hurricane Hugo
Numerical forecast guidance for Hurricane Hugo from the National Meteorological Center is examined, as well as forecasts from the European Center for Medium Range Forecasting and the United Kingdom Meteorological Office. No one forecast product ...
John H. Ward
Summary Verification Measures and Their Interpretation for Ensemble Forecasts
Ensemble prediction systems produce forecasts that represent the probability distribution of a continuous forecast variable. Most often, the verification problem is simplified by transforming the ensemble forecast into probability forecasts for ...
A. Allen Bradley; Stuart S. Schwartz
by by Esmeralda Sanchez The Office of Integrated Analysis and Forecasting has been providing an evaluation of the forecasts in the Annual Energy Outlook (AEO) annually since 1996. Each year, the forecast evaluation expands on that of the prior year by adding the most recent AEO and the most recent historical year of data. However, the underlying reasons for deviations between the projections and realized history tend to be the same from one evaluation to the next. The most significant conclusions are: * Over the last two decades, there have been many significant changes in laws, policies, and regulations that could not have been anticipated and were not assumed in the projections prior to their implementation. Many of these actions have had significant impacts on energy supply, demand, and prices; however, the
3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information
TIER Environmental Forecast Group Inc 3TIER TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name 3TIER Environmental Forecast Group Inc (3TIER) Place Seattle, Washington Zip 98121 Sector Renewable Energy Product Seattle-based, renewable energy assessment and forecasting company. Coordinates 47.60356°, -122.329439° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":47.60356,"lon":-122.329439,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}
Management of supply chain: an alternative modelling technique for forecasting
Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view
Datta, Shoumen
Local Forecast Communication In The Altiplano
Forecasts play an important role in planting decisions for Andean peasant producers. Predictions of the upcoming cropping season determine when, where, and what farmers will plant. This research looks at the sources of forecast information used ...
Jere L. Gilles; Corinne Valdivia
Economic and Statistical Measures of Forecast Accuracy
This paper argues in favour of a closer link between decision and forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued...
Granger, Clive W J; Pesaran, M Hashem
2013 Midyear Economic Forecast Sponsorship Opportunity
2013 Midyear Economic Forecast Sponsorship Opportunity Thursday, April 18, 2013, Hyatt Regency Irvine 11:30 a.m. 1:30 p.m. Dr. Anil Puri presents his annual Midyear Economic Forecast addressing
de Lijser, Peter
Forecasting consumer products using prediction markets
Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction ...
Trepte, Kai
Probabilistic Visibility Forecasting Using Bayesian Model Averaging
Bayesian model averaging (BMA) is a statistical postprocessing technique that has been used in probabilistic weather forecasting to calibrate forecast ensembles and generate predictive probability density functions (PDFs) for weather quantities. ...
Richard M. Chmielecki; Adrian E. Raftery
Intercomparison of Spatial Forecast Verification Methods
Advancements in weather forecast models and their enhanced resolution have led to substantially improved and more realistic-appearing forecasts for some variables. However, traditional verification scores often indicate poor performance because ...
Eric Gilleland; David Ahijevych; Barbara G. Brown; Barbara Casati; Elizabeth E. Ebert
Forecasting with Reference to a Specific Climatology
Seasonal forecasts are most commonly issued as anomalies with respect to some multiyear reference period. However, different seasonal forecasting centers use different reference periods. This paper shows that for near-surface temperature, ...
Emily Wallace; Alberto Arribas
The Automated Tropical Cyclone Forecasting System (ATCF)
The U.S. Navy Automated Tropical Cyclone Forecasting System (ATCF) is an IBM-AT compatible software package developed for the Joint Typhoon Warning Center (JTWC), Guam. ATCF is designed to assist forecasters with the process of making tropical ...
Ronald J. Miller; Ann J. Schrader; Charles R. Sampson; Ted L. Tsui
Probabilistic Quantitative Precipitation Forecasts for River Basins
A methodology has been formulated to aid a field forecaster in preparing probabilistic quantitative precipitation forecasts (QPFs) for river basins. The format of probabilistic QPF is designed to meet three requirements: (i) it is compatible with ...
Roman Krzysztofowicz; William J. Drzal; Theresa Rossi Drake; James C. Weyman; Louis A. Giordano
A General Framework for Forecast Verification
A general framework for forecast verification based on the joint distribution of forecasts and observations is described. For further elaboration of the framework, two factorizations of the joint distribution are investigated: 1) the calibration-...
Allan H. Murphy; Robert L. Winkler
Antarctic Satellite Meteorology: Applications for Weather Forecasting
For over 30 years, weather forecasting for the Antarctic continent and adjacent Southern Ocean has relied on weather satellites. Significant advancements in forecasting skill have come via the weather satellite. The advent of the high-resolution ...
Matthew A. Lazzara; Linda M. Keller; Charles R. Stearns; Jonathan E. Thom; George A. Weidner
Forecaster Workstation Design: Concepts and Issues
Some basic ideas about designing a meteorological workstation for operational weather forecasting are presented, in part as a complement to the recently published discussion of workstation design by R. R. Hoffman. Scientific weather forecasting ...
Charles A. Doswell III
Bayesian Model Verification of NWP Ensemble Forecasts
Forecasts of convective precipitation have large uncertainties. To consider the forecast uncertainties of convection-permitting models, a convection-permitting ensemble prediction system (EPS) based on the Consortium for Small-scale Modeling (...
Andreas R�pnack; Andreas Hense; Christoph Gebhardt; Detlev Majewski
Value from Ambiguity in Ensemble Forecasts
This study explores the objective application of ambiguity information, that is, the uncertainty in forecast probability derived from an ensemble. One application approach, called uncertainty folding, merges ambiguity with forecast uncertainty ...
Mark S. Allen; F. Anthony Eckel
Evaluation of LFM-2 Quantitative Precipitation Forecasts
The results of a near real time experiment designed to assess the state of the art of quantitative precipitation forecasting skill of the operational NMC LFM-2 are described. All available LFM-2 quantitative precipitation forecasts were verified ...
Application of Forecast Verification Science to Operational River Forecasting in the U.S. National Weather Service
Forecast verification in operational hydrology has been very limited to date, mainly due to the complexity of verifying both forcing input forecasts and hydrologic forecasts on multiple space�time scales. However, forecast verification needs to ...
Julie Demargne; Mary Mullusky; Kevin Werner; Thomas Adams; Scott Lindsey; Noreen Schwein; William Marosi; Edwin Welles
Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event
Meteorologists within the Forecast Branch (FB) of the National Meteorological Center (NMC) produce operational quantitative precipitation forecasts (QPFs). These manual forecasts are prepared utilizing various forecasting techniques, which are ...
Theodore W. Funk
Improving week two forecasts with multi-model re-forecast ensembles
Improving week two forecasts with multi-model re-forecast ensembles Jeffrey S. Whitaker and Xue Wei NOAA-CIRES Climate Diagnostics Center, Boulder, CO Fr´ed´eric Vitart Seasonal Forecasting Group, ECMWF dataset of ensemble 're-forecasts' from a single model can significantly improve the skill
Whitaker, Jeffrey S.
NREL: Energy Analysis - Energy Forecasting and Modeling Staff
Energy Forecasting and Modeling Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Geraly Amador Clayton Barrows Greg Brinkman Brian W Bush Stuart Cohen Carolyn Davidson Paul Denholm Victor Diakov Aron Dobos Easan Drury Kelly Eurek Janine Freeman Marissa Hummon Jennie Jorganson Jordan Macknick Trieu Mai David Mulcahy David Palchak Ben Sigrin Daniel Steinberg Patrick Sullivan Aaron Townsend Laura Vimmerstedt Andrew Weekley Owen Zinaman Photo of Clayton Barrows. Clayton Barrows Postdoctoral Researcher Areas of expertise Power system modeling Primary research interests Power and energy systems
A Rank Approach to Equity Forecast Construction
that are fit for their purpose; for example, returningaggregate county and sector forecasts that are consistent by construction....
Satchell, Stephen E; Wright, Stephen M
Forecasting for energy and chemical decision analysis
This paper focuses on uncertainty and bias in forecasts used for major energy and chemical investment decisions. Probability methods for characterizing uncertainty in the forecast are reviewed. Sources of forecasting bias are classified based on the results of relevant psychology research. Examples are drawn from the energy and chemical industry to illustrate the value of explicit characterization of uncertainty and reduction of bias in forecasts.
Cazalet, E.G.
NOAA'S Hurricane Intensity Forecasting Experiment: A Progress Report
An update of the progress achieved as part of the NOAA Intensity Forecasting Experiment (IFEX) is provided. Included is a brief summary of the noteworthy aircraft missions flown in the years since 2005, the first year IFEX flights occurred, as well as a ...
Robert Rogers; Sim Aberson; Altug Aksoy; Bachir Annane; Michael Black; Joseph Cione; Neal Dorst; Jason Dunion; John Gamache; Stan Goldenberg; Sundararaman Gopalakrishnan; John Kaplan; Bradley Klotz; Sylvie Lorsolo; Frank Marks; Shirley Murillo; Mark Powell; Paul Reasor; Kathryn Sellwood; Eric Uhlhorn; Tomislava Vukicevic; Jun Zhang; Xuejin Zhang
Voluntary Green Power Market Forecast through 2015
Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.
Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.
CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad
CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped
REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare
REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped
Load forecast and treatment of conservation
Load forecast and treatment of conservation July 28th 2010 Resource Adequacy Technical Committee conservation is implicitly incorporated in the short-term demand forecast? #12;3 Incorporating conservation in the short-term model Our short-term model is an econometric model which can not explicitly forecast
CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs
CALIFORNIA ENERGY COMMISSION STAFF FORECAST: AVERAGE RETAIL ELECTRICITY PRICES 2005 TO 2018 report, Staff Forecast: Retail Electricity Prices, 2005 to 2018, was prepared with contributions from the technical assistance provided by Greg Broeking of R.W. Beck, Inc. in preparing retail price forecasts
Blue Chip Consensus US GDP Forecast
and metro area from Moody�s Economy.com Equivalent to US-level Gross Domestic Product ? The GMP forecasts have a large impact on the peak load forecasts Rule of thumb: 1 % growth in RTO GMP ? approx. 1,000 MW growth in forecast RTO peak load
James F. Wilson
5, 183218, 2008 A rainfall forecast
HESSD 5, 183218, 2008 A rainfall forecast model using Artificial Neural Network N. Q. Hung et al An artificial neural network model for rainfall forecasting in Bangkok, Thailand N. Q. Hung, M. S. Babel, S Geosciences Union. 183 #12;HESSD 5, 183218, 2008 A rainfall forecast model using Artificial Neural Network N
System Demonstration Multilingual Weather Forecast Generation System
System Demonstration Multilingual Weather Forecast Generation System Tianfang Yao DongmoZhang Qian (Multilingual Weather Forecasts Assistant) system will be demonstrated. It is developed to generate the multilingual text of the weather forecasts automatically. The raw data from the weather observation can be used
(1) Ensemble forecast calibration & (2) using reforecasts
1 (1) Ensemble forecast calibration & (2) using reforecasts Tom Hamill NOAA Earth System Research · Calibration: ; the statistical adjustment of the (ensemble) forecast Rationale 1: Infer large-sample probabilities from small ensemble. Rationale 2: Remove bias, increase forecast reliability while preserving
Modeling and Forecasting Electric Daily Peak Loads
Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity 29, 2012 Preliminary Results of the Electricity Price Forecast Update As part of the Mid Term Assessment, staff is preparing a long term wholesale electricity market price forecast. A summary of the work
Abdel-Aal, Radwan E.
Consensus Coal Production And Price Forecast For
Consensus Coal Production And Price Forecast For West Virginia: 2011 Update Prepared for the West December 2011 © Copyright 2011 WVU Research Corporation #12;#12;W.Va. Consensus Coal Forecast Update 2011 i Table of Contents Executive Summary 1 Recent Developments 3 Consensus Coal Production And Price Forecast
Historical Maps Online
For 20 years, David Rumsey assembled a collection of more than 150,000 historical maps of the Americas and the world. Motivated by a desire to make his private map collection a free public resource, Rumsey then created an online map library, http://www.davidrumsey.com/, which currently has over 10,000 high resolution images of maps from his collection. He has also built a suite of tools for users to experience and interpret the maps online. These include GIS, which allows users to combine historical maps with modern geospatial data to see change over time. The online map collection can be accessed over the Internet from search engines, library catalogs, GIS databases and many other entry points. Rumsey continues to add new content to the online collection and develops new tools that improve both the user experience and the online library architecture.
Rumsey, David Y.
How Do You Like Your Weather?: Using Weather Forecast Data to Improve Short-Term Load Forecasts
This document provides a quick overview of weather forecasts as a data issue in the development of electricity demand forecasts. These are three sections in this Brief: o reasons behind the rise in interest in using weather forecasts in electricity forecasting models, o an overview of what some utilities are doing to evaluate weather forecasts, and o a resource list of weather forecast providers.
Analysis Papers > Annual Energy Outlook Forecast Evaluation Analysis Papers > Annual Energy Outlook Forecast Evaluation Release Date: February 2005 Next Release Date: February 2006 Printer-friendly version Annual Energy Outlook Forecast Evaluation* Table 1.Comparison of Absolute Percent Errors for Present and Current AEO Forecast Evaluations Printer Friendly Version Average Absolute Percent Error Variable AEO82 to AEO99 AEO82 to AEO2000 AEO82 to AEO2001 AEO82 to AEO2002 AEO82 to AEO2003 AEO82 to AEO2004 Consumption Total Energy Consumption 1.9 2.0 2.1 2.1 2.1 2.1 Total Petroleum Consumption 2.9 3.0 3.1 3.1 3.0 2.9 Total Natural Gas Consumption 7.3 7.1 7.1 6.7 6.4 6.5 Total Coal Consumption 3.1 3.3 3.5 3.6 3.7 3.8 Total Electricity Sales 1.9 2.0 2.3 2.3 2.3 2.4 Production Crude Oil Production 4.5 4.5 4.5 4.5 4.6 4.7
Price forecasting for notebook computers
This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.
Rutherford, Derek Paul
Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS
This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.
Thomas, L.C.
A Kalman-filter bias correction of ozone deterministic, ensemble-averaged, and probabilistic forecasts
Kalman filtering (KF) is used to postprocess numerical-model output to estimate systematic errors in surface ozone forecasts. It is implemented with a recursive algorithm that updates its estimate of future ozone-concentration bias by using past forecasts and observations. KF performance is tested for three types of ozone forecasts: deterministic, ensemble-averaged, and probabilistic forecasts. Eight photochemical models were run for 56 days during summer 2004 over northeastern USA and southern Canada as part of the International Consortium for Atmospheric Research on Transport and Transformation New England Air Quality (AQ) Study. The raw and KF-corrected predictions are compared with ozone measurements from the Aerometric Information Retrieval Now data set, which includes roughly 360 surface stations. The completeness of the data set allowed a thorough sensitivity test of key KF parameters. It is found that the KF improves forecasts of ozone-concentration magnitude and the ability to predict rare events, both for deterministic and ensemble-averaged forecasts. It also improves the ability to predict the daily maximum ozone concentration, and reduces the time lag between the forecast and observed maxima. For this case study, KF considerably improves the predictive skill of probabilistic forecasts of ozone concentration greater than thresholds of 10 to 50 ppbv, but it degrades it for thresholds of 70 to 90 ppbv. Moreover, KF considerably reduces probabilistic forecast bias. The significance of KF postprocessing and ensemble-averaging is that they are both effective for real-time AQ forecasting. KF reduces systematic errors, whereas ensemble-averaging reduces random errors. When combined they produce the best overall forecast.
Monache, L D; Grell, G A; McKeen, S; Wilczak, J; Pagowski, M O; Peckham, S; Stull, R; McHenry, J; McQueen, J
Support vector regression with chaos-based firefly algorithm for stock market price forecasting
Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box-Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market ... Keywords: Chaotic mapping, Firefly algorithm, Stock market price forecasting, Support vector regression
Ahmad Kazem; Ebrahim Sharifi; Farookh Khadeer Hussain; Morteza Saberi; Omar Khadeer Hussain
Forecasting the S&P 500 index using time series analysis and simulation methods
The S&P 500 represents a diverse pool of securities in addition to Large Caps. A range of audiences are interested in the S&P 500 forecasts including investors, speculators, economists, government and researchers. The ...
Chan, Eric Glenn
An Interactive Method for Estimating Maximum Hailstone Size from Forecast Soundings
A diagnostic/prognostic sounding analysis package is presented to aid operational forecasters. First, a diagnostic sounding analysis is shown which computes standard thermodynamic parameters while including a scheme to estimate the maximum hail ...
James T. Moore; John P. Pino
Subgrid Scale Physics in 1-Month Forecasts. Part I: Experiment with Four Parameterization Packages
Four packages of subgrid scale (SGS) physics parameterization are tested by including them in a general circulation model and by applying the four models to 1-month forecasts. The four models are formulated by accumulatively increasing the ...
J. Sirutis; K. Miyakoda
Simulations and Seasonal Prediction of the Asian Summer Monsoon in the NCEP Climate Forecast System
Analysis of the retrospective ensemble predictions (hindcasts) of the NCEP Climate Forecast System (CFS) indicates that the model successfully simulates many major features of the Asian summer monsoon including the climatology and interannual ...
Song Yang; Zuqiang Zhang; Vernon E. Kousky; R. Wayne Higgins; Soo-Hyun Yoo; Jianyin Liang; Yun Fan
Potential Impacts of the Saharan Air Layer on Numerical Model Forecasts of North Atlantic Tropical Cyclogenesis
Tropical cyclones have devastating impacts on countries across large parts of the globe, including the Atlantic basin. Thus, forecasting of the genesis of Atlantic tropical cyclones is important, but this problem remains a challenge for ...
Aaron S. Pratt; Jenni L. Evans
Great Historical Events That Were Significantly Affected by the Weather: Part 8, Germany's War on the Soviet Union, 1941-45. II. Some Important Weather Forecasts, 1942-45
Short- to medium-range weather forecasts were prepared by Soviet meteorologists for the Battle of Stalingrad. These included forecasts for days suitable for massing troops and equipment and for starting the Soviet offensive in November 1942 that ...
J. Neumann; H. Flohn
Forecasting Techniques The Use of Hourly Model-Generated Soundings to Forecast Mesoscale Phenomena. Part I: Initial Assessment in Forecasting Warm-Season Phenomena
Since late 1995, NCEP has made available to forecasters hourly model guidance at selected sites in the form of vertical profiles of various forecast fields. These profiles provide forecasters with increased temporal resolution and greater ...
Robert E. Hart; Gregory S. Forbes; Richard H. Grumm
Meese-Rogoff redux: Micro-based exchange-rate forecasting
Johnatban. "Exchange Rate Forecasting: The Errors We'veBased Exchange-Rate Forecasting By MARTIN D . D . EVANS ANDon longer-horizon forecasting, we examine forecasting over
Evans, MDD; Lyons, Richard K.
The Past as Prologue? Business Cycles and Forecasting since the 1960s
Forecasters,� Journal of Forecasting, Vol. 28, No. 2, Mar,of Macroeconomic Forecasting� Journal of Macroeconomics,of Federal Reserve Forecasting,� Journal of Macroeconomics,
Bardhan, Ashok Deo; Hicks, Daniel; Kroll, Cynthia A.; Yu, Tiffany
Material World: Forecasting Household Appliance Ownership in a Growing Global Economy
and V. Letschert (2005). Forecasting Electricity Demand in8364 Material World: Forecasting Household ApplianceMcNeil, 2008). Forecasting Diffusion Forecasting Variables
Letschert, Virginie
Critical Operating Constraint Forecasting (COCF)
This document represents the progress report and Task 1 letter report of the California Institute for Energy and Environment (CIEE) contract funded by the California Energy Commission (CEC), Critical Operating Constraint Forecasting (COCF) for California Independent System Operator (CAISO) Planning Phase. Task 1 was to accomplish the following items: Collect data from CAISO to set up the WECC power flow base case representing the CAISO system in the summer of 2006 Run TRACE for maximizing California Impo...
A Cosmology Forecast Toolkit -- CosmoLib
The package CosmoLib is a combination of a cosmological Boltzmann code and a simulation toolkit to forecast the constraints on cosmological parameters from future observations. In this paper we describe the released linear-order part of the package. We discuss the stability and performance of the Boltzmann code. This is written in Newtonian gauge and including dark energy perturbations. In CosmoLib the integrator that computes the CMB angular power spectrum is optimized for a $\\ell$-by-$\\ell$ brute-force integration, which is useful for studying inflationary models predicting sharp features in the primordial power spectrum of metric fluctuations. The numerical code and its documentation are available at http://www.cita.utoronto.ca/~zqhuang/CosmoLib.
Zhiqi Huang
A supply forecasting model for Zimbabwe's corn sector: a time series and structural analysis
The Zimbabwean government utilizes the corn supply forecasts to establish producer prices for the following growing season, estimate corn storage and handling costs, project corn import needs and associated costs, and to assess the Grain Marketing Board's financial resource needs. Thus, the corn supply forecasts are important information used by the government for contingency planning, decision-making, policy-formulation and implementation. As such, the need for accurate forecasts is obvious. The objectives of the study are: (a) determine how changes in the government-established producer price affects the quantity of corn supplied to the Grain Marketing Board by the large-scale corn-producing sector and (b) whether including rainfall or rainfall probabilities into econometric models would result in an improvement of corn supply forecasts compared to current forecasts by the government. In order to accomplish the first objective a supply elasticity model was specified and estimated using ordinary least squares. This model is intended to provide 'de insight to the government regarding the influence of the government-established corn price and other related variables on corn supplied to the Grain Marketing Board by the large-scale producers. Thus, the estimated model would be useful to the government when establishing corn prices in March/April for production in the following growing season (October - February). To achieve the second objective, preliminary analysis was carried out to verify whether there is statistical evidence to support the hypothesis that rainfall cause" corn production and supply, and also corn prices and sales. Specifically the preliminary analysis involved using the Granger causality tests, stationarity tests and innovation accounting (impulse responses and forecast error decomposition). Having verified and quantified the causal effects of rainfall on corn production and supply, the next task was to investigate whether including rainfall and/or drought probabilities into forecasting econometric models would help provide improved out-of-sample forecasts compared to the government's forecasts. The forecasting accuracy of the models (short-run) was evaluated using standard statistical measures such as, the mean square error (MSE), mean absolute percentage error (MAPEI), improved mean absolute percentage error (IMAPE) and Theil's U-statistic, and thereupon select the best model. The results indicated that by incorporating rainfall and/or rainfall probabilities into econometric forecasting models, there was substantial improvement in corn supply forecasts. It follows that the the government would likely find it beneficial to incorporate the rainfall variable into their forecasting effort.
Makaudze, Ephias
R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON July 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2000 NEW JERSEY of growth will decelerate over the forecast period. The R/ECON TM forecast for New Jersey in 2000 looks to decelerate over the course of the forecast. These forces will combine to push the unemployment rate to more
Increasing NOAA's computational capacity to improve global forecast modeling
1 Increasing NOAA's computational capacity to improve global forecast modeling A NOAA of the NWS's forecast products, even its regional forecast products, are constrained by the limitations of NOAA's global forecast model. Unfortunately, our global forecasts are less accurate than those from
Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts
The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (...
Felix Fundel; Andre Walser; Mark A. Liniger; Christoph Frei; Christof Appenzeller
Implications of Ensemble Quantitative Precipitation Forecast Errors on Distributed Streamflow Forecasting
Evaluating the propagation of errors associated with ensemble quantitative precipitation forecasts (QPFs) into the ensemble streamflow response is important to reduce uncertainty in operational flow forecasting. In this paper, a multifractal ...
Giuseppe Mascaro; Enrique R. Vivoni; Roberto Deidda
Evaluation of Probabilistic Precipitation Forecasts Determined from Eta and AVN Forecasted Amounts
This note examines the connection between the probability of precipitation and forecasted amounts from the NCEP Eta (now known as the North American Mesoscale model) and Aviation (AVN; now known as the Global Forecast System) models run over a 2-...
William A. Gallus Jr.; Michael E. Baldwin; Kimberly L. Elmore
Reliable Probabilistic Quantitative Precipitation Forecasts from a Short-Range Ensemble Forecasting System
A simple binning technique is developed to produce reliable 3-h probabilistic quantitative precipitation forecasts (PQPFs) from the National Centers for Environmental Prediction (NCEP) multimodel short-range ensemble forecasting system obtained ...
David J. Stensrud; Nusrat Yussouf
The Impact of Writing Area Forecast Discussions on Student Forecaster Performance
A brief study is provided on the forecast performance of students who write a mock area forecast discussion (AFD) on a weekly basis. Student performance was tracked for one semester (11 weeks) during the University of Missouri�Columbia's local ...
Patrick S. Market
An Operational Model for Forecasting Probability of Precipitation and Yes/No Forecast
An operational system for forecasting probability of precipitation (PoP) and yes/no forecast over 10 stations during monsoon season is developed. A perfect prog method (PPM) approach is followed for statistical interpretation of numerical weather ...
Ashok Kumar; Parvinder Maini; S. V. Singh
Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts
The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to ...
Brian Eder; Daiwen Kang; S. Trivikrama Rao; Rohit Mathur; Shaocai Yu; Tanya Otte; Ken Schere; Richard Wayland; Scott Jackson; Paula Davidson; Jeff McQueen; George Bridgers
Mathematical and computer modelling reports: Modeling and forecasting energy markets with the intermediate future forecasting system
This paper describes the Intermediate Future Forecasting System (IFFS), which is the model used to forecast integrated energy markets by the U.S. Energy Information Administration. The model contains representations of supply and demand for all of the ...
Frederic H. Murphy; John J. Conti; Susan H. Shaw; Reginald Sanders
BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multi-model Ensemble Forecasts
Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using one- to seven-day ensemble forecasts of 24-hour accumulated precipitation, and observations from 43 ...
Jianguo Liu; Zhenghui Xie
Evaluation of Probabilistic Medium-Range Temperature Forecasts from the North American Ensemble Forecast System
Ensemble temperature forecasts from the North American Ensemble Forecast System were assessed for quality against observations for 10 cities in western North America, for a 7-month period beginning in February 2007. Medium-range probabilistic ...
Further Evaluation of the National Meterological Center's Medium-Range Forecast Model Precpitation Forecasts
Precipitation forecasts made by the National Meteorological Center's medium-range forecast (MRF) model are evaluated for the period, 1 March 1987 to 31 March 1989. As shown by Roads and Maisel, the MRF model wet bias was substantially alleviated ...
John O. Roads; T. Norman Maisal; Jordan Alpert
Role of Retrospective Forecasts of GCMs Forced with Persisted SST Anomalies in Operational Streamflow Forecasts Development
Seasonal streamflow forecasts contingent on climate information are essential for water resources planning and management as well as for setting up contingency measures during extreme years. In this study, operational streamflow forecasts are ...
A. Sankarasubramanian; Upmanu Lall; Susan Espinueva
Evaluation of MJO Forecast Skill from Several Statistical and Dynamical Forecast Models
This work examines the performance of Madden�Julian oscillation (MJO) forecasts from NCEP�s coupled and uncoupled general circulation models (GCMs) and statistical models. The forecast skill from these methods is evaluated in near�real time. ...
Kyong-Hwan Seo; Wanqiu Wang; Jon Gottschalck; Qin Zhang; Jae-Kyung E. Schemm; Wayne R. Higgins; Arun Kumar
A Probabilistic Forecast Contest and the Difficulty in Assessing Short-Range Forecast Uncertainty
Results are presented from a probability-based weather forecast contest. Rather than evaluating the absolute errors of nonprobabilistic temperature and precipitation forecasts, as is common in other contests, this contest evaluated the skill of ...
Thomas M. Hamill; Daniel S. Wilks
NREL: Dynamic Maps, GIS Data, and Analysis Tools - Maps
Bookmark and Share Bookmark and Share Maps NREL's GIS team develops maps for various renewable resources and for specific projects. As a benefit to the public, a majority of static maps are offered and Google Map (KML/KMZ) files on a tool called MapSearch. Biomass Maps Maps showing the biomass resources available in the United States by county. Feedstock categories include crop residues; forest residues; primary and secondary mill residues; urban wood waste; and methane emissions from manure management, landfills, and domestic wastewater treatment. Federal Energy Management Program The Federal Energy Management Program (FEMP) teamed with Geospatial Analysis staff at NREL to update the analysis for this project and created an interactive FEMP Screening Map application. The previous maps have been
Forecasting Random Walks Under Drift Instability
Forecasting Random Walks Under Drift Instability? M. Hashem Pesaran University of Cambridge, CIMF, and USC Andreas Pick University of Cambridge, CIMF March 11, 2008 Abstract This paper considers forecast averaging when the same model is used... but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single...
Pesaran, M Hashem; Pick, Andreas
EIA - Forecasts and Analysis of Energy Data
H Tables H Tables Appendix H Comparisons With Other Forecasts, and Performance of Past IEO Forecasts for 1990, 1995, and 2000 Forecast Comparisons Three organizations provide forecasts comparable with those in the International Energy Outlook 2005 (IEO2005). The International Energy Agency (IEA) provides business as usual projections to the year 2030 in its World Energy Outlook 2004; Petroleum Economics, Ltd. (PEL) publishes world energy forecasts to 2025; and Petroleum Industry Research Associates (PIRA) provides projections to 2015. For this comparison, 2002 is used as the base year for all the forecasts, and the comparisons extend to 2025. Although IEAs forecast extends to 2030, it does not publish a projection for 2025. In addition to forecasts from other organizations, the IEO2005 projections are also compared with those in last years report (IEO2004). Because 2002 data were not available when IEO2004 forecasts were prepared, the growth rates from IEO2004 are computed from 2001.
Rolling 12 Month Forecast November-2008.xls
Month Exceedence Level: 90% (Dry) First Preference CVP Generation Project Use November 2008 October 2009 November 2008 Twelve-Month Forecast of CVP Generation and Base Resource...
Solar future: 1978. [Market forecast to 1992
The growth in sales of solar heating equipment is discussed. Some forecasts are made for the continued market growth of collectors, pool systems, and photovoltaics. (MOW)
Butt, S.H.
Energy conservation and official UK energy forecasts
Behind the latest United Kingdom (UK) official forecasts of energy demand are implicit assumptions about future energy-price elasticities. Mr. Pearce examines the basis of the forecasts and finds that the long-term energy-price elasticities that they imply are two or three times too low. The official forecasts substantially understate the responsiveness of demand to energy price rises. If more-realistic price elasticities were assumed, the official forecasts would imply a zero primary energy-demand growth to 2000. This raises the interesting possibility of a low energy future being brought about entirely by market forces. 15 references, 3 tables.
Pearce, D.
Geothermal wells: a forecast of drilling activity
Numbers and problems for geothermal wells expected to be drilled in the United States between 1981 and 2000 AD are forecasted. The 3800 wells forecasted for major electric power projects (totaling 6 GWe of capacity) are categorized by type (production, etc.), and by location (The Geysers, etc.). 6000 wells are forecasted for direct heat projects (totaling 0.02 Quads per year). Equations are developed for forecasting the number of wells, and data is presented. Drilling and completion problems in The Geysers, The Imperial Valley, Roosevelt Hot Springs, the Valles Caldera, northern Nevada, Klamath Falls, Reno, Alaska, and Pagosa Springs are discussed. Likely areas for near term direct heat projects are identified.
Brown, G.L.; Mansure, A.J.; Miewald, J.N.
Promotional forecasting in the grocery retail business
Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal ...
Koottatep, Pakawkul
Time Series Prediction Forecasting the Future and ...
Time Series Prediction Forecasting the Future and Understanding the Past Santa Fe Institute Proceedings on the Studies in the Sciences of ...
Forecasting Prices andForecasting Prices and Congestion forCongestion for
Abstract--In deregulated electricity markets, short-term load forecasting is important for reliable power322 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 1, FEBRUARY 2010 Short-Term Load Forecasting presents a similar day-based wavelet neural network method to forecast tomorrow's load. The idea
Tesfatsion, Leigh
Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations
Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12
1 East Central Area Reliability Coordination Agreement (ECAR) 1 East Central Area Reliability Coordination Agreement (ECAR) 2 Electric Reliability Council of Texas (ERCOT) 3 Mid-Atlantic Area Council (MAAC) 4 Mid-America Interconnected Network (MAIN) 5 Mid-Continent Area Power Pool (MAPP) 6. New York (NY) Southern Nevada (RA) 7. New England (NE) 8 Florida Reliability Coordinating Council (FL) 9 Southeastern Electric Reliability Council (SERC) 10 Southwest Power Pool (SPP) 11 Northwest Power Pool (NWP) 12. Rocky Mountain Power Area, Arizona, New Mexico, and 13 California (CA) Source: Energy Information Administration. Office of Integrated Analysis and Forecasting Figure 3. Petroleum Administration for Defense Districts Source: Energy Information Administration. Office of Integrated Analysis and Forecasting AK WA NV
Saudi Arabia - U.S. Energy Information Administration (EIA)
State energy information, ... Maps. Maps by energy source and topic, includes forecast maps. Countries. Country energy information, ... Installed Capa ...
Bulgaria - U.S. Energy Information Administration (EIA)
Annual Energy Outlook Forecast Evaluation - Table 1. Forecast Evaluations:
Average Absolute Percent Errors from AEO Forecast Evaluations: Average Absolute Percent Errors from AEO Forecast Evaluations: 1996 to 2000 Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Average Absolute Percent Error Variable 1996 Evaluation: AEO82 to AEO93 1997 Evaluation: AEO82 to AEO97 1998 Evaluation: AEO82 to AEO98 1999 Evaluation: AEO82 to AEO99 2000 Evaluation: AEO82 to AEO2000 Consumption Total Energy Consumption 1.8 1.6 1.7 1.7 1.8 Total Petroleum Consumption 3.2 2.8 2.9 2.8 2.9 Total Natural Gas Consumption 6.0 5.8 5.7 5.6 5.6 Total Coal Consumption 2.9 2.7 3.0 3.2 3.3 Total Electricity Sales 1.8 1.6 1.7 1.8 2.0 Production Crude Oil Production 5.1 4.2 4.3 4.5 4.5
MAPPING OUR UNDERWATER MARINE RESOURCES The MapCoast and BayMap Partnerships
MAPPING OUR UNDERWATER MARINE RESOURCES The MapCoast and BayMap Partnerships BAYMAP: CHARTING communities and underwater archaeological sites in a readily accessible GIS format. An interdisciplinary team underwater resources, including bathymetry, habitat, geology, soils/ sediment, and archeological resources
Wang, Y.Q. "Yeqiao"
Quantile Forecasting of Commodity Futures' Returns: Are Implied Volatility Factors Informative?
This study develops a multi-period log-return quantile forecasting procedure to evaluate the performance of eleven nearby commodity futures contracts (NCFC) using a sample of 897 daily price observations and at-the-money (ATM) put and call implied volatilities of the corresponding prices for the period from 1/16/2008 to 7/29/2011. The statistical approach employs dynamic log-returns quantile regression models to forecast price densities using implied volatilities (IVs) and factors estimated through principal component analysis (PCA) from the IVs, pooled IVs and lagged returns. Extensive in-sample and out-of-sample analyses are conducted, including assessment of excess trading returns, and evaluations of several combinations of quantiles, model specifications, and NCFC's. The results suggest that the IV-PCA-factors, particularly pooled return-IV-PCA-factors, improve quantile forecasting power relative to models using only individual IV information. The ratio of the put-IV to the call-IV is also found to improve quantile forecasting performance of log returns. Improvements in quantile forecasting performance are found to be better in the tails of the distribution than in the center. Trading performance based on quantile forecasts from the models above generated significant excess returns. Finally, the fact that the single IV forecasts were outperformed by their quantile regression (QR) counterparts suggests that the conditional distribution of the log-returns is not normal.
Dorta, Miguel
U.S. Department of Energy Workshop Report: Solar Resources and Forecasting
This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.
Stoffel, T.
Uses and Applications of Climate Forecasts for Power Utilities
The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-...
Stanley A. Changnon; Joyce M. Changnon; David Changnon
Forecasting and Verifying in a Field Research Project: DOPLIGHT '87
Verification of forecasts during research field experiments is discussed and exemplified using the DOPLIGHT '87 experiment. We stress the importance of forecast verification if forecasting is to be a serious component of the research. A direct ...
Charles A. Doswell III; John A. Flueck
On the Reliability and Calibration of Ensemble Forecasts
An important aspect of ensemble forecasting is that the resulting probabilities are reliable (i.e., the forecast probabilities match the observed frequencies). In the medium-range forecasting context, the literature tends to focus on the ...
Christine Johnson; Neill Bowler
Forecasting during the Lake-ICE/SNOWBANDS Field Experiments
Despite improvements in numerical weather prediction models, statistical models, forecast decision trees, and forecasting rules of thumb, human interpretation of meteorological information for a particular forecast situation can still yield a ...
Peter J. Sousounis; Greg E. Mann; George S. Young; Richard B. Wagenmaker; Bradley D. Hoggatt; William J. Badini
Experiments in Temperature and Precipitation Forecasting for Illinois
Six years of daily temperature and precipitation forecasting are studied for Urbana, Illinois. Minimum temperature forecast skills, measured against a climatological control, are 57%, 48%, 34% and 20% for the respective forecast ranges of one, ...
John R. Gyakum
Scoring Probabilistic Forecasts: The Importance of Being Proper
Questions remain regarding how the skill of operational probabilistic forecasts is most usefully evaluated or compared, even though probability forecasts have been a long-standing aim in meteorological forecasting. This paper explains the ...
Jochen Br�cker; Leonard A. Smith
Precipitation and Temperature Forecast Performance at the Weather Prediction Center
The role of the human forecaster in improving upon the accuracy of numerical weather prediction is explored using multi-year verification of human-generated short-range precipitation forecasts and medium-range maximum temperature forecasts from ...
David R. Novak; Christopher Bailey; Keith Brill; Patrick Burke; Wallace Hogsett; Robert Rausch; Michael Schichtel
Diversity in Interpretations of Probability: Implications for Weather Forecasting
Over the last years, probability weather forecasts have become increasingly popular due in part to the development of ensemble forecast systems. Despite its widespread use in atmospheric sciences, probability forecasting remains a subtle and ...
Ram�n de El�a; Ren� Laprise
Prediction of Consensus Tropical Cyclone Track Forecast Error
The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, ...
James S. Goerss
An Experiment in Mesoscale Weather Forecasting in the Michigan Area
During an experiment in mesoscale weather forecasting in the Michigan area, consensus improved over NWS guidance in maximum/minimum temperature and probability of precipitation forecasts out to 24 hours. Forecasts were generally best in the ...
Dennis G. Baker
The Economic Value Of Ensemble-Based Weather Forecasts
The potential economic benefit associated with the use of an ensemble of forecasts versus anequivalent or higher-resolution control forecast is discussed. Neither forecast systems are post-processed,except a simple calibration that is applied to ...
Yuejian Zhu; Zoltan Toth; Richard Wobus; David Richardson; Kenneth Mylne
A Probabilistic Forecast Approach for Daily Precipitation Totals
Commonly, postprocessing techniques are employed to calibrate a model forecast. Here, a probabilistic postprocessor is presented that provides calibrated probability and quantile forecasts of precipitation on the local scale. The forecasts are ...
Petra Friederichs; Andreas Hense
the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12
Forecasts of intercity passenger demand and energy use through 2000
The development of national travel demand and energy-use forecasts for automobile and common-carrier intercity travel through the year 2000. The forecasts are driven by the POINTS (Passenger Oriented Intercity Network Travel Simulation) model, a model direct-demand model which accounts for competition among modes and destinations. Developed and used to model SMSA-to-SMSA business and nonbusiness travel, POINTS is an improvement over earlier direct demand models because it includes an explicit representation of cities' relative accessibilities and a utility maximizing behavorial multimodal travel function. Within POINTS, pathbuilding algorithms are used to determine city-pair travel times and costs by mode, including intramodal transfer times. Other input data include projections of SMSA population, public and private sector employment, and hotel and other retail receipts. Outputs include forecasts of SMSA-to-SMSA person trips and person-miles of travel by mode. For the national forecasts, these are expanded to represent all intercity travel (trips greater than 100 miles, one way) for two fuel-price cases. Under both cases rising fuel prices, accompanied by substantial reductions in model-energy intensities, result in moderate growth in total intercity passenger travel. Total intercity passenger travel is predicted to grow at approximately one percent per year, slightly fster than population growth, while air travel grows almost twice as fast as population. The net effect of moderate travel growth and substantial reduction in model energy intensities is a reduction of approximately 50 percent in fuel consumption by the intercity passenger travel market.
Kaplan, M.P.; Vyas, A.D.; Millar, M.; Gur, Y.
Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Information
Forecast, ForskEL (Smart Grid Project) Forecast, ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Energy Forecast, ForskEL Country Denmark Coordinates 56.26392°, 9.501785° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}
Price and Load Forecasting in Volatile Energy Markets
With daily news stories about wildly fluctuating electricity prices and soaring natural gas prices, forecasters' responsibilities are expanding, visibility is increasing, and pressure exists to produce more frequent forecasts and more kinds of forecasts. The proceedings of EPRI's 13th Forecasting Symposium, held November 13-15 in Nashville, Tennessee, address current forecasting issues and developments, as well as explain the role that forecasters have played in recent events in energy markets.
Possibility of Skill Forecast Based on the Finite-Time Dominant Linear Solutions for a Primitive Equation Regional Forecast Model
The possibility of using forecast errors originating from the finite-time dominant linear modes for the prediction of forecast skill for a primitive equation regional forecast model is studied. This is similar to the method for skill prediction ...
Tomislava Vuki?evi?
New Climate Research Centers Forecast Changes and Challenges...
Climate Research Centers Forecast Changes and Challenges New Climate Research Centers Forecast Changes and Challenges October 25, 2013 - 12:24pm Addthis This artist's rendering...
Exploiting Domain Knowledge to Forecast Heating Oil Consumption
The GasDay laboratory at Marquette University provides forecasts of energy consumption. One such service is the Heating Oil Forecaster
George F. Corliss; Tsuginosuke Sakauchi; Steven R. Vitullo; Ronald H. Brown
SunShot Initiative: Forecasting and Influencing Technological...
Forecasting and Influencing Technological Progress in Solar Energy to someone by E-mail Share SunShot Initiative: Forecasting and Influencing Technological Progress in Solar Energy...
Building Energy Software Tools Directory: Energy Usage Forecasts
Alphabetically Tools by Platform PC Mac UNIX Internet Tools by Country Related Links Energy Usage Forecasts Energy Usage Forecasts Quick and easy web-based tool that provides...
Forecasting demand of commodities after natural disasters
Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster
Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua
Preemptive Forecasts Using an Ensemble Kalman Filter
An ensemble Kalman filter (EnKF) estimates the error statistics of a model forecast using an ensemble of model forecasts. One use of an EnKF is data assimilation, resulting in the creation of an increment to the first-guess field at the ...
Brian J. Etherton
Time series forecasting with Qubit Neural Networks
This paper proposes a quantum learning scheme approach for time series forecasting, through the application of the new non-standard Qubit Neural Network (QNN) model. The QNN description was adapted in this work in order to resemble classical Artificial ... Keywords: artificial intelligence, artificial neural networks, quantum computing, qubit neural networks, time series forecasting
Carlos R. B. Azevedo; Tiago A. E. Ferreira
Blasting Vibration Forecast Base on Neural Network
The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved ... Keywords: Blasting vibration, Neural network, Forecast
Haiwang Ye; Fang Liu; Jian Chang; Lin Feng; Yang Wang; Peng Yao; Kai Wu
Evaluating the Skill of Categorical Forecasts
A generalized skill score is presented for evaluating forecasts in any number of categories. Each forecast in a sample is given a mark; the skill score for the sample is just the average mark. Each mark has an expected value of zero for an ...
Neil D. Gordon
Incentives for Retailer Forecasting: Rebates vs. Returns
This paper studies a manufacturer that sells to a newsvendor retailer who can improve the quality of her demand information by exerting costly forecasting effort. In such a setting, contracts play two roles: providing incentives to influence the retailer's ... Keywords: endogenous adverse selection, forecasting, rebates, returns, supply chain contracting
Terry A. Taylor; Wenqiang Xiao
A spatially distributed flash flood forecasting model
This paper presents a distributed model that is in operational use for forecasting flash floods in northern Austria. The main challenge in developing the model was parameter identification which was addressed by a modelling strategy that involved a model ... Keywords: Distributed modelling, Dominant processes concept, Floods, Forecasting, Kalman Filter, Model accuracy, Parameter identification, Stream routing
G�nter Bl�schl; Christian Reszler; J�rgen Komma
The NCEP Climate Forecast System Version 2
The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled Reanalysis ...
Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-ya Chuang; Mark Iredell; Michael Ek; Jesse Meng; Rongqian Yang; Malaqu�as Pe�a Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker
Forecast of geothermal-drilling activity
The number of geothermal wells that will be drilled to support electric power production in the United States through 2000 A.D. are forecasted. Results of the forecast are presented by 5-year periods for the five most significant geothermal resources.
Mansure, A.J.; Brown, G.L.
Efficient forecasting for hierarchical time series
Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels based ... Keywords: forecasting, hierarchies, optimization, time series
Lars Dannecker; Robert Lorenz; Philipp R�sch; Wolfgang Lehner; Gregor Hackenbroich
Making Forecasts and Weather Normalization Work Together
Electric utility industry restructuring has changed the consistency between weather-normalized sales and energy forecasts. This Technology Review discusses the feasibility of integrating weather normalization and forecasting processes, and addresses whether the conflicting goal of obtaining greater consistency and accuracy with fewer staff resources can be met with more integrated approaches.
Sheet3 Sheet2 Sheet1 Figure 106. Average annual minemouth coal prices by region, 1990-2040 (2011 dollars per million Btu) Appalachia Interior West US Average
Evaluating the Cloud Cover Forecast of NCEP Global Forecast System with Satellite Observation
To assess the quality of daily cloud cover forecast generated by the operational global numeric model, the NCEP Global Forecast System (GFS), we compose a large sample with outputs from GFS model and satellite observations from the International Satellite Cloud Climatology Project (ISCCP) in the period of July 2004 to June 2008, to conduct a quantitative and systematic assessment of the performance of a cloud model that covers a relatively long range of time, basic cloud types, and in a global view. The evaluation has revealed the goodness of the model forecast, which further illustrates our completeness on understanding cloud generation mechanism. To quantity the result, we found a remarkably high correlation between the model forecasts and the satellite observations over the entire globe, with mean forecast error less than 15% in most areas. Considering a forecast within 30% difference to the observation to be a "good" one, we find that the probability for the GFS model to make good forecasts varies between...
Ye, Quanzhi
PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico | Open
Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Jump to: navigation, search Name PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Agency/Company /Organization Pacific Northwest National Laboratory Sector Energy Topics Co-benefits assessment, - Environmental and Biodiversity, - Health, Background analysis Resource Type Publications Website http://www.pnl.gov/atmospheric Country Mexico UN Region Latin America and the Caribbean References PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico[1] PNNL Publications on WRF-Chem modeling in Mexico include: Fast JD, M Shrivastava, RA Zaveri, and JC. Barnard. 2010. "Modeling particulates and direct radiative forcing from urban to synoptic scales downwind of Mexico City." Annual European Geosciences Union Assembly,
Model documentation: electricity market module. [15 year forecasts
This report documents the electricity market model. This model is a component of the Intermediate Future Forecasting System (IFFS), the energy market model used to provide projections of energy markets up to 15 years into the future. The electricity market model was developed by the Supply Analysis and Integration Branch as part of building the larger system. This report is written for an audience consisting of mathematical economists, statisticians, operations research analysts, and utility planners. This report contains an overview and a mathematical specification of the electricity market module. It includes a description of the model logic and the individual subroutines in the computer code. A companion document Intermediate Future Forecasting System: Executive Summary (DOE/EIA-430) provides an overview of the components in IFFS and their linkages. 22 figures, 2 tables.
Sanders, R.C.; Murphy, F.H.
Earthquake Forecast via Neutrino Tomography
We discuss the possibility of forecasting earthquakes by means of (anti)neutrino tomography. Antineutrinos emitted from reactors are used as a probe. As the antineutrinos traverse through a region prone to earthquakes, observable variations in the matter effect on the antineutrino oscillation would provide a tomography of the vicinity of the region. In this preliminary work, we adopt a simplified model for the geometrical profile and matter density in a fault zone. We calculate the survival probability of electron antineutrinos for cases without and with an anomalous accumulation of electrons which can be considered as a clear signal of the coming earthquake, at the geological region with a fault zone, and find that the variation may reach as much as 3% for $\\bar \
Bin Wang; Ya-Zheng Chen; Xue-Qian Li
Decision support for financial forecasting
A primary mission of the Budget Management Division of the Air Force is fiscal analysis. This involves formulating, justifying, and tracking financial data during budget preparation and execution. An essential requirement of this process is the ready availability and easy manipulation of past and current budget data. This necessitates the decentralization of the data. A prototypical system, BAFS (Budget Analysis and Forecasting System), that provides such a capability is presented. In its current state, the system is designed to be a decision support tool. A brief report of the budget decisions and activities is presented. The system structure and its major components are discussed. An insight into the implementation strategies and the tool used is provided. The paper concludes with a discussion of future enhancements and the system's evolution into an expert system. 4 refs., 3 figs.
Jairam, B.N.; Morris, J.D.; Emrich, M.L.; Hardee, H.K.
Construction Safety Forecast for ITER
The International Thermonuclear Experimental Reactor (ITER) project is poised to begin its construction activity. This paper gives an estimate of construction safety as if the experiment was being built in the United States. This estimate of construction injuries and potential fatalities serves as a useful forecast of what can be expected for construction of such a major facility in any country. These data should be considered by the ITER International Team as it plans for safety during the construction phase. Based on average U.S. construction rates, ITER may expect a lost workday case rate of < 4.0 and a fatality count of 0.5 to 0.9 persons per year.
cadwallader, lee charles
Application of the Weather Research and Forecasting Model for Air Quality Modeling in the San Francisco Bay Area
The Weather Research and Forecasting (WRF) model is evaluated by conducting various sensitivity experiments over central California (CA) including the San Francisco Bay Area (SFBA), with the goal of establishing a WRF model configuration to be ...
Raphael E. Rogers; Aijun Deng; David R. Stauffer; Brian J. Gaudet; Yiqin Jia; Su-Tzai Soong; Saffet Tanrikulu
The Weather Research and Forecasting (WRF) model is evaluated by conducting various sensitivity experiments over central California including the San Francisco Bay Area (SFBA), with the goal of establishing a WRF model configuration to be used by ...
Sensitivity of 0�12-h Warm-Season Precipitation Forecasts over the Central United States to Model Initialization
Sensitivity of 0�12-h warm-season precipitation forecasts to atmospheric initial conditions, including those from different large-scale model analyses and from rapid cycled (RC) three-dimensional variational data assimilations (3DVAR) with and ...
Juanzhen Sun; Stanley B. Trier; Qingnong Xiao; Morris L. Weisman; Hongli Wang; Zhuming Ying; Mei Xu; Ying Zhang
Forecast Bias Correction: A Second Order Method
The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.
Crowell, Sean
Industrial production index forecast: Methods comparison
The purpose of this work is to investigate the suitability of different methods as short term forecast tools. It is studied and compared the application of the Kalman filter method with other forecasting methods when applied to a set of qualitative and quantitative information. The work data set is made of qualitative surveys of conjunture and the industrial production index (IPI). The objective is the attainment of short term forecast models for the Portuguese IPI of the transforming industry. After the previous treatment of the data
M. Filomena Teodoro
CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the residential sector forecast. Mohsen Abrishami prepared the commercial sector forecast. Lynn
R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON December 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1999 NEW and wage growth slow later in the forecast, income growth will average 5% a year between 2000 and 2004. Over the forecast period, population growth will average 0.5% a year. The population will rise from 8
R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON July 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 2001 NEW JERSEY each year. The R/ECONTM forecast for New Jersey looks for growth in real output of 2.6 percent years. Over the forecast period, both the construction and manufacturing sectors will lose jobs
R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON April 2001 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2001 NEW JERSEY and 2005, and by an average of 43,000 thereafter (from 2005 to 2020). The R/ECONTM forecast for New Jersey.6 percent a year over the rest of the forecast period. Personal income will rise 5.6 percent this year, down
R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON October 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 1999 NEW JERSEY the rate of inflation should remain under 3% a year. (See Table 1.) #12;Throughout the forecast period and wage growth slow later in the forecast period, income growth will average 4.8% a year between 2000
Does increasing model stratospheric resolution improve extended range forecast skill?
Does increasing model stratospheric resolution improve extended range forecast skill? Greg Roff,1 forecast skill at high Southern latitudes is explored. Ensemble forecasts are made for two model configurations that differ only in vertical resolution above 100 hPa. An ensemble of twelve 30day forecasts
PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Bryan Alcorn and Mehrzad Soltani Nia prepared the industrial forecast. Miguel Garcia- Cerrutti
R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON December 1998 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF DECEMBER 1998 NEW 1997 will continue-- though at a reduced rate--through the forecast period that ends in 2001. New inflation of about 1.5%. In 1998, R/ECONTM forecasts that employment will rise by 76,000 jobs, or 2
R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON October 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF OCTOBER 2000 NEW JERSEY and 2002, with 84,800 jobs being added over the two-year period. The R/ECON TM forecast for New Jersey the rest of the forecast period as foreign immigration declines and the population ages. In the next 10
R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON April 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 1999 NEW JERSEY forecast for New Jersey is for a continuation of the current expansion but at a somewhat slower pace in employment through the forecast period will be in services and trade. We also expect considerable growth
R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON July 1999 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF JULY 1999 NEW JERSEY forecast for New Jersey is for a continuing but slowing expansion. (See Table 1.) In 1998, employment rose increased by 0.7% in 1998. It will slow a bit over the forecast period as foreign immigration declines. #12
R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE
R/ECON April 2000 Forecast RUTGERS ECONOMIC ADVISORY SERVICE FORECAST OF APRIL 2000 NEW JERSEY to more inflation and higher interest rates. The R/ECON TM forecast for New Jersey looks for employment.6% a year over the forecast period. The services and trade sectors will provide 90% of the net increase
Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast uncertainty
Atmospheric Lagrangian coherent structures considering unresolved turbulence and forecast, the uncertainty of the forecast FTLE fields is analyzed using ensemble forecasting. Unavoidable errors of the forecast velocity data due to the chaotic dynamics of the atmosphere is the salient reason for errors
Ross, Shane
A New Measure of Earnings Forecast Uncertainty Xuguang Sheng
A New Measure of Earnings Forecast Uncertainty Xuguang Sheng American University Washington, D of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations
Kim, Kiho
AN ANALYSIS OF FORECAST BASED REORDER POINT POLICIES : THE BENEFIT OF USING FORECASTS Mohamed Zied Ch^atenay-Malabry Cedex, France Abstract: In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given
Time dependent Directional Profit Model for Financial Time Series Forecasting
Time dependent Directional Profit Model for Financial Time Series Forecasting Jingtao YAO Chew firstname.lastname@example.com Abstract Goodnessoffit is the most popular criterion for neural network time series forecasting. In the context of financial time series forecasting, we are not only concerned at how good the forecasts fit
Yao, JingTao
A Study on Training Criteria for Financial Time Series Forecasting
A Study on Training Criteria for Financial Time Series Forecasting JingTao YAO Dept of Information on goodness-of-fit which is also the most popular criterion forecasting. How ever, in the context of financial time series forecasting, we are not only concerned at how good the forecasts fit their target. In order
A new class of hybrid models for time series forecasting
Applying quantitative models for forecasting and assisting investment decision making has become more indispensable in business practices than ever before. Improving forecasting especially time series forecasting accuracy is an important yet often difficult ... Keywords: Artificial neural networks (ANNs), Auto-Regressive Integrated Moving Average (ARIMA), Hybrid models, Probabilistic neural networks (PNNs), Time series forecasting
Mehdi Khashei; Mehdi Bijari
Optimal Updating of Forecasts for the Timing of Future Events
A major problem in forecasting is estimating the time of some future event. traditionally, forecasts are designed to minimize an error cost function that is evaluated once, possibly when the event occurs and forecast accuracy can be determined. However, ... Keywords: Air Transportation, Dynamic Programming Applications, Forecasting
Juhwen Hwang; Medini R. Singh; W. J. Hurley; Robert A. Shumsky
or over predicting electricity demand due to poor weather forecasts is several hundred million dollars outages that many in the area experienced. Deep Thunder can also improve generation-side load forecasting by providing high-resolution weather forecast data for use in electricity demand forecast models. Integrating
Manry, Michael
Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)
This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.
Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.
Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy
Customization and Marketing of Monsoon Forecasts A CSIRCMMACS Synergy Criteria for Technical forecasts of monsoon can significantly aid many sectors like agriculture, power and production industries to the operational forecast, to develop and deliver customized monsoon forecasts based on user need is required
Swathi, P S
Short-term streamflow forecasting: ARIMA vs neural networks
Streamflow forecasting is very important for water resources management and flood defence. In this paper two forecasting methods are compared: ARIMA versus a multilayer perceptron neural network. This comparison is done by forecasting a streamflow of ... Keywords: artificial neural networks, auto regressive integrated moving average, forecasting, streamflow
Juan Frausto-Solis; Esmeralda Pita; Javier Lagunas
Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)
This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.
Hodge, B. M.; Ela, E.; Milligan, M.
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Help » Web Site Map Help » Web Site Map Web Site Map The links listed below include all pages on the site except document topic pages. Home Privacy/Security Help Web Site Map Mailing Services Remove me from the List Contact Us About Us News and Events News Archives News/Media FAQs Internet Resources Documents DUF6 EIS Historical Context What is an EIS? Why EIS is Needed Who is Responsible? EIS Process EIS Topics EIS Alternatives EIS Schedule Public Involvement Opportunities Public Comment Form For More Info DUF6 Management and Uses Management Responsibilities DUF6 Storage How DUF6 is Stored Where DUF6 is Stored Cylinder Leakage DUF6 Storage Safety DUF6 PEIS Cylinder Surveillance and Maintenance Conversion Potential DU Uses "Business Case" for R&D on Beneficial Uses of DU Catalysts for Destruction of Air Pollutants
Press Room - U.S. Energy Information Administration (EIA)
Alternative Fuels. Includes hydropower, solar, wind, geothermal, biomass and ethanol. ... Maps by energy source and topic, includes forecast maps. Countries.
Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method
There is a huge demand in the industry to forecast production in shale gas reservoirs accurately. There are many methods including volumetric, Decline Curve Analysis (DCA), analytical simulation and numerical simulation. Each one of these methods has its advantages and disadvantages, but only the DCA technique can use readily available production data to forecast rapidly and to an extent accurately. The DCA methods in use in the industry such as the Arps method had originally been developed for Boundary dominated flow (BDF) wells but it has been observed in shale reservoirs the predominant flow regime is transient flow. Therefore it was imperative to develop newer models to match and forecast transient flow regimes. The SEDM/SEPD, the Duong model and the Arps with a minimum decline rate are models that have the ability to match and forecast wells with transient flow followed by boundary flow. I have revised the Duong model to forecast better than the original model. I have also observed a certain variation of the Duong model proves to be a robust model for most of the well cases and flow regimes. The modified Duong has been shown to work best compared to other deterministic models in most cases. For grouped datasets the SPED & Duong models forecast accurately while the Modified Arps does a poor job.
Joshi, Krunal Jaykant
Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint
The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.
Florita, A.; Hodge, B. M.; Milligan, M.
How Do Forecasters Utilize Output From A Convection-Permitting Ensemble Forecast System? Case Study Of A High-Impact Precipitation Event
The proliferation of ensemble forecast system output in recent years motivates this investigation into how operational forecasters utilize convection-permitting ensemble forecast system guidance in the forecast preparation process. A sixteen-...
Clark Evans; Donald F. Van Dyke; Todd Lericos
New results in forecasting of photovoltaic systems output based on solar radiation forecasting
Accurate short term forecasting of photovoltaic (PV) systems output has a great significance for fast development of PV parks in South-East Europe
Laurentiu Fara
Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Analysis Papers > Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Download Adobe Acrobat Reader Printer friendly version on our site are provided in Adobe Acrobat Spreadsheets are provided in Excel Actual vs. Forecasts Formats Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF Table 12. World Oil Prices Excel, PDF Table 13. Natural Gas Wellhead Prices
Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Modeling and Analysis Papers> Annual Energy Outlook Forecast Evaluation>Tables Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) MS Excel Viewer PDF (Acrobat Reader required Download Acrobat Reader ) Adobe Acrobat Reader Logo Table 2. Total Energy Consumption Excel, PDF Table 3. Total Petroleum Consumption Excel, PDF Table 4. Total Natural Gas Consumption Excel, PDF Table 5. Total Coal Consumption Excel, PDF Table 6. Total Electricity Sales Excel, PDF Table 7. Crude Oil Production Excel, PDF Table 8. Natural Gas Production Excel, PDF Table 9. Coal Production Excel, PDF Table 10. Net Petroleum Imports Excel, PDF Table 11. Net Natural Gas Imports Excel, PDF
Annual Energy Outlook Forecast Evaluation 2004
2004 2004 * The Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) has produced annual evaluations of the accuracy of the Annual Energy Outlook (AEO) since 1996. Each year, the forecast evaluation expands on the prior year by adding the projections from the most recent AEO and replacing the historical year of data with the most recent. The forecast evaluation examines the accuracy of AEO forecasts dating back to AEO82 by calculating the average absolute percent errors for several of the major variables for AEO82 through AEO2004. (There is no report titled Annual Energy Outlook 1988 due to a change in the naming convention of the AEOs.) The average absolute percent error is the simple mean of the absolute values of the percentage difference between the Reference Case projection and the
Annual Energy Outlook 2001 - Forecast Comparisons
Forecast Comparisons Forecast Comparisons Economic Growth World Oil Prices Total Energy Consumption Residential and Commercial Sectors Industrial Sector Transportation Sector Electricity Natural Gas Petroleum Coal Three other organizationsStandard & Poors DRI (DRI), the WEFA Group (WEFA), and the Gas Research Institute (GRI) [95]also produce comprehensive energy projections with a time horizon similar to that of AEO2001. The most recent projections from those organizations (DRI, Spring/Summer 2000; WEFA, 1st Quarter 2000; GRI, January 2000), as well as other forecasts that concentrate on petroleum, natural gas, and international oil markets, are compared here with the AEO2001 projections. Economic Growth Differences in long-run economic forecasts can be traced primarily to
Dynamical Properties of Model Output Statistics Forecasts
The dynamical properties of forecasts corrected using model output statistics (MOS) schemes are explored, with emphasis on the respective role of model and initial condition uncertainties. Analytical and numerical investigations of low-order ...
S. Vannitsem; C. Nicolis
Scientific Verification of Deterministic River Stage Forecasts
One element of a complete verification system is the ability to determine why forecasts behave as they do. This paper describes and demonstrates an operationally feasible method for conducting this type of diagnostic verification analysis. ...
Edwin Welles; Soroosh Sorooshian
Forecast U.S. Distillate Stocks
EIA is not projecting a large recovery over the summer, but because refineries are forecast to run at high utilization rates, they may produce more distillate than expected and...
EIA lowers forecast for summer gasoline prices
EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be lower this summer than previously thought. The price for regular gasoline this summer is now...
Visualizing Multiple Measures of Forecast Quality
A method for visually representing multiple measures of dichotomous (yes�no) forecast quality (probability of detection, false alarm ratio, bias, and critical success index) in a single diagram is presented. Illustration of the method is provided ...
Paul J. Roebber
Using Climate Forecasts for Drought Management
Drought hazards, and the ability to mitigate them with advance warning, offer potentially valuable applications of climate forecast products. Yet the value is often untapped, owing to the gap between climate science and societal decisions. This ...
Anne C. Steinemann
Assessing the Usefulness of Probabilistic Forecasts
The errors in both the initialization and simulated evolution of weather and climate models create significant uncertainties in forecasts at lead times beyond a few days. Modern prediction systems sample the sources of these uncertainties to ...
An Objective Basis for Forecasting Tornado Intensity
Although violent tornadoes comprise only 2.3% of tornado occurrences in the United States, they cause 68% of the fatalities attributed to tornadoes and severe thunderstorms. Despite these statistics, no attempt is made to forecast or warn of ...
J. R. Colquhoun; D. J. Shepherd
Hypothesis Tests for Evaluating Numerical Precipitation Forecasts
When evaluating differences between competing precipitation forecasts, formal hypothesis testing is rarely performed. This may be due to the difficulty in applying common tests given the spatial correlation of and non-normality of errors. ...
Thomas M. Hamill
The ENIAC Forecasts: A Re-creation
The numerical forecasts made in 1950 using the Electronic Numerical Integrator and Computer (ENIAC) paved the way for the remarkable advances that have been made over the past half-century in weather prediction and climate modeling. We review the ...
Artificial Skill and Validation in Meteorological Forecasting
The results of a simulation study of multiple regression prediction models for meteorological forecasting are reported. The effects of sample size, amount, and severity of nonrepresentative data in the population, inclusion of noninformative ...
Paul W. Mielke Jr.; Kenneth J. Berry; Christopher W. Landsea; William M. Gray
Skill of Multimodel ENSO Probability Forecasts
The cross-validated hindcast skills of various multimodel ensemble combination strategies are compared for probabilistic predictions of monthly SST anomalies in the ENSO-related Ni�o-3.4 region of the tropical Pacific Ocean. Forecast data from ...
Michael K. Tippett; Anthony G. Barnston
Assessing Forecast Skill through Cross Validation
This study explains the method of cross validation for assessing forecast skill of empirical prediction models. Cross validation provides a relatively accurate measure of an empirical procedure's ability to produce a useful prediction rule from a ...
J. B. Elsner; C. P. Schmertmann
Dynamic Algorithm for Space Weather Forecasting System
We propose to develop a dynamic algorithm that intelligently analyzes existing solar weather data and constructs an increasingly more accurate equation/algorithm for predicting solar weather accurately in real time. This dynamic algorithm analyzes a wealth of data derived from scientific research and provides increasingly accurate solar forecasts. As the database of information grows over time, this algorithm perfects itself and reduces forecast uncertainties. This will provide a vastly more effective way of processing existing data for practical use in the public and private sectors. Specifically, we created an algorithm that stores data from several sources in a way that is useable, we created the ?dynamic algorithm? used for creating accurate/effective forecasts, and we have performed preliminary benchmarks on this algorithm. The preliminary benchmarks yield surprisingly effective results thus far?forecasts have been made 8-16 hours into the future with significant magnitude and trend accuracy, which is a vast improvement over current methods employed.
Fischer, Luke D.
Forecasting Resource Supply from Scarcity Rent Data
Forecasting Resource Supply from Scarcity Rent Data Speaker(s): Larry Dale Date: December 18, 2000 - 12:00pm Location: 90-3122 Seminar HostPoint of Contact: Diana Morris This talk...
Flood Forecasting in River System Using ANFIS
The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.
Ullah, Nazrin; Choudhury, P. [Dept. of Civil Eng., NIT, Silchar (India)
Updated Satellite Technique to Forecast Heavy Snow
Certain satellite interpretation techniques have proven quite useful in the heavy snow forecast process. Those considered best are briefly reviewed, and another technique is introduced. This new technique was found to be most valuable in cyclonic ...
Edward C. Johnston
Optimization of Value of Aerodrome Forecasts
Prediction of short-term variations of vital boundary layer conditions at airports, such as visibility and cloud base, is important to the safe and economic operation of airlines. Results of an experiment involving groups of forecasters at three ...
Ross Keith
Severe Thunderstorm Forecasting: A Historical Perspective
Techniques that have evolved during the hundred years that scientific severe thunderstorm forecasts have been prepared are reviewed. The early empirical rules developed by Finley, Showalter and Fulks, Fawbush, Miller and Starrett, and others have ...
Joseph T. Schaefer
NCEP Dynamical Seasonal Forecast System 2000
The new National Centers for Environmental Prediction (NCEP) numerical seasonal forecast system is described in detail. The new system is aimed at a next-generation numerical seasonal prediction in which focus is placed on land processes, initial ...
Masao Kanamitsu; Arun Kumar; Hann-Ming Henry Juang; Jae-Kyung Schemm; Wanqui Wang; Fanglin Yang; Song-You Hong; Peitao Peng; Wilber Chen; Shrinivas Moorthi; Ming Ji
MM5 Contrail Forecasting in Alaska
The fifth-generation Pennsylvania State University�National Center for Atmospheric Research (PSU�NCAR) Mesoscale Model (MM5) is being used for forecasting the atmospheric layers of aircraft condensation trail (contrail) formation. Contrail ...
Martin Stuefer; Xiande Meng; Gerd Wendler
Medium- and Long-Range Forecasting
In contrast to short and extended range forecasts, predictions for periods beyond 5 days use time-averaged, midtropospheric height fields as their primary guidance. As time ranges are increased to 3O- and 90-day outlooks, guidance increasingly ...
A. James Wagner
Consensus Forecasts of Modeled Wave Parameters
The use of numerical guidance has become integral to the process of modern weather forecasting. Using various techniques, postprocessing of numerical model output has been shown to mitigate some of the deficiencies of these models, producing more ...
Tom H. Durrant; Frank Woodcock; Diana J. M. Greenslade
Computer Generation of Marine Weather Forecast Text
MARWORDS is a natural language text generation system which has been developed to synthesize marine forecasts for the Davis Strait area in Northern Canada. It uses standard manually produced predictions of wind speed, air temperature, and other ...
E. Goldberg; R. Kittredge; A. Polgu�re
Spread Calibration of Ensemble MOS Forecasts
Ensemble forecasting systems often contain systematic biases and spread deficiencies that can be corrected by statistical postprocessing. This study presents an improvement to an ensemble statistical postprocessing technique, called ensemble ...
Bruce A. Veenhuis
Snowfall Limit Forecasts and Hydrological Modeling
Hydrological flood forecasting in mountainous areas requires accurate partitioning between rain and snowfall to properly estimate the extent of runoff contributing areas. Here a method to make use of snowfall limit information�a standard output of ...
Cara Tobin; Andrea Rinaldo; Bettina Schaefli
Ensemble Forecast of a Typhoon Flood Event
A high-resolution nested regional spectral model and an ensemble prediction system are combined to forecast the track, intensity, and flooding precipitation arising from Typhoon Winnie of August 1997, which eventually reached supertyphoon status. ...
Brian P. Mackey; T. N. Krishnamurti
Potential Economic Value of Seasonal Hurricane Forecasts
This paper explores the potential utility of seasonal Atlantic hurricane forecasts to a hypothetical property insurance firm whose insured properties are broadly distributed along the U.S. Gulf and East Coasts. Using a recently developed hurricane ...
Kerry Emanuel; Fabian Fondriest; James Kossin
Airborne Volcanic Ash Forecast Area Reliability
In support of aircraft flight safety operations, daily comparisons between modeled, hypothetical, volcanic ash plumes calculated with meteorological forecasts and analyses were made over a 1.5-yr period. The Hybrid Single-Particle Lagrangian ...
Barbara J. B. Stunder; Jerome L. Heffter; Roland R. Draxler
River flow forecasting with constructive neural network
In utilities using a mixture of hydroelectric and non-hydroelectric power, the economics of the hydroelectric plants depend upon the reservoir height and the inflow into the reservoir for several months into the future. Accurate forecasts of reservoir ...
M�user Valen�a; Teresa Ludermir; Anelle Valen�a
Forecast verification: Its Complexity and Dimensionality
Two fundamental characteristics of forecast verification problems�complexity and dimensionality�are described. To develop quantitative definitions of these characteristics, a general framework for the problem of absolute verification (AV) is ...
Ceiling and Visibility Forecasts via Neural Networks
Statistical postprocessing of numerical model output can improve forecast quality, especially when model output is combined with surface observations. In this article, the development of nonlinear postprocessors for the prediction of ceiling and ...
Caren Marzban; Stephen Leyton; Brad Colman
Annual Energy Outlook Forecast Evaluation 2005
Forecast Evaluation 2005 Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 Annual Energy Outlook Forecast Evaluation 2005 * Then Energy Information Administration (EIA) produces projections of energy supply and demand each year in the Annual Energy Outlook (AEO). The projections in the AEO are not statements of what will happen but of what might happen, given the assumptions and methodologies used. The projections are business-as-usual trend projections, given known technology, technological and demographic trends, and current laws and regulations. Thus, they provide a policy-neutral reference case that can be used to analyze policy initiatives. EIA does not propose or advocate future legislative and regulatory changes. All laws are assumed to remain as currently enacted; however, the impacts of emerging regulatory changes, when defined, are reflected.
energy data + forecasting | OpenEI Community
energy data + forecasting energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in formulating policies and energy plans based on easy to use forecasting tools, visualizations, sankey diagrams, and open data. The platform will live on OpenEI and this community was established to initiate discussion around continuous development of this tool, integrating it with new datasets, and connecting with the community of users who will want to contribute data to the tool and use the tool for planning purposes. Links: FRED beta demo energy data + forecasting Syndicate content 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2084382122
Wind Speed Forecasting for Power System Operation
In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system operation in terms of the efficiency of the system. The goal of this dissertation is to develop advanced statistical wind speed predictive models to reduce the uncertainties in wind, especially the short-term future wind speed. Moreover, a criterion is proposed to evaluate the performance of models. Cost reduction in power system operation, as proposed, is more realistic than prevalent criteria, such as, root mean square error (RMSE) and absolute mean error (MAE). Two advanced space-time statistical models are introduced for short-term wind speed forecasting. One is a modified regime-switching, space-time wind speed fore- casting model, which allows the forecast regimes to vary according to the dominant wind direction and seasons. Thus, it avoids a subjective choice of regimes. The other one is a novel model that incorporates a new variable, geostrophic wind, which has strong influence on the surface wind, into one of the advanced space-time statistical forecasting models. This model is motivated by the lack of improvement in forecast accuracy when using air pressure and temperature directly. Using geostrophic wind in the model is not only critical, it also has a meaningful geophysical interpretation. The importance of model evaluation is emphasized in the dissertation as well. Rather than using RMSE or MAE, the performance of both wind forecasting models mentioned above are assessed by economic benefits with real wind farm data from Pacific Northwest of the U.S and West Texas. Wind forecasts are incorporated into power system economic dispatch models, and the power system operation cost is used as a loss measure for the performance of the forecasting models. From another perspective, the new criterion leads to cost-effective scheduling of system-wide wind generation with potential economic benefits arising from the system-wide generation of cost savings and ancillary services cost savings. As an illustration, the integrated forecasts and economic dispatch framework are applied to the Electric Reliability Council of Texas (ERCOT) equivalent 24- bus system. Compared with persistence and autoregressive models, the first model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars. For the second model, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model.
Zhu, Xinxin
Wind Energy Forecasting Technology Update: 2004
This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.
A q-deformed nonlinear map
A scheme of q-deformation of nonlinear maps is introduced. As a specific example, a q-deformation procedure related to the Tsallis q-exponential function is applied to the logistic map. Compared to the canonical logistic map, the resulting family of q-logistic maps is shown to have a wider spectrum of interesting behaviours, including the co-existence of attractors -- a phenomenon rare in one dimensional maps.
Ramaswamy Jaganathan; Sudeshna Sinha
Cosmic string induced CMB maps
We compute maps of CMB temperature fluctuations seeded by cosmic strings using high resolution simulations of cosmic strings in a Friedmann-Robertson-Walker universe. We create full-sky, 18 deg. and 3 deg. CMB maps, including the relevant string contribution at each resolution from before recombination to today. We extract the angular power spectrum from these maps, demonstrating the importance of recombination effects. We briefly discuss the probability density function of the pixel temperatures, their skewness, and kurtosis.
Landriau, M. [Max-Planck-Institut fuer extraterrestrische Physik, Giessenbachstrasse 1, 85748 Garching (Germany); Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Shellard, E. P. S. [Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA (United Kingdom)
Analysis of PG&E`s residential end-use metered data to improve electricity demand forecasts -- final report
This report summarizes findings from a unique project to improve the end-use electricity load shape and peak demand forecasts made by the Pacific Gas and Electric Company (PG&E) and the California Energy Commission (CEC). First, the direct incorporation of end-use metered data into electricity demand forecasting models is a new approach that has only been made possible by recent end-use metering projects. Second, and perhaps more importantly, the joint-sponsorship of this analysis has led to the development of consistent sets of forecasting model inputs. That is, the ability to use a common data base and similar data treatment conventions for some of the forecasting inputs frees forecasters to concentrate on those differences (between their competing forecasts) that stem from real differences of opinion, rather than differences that can be readily resolved with better data. The focus of the analysis is residential space cooling, which represents a large and growing demand in the PG&E service territory. Using five years of end-use metered, central air conditioner data collected by PG&E from over 300 residences, we developed consistent sets of new inputs for both PG&E`s and CEC`s end-use load shape forecasting models. We compared the performance of the new inputs both to the inputs previously used by PG&E and CEC, and to a second set of new inputs developed to take advantage of a recently added modeling option to the forecasting model. The testing criteria included ability to forecast total daily energy use, daily peak demand, and demand at 4 P.M. (the most frequent hour of PG&E`s system peak demand). We also tested the new inputs with the weather data used by PG&E and CEC in preparing their forecasts.
Eto, J.H.; Moezzi, M.M.
Site Map
Home » Site Map Home » Site Map Site Map Home About Overview NERSC Mission Contact us Staff Center Leadership Sudip Dosanjh Select Publications Jeff Broughton Katie Antypas John Shalf Francesca Verdier Center Administration James Craw Norma Early Jeff Grounds Betsy MacGowan Zaida McCunney Lynn Rippe Suzanne Stevenson David Tooker Center Communications Jon Bashor Linda Vu Margie Wylie Kathy Kincade Advanced Technologies Group Nicholas Wright Brian Austin Research Projects Matthew Cordery Christopher Daley Analytics Group Peter Nugent David Camp Hank Childs Harinarayan Krishnan Burlen Loring Joerg Meyer Prabhat Oliver Ruebel Daniela Ushizima Gunther Weber Yushu Yao Computational Systems Group Jay Srinivasan James Botts Scott Burrow Tina Butler Nick Cardo Tina Declerck Ilya Malinov David Paul Larry Pezzaglia Iwona Sakrejda
Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast
Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan
Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast
Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast Summary............................................................................................................ 2 Sixth Power Plan Demand Forecast................................................................................................ 4 Demand Forecast Range
Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast
Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range
Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast
Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast.................................................................................. 19 Forecasting Commercial Floor Space Requirements
Developing a Practical Forecasting Screener for Domestic Violence Incidents for the Los Angeles County Sheriff's Department
Developing a Practical Forecasting Screener for Domesticdevelop a state-of-the- art forecasting tool to predict suchto be used solely for forecasting. Whether these perceptions
Berk, Richard; He, Yan; Sorenson, Susan B.
Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow
econ. WEATHER AND FORECASTING Environmental decisions (1993seasonal, and WEATHER AND FORECASTING V OLUME 19 spatialfor details. WEATHER AND FORECASTING V OLUME 19 T ABLE 2.
Simpson, James J; Dettinger, M D; Gehrke, F; McIntire, T J; Hufford, G L
Richard Berk; Yan He; Susan B. Sorenson
Reliable before-fabrication forecasting of expected surface slope distributions for x-ray optics
Reliable before-fabrication forecasting of expected surfacefor highly reliable forecasting of the expected surfaceaccuracy of this type of forecasting by comparing the power
Yashchuk, Yekaterina V.
Berk, Richard; Sorenson, Susan B.; He, Yan
Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework
Calibrated probabilistic forecasting using ensemble modelSutcliffe (1970), River flow forecasting through conceptuala Distributed Flood Forecasting Model with Input Uncertainty
Li, M.
Implementing Innovation in Planning Practice: The Case of Travel Demand Forecasting
Urban Travel Demand Forecasting Project. Institute ofTRB. Metropolitan Travel Forecasting: Current Practice andPurvis. Regional Travel Forecasting Model System for the San
Newmark, Gregory Louis
Controlling inventory by improving demand forecasting within the alcoholic beverage industry : a case study.
??This thesis explores how combing statistical demand forecasting methods and causal forecasting methods with judgmental forecasts via a Sales and Operation Planning process can improve� (more)
Deng, Xiaomu
Bayesian Statistics and Its Application to Quantitative Trait Loci Mapping.
??Quantitative trait loci (QTL) mapping is one of the applications of statistics in genetics.This dissertation focuses two problems on QTL mapping which include a newpermutation� (more)
Che, Xiaohong
Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)
Reports and Publications (EIA)
The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.
Information Center
Forecasting Solar Radiation -- Preliminary Evaluation of an Approach Based upon the National Forecast Database
Our objective is to develop, and undertake a preliminary evaluation of a simple solar radiation forecast model using sky cover predictions from the National Digital Forecast Database as an input. This report describes the model and presents a limited evaluation of its performance against ground-measured and satellite-derived irradiances in Albany, New York.
Perez, R.; Moore, K.; Wilcox, S.; Renne, D.; Zelenka, A.
Maintaining the Role of Humans in the Forecast Process: Analyzing the Psyche of Expert Forecasters
The Second Forum on the Future Role of the Human in the Forecast Process occurred on 2�3 August 2005 at the American Meteorological Society's Weather Analysis and Forecasting Conference in Washington, D.C. The forum consisted of three sessions. ...
Neil A. Stuart; David M. Schultz; Gary Klein
Mid-range energy-forecasting system: structure, forecasts, and critique
The Mid-Range Energy Forecasting System (MEFS) is a large-scale, interdisciplinary model of the US energy system maintained by the US Department of Energy. MEFS provides long-run regional forecasts of delivered prices for electricity, coal, gasoline, residual, distillate, and natural gas. A number of sets of MEFS forecasts are usually issued, each set corresponding to a different scenario. Because it forecasts prices and since these forecasts are regularly disseminated, MEFS is of considerable practical interest. A critical guide of the model's output for potential users is provided in this paper. The model's logic is described, the latest forecasts from MEFS are presented, and the reasonableness of both the forecasts and the methodology are critically evaluated. The manner in which MEFS interfaces with the Oil Market Simulation Model, which forecasts crude oil price, is also discussed. The evaluation concludes that while there are serious problems with MEFS, selective use can prove very helpful. 17 references, 1 figure, 2 tables.
DeSouza, G.
Manhattan Project: Maps
Office of Scientific and Technical Information (OSTI)
MAPS MAPS Resources Scroll down to view thumbnails of each map. Leslie Groves looks at a map of Japan. Manhattan Project: General Manhattan Project Facilities Places map "Signature Facilities of the MED" map Hanford Hanford map Hanford (black and white) map Hanford Site Diagram Hanford Site Location Map Hanford: Native Peoples map Hanford: Town map Los Alamos Map of Los Alamos, New Mexico Los Alamos: "Tech Area" map Oak Ridge Map of Clinton Engineer Works, Oak Ridge Clinton Engineer Works, Oak Ridge (black and white) map Oak Ridge: Projected Site for Atomic Production Plants, 1942, map Other Flight paths for Hiroshima and Nagasaki missions map Map of the Trinity Test Site Post-War U.S. Nuclear Tests map Manhattan Project Facilities Manhattan Project Facilities
Model documentation report: Short-term Integrated Forecasting System demand model 1985. [(STIFS)
The Short-Term Integrated Forecasting System (STIFS) Demand Model consists of a set of energy demand and price models that are used to forecast monthly demand and prices of various energy products up to eight quarters in the future. The STIFS demand model is based on monthly data (unless otherwise noted), but the forecast is published on a quarterly basis. All of the forecasts are presented at the national level, and no regional detail is available. The model discussed in this report is the April 1985 version of the STIFS demand model. The relationships described by this model include: the specification of retail energy prices as a function of input prices, seasonal factors, and other significant variables; and the specification of energy demand by product as a function of price, a measure of economic activity, and other appropriate variables. The STIFS demand model is actually a collection of 18 individual models representing the demand for each type of fuel. The individual fuel models are listed below: motor gasoline; nonutility distillate fuel oil, (a) diesel, (b) nondiesel; nonutility residual fuel oil; jet fuel, kerosene-type and naphtha-type; liquefied petroleum gases; petrochemical feedstocks and ethane; kerosene; road oil and asphalt; still gas; petroleum coke; miscellaneous products; coking coal; electric utility coal; retail and general industry coal; electricity generation; nonutility natural gas; and utility petroleum. The demand estimates produced by these models are used in the STIFS integrating model to produce a full energy balance of energy supply, demand, and stock change. These forecasts are published quarterly in the Outlook. Details of the major changes in the forecasting methodology and an evaluation of previous forecast errors are presented once a year in Volume 2 of the Outlook, the Methodology publication.
SRNL - Directions and Maps
Map of SRS, with Georgia and South Carolina Map of SRS, with Georgia and South Carolina Directions and Maps The Savannah River National Laboratory is located at the Savannah River Site , a 310 square mile site located in the southeastern coastal area of the United States in the state of South Carolina. It is bordered to the west by the Savannah River and Georgia, and is close to several major cities, including Augusta and Savannah (Ga.), Columbia, Greenville, and Charleston (S.C.). It is in an area residents refer to as the Central Savannah River Area, or CSRA. The Aiken County Technology Laboratory (which houses SRNL's biotechnology laboratories and certain waste treatment technology laboratories) and the Center for Hydrogen Research are located at Aiken County's Savannah River Research Campus, located adjacent to SRS.
Forecast of Contracting and Subcontracting Opportunities, Fiscal year 1995
Welcome to the US Department of Energy`s Forecast of Contracting and Subcontracting Opportunities. This forecast, which is published pursuant to Public Low 100--656, ``Business Opportunity Development Reform Act of 1988,`` is intended to inform small business concerns, including those owned and controlled by socially and economically disadvantaged individuals, and women-owned small business concerns, of the anticipated fiscal year 1995 contracting and subcontracting opportunities with the Department of Energy and its management and operating contractors and environmental restoration and waste management contractors. This document will provide the small business contractor with advance notice of the Department`s procurement plans as they pertain to small, small disadvantaged and women-owned small business concerns.Opportunities contained in the forecast support the mission of the Department, to serve as advocate for the notion`s energy production, regulation, demonstration, conservation, reserve maintenance, nuclear weapons and defense research, development and testing, when it is a national priority. The Department`s responsibilities include long-term, high-risk research and development of energy technology, the marketing of Federal power, and maintenance of a central energy data collection and analysis program. A key mission for the Department is to identify and reduce risks, as well as manage waste at more than 100 sites in 34 states and territories, where nuclear energy or weapons research and production resulted in radioactive, hazardous, and mixed waste contamination. Each fiscal year, the Department establishes contracting goals to increase contracts to small business concerns and meet our mission objectives.
Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices
forecasts (or any other forecast, for that matter) in makingcase natural gas price forecast, but to also examine a wideAEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices
Bolinger, Mark A.
Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets
the accuracy of two methods to forecast natural gas prices:forecasting models along with the AEO forecast. Appendix ATable 1. Forecast Year AEO Predicted Price from 1996-2003
Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry
Communicating Uncertainty in Weather Forecasts: A Survey of the U.S. Public
Weather forecasts are inherently uncertain, and meteorologists have information about weather forecast uncertainty that is not readily available to most forecast users. Yet effectively communicating forecast uncertainty to nonmeteorologists ...
Rebecca E. Morss; Julie L. Demuth; Jeffrey K. Lazo
Annual Energy Outlook Forecast Evaluation Annual Energy Outlook Forecast Evaluation Actual vs. Forecasts Available formats Excel (.xls) for printable spreadsheet data (Microsoft Excel required) PDF (Acrobat Reader required) Table 2. Total Energy Consumption HTML, Excel, PDF Table 3. Total Petroleum Consumption HTML, Excel, PDF Table 4. Total Natural Gas Consumption HTML, Excel, PDF Table 5. Total Coal Consumption HTML, Excel, PDF Table 6. Total Electricity Sales HTML, Excel, PDF Table 7. Crude Oil Production HTML, Excel, PDF Table 8. Natural Gas Production HTML, Excel, PDF Table 9. Coal Production HTML, Excel, PDF Table 10. Net Petroleum Imports HTML, Excel, PDF Table 11. Net Natural Gas Imports HTML, Excel, PDF Table 12. Net Coal Exports HTML, Excel, PDF Table 13. World Oil Prices HTML, Excel, PDF
Oil Markets Oil Markets IEO2005 projects that world crude oil prices in real 2003 dollars will decline from their current level by 2010, then rise gradually through 2025. In the International Energy Outlook 2005 (IEO2005) reference case, world demand for crude oil grows from 78 million barrels per day in 2002 to 103 million barrels per day in 2015 and to just over 119 million barrels per day in 2025. Much of the growth in oil consumption is projected for the emerging Asian nations, where strong economic growth results in a robust increase in oil demand. Emerging Asia (including China and India) accounts for 45 percent of the total world increase in oil use over the forecast period in the IEO2005 reference case. The projected increase in world oil demand would require an increment to world production capability of more than 42 million barrels per day relative to the 2002 crude oil production capacity of 80.0 million barrels per day. Producers in the Organization of Petroleum Exporting Countries (OPEC) are expected to be the major source of production increases. In addition, non-OPEC supply is expected to remain highly competitive, with major increments to supply coming from offshore resources, especially in the Caspian Basin, Latin America, and deepwater West Africa. The estimates of incremental production are based on current proved reserves and a country-by-country assessment of ultimately recoverable petroleum. In the IEO2005 oil price cases, the substantial investment capital required to produce the incremental volumes is assumed to exist, and the investors are expected to receive at least a 10-percent return on investment.
Do Investors Forecast Fat Firms? Evidence from the Gold Mining Industry
Economists� Gold Price Forecasts,� Australian Journal ofDo Investors Forecast Fat Firms? Evidence from the Gold
Borenstein, Severin; Farrell, Joseph
The Effect of Probabilistic Information on Threshold Forecasts
The study reported here asks whether the use of probabilistic information indicating forecast uncertainty improves the quality of deterministic weather decisions. Participants made realistic wind speed forecasts based on historical information in ...
Susan Joslyn; Karla Pak; David Jones; John Pyles; Earl Hunt
Proper Scores for Probability Forecasts Can Never Be Equitable
Verification is an important part of any forecasting system. It is usually achieved by computing the value of some measure or score that indicates how good the forecasts are. Many possible verification measures have been proposed, and to choose ...
Ian T. Jolliffe; David B. Stephenson
How Essential is Hydrologic Model Calibration to Seasonal Streamflow Forecasting?
Hydrologic model calibration is usually a central element of streamflow forecasting based on the ensemble streamflow prediction (ESP) method. Evaluation measures of forecast errors such as root-mean-square error (RMSE) are heavily influenced by ...
Xiaogang Shi; Andrew W. Wood; Dennis P. Lettenmaier
Empirical Correction of the NCEP Global Forecast System
This paper examines the extent to which an empirical correction method can improve forecasts of the National Centers for Environmental Prediction (NCEP) operational Global Forecast System. The empirical correction is based on adding a forcing ...
Xiaosong Yang; Timothy DelSole; Hua-Lu Pan
J.P. Finley: The First Severe Storms Forecaster
During the 19th century, while others were debating about the theory and morphology of tornadoes, Finley set out to prove that tornadoes, like other weather phenomena, could be forecast. He developed forecast rules and made experimental ...
Joseph G. Galway
On Peirce�s Motivation for Equitability in Forecast Verification
In 1884, Peirce proposed a new two-category score for deterministic forecasts. The score was motivated by the desire to estimate the number of correct forecasts based on sound reasoning, without being sensitive to the frequency distribution of any ...
Mark J. Rodwell
Factors Influencing Skill Improvements in the ECMWF Forecasting System
During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. There are three major contributing factors: 1) improvements in the forecast model, 2) improvements in the data assimilation, and 3) the increased number of ...
Linus Magnusson; Erland K�ll�n
Using Wind Anomalies to Forecast East Coast Winter Storms
Forecasting major winter storms is a critical function for all weather services. Conventional model-derived fields from numerical weather prediction models most frequently utilized by operational forecasters, such as pressure level geopotential ...
Neil A. Stuart; Richard H. Grumm
Downscaling Ensemble Weather Predictions for Improved Week-2 Hydrologic Forecasting
This study investigates the use of large-scale ensemble weather predictions provided by the National Centers for Environmental Prediction (NCEP) Global Forecast System [GFS; formerly known as Medium-Range Forecast (MRF)] for improving week-2 ...
Xiaoli Liu; Paulin Coulibaly
The Effectiveness of Weather Forecasts in Decision Making: An Example
Decision models involving prescribed fire (the use of fire as a silvicultural tool) were used to analyze the utility of four types of weather information as forecasts: climatology, current weather observations (used as a persistence forecast), ...
R. William Furman
The Science of NOAA's Operational Hydrologic Ensemble Forecast Service
NOAA's National Weather Service (NWS) is implementing a short- to long-range Hydrologic Ensemble Forecast Service (HEFS). The HEFS addresses the need to quantify uncertainty in hydrologic forecasts for flood risk management, water supply management, ...
Julie Demargne; Limin Wu; Satish Regonda; James Brown; Haksu Lee; Minxue He; Dong-Jun Seo; Robert Hartman; Henry D. Herr; Mark Fresch; John Schaake; Yuejian Zhu
Confidence Builders: Evaluating Seasonal Climate Forecasts from User Perspectives
Water managers, cattle ranchers, and wildland fire managers face several barriers to effectively using climate forecasts. Repeatedly, these decision makers state that they lack any quantitative basis for evaluating forecast credibility. That is ...
Holly C. Hartmann; Thomas C. Pagano; S. Sorooshian; R. Bales
Threshold Relative Humidity Duration Forecasts for Plant Disease Prediction
Duration of high relative humidity periods is an important component of many plant disease development models. Performance of forecasts of this quantity, based on the model output statistics 3-h temperature and dewpoint forecasts produced by the ...
Daniel S. Wilks; Karin W. Shen
The Canadian Regional Data Assimilation and Forecasting System
This paper describes the recent changes to the regional data assimilation and forecasting system at the Canadian Meteorological Center. A major aspect is the replacement of the currently operational global variable resolution forecasting approach ...
Luc Fillion; Monique Tanguay; Ervig Lapalme; Bertrand Denis; Michel Desgagne; Vivian Lee; Nils Ek; Zhuo Liu; Manon Lajoie; Jean-Fran�ois Caron; Christian Pag�
Architect Of Severe Storm Forecasting: Colonel Robert C. Miller
The career of severe storm forecaster and teacher Colonel Robert Miller (1920�98) is historicallyreviewed and evaluated. His pathway to the position of recognized authority in severe storm forecasting is examined in light of his early education ...
John M. Lewis; Robert A. Maddox; Charlie A. Crisp
Forecasting the 12�14 March 1993 Superstorm
This paper describes the decision-making process used by the forecasters in the National Meteorological Center's Meteorological Operations Division and in Weather Forecast Offices of the National Weather Service to provide the successful ...
Louis W. Uccellini; Paul J. Kocin; Russell S. Schneider; Paul M. Stokols; Russell A. Dorr
A Nested Spectral Model for Hurricane Track Forecasting
A numerical method for analysing and forecasting a wide range of horizontal scales of motion is tested in a barotropic hurricane track forecast model. The numerical method uses cubic B-spline representations of variables on nested domains. The ...
Mark Demaria; Sim D. Aberson; Katsuyuki V. Ooyama; Stephen J. Lord
Does Distance from the Forecast Site Affect Skill?
An outstanding issue in the assessment of forecast skill (and value) is whether any advantage that can be obtained through regional knowledge not readily available to distant forecasters supersedes the leveling effect of information obtained by ...
Paul J. Roebber; Lance F. Bosart; Gregory S. Forbes
Skill in Precipitation Forecasting in the National Weather Service
All known long-term records of forecasting performance for different types of precipitation forecasts in the National Weather Service were examined for relative skill and secular trends in skill. The largest upward trends were achieved by local ...
Jerome P. Charba; William H. Klein
Extended-Range Probability Forecasts Based on Dynamical Model Output
A probability forecast has advantages over a deterministic forecast as the former offers information about the probabilities of various possible future states of the atmosphere. As physics-based numerical models find their success in modern ...
Jianfu Pan; Huug van den Dool
Potential to Improve Forecasting Accuracy: Advances in Supply Chain Management
Forecasting is a necessity almost in any operation. However, the tools of forecasting are still primitive in view of the great strides made by research and the increasing abundance of data made possible by automatic ...
The Application of Signal Detection Theory to Weather Forecasting Behavior
A variety of measures are used to judge the skill and accuracy with which forecasters predict the weather and to verify forecasts: Such measures can confound accuracy with decision strategy and sometimes give conflicting indications of ...
Lewis O. Harvey Jr.; Kenneth R. Hammond; Cynthia M. Lusk; Ernest F. Mross
Univariate Modeling and Forecasting of Monthly Energy Demand Time Series
in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand
Correcting Errors in Streamflow Forecast Ensemble Mean and Spread
When hydrological models are used for probabilistic streamflow forecasting in the Ensemble Streamflow Prediction (ESP) framework, the deterministic components of the approach can lead to errors in the estimation of forecast uncertainty, as ...
Andrew W. Wood; John C. Schaake
Potential Economic Value of Ensemble-Based Surface Weather Forecasts
The possible economic value of the quantification of uncertainty in future ensemble-based surface weather forecasts is investigated using a formal, idealized decision model. Current, or baseline, weather forecasts are represented by probabilistic ...
Daniel S. Wilks; Thomas M. Hamill
Bayesian Approach to Decision Making Using Ensemble Weather Forecasts
The economic value of ensemble-based weather or climate forecasts is generally assessed by taking the ensembles at �face value.� That is, the forecast probability is estimated as the relative frequency of occurrence of an event among a limited ...
Richard W. Katz; Martin Ehrendorfer
Comparative Evaluation of Weather Forecasting Systems: Sufficiency, Quality, and Accuracy
The concept of sufficiency, originally introduced in the context of the comparison of statistical experiments, has recently been shown to provide a coherent basis for comparative evaluation of forecasting systems. Specifically, forecasting system ...
Martin Ehrendorfer; Allan H. Murphy
A Bayesian Approach to Predictor Selection for Seasonal Streamflow Forecasting
Statistical methods commonly used for forecasting climate and streamflows require the selection of appropriate predictors. Poorly designed predictor selection procedures can result in poor forecasts for independent events. This paper introduces a ...
David E. Robertson; Q. J. Wang
Interpretation of Rank Histograms for Verifying Ensemble Forecasts
Rank histograms are a tool for evaluating ensemble forecasts. They are useful for determining the reliability of ensemble forecasts and for diagnosing errors in its mean and spread. Rank histograms are generated by repeatedly tallying the rank of ...
One-Month Forecast Experiments�without Anomaly Boundary Forcings
A series of one-month forecasts were carried out for eight January cases, using a particular prediction model and prescribing climatological sea-surface temperature as the boundary condition. Each forecast is a stochastic prediction that consists ...
K. Miyakoda; J. Sirutis; J. Ploshay
Objective Limits on Forecasting Skill of Rare Events
A method for determining baselines of skill for the purpose of the verification of rare-event forecasts is described and examples are presented to illustrate the sensitivity to parameter choices. These �practically perfect� forecasts are designed ...
Nathan M. Hitchens; Harold E. Brooks; Michael P. Kay
Evaluation of Eta�RSM Ensemble Probabilistic Precipitation Forecasts
The accuracy of short-range probabilistic forecasts of quantitative precipitation (PQPF) from the experimental Eta�Regional Spectral Model ensemble is compared with the accuracy of forecasts from the Nested Grid Model�s model output statistics (...
Thomas M. Hamill; Stephen J. Colucci
Verification of Eta�RSM Short-Range Ensemble Forecasts
Motivated by the success of ensemble forecasting at the medium range, the performance of a prototype short-range ensemble forecast system is examined. The ensemble dataset consists of 15 case days from September 1995 through January 1996. There ...
Making Forecasts Meaningful: Explanations of Problematic Predictions in Northeast Brazil
This study illustrates the need to consider the multiple interpretations and experiences that influence how climate forecasts are evaluated in local contexts when assessing how useful forecasts can be for increasing the resilience of rural ...
An Improved Operational System for Forecasting Precipitation Type
A Model Output Statistics system for forecasting the conditional probability of precipitation type (PoPT) became operational within the National Weather Service in September 1978. Forecasts are provided for three precipitation type categories: ...
Joseph R. Bocchieri; George J. Maglaras
River Forecast Application for Water Management: Oil and Water?
Managing water resources generally and managing reservoir operations specifically have been touted as opportunities for applying forecasts to improve decision making. Previous studies have shown that the application of forecasts into water ...
Kevin Werner; Kristen Averyt; Gigi Owen
Statistical Extension of the National Hurricane Center 5-Day Forecasts
U.S. National Hurricane Center (NHC) forecasts for tropical cyclone tracks and wind speeds are extended in time to produce spatially disaggregated probability forecasts for landfall location and intensity, using a weighted bootstrap procedure. ...
Daniel S. Wilks; Charles J. Neumann; Miles B. Lawrence
Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting
Operational flood forecasting requires that accurate estimates of the uncertainty associated with model-generated streamflow forecasts be provided along with the probable flow levels. This paper demonstrates a stochastic ensemble implementation ...
Jasper A. Vrugt; Hoshin V. Gupta; Breannd�n� Nuall�in; Willem Bouten
A web-based Hong Kong tourism demand forecasting system
Accurate predictions of future business activities are important for business decision-making. As a consequence, powerful and simple forecasting processes are urgently pursued by decision-makers. This study presents a tourism demand forecasting system ...
Haiyan Song; Zixuan Gao; Xinyan Zhang; Shanshan Lin