Sample records for arctic sea ice

1. Arctic tides from GPS on sea ice

Kildegaard Rose, Stine; Skourup, Henriette; Forsberg, René

The presence of sea-ice in the Arctic Ocean plays a significant role in the Arctic climate. Sea ice dampens the ocean tide amplitude with the result that global tidal models which use only astronomical data perform less accurately in the polar regions. This study presents a kinematic processing of...... Global Positioning System (GPS) buoys placed on sea-ice at five different sites north of Greenland for the study of sea level height and tidal analysis to improve tidal models in the Central Arctic. The GPS measurements are compared with the Arctic tidal model AOTIM-5, which assimilates tide-gauges and...

2. Arctic Landfast Sea Ice 1953-1998

National Oceanic and Atmospheric Administration, Department of Commerce — The files in this data set contain landfast sea ice data (monthly means) gathered from both Russian Arctic and Antarctic Research Institute (AARI) and Canadian Ice...

3. Predictability of the Arctic sea ice edge

Goessling, H. F.; Tietsche, S.; Day, J. J.; Hawkins, E.; Jung, T.

2016-02-01

Skillful sea ice forecasts from days to years ahead are becoming increasingly important for the operation and planning of human activities in the Arctic. Here we analyze the potential predictability of the Arctic sea ice edge in six climate models. We introduce the integrated ice-edge error (IIEE), a user-relevant verification metric defined as the area where the forecast and the "truth" disagree on the ice concentration being above or below 15%. The IIEE lends itself to decomposition into an absolute extent error, corresponding to the common sea ice extent error, and a misplacement error. We find that the often-neglected misplacement error makes up more than half of the climatological IIEE. In idealized forecast ensembles initialized on 1 July, the IIEE grows faster than the absolute extent error. This means that the Arctic sea ice edge is less predictable than sea ice extent, particularly in September, with implications for the potential skill of end-user relevant forecasts.

4. Arctic and Southern Ocean Sea Ice Concentrations

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly sea ice concentration for Arctic (1901 to 1995) and Southern oceans (1973 to 1990) were digitized on a standard 1-degree grid (cylindrical projection) to...

5. Influence of sea ice on Arctic precipitation.

Kopec, Ben G; Feng, Xiahong; Michel, Fred A; Posmentier, Eric S

2016-01-01

Global climate is influenced by the Arctic hydrologic cycle, which is, in part, regulated by sea ice through its control on evaporation and precipitation. However, the quantitative link between precipitation and sea ice extent is poorly constrained. Here we present observational evidence for the response of precipitation to sea ice reduction and assess the sensitivity of the response. Changes in the proportion of moisture sourced from the Arctic with sea ice change in the Canadian Arctic and Greenland Sea regions over the past two decades are inferred from annually averaged deuterium excess (d-excess) measurements from six sites. Other influences on the Arctic hydrologic cycle, such as the strength of meridional transport, are assessed using the North Atlantic Oscillation index. We find that the independent, direct effect of sea ice on the increase of the percentage of Arctic sourced moisture (or Arctic moisture proportion, AMP) is 18.2 ± 4.6% and 10.8 ± 3.6%/100,000 km(2) sea ice lost for each region, respectively, corresponding to increases of 10.9 ± 2.8% and 2.7 ± 1.1%/1 °C of warming in the vapor source regions. The moisture source changes likely result in increases of precipitation and changes in energy balance, creating significant uncertainty for climate predictions. PMID:26699509

6. Contrasting Arctic and Antarctic sea ice temperatures

Vancoppenolle, Martin; Raphael, Marilyn; Rousset, Clément; Vivier, Frédéric; Moreau, Sébastien; Delille, Bruno; Tison, Jean-Louis

2016-04-01

Sea ice temperature affects the sea ice growth rate, heat content, permeability and habitability for ice algae. Large-scale simulations with NEMO-LIM suggest large ice temperature contrasts between the Arctic and the Antarctic sea ice. First, Antarctic sea ice proves generally warmer than in the Arctic, in particular during winter, where differences reach up to ~10°C. Second, the seasonality of temperature is different among the two hemispheres: Antarctic ice temperatures are 2-3°C higher in spring than they are in fall, whereas the opposite is true in the Arctic. These two key differences are supported by the available ice core and mass balance buoys temperature observations, and can be attributed to differences in air temperature and snow depth. As a result, the ice is found to be habitable and permeable over much larger areas and much earlier in late spring in the Antarctic as compared with the Arctic, which consequences on biogeochemical exchanges in the sea ice zone remain to be evaluated.

7. The Last Arctic Sea Ice Refuge

Pfirman, S. L.; Tremblay, B.; Newton, R.; Fowler, C.

2010-12-01

Summer sea ice may persist along the northern flank of Canada and Greenland for decades longer than the rest of the Arctic, raising the possibility of a naturally formed refugium for ice-associated species. Observations and models indicate that some ice in this region forms locally, while some is transported to the area by winds and ocean currents. Depending on future changes in melt patterns and sea ice transport rates, both the central Arctic and Siberian shelf seas may be sources of ice to the region. An international system of monitoring and management of the sea ice refuge, along with the ice source regions, has the potential to maintain viable habitat for ice-associated species, including polar bears, for decades into the future. Issues to consider in developing a strategy include: + the likely duration and extent of summer sea ice in this region based on observations, models and paleoenvironmental information + the extent and characteristics of the “ice shed” contributing sea ice to the refuge, including its dynamics, physical and biological characteristics as well as potential for contamination from local or long-range sources + likely assemblages of ice-associated species and their habitats + potential stressors such as transportation, tourism, resource extraction, contamination + policy, governance, and development issues including management strategies that could maintain the viability of the refuge.

8. Arctic sea ice balance and climate

Proxy data and local historical records show that sea ice extent has undergone large secular variations over past millennia and centuries, for reasons that are only qualitatively understood. Since the onset of systematic observations in situ and satellites, the record shows a remarkable constancy of the annual cycle of the arctic sea ice cover. This cycle is described by a continuity equation that is used to discuss the mechanisms relating ice extent and thickness to climate, and to illustrate how ice formation, transport, and melting combine to produce the seasonal cycle of sea ice cover. The heat balances and stresses at the surface and bottom of the sea ice are external forcing functions with small-scale and large-scale feedbacks. Examples are the stable stratification of the ocean boundary layer caused by bottom melting and surface drainage which suppress the vertical ocean heat flux, and the arctic summer stratus which forms over ice-covered ocean regions and limits surface melting. Recent efforts to model the seasonal cycle of sea ice in the Arctic are discussed in light of the observational record. A promising new development is the incorporation of satellite data as explicit variables carried in dynamic-thermodynamic ice models. Of special interest in the context of climate is the fresh water budget of the Arctic Basin. Its largest components, the runoff generated by mid-latitude precipitation over the Eurasian continent, and the ice export driven by the wind field over the Arctic Basin, have no immediately apparent connection. Taking into account all other components of the fresh water balance, Aagaard and Carmack estimate that the contemporary influx and outflux of fresh water at the perimeter of the Arctic Basin are equal. The unraveling of the mechanisms responsible for this equality, and the consequence of a possible imbalance remain challenging questions

9. History of sea ice in the Arctic

Polyak, Leonid; Alley, Richard B.; Andrews, John T.;

2010-01-01

Optimum, and consistently covered at least part of the Arctic Ocean for no less than the last 13–14 million years. Ice was apparently most widespread during the last 2–3 million years, in accordance with Earth’s overall cooler climate. Nevertheless, episodes of considerably reduced sea ice or even......-scale) and lower-magnitude variability. The current reduction in Arctic ice cover started in the late 19th century, consistent with the rapidly warming climate, and became very pronounced over the last three decades. This ice loss appears to be unmatched over at least the last few thousand years and...

10. Arctic sea ice and Eurasian climate: A review

Gao, Yongqi; Sun, Jianqi; Li, Fei; HE Shengping; Sandven, Stein; Yan, Qing; Zhang, Zhongshi; Lohmann, Katja; Keenlyside, Noel; Furevik, Tore; Suo, Lingling

2014-01-01

The Arctic plays a fundamental role in the climate system and has shown significant climate change in recent decades, including the Arctic warming and decline of Arctic sea-ice extent and thickness. In contrast to the Arctic warming and reduction of Arctic sea ice, Europe, East Asia and North America have experienced anomalously cold conditions, with record snowfall during recent years. In this paper, we review current understanding of the sea-ice impacts on the Eurasian climate. Paleo, obser...

11. Comparative Views of Arctic Sea Ice Growth

2000-01-01

12. The early twentieth century warming and winter Arctic sea ice

V. A. Semenov

2012-06-01

Full Text Available The Arctic featured the strongest surface warming over the globe during the recent decades, and the temperature increase was accompanied by a rapid decline in sea ice extent. However, little is known about Arctic sea ice change during the Early Twentieth Century Warming (ETCW during 1920–1940, also a period of a strong surface warming, both globally and in the Arctic. Here, we investigate the sensitivity of Arctic winter surface air temperature (SAT to sea ice during 1875–2008 by means of simulations with an atmospheric general circulation model (AGCM forced by estimates of the observed sea surface temperature (SST and sea ice concentration. The Arctic warming trend since the 1960s is very well reproduced by the model. In contrast, ETCW in the Arctic is hardly captured. This is consistent with the fact that the sea ice extent in the forcing data does not strongly vary during ETCW. AGCM simulations with observed SST but fixed sea ice reveal a strong dependence of winter SAT on sea ice extent. In particular, the warming during the recent decades is strongly underestimated by the model, if the sea ice extent does not decline and varies only seasonally. This suggests that a significant reduction of Arctic sea ice extent may have also accompanied the Early Twentieth Century Warming, pointing toward an important link between anomalous sea ice extent and Arctic surface temperature variability.

13. The early twentieth century warming and winter Arctic sea ice

V. A. Semenov

2012-11-01

Full Text Available The Arctic has featured the strongest surface warming over the globe during the recent decades, and the temperature increase has been accompanied by a rapid decline in sea ice extent. However, little is known about Arctic sea ice change during the early twentieth century warming (ETCW during 1920–1940, also a period of a strong surface warming, both globally and in the Arctic. Here, we investigate the sensitivity of Arctic winter surface air temperature (SAT to sea ice during 1875–2008 by means of simulations with an atmospheric general circulation model (AGCM forced by estimates of the observed sea surface temperature (SST and sea ice concentration. The Arctic warming trend since the 1960s is very well reproduced by the model. In contrast, ETCW in the Arctic is hardly captured. This is consistent with the fact that the sea ice extent in the forcing data does not strongly vary during ETCW. AGCM simulations with observed SST but fixed sea ice reveal a strong dependence of winter SAT on sea ice extent. In particular, the warming during the recent decades is strongly underestimated by the model, if the sea ice extent does not decline and varies only seasonally. This suggests that a significant reduction of winter Arctic sea ice extent may have also accompanied the early twentieth century warming, pointing toward an important link between anomalous sea ice extent and Arctic surface temperature variability.

14. High resolution modelling of the decreasing Arctic sea ice

Madsen, K. S.; Rasmussen, T. A. S.; Blüthgen, Jonas;

2012-01-01

The Arctic sea ice cover has been rapidly decreasing and thinning over the last decade, with minimum ice extent in 2007 and almost as low extent in 2011. This study investigates two aspects of the decreasing ice cover; first the large scale thinning and changing dynamics of the polar sea ice, and...

15. SEDNA: Sea ice Experiment - Dynamic Nature of the Arctic

National Oceanic and Atmospheric Administration, Department of Commerce — The Sea Ice Experiment - Dynamic Nature of the Arctic (SEDNA) is an international collaborative effort to improve the understanding of the interaction between sea...

16. Canadian Ice Service Arctic Regional Sea Ice Charts in SIGRID-3 Format

National Oceanic and Atmospheric Administration, Department of Commerce — The Canadian Ice Service (CIS) produces digital Arctic regional sea ice charts for marine navigation, climate research, and input to the Global Digital Sea Ice Data...

17. Arctic Sea Ice and Its Changes during the Satellite Period

Wang, X.; Liu, Y.; Key, J. R.

2009-12-01

Sea ice is a very important indicator and an effective modulator of regional and global climate change. Changes in sea ice will significantly affect the complex exchanges of momentum, heat, and mass between sea and the atmosphere, along with profound socio-economic influences due to its role in transportation, fisheries, hunting, polar animal habitat. Over the last two decades of the 20th century, the Arctic underwent significant changes in sea ice as part of the accelerated global warming of that period. More accurate, consistent, and detailed ice thickness, extent, and volume data are critical for a wide range of applications including climate change detection, climate modeling, and operational applications such as shipping and hazard mitigation. Satellite data provide an unprecedented opportunity to estimate and monitor Arctic sea ice routinely with relatively high spatial and temporal resolutions. In this study, a One-dimensional Thermodynamic Ice Model (OTIM) has been developed to estimate sea ice thickness based on the surface energy balance at a thermo-equilibrium state, containing all components of the surface energy balance. The OTIM has been extensively validated against submarine Upward-Looking Sonar (ULS) measurements, meteorological station measurements, and comprehensive numerical model simulations. Overall, OTIM-estimated sea ice thickness is accurate to within about 20% error when compared to submarine ULS ice thickness measurements and Canadian meteorological station measurements for ice less than 3 m. Along with sea ice extent information from the SSM/I, the Arctic sea ice volume can be estimated for the satellite period from 1984 to 2004. The OTIM has been used with satellite data from the extended Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP-x) products for the Arctic sea ice thickness, and sequentially sea ice volume estimations, and following statistical analysis of spatial and temporal distribution and trends in sea

18. Optical properties of melting first-year Arctic sea ice

Light, Bonnie; Perovich, Donald K.; Webster, Melinda A.; Polashenski, Christopher; Dadic, Ruzica

2015-11-01

The albedo and transmittance of melting, first-year Arctic sea ice were measured during two cruises of the Impacts of Climate on the Eco-Systems and Chemistry of the Arctic Pacific Environment (ICESCAPE) project during the summers of 2010 and 2011. Spectral measurements were made for both bare and ponded ice types at a total of 19 ice stations in the Chukchi and Beaufort Seas. These data, along with irradiance profiles taken within boreholes, laboratory measurements of the optical properties of core samples, ice physical property observations, and radiative transfer model simulations are employed to describe representative optical properties for melting first-year Arctic sea ice. Ponded ice was found to transmit roughly 4.4 times more total energy into the ocean, relative to nearby bare ice. The ubiquitous surface-scattering layer and drained layer present on bare, melting sea ice are responsible for its relatively high albedo and relatively low transmittance. Light transmittance through ponded ice depends on the physical thickness of the ice and the magnitude of the scattering coefficient in the ice interior. Bare ice reflects nearly three-quarters of the incident sunlight, enhancing its resiliency to absorption by solar insolation. In contrast, ponded ice absorbs or transmits to the ocean more than three-quarters of the incident sunlight. Characterization of the heat balance of a summertime ice cover is largely dictated by its pond coverage, and light transmittance through ponded ice shows strong contrast between first-year and multiyear Arctic ice covers.

19. Skill improvement of dynamical seasonal Arctic sea ice forecasts

Krikken, Folmer; Schmeits, Maurice; Vlot, Willem; Guemas, Virginie; Hazeleger, Wilco

2016-05-01

We explore the error and improve the skill of the outcome from dynamical seasonal Arctic sea ice reforecasts using different bias correction and ensemble calibration methods. These reforecasts consist of a five-member ensemble from 1979 to 2012 using the general circulation model EC-Earth. The raw model reforecasts show large biases in Arctic sea ice area, mainly due to a differently simulated seasonal cycle and long term trend compared to observations. This translates very quickly (1-3 months) into large biases. We find that (heteroscedastic) extended logistic regressions are viable ensemble calibration methods, as the forecast skill is improved compared to standard bias correction methods. Analysis of regional skill of Arctic sea ice shows that the Northeast Passage and the Kara and Barents Sea are most predictable. These results show the importance of reducing model error and the potential for ensemble calibration in improving skill of seasonal forecasts of Arctic sea ice.

20. Marine Transportation Implications of the Last Arctic Sea Ice Refuge

Brigham, L. W.

2010-12-01

Marine access is increasing throughout the Arctic Ocean and the 'Last Arctic Sea Ice Refuge' may have implications for governance and marine use in the region. Arctic marine transportation is increasing due to natural resource developemnt, increasing Arctic marine tourism, expanded Arctic marine research, and a general linkage of the Arctic to the gloabl economy. The Arctic Council recognized these changes with the release of the Arctic Marine Shipping Assessment of 2009. This key study (AMSA)can be viewed as a baseline assessment (using the 2004 AMSA database), a strategic guide for a host of stakeholders and actors, and as a policy document of the Arctic Council. The outcomes of AMSA of direct relevance to the Ice Refuge are within AMSA's 17 recommendations provided under three themes: Enhancing Arctic Marine Safety, Protecting Arctic People and the Environment, and Building the Arctic Marine Infrastructure. Selected recommendations of importance to the Ice Refuge include: a mandatory polar navigation code; identifying areas of heightened ecological and cultural significance; potential designation of special Arctic marine areas; enhancing the tracking and monitoring of Arctic marine traffic; improving circumpolar environmental response capacity; developing an Arctic search and rescue agreement; and, assessing the effects of marine transportation on marine mammals. A review will be made of the AMSA outcomes and how they can influence the governance, marine use, and future protection of this unique Arctic marine environment.

1. Arctic Tides from GPS on sea-ice

Kildegaard Rose, Stine; Skourup, Henriette; Forsberg, René

2013-01-01

The presence of sea-ice in the Arctic Ocean plays a significant role in the Arctic climate. Sea-ice dampens the ocean tide amplitude with the result that global tidal models perform less accurately in the polar regions. This paper presents, a kinematic processing of global positioning system (GPS......) placed on sea-ice, at six different sites north of Greenland for the preliminary study of sea surface height (SSH), and tidal analysis to improve tide models in the Central Arctic. The GPS measurements are compared with the Arctic tide model AOTIM-5, which assimilates tide-gauges and altimetry data. The...... results show coherence between the GPS buoy measurements, and the tide model. Furthermore, we have proved that the reference ellipsoid of WGS84, can be interpolated to the tidal defined zero level by applying geophysical corrections to the GPS data....

2. Sea ice in the Canadian Arctic in the 21. century

Climate warming will occur first and most intensely in Arctic regions, according to the numerical simulations of future climate performed with different Global Climate Models (GCMs). It includes the simulations performed by the Meteorological Service of Canada. The observations gathered in the Arctic indicate that the present warming has no precedent over the past four hundred years. Since the 1970s, data acquired mainly by satellite indicates that the extent of Arctic sea ice decreased at a rate of approximately three per cent per decade. Over the period 1969-2000, a similar rate of decrease has been observed within Canadian Arctic waters. Over the past forty years, estimates of the thickness of ice in the Arctic, based on submarine measurements, show a 40 per cent decrease. By 2050, if all the conditions remain as they are, the Arctic Ocean could be ice free. The most widely held scientific opinion seems to be that in the future there will be less ice in the Arctic than what was observed in the past, an opinion that is still being debated by scientists. The development of local natural resources and trans-shipment between Europe and Asia could increase dramatically in a future with less ice. Marine transportation in the Canadian Arctic would be expanded. Climatological analysis results of Canadian ice information is presented by the authors, and they have chosen to discuss various probable scenarios related to ice conditions during this century. 13 refs., 8 figs

3. The changing Arctic Sea ice cover : regional and seasonal aspects

Steene, Rebekka Jastamin

2015-01-01

As global climate changes are becoming increasingly evident, increasing air temperatures, melting glaciers, rising sea levels, and decreasing biodiversity is observed at increasing rates worldwide. The Arctic sea ice cover has has become a key indicator of the ongoing global climate change through its substantial decline in both extent and thickness. In this study we show how the observed regression of the Northern Hemisphere sea ice is distributed over different regions of the...

4. Coincident multiscale estimates of Arctic sea ice thickness

Gardner, Joan; Richter-Menge, Jackie; Farrell, Sinead; Brozena, John

2012-02-01

Recent dramatic changes in the characteristics of the Arctic sea ice cover have sparked interest and concern from a wide range of disciplines including socioeconomics, maritime safety and security, and resource management, as well as basic research science. Though driven by different priorities, common to all is the demand for an improved ability to monitor and forecast changes in the sea ice cover. Key to meeting this demand is further improvement in the quality of observations collected from remote platforms. Satellites provide an important platform for instruments designed to monitor basin-wide changes in the volume of the ice cover, a function of ice extent and thickness. Remote techniques to monitor sea ice extent in all seasons are well developed—these observations reveal a dramatic decline in summer sea ice extent since 1979, when satellite records became available. Further, they indicate that the decline has been facilitated by a dramatic decrease in the extent of perennial (i.e., multiyear) ice. Combined estimates of ice thickness derived from submarine records between 1958 and 2000, and Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry from 2003 to 2008, provide the longest-term record of sea ice thickness observations. These data suggest a decrease in the mean overall thickness of the sea ice over a region covering about 38% of the Arctic Ocean.

5. Age characteristics in a multidecadal Arctic sea ice simulation

Hunke, Elizabeth C [Los Alamos National Laboratory; Bitz, Cecllia M [UNIV. OF WASHINGTON

2008-01-01

Results from adding a tracer for age of sea ice to a sophisticated sea ice model that is widely used for climate studies are presented. The consistent simulation of ice age, dynamics, and thermodynamics in the model shows explicitly that the loss of Arctic perennial ice has accelerated in the past three decades, as has been seen in satellite-derived observations. Our model shows that the September ice age average across the Northern Hemisphere varies from about 5 to 8 years, and the ice is much younger (about 2--3 years) in late winter because of the expansion of first-year ice. We find seasonal ice on average comprises about 5% of the total ice area in September, but as much as 1.34 x 10{sup 6} km{sup 2} survives in some years. Our simulated ice age in the late 1980s and early 1990s declined markedly in agreement with other studies. After this period of decline, the ice age began to recover, but in the final years of the simulation very little young ice remains after the melt season, a strong indication that the age of the pack will again decline in the future as older ice classes fail to be replenished. The Arctic ice pack has fluctuated between older and younger ice types over the past 30 years, while ice area, thickness, and volume all declined over the same period, with an apparent acceleration in the last decade.

6. Sea Ice Edge Location and Extent in the Russian Arctic, 1933-2006

National Oceanic and Atmospheric Administration, Department of Commerce — The Sea Ice Edge Location and Extent in the Russian Arctic, 1933-2006 data are derived from sea ice charts from the Arctic and Antarctic Research Institute (AARI),...

7. Evaluation of Arctic Sea Ice Thickness Simulated by Arctic Ocean Model Intercomparison Project Models

Johnson, Mark; Proshuntinsky, Andrew; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nikolay; Kwok, Ron; Maslowski, Wieslaw; Hakkinen, Sirpa; Ashik, Igor; De Cuevas, Beverly

2012-01-01

Six Arctic Ocean Model Intercomparison Project model simulations are compared with estimates of sea ice thickness derived from pan-Arctic satellite freeboard measurements (2004-2008); airborne electromagnetic measurements (2001-2009); ice draft data from moored instruments in Fram Strait, the Greenland Sea, and the Beaufort Sea (1992-2008) and from submarines (1975-2000); and drill hole data from the Arctic basin, Laptev, and East Siberian marginal seas (1982-1986) and coastal stations (1998-2009). Despite an assessment of six models that differ in numerical methods, resolution, domain, forcing, and boundary conditions, the models generally overestimate the thickness of measured ice thinner than approximately 2 mand underestimate the thickness of ice measured thicker than about approximately 2m. In the regions of flat immobile landfast ice (shallow Siberian Seas with depths less than 25-30 m), the models generally overestimate both the total observed sea ice thickness and rates of September and October ice growth from observations by more than 4 times and more than one standard deviation, respectively. The models do not reproduce conditions of fast ice formation and growth. Instead, the modeled fast ice is replaced with pack ice which drifts, generating ridges of increasing ice thickness, in addition to thermodynamic ice growth. Considering all observational data sets, the better correlations and smaller differences from observations are from the Estimating the Circulation and Climate of the Ocean, Phase II and Pan-Arctic Ice Ocean Modeling and Assimilation System models.

8. Relating Regional Arctic Sea Ice and climate extremes over Europe

Ionita-Scholz, Monica; Grosfeld, Klaus; Lohmann, Gerrit; Scholz, Patrick

2016-04-01

The potential increase of temperature extremes under climate change is a major threat to society, as temperature extremes have a deep impact on environment, hydrology, agriculture, society and economy. Hence, the analysis of the mechanisms underlying their occurrence, including their relationships with the large-scale atmospheric circulation and sea ice concentration, is of major importance. At the same time, the decline in Arctic sea ice cover during the last 30 years has been widely documented and it is clear that this change is having profound impacts at regional as well as planetary scale. As such, this study aims to investigate the relation between the autumn regional sea ice concentration variability and cold winters in Europe, as identified by the numbers of cold nights (TN10p), cold days (TX10p), ice days (ID) and consecutive frost days (CFD). We analyze the relationship between Arctic sea ice variation in autumn (September-October-November) averaged over eight different Arctic regions (Barents/Kara Seas, Beaufort Sea, Chukchi/Bering Seas, Central Arctic, Greenland Sea, Labrador Sea/Baffin Bay, Laptev/East Siberian Seas and Northern Hemisphere) and variations in atmospheric circulation and climate extreme indices in the following winter season over Europe using composite map analysis. Based on the composite map analysis it is shown that the response of the winter extreme temperatures over Europe is highly correlated/connected to changes in Arctic sea ice variability. However, this signal is not symmetrical for the case of high and low sea ice years. Moreover, the response of temperatures extreme over Europe to sea ice variability over the different Arctic regions differs substantially. The regions which have the strongest impact on the extreme winter temperature over Europe are: Barents/Kara Seas, Beaufort Sea, Central Arctic and the Northern Hemisphere. For the years of high sea ice concentration in the Barents/Kara Seas there is a reduction in the number

9. A rapidly declining perennial sea ice cover in the Arctic

Comiso, Josefino C.

2002-10-01

The perennial sea ice cover in the Arctic is shown to be declining at -9% per decade using satellite data from 1978 to 2000. A sustained decline at this rate would mean the disappearance of the multiyear ice cover during this century and drastic changes in the Arctic climate system. An apparent increase in the fraction of second year ice in the 1990s is also inferred suggesting an overall thinning of the ice cover. Surface ice temperatures derived from satellite data are negatively correlated with perennial ice area and are shown to be increasing at the rate of 1.2 K per decade. The latter implies longer melt periods and therefore decreasing ice volume in the more recent years.

10. Arctic sea ice decline contributes to thinning lake ice trend in northern Alaska

Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Cai, Lei

2016-07-01

Field measurements, satellite observations, and models document a thinning trend in seasonal Arctic lake ice growth, causing a shift from bedfast to floating ice conditions. September sea ice concentrations in the Arctic Ocean since 1991 correlate well (r = +0.69, p characterizing lake ice conditions. A lake ice growth model forced with Weather Research and Forecasting model output produced a 7% decrease in lake ice growth when 2007/08 sea ice was imposed on 1991/92 climatology and a 9% increase in lake ice growth for the opposing experiment. Here, we clearly link early winter ‘ocean-effect’ snowfall and warming to reduced lake ice growth. Future reductions in sea ice extent will alter hydrological, biogeochemical, and habitat functioning of Arctic lakes and cause sub-lake permafrost thaw.

11. Seasonal evolution of melt ponds on Arctic sea ice

Webster, Melinda A.; Rigor, Ignatius G.; Perovich, Donald K.; Richter-Menge, Jacqueline A.; Polashenski, Christopher M.; Light, Bonnie

2015-09-01

The seasonal evolution of melt ponds has been well documented on multiyear and landfast first-year sea ice, but is critically lacking on drifting, first-year sea ice, which is becoming increasingly prevalent in the Arctic. Using 1 m resolution panchromatic satellite imagery paired with airborne and in situ data, we evaluated melt pond evolution for an entire melt season on drifting first-year and multiyear sea ice near the 2011 Applied Physics Laboratory Ice Station (APLIS) site in the Beaufort and Chukchi seas. A new algorithm was developed to classify the imagery into sea ice, thin ice, melt pond, and open water classes on two contrasting ice types: first-year and multiyear sea ice. Surprisingly, melt ponds formed ˜3 weeks earlier on multiyear ice. Both ice types had comparable mean snow depths, but multiyear ice had 0-5 cm deep snow covering ˜37% of its surveyed area, which may have facilitated earlier melt due to its low surface albedo compared to thicker snow. Maximum pond fractions were 53 ± 3% and 38 ± 3% on first-year and multiyear ice, respectively. APLIS pond fractions were compared with those from the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaign. APLIS exhibited earlier melt and double the maximum pond fraction, which was in part due to the greater presence of thin snow and first-year ice at APLIS. These results reveal considerable differences in pond formation between ice types, and underscore the importance of snow depth distributions in the timing and progression of melt pond formation.

12. Controls on Arctic sea ice from first-year and multi-year survival rates

Hunke, Jes [Los Alamos National Laboratory

2009-01-01

The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi year ice. The transition to an Arctic that is populated by thinner first year sea ice has important implications for future trends in area and volume. Here we develop a reduced model for Arctic sea ice with which we investigate how the survivability of first year and multi year ice control the mean state, variability, and trends in ice area and volume.

13. Seasonal cycle of solar energy fluxes through Arctic sea ice

S. Arndt

2014-06-01

Full Text Available Arctic sea ice has not only decreased considerably during the last decades, but also changed its physical properties towards a thinner and more seasonal cover. These changes strongly impact the energy budget and might affect the ice-associated ecosystem of the Arctic. But until now, it is not possible to quantify shortwave energy fluxes through sea ice sufficiently well over large regions and during different seasons. Here, we present a new parameterization of light transmittance through sea ice for all seasons as a function of variable sea ice properties. The annual maximum solar heat flux of 30 × 105 J m−2 occurs in June, then also matching the under ice ocean heat flux. Furthermore, our results suggest that 96% of the total annual solar heat input occurs from May to August, during four months only. Applying the new parameterization on remote sensing and reanalysis data from 1979 to 2011, we find an increase in light transmission of 1.5% a−1 for all regions. Sensitivity studies reveal that the results strongly depend on the timing of melt onset and the correct classification of ice types. Hence, these parameters are of great importance for quantifying under-ice radiation fluxes and the uncertainty of this parameterization. Assuming a two weeks earlier melt onset, the annual budget increases by 20%. Continuing the observed transition from Arctic multi- to first year sea ice could increase light transmittance by another 18%. Furthermore, the increase in light transmission directly contributes to an increase in internal and bottom melt of sea ice, resulting in a positive transmittance-melt feedback process.

14. Impacts of Declining Arctic Sea Ice: An International Challenge

Serreze, M.

2008-12-01

As reported by the National Snow and Ice Data Center in late August of 2008, Arctic sea ice extent had already fallen to its second lowest level since regular monitoring began by satellite. As of this writing, we were closing in on the record minimum set in September of 2007. Summers may be free of sea ice by the year 2030. Recognition is growing that ice loss will have environmental impacts that may extend well beyond the Arctic. The Arctic Ocean will in turn become more accessible, not just to tourism and commercial shipping, but to exploitation of oil wealth at the bottom of the ocean. In recognition of growing accessibility and oil operations, the United States Coast Guard set up temporary bases this summer at Barrow and Prudhoe Bay, AK, from which they conducted operations to test their readiness and capabilities, such as for search and rescue. The Canadians have been busy showing a strong Arctic presence. In August, a German crew traversed the Northwest Passage from east to west in one of their icebreakers, the Polarstern. What are the major national and international research efforts focusing on the multifaceted problem of declining sea ice? What are the areas of intersection, and what is the state of collaboration? How could national and international collaboration be improved? This talk will review some of these issues.

15. Decadal to seasonal variability of Arctic sea ice albedo

Agarwal, S; Moon, W.; Wettlaufer, J. S.

2011-01-01

A controlling factor in the seasonal and climatological evolution of the sea ice cover is its albedo $\\alpha$. Here we analyze Arctic data from the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder and assess the seasonality and variability of broadband albedo from a 23 year daily record. We produce a histogram of daily albedo over ice covered regions in which the principal albedo transitions are seen; high albedo in late winter and spring, the onset of snow melt and melt pond...

16. A recent bifurcation in Arctic sea-ice cover

Livina, Valerie N

2012-01-01

There is ongoing debate over whether Arctic sea-ice has already passed a 'tipping point', or whether it will do so in future, with several recent studies arguing that the loss of summer sea ice does not involve a bifurcation because it is highly reversible in models. Recently developed methods can detect and sometimes forewarn of bifurcations in time-series data, hence we applied them to satellite data for Arctic sea-ice cover. Here we show that a new low ice cover state has appeared from 2007 onwards, which is distinct from the normal state of seasonal sea ice variation, suggesting a bifurcation has occurred from one attractor to two. There was no robust early warning signal of critical slowing down prior to this bifurcation, consistent with it representing the appearance of a new ice cover state rather than the loss of stability of the existing state. The new low ice cover state has been sampled predominantly in summer-autumn and seasonal forcing combined with internal climate variability are likely respons...

17. Arctic Sea Ice Simulation in the PlioMIP Ensemble

Howell, Fergus W.; Haywood, Alan M.; Otto-Bliesner, Bette L.; Bragg, Fran; Chan, Wing-Le; Chandler, Mark A.; Contoux, Camille; Kamae, Youichi; Abe-Ouchi, Ayako; Rosenbloom, Nan A.; Stepanek, Christian; Zhang, Zhongshi

2016-01-01

Eight general circulation models have simulated the mid-Pliocene warm period (mid-Pliocene, 3.264 to 3.025 Ma) as part of the Pliocene Modelling Intercomparison Project (PlioMIP). Here, we analyse and compare their simulation of Arctic sea ice for both the pre-industrial period and the mid-Pliocene. Mid-Pliocene sea ice thickness and extent is reduced, and the model spread of extent is more than twice the pre-industrial spread in some summer months. Half of the PlioMIP models simulate ice-free conditions in the mid-Pliocene. This spread amongst the ensemble is in line with the uncertainties amongst proxy reconstructions for mid-Pliocene sea ice extent. Correlations between mid-Pliocene Arctic temperatures and sea ice extents are almost twice as strong as the equivalent correlations for the pre-industrial simulations. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.

18. Controls on Arctic sea ice from first-year and multi-year ice survival rates

Armour, K.; Bitz, C. M.; Hunke, E. C.; Thompson, L.

2009-12-01

The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi-year (MY) ice. The transition to an Arctic that is populated by thinner first-year (FY) sea ice has important implications for future trends in area and volume. We develop a reduced model for Arctic sea ice with which we investigate how the survivability of FY and MY ice control various aspects of the sea-ice system. We demonstrate that Arctic sea-ice area and volume behave approximately as first-order autoregressive processes, which allows for a simple interpretation of September sea-ice in which its mean state, variability, and sensitivity to climate forcing can be described naturally in terms of the average survival rates of FY and MY ice. This model, used in concert with a sea-ice simulation that traces FY and MY ice areas to estimate the survival rates, reveals that small trends in the ice survival rates explain the decline in total Arctic ice area, and the relatively larger loss of MY ice area, over the period 1979-2006. Additionally, our model allows for a calculation of the persistence time scales of September area and volume anomalies. A relatively short memory time scale for ice area (~ 1 year) implies that Arctic ice area is nearly in equilibrium with long-term climate forcing at all times, and therefore observed trends in area are a clear indication of a changing climate. A longer memory time scale for ice volume (~ 5 years) suggests that volume can be out of equilibrium with climate forcing for long periods of time, and therefore trends in ice volume are difficult to distinguish from its natural variability. With our reduced model, we demonstrate the connection between memory time scale and sensitivity to climate forcing, and discuss the implications that a changing memory time scale has on the trajectory of ice area and volume in a warming climate. Our findings indicate that it is unlikely that a “tipping point” in September ice area and volume will be

19. Characterizing Arctic sea ice topography using high-resolution IceBridge data

Petty, Alek A.; Tsamados, Michel C.; Kurtz, Nathan T.; Farrell, Sinead L.; Newman, Thomas; Harbeck, Jeremy P.; Feltham, Daniel L.; Richter-Menge, Jackie A.

2016-05-01

We present an analysis of Arctic sea ice topography using high-resolution, three-dimensional surface elevation data from the Airborne Topographic Mapper, flown as part of NASA's Operation IceBridge mission. Surface features in the sea ice cover are detected using a newly developed surface feature picking algorithm. We derive information regarding the height, volume and geometry of surface features from 2009 to 2014 within the Beaufort/Chukchi and Central Arctic regions. The results are delineated by ice type to estimate the topographic variability across first-year and multi-year ice regimes. The results demonstrate that Arctic sea ice topography exhibits significant spatial variability, mainly driven by the increased surface feature height and volume (per unit area) of the multi-year ice that dominates the Central Arctic region. The multi-year ice topography exhibits greater interannual variability compared to the first-year ice regimes, which dominates the total ice topography variability across both regions. The ice topography also shows a clear coastal dependency, with the feature height and volume increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. A strong correlation between ice topography and ice thickness (from the IceBridge sea ice product) is found, using a square-root relationship. The results allude to the importance of ice deformation variability in the total sea ice mass balance, and provide crucial information regarding the tail of the ice thickness distribution across the western Arctic. Future research priorities associated with this new data set are presented and discussed, especially in relation to calculations of atmospheric form drag.

20. Arctic Sea Ice Thickness - Past, Present And Future

2007-12-01

In November 2005 the International Workshop on Arctic Sea Ice Thickness: Past, Present and Future was held at Rungstedgaard Conference Center, near Copenhagen, Denmark. The proceedings of the Workshop were subsequently published as a book by the European Commission. In this review we summarise the conclusions of the Workshop on the techniques which show the greatest promise for thickness monitoring on different spatial and temporal scales, and for different purposes. Sonic methods, EM techniques, buoys and satellite methods will be considered. Some copies of the book will be available at the lecture, and others can be ordered from the European Commission. The paper goes on to consider early results from some of the latest measurements on Arctic sea ice thickness done in 2007. These comprise a trans-Arctic voyage by a UK submarine, HMS "Tireless", equipped with a Kongsberg 3002 multibeam sonar which generates a 3-D digital terrain map of the ice underside; and experiments at the APLIS ice station in the Beaufort Sea carried out by the Gavia AUV equipped with a GeoSwath interferometric sonar. In both cases 3-D mapping of sea ice constitutes a new step forward in sea ice data collection, but in the case of the submarine the purpose is to map change in ice thickness (comparing results with a 2004 "Tireless" cruise and with US and UK data prior to 2000), while for the small AUV the purpose is intensive local mapping of a few ridges to improve our knowledge of their structure, as part of a multisensor programme

1. Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice

andersen, susanne; Tonboe, R.; Kaleschke, L.; Heygster, G.; Pedersen, Leif Toudal

[1] Measurements of sea ice concentration from the Special Sensor Microwave Imager (SSM/I) using seven different algorithms are compared to ship observations, sea ice divergence estimates from the Radarsat Geophysical Processor System, and ice and water surface type classification of 59 wide...... trusted subset of the SAR scenes across the central Arctic allow the separation of the ice concentration uncertainty due to emissivity variations and sensor noise from other error sources during the winter of 2003-2004. Depending on the algorithm, error standard deviations from 2.5 to 5.0% are found with...... sensor noise between 1.3 and 1.8%. This is in accord with variability estimated from analysis of SSM/I time series. Algorithms, which primarily use 85 GHz information, consistently give the best agreement with both SAR ice concentrations and ship observations. Although the 85 GHz information is more...

2. Peopling of the high Arctic - induced by sea ice?

Funder, Svend

2010-05-01

'We travelled in the winter after the return of daylight and did not go into fixed camp until spring, when the ice broke up. There was good hunting on the way, seals, beluga, walrus, bear.' (From Old Merkrusârk's account of his childhood's trek from Baffin Island to Northwest Greenland, told to Knud Rasmussen on Saunders Island in 1904) Five thousand years ago people moving eastwards from Beringia spread over the barrens of the Canadian high Arctic. This was the first of three waves of prehistoric Arctic 'cultures', which eventually reached Greenland. The passage into Greenland has to go through the northernmost and most hostile part of the country with a 5 month Polar night, and to understand this extraordinary example of human behaviour and endurance, it has been customary to invoke a more favourable (warmer) climate. This presentation suggests that land-fast sea ice, i.e. stationary sea ice anchored to the coast, is among the most important environmental factors behind the spread of prehistoric polar cultures. The ice provides the road for travelling and social communion - and access to the most important source of food, the ocean. In the LongTerm Project (2006 and 2007) we attempted to establish a Holocene record for sea ice variations along oceanic coasts in northernmost Greenland. Presently the coasts north of 80° N are beleaguered by year-round sea ice - for ten months this is land-fast ice, and only for a period in the stormy autumn months are the coasts exposed to pack-ice. This presentation Land-fast ice - as opposed to pack-ice - is a product of local temperatures, but its duration over the year, and especially into the daylight season, is also conditioned by other factors, notably wind strength. In the geological record we recognize long lasting land-fast ice by two absences: absence of traces of wave action (no beach formation), which, however, can also be a result of pack-ice along the coast; - and absence of driftwood on the shore (land-fast ice

3. The retreat of Arctic sea ice: flash-back on the latest decades

The melting of the world's ice and snow, including Arctic sea ice is probably one of the most striking pictures of ongoing climate change. Arctic sea ice cover is now observed in real-time by satellite, and its changes in time are probably more visible to the general public than long term temperature or precipitation changes. However, the interpretation of the current retreat of Arctic sea ice is not straightforward. This article reviews progress in the scientific understanding of recent trends in sea ice due to recent observations and breakthroughs in sea ice modelling. (author)

4. Stochastic dynamics of Arctic sea ice Part I: Additive noise

Moon, Woosok

2015-01-01

We analyze the numerical solutions of a stochastic Arctic sea ice model with constant additive noise over a wide range of external heat-fluxes, $\\Delta F_0$, which correspond to greenhouse gas forcing. The variability that the stochasticity provides to the deterministic steady state solutions (perennial and seasonal ice states) is illustrated by examining both the stochastic paths and probability density functions (PDFs). The principal stochastic moments (standard deviation, mean and skewness) are calculated and compared with those determined from a stochastic perturbation theory described previously by Moon and Wettlaufer (2013). We examine in detail the competing roles of the destabilizing sea ice-albedo-feedback and the stabilizing long-wave radiative loss contributions to the variability of the ice cover under increased greenhouse-gas forcing. In particular, the variability of the stochastic paths at the end of summer shows a clear maximum, which is due to the combination of the increasing importance of t...

5. Sea ice inertial oscillation magnitudes in the Arctic basin

F. Gimbert

2012-06-01

Full Text Available An original method to quantify the amplitude of inertial motion of oceanic and ice drifters, through the introduction of a non-dimensional parameter M defined from a spectral analysis, is presented. A strong seasonal dependence of the magnitude of sea ice inertial oscillations is revealed, in agreement with the corresponding annual cycles of sea ice extent, concentration, thickness, advection velocity, and deformation rates. The spatial pattern of the magnitude of the sea ice inertial oscillations over the Arctic basin is also in agreement with the sea ice thickness and concentration patterns. This argues for a strong link between the magnitude of inertial motion on one hand, the dissipation of energy through mechanical processes, and the cohesiveness of the cover on the other hand. Finally, a significant pluri-annual evolution towards greater magnitudes of inertial oscillations in recent years, in both summer and winter, is reported, thus concomitant with reduced sea ice thickness, concentration and spatial extent.

6. The impact of under-ice melt ponds on Arctic sea ice volume

Smith, Naomi; Flocco, Daniela; Feltham, Daniel

2016-04-01

A one-dimensional, thermodynamic model of Arctic sea ice [Flocco et al, 2015] has been adapted to study the evolution of under-ice melt ponds, pools of fresh water that are found below the Arctic sea ice, and false bottoms, sheets of ice that form at the boundary between the under-ice melt pond and the oceanic mixed layer. Over time, either the under-ice melt pond freezes or the false bottom is completely ablated. We have been investigating the impact that these features have on the growth or ablation of sea ice during the time that they are present. The sensitivity of our model to a range of parameters has been tested, revealing some interesting effects of the thermodynamic processes taking place during the life-cycle of these phenomena. For example, the under-ice melt pond and its associated false bottom can insulate the sea ice layer from ocean, increasing the thickness of sea ice present at the end of the time frame considered. A comparison of the results of the model of under-ice melt pond evolution with that of sea ice with a bare base has been used to estimate the impact of under-ice melt ponds on sea ice volume towards the end of the melt season. We find that the under-ice melt ponds could have a significant impact on the mass balance of the sea ice, suggesting that it could be desirable to include a parameterisation of the effects of under-ice melt pond in the sea ice components of climate models.

7. Intercomparison of the Arctic sea ice cover in global ocean-sea ice reanalyses from the ORA-IP project

Chevallier, Matthieu; Smith, Gregory C.; Dupont, Frédéric; Lemieux, Jean-François; Forget, Gael; Fujii, Yosuke; Hernandez, Fabrice; Msadek, Rym; Peterson, K. Andrew; Storto, Andrea; Toyoda, Takahiro; Valdivieso, Maria; Vernieres, Guillaume; Zuo, Hao; Balmaseda, Magdalena; Chang, You-Soon; Ferry, Nicolas; Garric, Gilles; Haines, Keith; Keeley, Sarah; Kovach, Robin M.; Kuragano, Tsurane; Masina, Simona; Tang, Yongming; Tsujino, Hiroyuki; Wang, Xiaochun

2016-01-01

Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent

8. Arctic Sea Ice Changes, Interactions, and Feedbacks on the Arctic Climate during the Satellite Era

Wang, X.; Key, J. R.; Liu, Y.

2011-12-01

Of all the components of the Earth climate system, the cryosphere is arguably the least understood even though it is a very important indicator and an effective modulator of regional and global climate change. Changes in sea ice will significantly affect exchanges of momentum, heat, and mass between the ocean and the atmosphere, and have profound socio-economic impacts on transportation, fisheries, hunting, polar animal habitat and more. In the last three decades, the Arctic underwent significant changes in sea ice as part of the accelerated global climate change. With the recently developed One-dimensional Thermodynamic Ice Model (OTIM), sea and lake ice thickness and trends can be reasonably estimated. The OTIM has been extensively validated against submarine and moored upward-looking sonar measurements, meteorological station measurements, and comprehensive numerical model simulations. The Extended AVHRR Polar Pathfinder (APP-x) dataset has 25 climate parameters covering surface, cloud, and sea ice properties as well as surface and top-of-atmosphere radiative fluxes for the period 1982 - 2004 over the Arctic and Antarctic at 25 km resolution. The OTIM has been used with APP-x dataset for Arctic sea ice thickness and volume estimation. Statistical analysis of spatial and temporal distributions and trends in sea ice extent, thickness, and volume over the satellite period has been performed, along with the temporal analysis of first year and multiple year sea ice extent changes. Preliminary results show clear evidence that Arctic sea ice has been experiencing significant changes over the last two decades of the 20th century. The Arctic sea ice has been shrinking unexpectedly fast with the declines in sea ice extent, thickness, and volume, most apparent in the fall season. Moreover, satellites provide an unprecedented opportunity to observe Arctic sea ice and its changes with high spatial and temporal coverage that is making it an ideal data source for mitigating

9. Dipole anomaly in the Arctic atmosphere and winter Arctic sea ice motion

WU; Bingyi; ZHANG; Renhe

2005-01-01

This paper investigates a previously-ignored atmospheric circulation anomaly-di- pole structure anomaly in the arctic atmosphere, and its relationship with the winter sea ice motion, based on analyses of the International Arctic Buoy Programme Data (1979-1998) and datasets from the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) for the period of 1960-2002. The dipole structure anomaly is the second-leading mode of EOF of monthly mean SLP north of 70(N during the winter season (Oct.-Mar.), which accounts for 13% of the variance. One of its two anomaly centers is over the Canadian Archipelago; the other is situated over northern Eurasia and the Siberian marginal seas. Due to the dipole structure anomaly's strong meridionality, it becomes an important mechanism to drive both anomalous sea ice export out of the Arctic Basin and cold air outbreaks into the Barents Sea, the Nordic Seas and northern Europe.

10. The uniaxial compressive strength of the Arctic summer sea ice

HAN Hongwei; LI Zhijun; HUANG Wenfeng; LU Peng; LEI Ruibo

2015-01-01

The results on the uniaxial compressive strength of Arctic summer sea ice are presented based on the sam-ples collected during the fifth Chinese National Arctic Research Expedition in 2012 (CHINARE-2012). Exper-imental studies were carried out at different testing temperatures (−3, −6 and −9°C), and vertical samples were loaded at stress rates ranging from 0.001 to 1 MPa/s. The temperature, density, and salinity of the ice were measured to calculate the total porosity of the ice. In order to study the effects of the total porosity and the density on the uniaxial compressive strength, the measured strengths for a narrow range of stress rates from 0.01 to 0.03 MPa/s were analyzed. The results show that the uniaxial compressive strength decreases linearly with increasing total porosity, and when the density was lower than 0.86 g/cm3, the uniaxial com-pressive strength increases in a power-law manner with density. The uniaxial compressive behavior of the Arctic summer sea ice is sensitive to the loading rate, and the peak uniaxial compressive strength is reached in the brittle-ductile transition range. The dependence of the strength on the temperature shows that the calculated average strength in the brittle-ductile transition range, which was considered as the peak uniaxial compressive strength, increases steadily in the temperature range from −3 to −9°C.

11. The ASIBIA sea-ice facility: First results from the Atmosphere-Sea-Ice-Biogeochemistry in the Arctic chamber

France, James L.; Thomas, Max

2016-04-01

Working in the natural ocean-ice-atmosphere system is very difficult, as conducting fieldwork on sea-ice presents many challenges ice including costs, safety, experimental controls and access. The new ASIBIA (Atmosphere-Sea-Ice-Biogeochemistry in the Arctic) coupled Ocean-Sea-Ice-(Snow)-Atmosphere chamber facility at the University of East Anglia, UK, we are aiming to perform controlled first-year sea-ice investigations in areas such as sea-ice physics, physicochemical and biogeochemical processes in sea-ice and quantification of the bi-directional flux of gases in various states of first-year sea-ice conditions. The facility is a medium sized chamber with programmable temperatures from -55°C to +30°C, allowing a full range of first year sea-ice growing conditions in both the Arctic and Antarctic to be simulated. The water depth can be up to 1 m (including up to 25 cm of sea-ice) and an optional 1 m tall Teflon film atmosphere on top of the sea-ice, thus creating a closed and coupled ocean-sea-ice-atmosphere mesocosm. Ice growth in the tank is well suited for studying first-year sea-ice physical properties, with in-situ ice-profile measurements of temperature, salinity, conductivity, pressure and spectral light transmission. Underwater and above ice cameras are installed to record the physical development of the sea-ice. Here, we present the data from the first suites of experiments in the ASIBIA chamber focussing on sea-ice physics and give a brief description of the capabilities of the facility going forward. The ASIBIA chamber was funded as part of an ERC consolidator grant to the late Prof. Roland von Glasow and we hope this work and further development of the facility will act as a lasting legacy.

12. On the existence of stable seasonally varying Arctic sea ice

Moon, W

2012-01-01

Within the framework lower order thermodynamic theories for the climatic evolution of Arctic sea ice we isolate the conditions required for the existence of stable seasonally-varying ice states. This is done by constructing a two-season model from the continuously evolving theory of Eisenman and Wettlaufer (2009) and showing that the necessary and sufficient condition for stable seasonally-varying states resides in the relaxation of the constant annual average short-wave radiative forcing. This forcing is examined within the scenario of greenhouse gas warming, as a function of which stability conditions are discerned.

13. Evaluation of Arctic Sea Ice Thickness Simulated by AOMIP Models

Johnson, Mark; Proshutinsky, Andrey; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nimolay; Kwok, Ron; Maslowski, Wieslaw; Hakkinen, Sirpa; Ashik, Igor; de Cuevas, Beverly

2011-01-01

We compare results from six AOMIP model simulations with estimates of sea ice thickness obtained from ICESat, moored and submarine-based upward looking sensors, airborne electromagnetic measurements and drill holes. Our goal is to find patterns of model performance to guide model improvement. The satellite data is pan-arctic from 2004-2008, ice-draft data is from moored instruments in Fram Strait, the Greenland Sea and the Beaufort Sea from 1992-2008 and from submarines from 1975-2000. The drill hole data are from the Laptev and East Siberian marginal seas from 1982-1986 and from coastal stations from 1998-2009. While there are important caveats when comparing modeled results with measurements from different platforms and time periods such as these, the models agree well with moored ULS data. In general, the AOMIP models underestimate the thickness of measured ice thicker than about 2 m and overestimate thickness of ice thinner than 2 m. The simulated results are poor over the fast ice and marginal seas of the Siberian shelves. Averaging over all observational data sets, the better correlations and smaller differences from observed thickness are from the ECCO2 and UW models.

14. Recent wind driven high sea ice export in the Fram Strait contributes to Arctic sea ice decline

L. H. Smedsrud

2011-05-01

Full Text Available Arctic sea ice area decrease has been visible for two decades, and continues at a steady rate. Apart from melting, the southward drift through Fram Strait is the main loss. We present high resolution sea ice drift across 79° N from 2004 to 2010. The ice drift is based on radar satellite data and correspond well with variability in local geostrophic wind. The underlying current contributes with a constant southward speed close to 5 cm s−1, and drives about 33 % of the ice export. We use geostrophic winds derived from reanalysis data to calculate the Fram Strait ice area export back to 1957, finding that the sea ice area export recently is about 25 % larger than during the 1960's. The increase in ice export occurred mostly during winter and is directly connected to higher southward ice drift velocities, due to stronger geostrophic winds. The increase in ice drift is large enough to counteract a decrease in ice concentration of the exported sea ice. Using storm tracking we link changes in geostrophic winds to more intense Nordic Sea low pressure systems. Annual sea ice export likely has a significant influence on the summer sea ice variability and we find low values in the 60's, the late 80's and 90's, and particularly high values during 2005–2008. The study highlight the possible role of variability in ice export as an explanatory factor for understanding the dramatic loss of Arctic sea ice the last decades.

15. Near Real Time Arctic sea ice thickness and volume from CryoSat-2

Tilling, R. L.; Ridout, A; Shepherd, A.

2016-01-01

Timely observations of sea ice thickness help us to understand Arctic climate, and can support maritime activities in the Polar Regions. Although it is possible to calculate Arctic sea ice thickness using measurements acquired by CryoSat-2, the latency of the final release dataset is typically one month, due to the time required to determine precise satellite orbits. We use a new fast delivery CryoSat-2 dataset based on preliminary orbits to compute Arctic sea ice thickness ...

16. Development, sensitivity analysis, and uncertainty quantification of high-fidelity arctic sea ice models.

Peterson, Kara J.; Bochev, Pavel Blagoveston; Paskaleva, Biliana S.

2010-09-01

Arctic sea ice is an important component of the global climate system and due to feedback effects the Arctic ice cover is changing rapidly. Predictive mathematical models are of paramount importance for accurate estimates of the future ice trajectory. However, the sea ice components of Global Climate Models (GCMs) vary significantly in their prediction of the future state of Arctic sea ice and have generally underestimated the rate of decline in minimum sea ice extent seen over the past thirty years. One of the contributing factors to this variability is the sensitivity of the sea ice to model physical parameters. A new sea ice model that has the potential to improve sea ice predictions incorporates an anisotropic elastic-decohesive rheology and dynamics solved using the material-point method (MPM), which combines Lagrangian particles for advection with a background grid for gradient computations. We evaluate the variability of the Los Alamos National Laboratory CICE code and the MPM sea ice code for a single year simulation of the Arctic basin using consistent ocean and atmospheric forcing. Sensitivities of ice volume, ice area, ice extent, root mean square (RMS) ice speed, central Arctic ice thickness, and central Arctic ice speed with respect to ten different dynamic and thermodynamic parameters are evaluated both individually and in combination using the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA). We find similar responses for the two codes and some interesting seasonal variability in the strength of the parameters on the solution.

17. Influence of winter sea-ice motion on summer ice cover in the Arctic

Noriaki Kimura

2013-11-01

Full Text Available Summer sea-ice cover in the Arctic varies largely from year to year owing to several factors. This study examines one such factor, the relationship between interannual difference in winter ice motion and ice area in the following summer. A daily-ice velocity product on a 37.5-km resolution grid is prepared using the satellite passive microwave sensor Advanced Microwave Scanning Radiometer—Earth Observing System data for the nine years of 2003–2011. Derived daily-ice motion reveals the dynamic modification of the winter ice cover. The winter ice divergence/convergence is strongly related to the summer ice cover in some regions; the correlation coefficient between the winter ice convergence and summer ice area ranges between 0.5 and 0.9 in areas with high interannual variability. This relation implies that the winter ice redistribution controls the spring ice thickness and the summer ice cover.

18. Regional dependence in the rapid loss of Arctic sea ice

Close, Sally; Houssais, Marie-Noëlle; Herbaut, Christophe

2016-04-01

The accelerating rate of sea ice decline in the Arctic, particularly in the summer months, has been well documented by previous studies. However, the methods of analysis used to date have tended to employ pre-defined regions over which to determine sea ice loss, potentially masking regional variability within these regions. Similarly, evidence of acceleration has frequently been based on decade-to-decade comparisons that do not precisely quantify the timing of the increase in rate of decline. In this study, we address this issue by quantifying the onset time of rapid loss in sea ice concentration on a point-by-point basis, using an objective method applied to satellite passive microwave data. Seasonal maps of onset time are produced, and reveal strong regional dependency, with differences of up to 20 years in onset time between the various subregions of the Arctic. In certain cases, such as the Laptev Sea, strong spatial variability is found even at the regional scale, suggesting that caution should be employed in the use of geographically-based region definitions that may be misaligned with the physical response. The earliest onset times are found in the Pacific sector, where certain areas undergo a transition ca. 1992. In contrast, onset times in the Atlantic sector are much more recent. Rates of decline prior to and following the onset of rapid decline are calculated, and suggest that the post-onset rate of loss is weakest in the Pacific sector and greatest in the Barents Sea region. Coherency is noted in the season-to-season response, both at interannual and longer time scales. Our results describe a series of spatially self-consistent regional responses, and may be useful in understanding the primary drivers of recent sea ice loss.

19. Fine-resolution simulation of surface current and sea ice in the Arctic Mediterranean Seas

LIU Xiying; ZHANG Xuehong; YU Rucong; LIU Hailong; LI Wei

2007-01-01

A fine-resolution model is developed for ocean circulation simulation in the National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG),Chinese Academy of Sciences, and is applied to simulate surface current and sea ice variations in the Arctic Mediterranean Seas. A dynamic sea ice model in elastic-viscous-plastic rheology and a thermodynamic sea ice model are employed. A 200-year simulation is performed and a dimatological average of a 10-year period (141 st-150 th) is presented with focus on sea ice concentration and surface current variations in the Arctic Mediterranean Seas. The model is able to simulate well the East Greenland Current, Beaufort Gyre and the Transpolar Drift, but the simulated West Spitsbergen Current is small and weak. In the March climatology, the sea ice coverage can be simulated well except for a bit more ice in east of Spitsbergen Island. The result is also good for the September scenario except for less ice concentration east of Greenland and greater ice concentration near the ice margin. The extra ice east of Spitsbergen Island is caused by sea ice current convergence forced by atmospheric wind stress.

20. Investigating changes in the climate- and ecosystemof Arctic sea ice using remotely operated vehicles

Katlein, Christian; Arndt, Stefanie; Fernandez Mendez, Mar; Lange, Benjamin; Nicolaus, Marcel; Wenzhöfer, Frank; Jakuba, Mike; German, Chris

2014-01-01

The Arctic Ocean is currently undergoing a dramatic change. Decreasing sea-ice extent, thickness and age are changing important processes in the climate system. An increasing coverage of the sea ice by melt ponds and an increased amount of light transmitted to the upper ocean are also affecting the ice associated ecosystem. To document these changes, we operated different remotely operated vehicles (ROV) underneath the drifting sea ice of the Central Arctic Ocean. The newest under...

1. Causes for different spatial distributions of minimum Arctic sea-ice extent in 2007 and 2012

CUI Hongyan; QIAO Fangli; SHU Qi; SONG Yajuan; JIANG Chunfei

2015-01-01

Satellite records show the minimum Arctic sea ice extents (SIEs) were observed in the Septembers of 2007 and 2012, but the spatial distributions of sea ice concentration reduction in these two years were quite different. Atmospheric circulation pattern and the upper-ocean state in summer were investigated to explain the difference. By employing the ice-temperature and ice-specific humidity (SH) positive feedbacks in the Arctic Ocean, this paper shows that in 2007 and 2012 the higher surface air temperature (SAT) and sea level pressure (SLP) accompanied by more surface SH and higher sea surface temperature (SST), as a consequence, the strengthened poleward wind was favorable for melting summer Arctic sea ice in different regions in these two years. SAT was the dominant factor influencing the distribution of Arctic sea ice melting. The correlation coefficient is–0.84 between SAT anomalies in summer and the Arctic SIE anomalies in autumn. The increase SAT in different regions in the summers of 2007 and 2012 corresponded to a quicker melting of sea ice in the Arctic. The SLP and related wind were promoting factors connected with SAT. Strengthening poleward winds brought warm moist air to the Arctic and accelerated the melting of sea ice in different regions in the summers of 2007 and 2012. Associated with the rising air temperature, the higher surface SH and SST also played a positive role in reducing summer Arctic sea ice in different regions in these two years, which form two positive feedbacks mechanism.

2. Links between Arctic sea ice and extreme summer precipi- tation in China：an alternative view

Petteri Uotila; Alexey Karpechko; Timo Vihma

2014-01-01

Potential links between the Arctic sea-ice concentration anomalies and extreme precipitation in China are explored. Associations behind these links can be explained by physical interpretations aided by visualisations of temporarily lagged composites of variables such as atmospheric mean sea level pressure and sea surface temperature. This relatively simple approach is veriifed by collectively examining already known links between the Arctic sea ice and rainfall in China. For example, similarities in the extreme summer rainfall response to Arctic sea-ice concentration anomalies either in winter (DJF) or in spring (MAM) are highlighted. Furthermore, new links between the Arctic sea ice and the extreme weather in India and Eurasia are proposed. The methodology developed in this study can be further applied to identify other remote impacts of the Arctic sea ice variability.

3. Biopolymers form a gelatinous microlayer at the air-sea interface when Arctic sea ice melts

Galgani, Luisa; Piontek, Judith; Engel, Anja

2016-07-01

The interface layer between ocean and atmosphere is only a couple of micrometers thick but plays a critical role in climate relevant processes, including the air-sea exchange of gas and heat and the emission of primary organic aerosols (POA). Recent findings suggest that low-level cloud formation above the Arctic Ocean may be linked to organic polymers produced by marine microorganisms. Sea ice harbors high amounts of polymeric substances that are produced by cells growing within the sea-ice brine. Here, we report from a research cruise to the central Arctic Ocean in 2012. Our study shows that microbial polymers accumulate at the air-sea interface when the sea ice melts. Proteinaceous compounds represented the major fraction of polymers supporting the formation of a gelatinous interface microlayer and providing a hitherto unrecognized potential source of marine POA. Our study indicates a novel link between sea ice-ocean and atmosphere that may be sensitive to climate change.

4. Trends in sea-ice variability on the way to an ice-free Arctic

Bathiany, Sebastian; Williamson, Mark S; Lenton, Timothy M; Scheffer, Marten; van Nes, Egbert; Notz, Dirk

2016-01-01

It has been widely debated whether Arctic sea-ice loss can reach a tipping point beyond which a large sea-ice area disappears abruptly. The theory of dynamical systems predicts a slowing down when a system destabilises towards a tipping point. In simple stochastic systems this can result in increasing variance and autocorrelation, potentially yielding an early warning of an abrupt change. Here we aim to establish whether the loss of Arctic sea ice would follow these conceptual predictions, and which trends in sea ice variability can be expected from pre-industrial conditions toward an Arctic that is ice-free during the whole year. To this end, we apply a model hierarchy consisting of two box models and one comprehensive Earth system model. We find a consistent and robust decrease of the ice volume's annual relaxation time before summer ice is lost because thinner ice can adjust more quickly to perturbations. Thereafter, the relaxation time increases, mainly because the system becomes dominated by the ocean wa...

5. Influence of ice thickness and surface properties on light transmission through Arctic sea ice

Katlein, C.; Arndt, S.; Nicolaus, M.; Perovich, D. K.; Jakuba, M.; Suman, S.; Elliott, S.; Whitcomb, L. L.; McFarland, C.; Gerdes, R.; Boetius, A.

2015-12-01

The changes in physical properties of sea ice such as decreased thickness and increased melt pond cover observed over the last decades severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role in the amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to undertake challenging research at the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance onboard the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely-piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three-dimensional under-ice topography and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties during summer on the spatial variability of light transmittance. Results show that surface properties dominate the spatial distribution of the under-ice light field on small scales (<1000m²), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we suggest an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

6. Influence of ice thickness and surface properties on light transmission through Arctic sea ice

Katlein, Christian; Arndt, Stefanie; Nicolaus, Marcel; Perovich, Donald K.; Jakuba, Michael V.; Suman, Stefano; Elliott, Stephen; Whitcomb, Louis L.; McFarland, Christopher J.; Gerdes, Rüdiger; Boetius, Antje; German, Christopher R.

2015-09-01

The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea-ice-melt and under-ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under-ice radiance and irradiance using the new Nereid Under-Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H-ROV) designed for both remotely piloted and autonomous surveys underneath land-fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under-ice optical measurements with three dimensional under-ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice-thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under-ice light field on small scales (<1000 m2), while sea ice-thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

7. Polar bear and walrus response to the rapid decline in Arctic sea ice

Oakley, K.; Whalen, M.; Douglas, D.; Udevitz, M.; Atwood, T.; Jay, C.

2012-01-01

The Arctic is warming faster than other regions of the world due to positive climate feedbacks associated with loss of snow and ice. One highly visible consequence has been a rapid decline in Arctic sea ice over the past 3 decades - a decline projected to continue and result in ice-free summers likely as soon as 2030. The polar bear (Ursus maritimus) and the Pacific walrus (Odobenus rosmarus divergens) are dependent on sea ice over the continental shelves of the Arctic Ocean's marginal seas. The continental shelves are shallow regions with high biological productivity, supporting abundant marine life within the water column and on the sea floor. Polar bears use sea ice as a platform for hunting ice seals; walruses use sea ice as a resting platform between dives to forage for clams and other bottom-dwelling invertebrates. How have sea ice changes affected polar bears and walruses? How will anticipated changes affect them in the future?

8. Propaganda, News, or Education: Reporting Changing Arctic Sea Ice Conditions

Leitzell, K.; Meier, W.

2010-12-01

The National Snow and Ice Data Center provides information on Arctic sea ice conditions via the Arctic Sea Ice News & Analysis (ASINA) website. As a result of this effort to explain climatic data to the general public, we have attracted a huge amount of attention from our readers. Sometimes, people write to thank us for the information and the explanation. But people also write to accuse us of bias, slant, or outright lies in our posts. The topic of climate change is a minefield full of political animosity, and even the most carefully written verbiage can appear incomplete or biased to some audiences. Our strategy has been to report the data and stick to the areas in which our scientists are experts. The ASINA team carefully edits our posts to make sure that all statements are based on the science and not on opinion. Often this means using some technical language that may be difficult for a layperson to understand. However, we provide concise definitions for technical terms where appropriate. The hope is that by communicating the data clearly, without an agenda, we can let the science speak for itself. Is this an effective strategy to communicate clearly about the changing climate? Or does it downplay the seriousness of climate change? By writing at a more advanced level and avoiding oversimplification, we require our readers to work harder. But we may also maintain the attention of skeptics, convincing them to read further and become more knowledgeable about the topic.

9. Sea ice concentration and sea ice drift for the Arctic summer using C- and L-band SAR

Johansson, Malin; Berg, Anders; Eriksson, Leif

2014-05-01

The decreasing amount of sea ice and changes from multi-year ice to first year ice within the Arctic Ocean opens up for increased maritime activities. These activities include transportation, fishing and tourism. One of the major threats for the shipping is the presence of sea ice. Should an oil spill occur, the search and rescue is heavily dependent on constant updates of sea ice movements, both to enable a safer working environment and to potentially prevent the oil from reaching the sea ice. It is therefore necessary to have accurate and updated sea ice charts for the Arctic Ocean during the entire year. During the melt season that ice is subject to melting conditions making satellite observations of sea ice more difficult. This period coincides with the peak in marine shipping activities and therefore requires highly accurate sea ice concentration estimates. Synthetic Aperture Radar (SAR) are not hindered by clouds and do not require daylight. The continuous record and high temporal resolution makes C-band data preferable as input data for operational sea ice mapping. However, with C-band SAR it is sometimes difficult to distinguish between a wet sea ice surface and surrounding open water. L-band SAR has a larger penetration depth and has been shown to be less sensitive to less sensitive than C-band to the melt season. Inclusion of L-band data into sea chart estimates during the melt season in particular could therefore improve sea ice monitoring. We compare sea ice concentration melt season observations using Advanced Land Observing Satellite (ALOS) L-band images with Envisat ASAR C-band images. We evaluate if L-band images can be used to improve separation of wet surface ice from open water and compare with results for C-band.

10. Isolation of novel psychrophilic bacteria from Arctic sea ice

2006-01-01

The phylogenetic diversity of culturable psychrophilic bacteria associated with sea ice from the high latitude regions of Canadian Basin and Chukchi Sea, Arctic, was investigated. A total of 34 psychropilic strains were isolated using three methods of (Ⅰ) dilution plating (at 4 ℃), (Ⅱ) bath culturing (at -1 ℃) and dilution plating, and (Ⅲ) cold shock (-20 ℃ for 24 h), bath culturing and dilution plating under aerobic conditions. Sea-ice samples were exposed to -20 ℃ for 24 h that might reduce the number of common microorganisms and encourage outgrowth of psychrophilic strains. This process might be able to be introduced to isolation psychrophilic bacteria from other environmental samples in future study. 16S rDNA nearly full-length sequence analysis revealed that psychrophilic strains felled in two phylogenetic divisions, γ-proteobacteria (in the genera Colwellia、Marinobacter、Shewanella、Glaciecola、Marinomonas and Pseudoalteromonas) and Cytophaga-Flexibacter-Bacteroides (Flavobacterium and Psychroflexus). Fifteen of bacterial isolates quite likely represented novel species (16S rDNA sequence similarity below 98%). One of strains (BSi20002) from Canadian Basin showed 100% sequence similarity to that of Marinobacter sp. ANT8277 isolated from the Antarctic Weddell sea ice, suggesting bacteria may have a bipolar distribution at the species level.

11. Exploring Arctic Transpolar Drift During Dramatic Sea Ice Retreat

Gascard, J.C.; Festy, J.; le Goff, H.;

2008-01-01

The Arctic is undergoing significant environmental changes due to climate warming. The most evident signal of this warming is the shrinking and thinning of the ice cover of the Arctic Ocean. If the warming continues, as global climate models predict, the Arctic Ocean will change from a perennially...

12. Apparent Arctic sea ice modeling improvement caused by volcanoes

Rosenblum, Erica

2016-01-01

The downward trend in Arctic sea ice extent is one of the most dramatic signals of climate change during recent decades. Comprehensive climate models have struggled to reproduce this, typically simulating a slower rate of sea ice retreat than has been observed. However, this bias has been substantially reduced in models participating in the most recent phase of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). This improvement has been attributed to improved physics in the models. Here we examine simulations from CMIP3 and CMIP5 and find that simulated sea ice trends are strongly influenced by historical volcanic forcing, which was included in all of the CMIP5 models but in only about half of the CMIP3 models. The volcanic forcing causes temporary simulated cooling in the 1980s and 1990s, which contributes to raising the simulated 1979-2013 global-mean surface temperature trends to values substantially larger than observed. This warming bias is accompan...

13. Decadal to seasonal variability of Arctic sea ice albedo

Agarwal, S; Wettlaufer, J S

2011-01-01

A controlling factor in the seasonal and climatological evolution of the sea ice cover is its albedo $\\alpha$. Here we analyze Arctic data from the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder and assess the seasonality and variability of broadband albedo from a 23 year daily record. We produce a histogram of daily albedo over ice covered regions in which the principal albedo transitions are seen; high albedo in late winter and spring, the onset of snow melt and melt pond formation in the summer, and fall freeze up. The bimodal late summer distribution demonstrates the combination of the poleward progression of the onset of melt with the coexistence of perennial bare ice with melt ponds and open water, which then merge to a broad peak at $\\alpha \\gtrsim$ 0.5. We find the interannual variability to be dominated by the low end of the $\\alpha$ distribution, highlighting the controlling influence of the ice thickness distribution and large-scale ice edge dynamics. The statistics obtained pro...

14. Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N.

2011-01-01

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

15. Radar and laser altimeter measurements over Arctic sea ice.

Giles, K. A.

2005-01-01

To validate sea ice models, basin wide sea ice thickness measurements with an accuracy of 0.5 m are required to analyse trends in sea ice thickness, it is necessary to detect changes in sea ice thickness of 4 cm per year on a basin wide scale. The estimated error on satellite radar altimeter estimates of sea ice thickness is 0.45 m and the estimated error on satellite laser altimetry estimates of sea ice thickness is 0.78 m. The Laser Radar Altimetry (LaRA) field campaign took place in the Ar...

16. Ice–ocean coupled computations for sea-ice prediction to support ice navigation in Arctic sea routes

Liyanarachchi Waruna Arampath De Silva

2015-11-01

Full Text Available With the recent rapid decrease in summer sea ice in the Arctic Ocean extending the navigation period in the Arctic sea routes (ASR, the precise prediction of ice distribution is crucial for safe and efficient navigation in the Arctic Ocean. In general, however, most of the available numerical models have exhibited significant uncertainties in short-term and narrow-area predictions, especially in marginal ice zones such as the ASR. In this study, we predict short-term sea-ice conditions in the ASR by using a mesoscale eddy-resolving ice–ocean coupled model that explicitly treats ice floe collisions in marginal ice zones. First, numerical issues associated with collision rheology in the ice–ocean coupled model (ice–Princeton Ocean Model [POM] are discussed and resolved. A model for the whole of the Arctic Ocean with a coarser resolution (about 25 km was developed to investigate the performance of the ice–POM model by examining the reproducibility of seasonal and interannual sea-ice variability. It was found that this coarser resolution model can reproduce seasonal and interannual sea-ice variations compared to observations, but it cannot be used to predict variations over the short-term, such as one to two weeks. Therefore, second, high-resolution (about 2.5 km regional models were set up along the ASR to investigate the accuracy of short-term sea-ice predictions. High-resolution computations were able to reasonably reproduce the sea-ice extent compared to Advanced Microwave Scanning Radiometer–Earth Observing System satellite observations because of the improved expression of the ice–albedo feedback process and the ice–eddy interaction process.

17. Spectral albedo and transmittance of thin young Arctic sea ice

Taskjelle, Torbjørn; Hudson, Stephen R.; Granskog, Mats A.; Nicolaus, Marcel; Lei, Ruibo; Gerland, Sebastian; Stamnes, Jakob J.; Hamre, Børge

2016-01-01

Spectral albedo and transmittance in the range were measured on three separate dates on less than thick new Arctic sea ice growing on Kongsfjorden, Svalbard at , . Inherent optical properties, including absorption coefficients of particulate and dissolved material, were obtained from ice samples and fed into a radiative transfer model, which was used to analyze spectral albedo and transmittance and to study the influence of clouds and snow on these. Integrated albedo and transmittance for photosynthetically active radiation () were in the range 0.17-0.21 and 0.77-0.86, respectively. The average albedo and transmittance of the total solar radiation energy were 0.16 and 0.51, respectively. Values inferred from the model indicate that the ice contained possibly up to 40% brine and only 0.6% bubbles. Angular redistribution of solar radiation by clouds and snow was found to influence both the wavelength-integrated value and the spectral shape of albedo and transmittance. In particular, local peaks and depressions in the spectral albedo and spectral transmittance were found for wavelengths within atmospheric absorption bands. Simulated and measured transmittance spectra were within 5% for most of the wavelength range, but deviated up to 25% in the vicinity of , indicating the need for more optical laboratory measurements of pure ice, or improved modeling of brine optical properties in this near-infrared wavelength region.

18. The influence of winter cloud on summer sea ice in the Arctic, 1983-2013

Letterly, Aaron; Key, Jeffrey; Liu, Yinghui

2016-03-01

Arctic sea ice extent has declined dramatically over the last two decades, with the fastest decrease and greatest variability in the Beaufort, Chukchi, and East Siberian Seas. Thinner ice in these areas is more susceptible to changes in cloud cover, heat and moisture advection, and surface winds. Using two climate reanalyses and satellite data, it is shown that increased wintertime surface cloud forcing contributed to the 2007 summer sea ice minimum. An analysis over the period 1983-2013 reveals that reanalysis cloud forcing anomalies in the East Siberian and Kara Seas precondition the ice pack and, as a result, explain 25% of the variance in late summer sea ice concentration. This finding was supported by Moderate Resolution Imaging Spectroradiometer cloud cover anomalies, which explain up to 45% of the variance in sea ice concentration. Results suggest that winter cloud forcing anomalies in this area have predictive capabilities for summer sea ice anomalies across much of the central and Eurasian Arctic.

19. Less winter cloud aids summer 2013 Arctic sea ice return from 2012 minimum

In September 2012, Arctic sea ice cover reached a record minimum for the satellite era. The following winter the sea ice quickly returned, carrying through to the summer when ice extent was 48% greater than the same time in 2012. Most of this rebound in the ice cover was in the Chukchi and Beaufort Seas, areas experiencing the greatest decline in sea ice over the last three decades. A variety of factors, including ice dynamics, oceanic and atmospheric heat transport, wind, and solar insolation anomalies, may have contributed to the rebound. Here we show that another factor, below-average Arctic cloud cover in January–February 2013, resulted in a more strongly negative surface radiation budget, cooling the surface and allowing for greater ice growth. More thick ice was observed in March 2013 relative to March 2012 in the western Arctic Ocean, and the areas of ice growth estimated from the negative cloud cover anomaly and advected from winter to summer with ice drift data, correspond well with the September ice concentration anomaly pattern. Therefore, decreased wintertime cloud cover appears to have played an important role in the return of the sea ice cover the following summer, providing a partial explanation for large year-to-year variations in an otherwise decreasing Arctic sea ice cover. (paper)

20. Growth limitation of three Arctic sea ice algal species

Sogaard, D.H.; Hansen, P.J.; Rysgaard, Søren;

2011-01-01

The effect of salinity, pH, and dissolved inorganic carbon (TCO(2)) on growth and survival of three Arctic sea ice algal species, two diatoms (Fragilariopsis nana and Fragilariopsis sp.), and one species of chlorophyte (Chlamydomonas sp.) was assessed in controlled laboratory experiments. Our...... maximal growth rate at pH 8.0 and/or 8.5. The two diatom species stopped growing at pH > 9.5, while the chlorophyte species still was able to grow at a rate which was 1/3 of its maximum growth rate at pH 10. Thus, Chlamydomonas sp. was able to grow at high pH levels in the succession experiment and...

1. Arctic sea ice freeboard from AltiKa and comparison with CryoSat-2 and Operation IceBridge

Armitage, T. W. K.; Ridout, A. L.

2015-01-01

Satellite radar altimeters have improved our knowledge of Arctic sea ice thickness over the past decade. The main sources of uncertainty in sea ice thickness retrievals are associated with inadequate knowledge of the snow layer depth and the radar interaction with the snow pack. Here we adapt a method of deriving sea ice freeboard from CryoSat-2 to data from the AltiKa Ka band radar altimeter over the 2013–14 Arctic sea ice growth season. AltiKa measures basin-averaged freeboards between 4.4 ...

2. Arctic sea ice response to atmospheric forcings with varying levels of anthropogenic warming and climate variability

Zhang, Jinlun; Steele, Michael; Schweiger, Axel

2010-10-01

Numerical experiments are conducted to project arctic sea ice responses to varying levels of future anthropogenic warming and climate variability over 2010-2050. A summer ice-free Arctic Ocean is likely by the mid-2040s if arctic surface air temperature (SAT) increases 4°C by 2050 and climate variability is similar to the past relatively warm two decades. If such a SAT increase is reduced by one-half or if a future Arctic experiences a range of SAT fluctuation similar to the past five decades, a summer ice-free Arctic Ocean would be unlikely before 2050. If SAT increases 4°C by 2050, summer ice volume decreases to very low levels (10-37% of the 1978-2009 summer mean) as early as 2025 and remains low in the following years, while summer ice extent continues to fluctuate annually. Summer ice volume may be more sensitive to warming while summer ice extent more sensitive to climate variability. The rate of annual mean ice volume decrease relaxes approaching 2050. This is because, while increasing SAT increases summer ice melt, a thinner ice cover increases winter ice growth. A thinner ice cover also results in a reduced ice export, which helps to further slow ice volume loss. Because of enhanced winter ice growth, arctic winter ice extent remains nearly stable and therefore appears to be a less sensitive climate indicator.

3. The impact of varying atmospheric forcing on the thickness of arctic multi-year sea ice

Dumas, J. A.; Flato, G. M.; Weaver, A. J.

2003-09-01

A 1-D thermodynamic sea ice model, forced with North Pole Drift Station observations from 1954-91, is used to study the effect of changing atmospheric forcing on multi-year Arctic sea ice. From 1954-70, most seasons show positive trends in calculated sea ice thickness over much of the Arctic. A dip in calculated ice thickness takes place between 1971-77 over most of the Arctic. Following the North Pacific regime shift in 1976-1977, the period 1978-91 reveals large negative trends in calculated sea ice thickness in all seasons. The results indicate that an important part of the variability and trends in Arctic sea ice thickness is thermodynamically-driven. Of the total variance in multi-year sea ice thickness, 10 to 20% is explained by variations in the Arctic Oscillation and Pacific North American patterns. The multi-year ice thickness response to a positive wintertime Arctic Oscillation anomaly occurs the following summer and persists for more than a year.

4. Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

2016-04-01

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local

5. Sensitivity of Arctic warming to sea ice concentration

Yim, Bo Young; Min, Hong Sik; Kim, Baek-Min; Jeong, Jee-Hoon; Kug, Jong-Seong

2016-06-01

We examine the sensitivity of Arctic amplification (AA) to background sea ice concentration (SIC) under greenhouse warming by analyzing the data sets of the historical and Representative Concentration Pathway 8.5 runs of the Coupled Model Intercomparison Project Phase 5. To determine whether the sensitivity of AA for a given radiative forcing depends on background SIC state, we examine the relationship between the AA trend and mean SIC on moving 30 year windows from 1960 to 2100. It is found that the annual mean AA trend varies depending on the mean SIC condition. In particular, some models show a highly variable AA trend in relation to the mean SIC clearly. In these models, the AA trend tends to increase until the mean SIC reaches a critical level (i.e., 20-30%), and the maximum AA trend is almost 3 to 5 times larger than the trend in the early stage of global warming (i.e., 50-60%, 60-70%). However, the AA trend tends to decrease after that. Further analysis shows that the sensitivity of AA trend to mean SIC condition is closely related to the feedback processes associated with summer surface albedo and winter turbulent heat flux in the Arctic Ocean.

6. Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

T. S. Rogers

2013-02-01

Full Text Available There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice loss has varied, with a significantly larger decline of winter maximum (January–March extent in the Atlantic region than in other sectors. A lead–lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

7. Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry in the Community Climate System Model

Deal, Clara [Univ. of Alaska, Fairbanks, AL (United States); Jin, Meibing [Univ. of Alaska, Fairbanks, AL (United States)

2013-06-30

Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacks between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine

8. Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation

Howell, Fergus W.; Haywood, Alan M.; Dowsett, Harry J.; Pickering, Steven J.

2016-01-01

General circulation model (GCM) simulations of the mid-Pliocene Warm Period (mPWP, 3.264 to 3.025 Myr ago) do not reproduce the magnitude of Northern Hemisphere high latitude surface air and sea surface temperature (SAT and SST) warming that proxy data indicate. There is also large uncertainty regarding the state of sea ice cover in the mPWP. Evidence for both perennial and seasonal mPWP Arctic sea ice is found through analyses of marine sediments, whilst in a multi-model ensemble of mPWP climate simulations, half of the ensemble simulated ice-free summer Arctic conditions. Given the strong influence that sea ice exerts on high latitude temperatures, an understanding of the nature of mPWP Arctic sea ice would be highly beneficial.

9. Identification of paleo Arctic winter sea ice limits and the marginal ice zone: Optimised biomarker-based reconstructions of late Quaternary Arctic sea ice

Belt, Simon T.; Cabedo-Sanz, Patricia; Smik, Lukas; Navarro-Rodriguez, Alba; Berben, Sarah M. P.; Knies, Jochen; Husum, Katrine

2015-12-01

during the early Holocene, but this interpretation requires further investigation. In contrast, IP25 and HBI III data obtained from a core from the northern Barents Sea demonstrate that seasonal sea ice prevailed throughout the Holocene, but with a gradual shift from winter ice edge conditions during the early Holocene to more sustained ice cover in the Neoglacial; a directional shift that has undergone a reverse in the last ca. 150 yr according to observational records. Our combined surface and downcore datasets suggest that combined analysis of IP25 and HBI III can provide information on temporal variations in the position of the maximum (winter) Arctic sea ice extent, together with insights into sea ice seasonality by characterisation of the MIZ. Combining IP25 with HBI III in the form of the previously proposed PIP25 index yields similar outcomes to those obtained using brassicasterol as the phytoplankton marker. Importantly, however, some problems associated with use of a variable balance factor employed in the PIP25 calculation, are potentially alleviated using HBI III.

10. Impact of aerosol emission controls on future Arctic sea ice cover

Gagné, M.-È.; Gillett, N. P.; Fyfe, J. C.

2015-10-01

We examine the response of Arctic sea ice to projected aerosol and aerosol precursor emission changes under the Representative Concentration Pathway (RCP) scenarios in simulations of the Canadian Earth System Model. The overall decrease in aerosol loading causes a warming, largest over the Arctic, which leads to an annual mean reduction in sea ice extent of approximately 1 million km2 over the 21st century in all RCP scenarios. This accounts for approximately 25% of the simulated reduction in sea ice extent in RCP 4.5, and 40% of the reduction in RCP 2.5. In RCP 4.5, the Arctic ocean is projected to become ice-free during summertime in 2045, but it does not become ice-free until 2057 in simulations with aerosol precursor emissions held fixed at 2000 values. Thus, while reductions in aerosol emissions have significant health and environmental benefits, their substantial contribution to projected Arctic climate change should not be overlooked.

11. Sea Ice Charts of the Russian Arctic in Gridded Format, 1933-2006

National Oceanic and Atmospheric Administration, Department of Commerce — The Arctic and Antarctic Research Institute (AARI) in St. Petersburg, Russia, produces sea ice charts for safety of navigation in the polar regions and for other...

12. Halogen-based reconstruction of Russian Arctic sea ice area from the Akademii Nauk ice core (Severnaya Zemlya)

Spolaor, A.; Opel, T.; McConnell, J. R.; Maselli, O. J.; Spreen, G.; Varin, C.; Kirchgeorg, T.; Fritzsche, D.; Saiz-Lopez, A.; Vallelonga, P.

2016-01-01

The role of sea ice in the Earth climate system is still under debate, although it is known to influence albedo, ocean circulation, and atmosphere-ocean heat and gas exchange. Here we present a reconstruction of 1950 to 1998 AD sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic). The chemistry of halogens bromine (Br) and iodine (I) is strongly active and influenced by sea ice dynamics, in terms of physical, chemical and biological process. Bromine reacts on the sea ice surface in autocatalyzing "bromine explosion" events, causing an enrichment of the Br / Na ratio and hence a bromine excess (Brexc) in snow compared to that in seawater. Iodine is suggested to be emitted from algal communities growing under sea ice. The results suggest a connection between Brexc and spring sea ice area, as well as a connection between iodine concentration and summer sea ice area. The correlation coefficients obtained between Brexc and spring sea ice (r = 0.44) as well as between iodine and summer sea ice (r = 0.50) for the Laptev Sea suggest that these two halogens could become good candidates for extended reconstructions of past sea ice changes in the Arctic.

13. Interplay between linear, dissipative and permanently critical mechanical processes in Arctic sea ice

A. Chmel; Smirnov, V; Panov, A.

2010-01-01

Mechanical processes in the Arctic ice pack result in fragmented sea ice cover, the regular geometry of which could be described in main features in terms of the conventional mechanics. However, the size distribution of sea ice floes does not exhibit the random (poissonian-like) statistics and follows the power law typical for self-similar (fractal) structures. The analysis of ice floe oscillations in the frequency range specific for cracking, shearing and stick-slip motion evidences the self...

14. Stochastic dynamics of Arctic sea ice Part II: Multiplicative noise

Moon, Woosok

2015-01-01

We analyze the numerical solutions of a stochastic Arctic sea ice model with multiplicative noise over a wide range of external heat-fluxes, $\\Delta F_0$, which correspond to greenhouse gas forcing. When the noise is multiplicative, the noise-magnitude depends on the state-variable, and this will influence the statistical moments in a manner that differs from the additive case, which we analyzed in Part I of this study. The state variable describing the deterministic backbone of our model is the energy, $E(t)$, contained in the ice or the ocean and for a thorough comparison and contrast we choose the simplest form of multiplicative noise $\\sigma E(t) \\xi(t)$, where $\\sigma$ is the noise amplitude and $\\xi(t)$ is the noise process. The case of constant additive noise (CA) we write as $\\sigma\\overline{E_S}\\xi(t)$, in which $\\overline{E_S}$ is the seasonally averaged value of the periodic deterministic steady-state solution $E_S(t)$, or the deterministic seasonal cycle. We then treat the case of seasonally-varyi...

15. Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice

Zygmuntowska, M.; Khvorostovsky, K.; V. Helm; S. Sandven

2013-01-01

Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat-2 was launched in 2010 carrying a Ku-band radar altimeter (SIRAL) designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300m along track. In this study, airborne Ku-band radar altimeter data over different ...

16. Quantifying the contribution of natural variability to September Arctic sea ice decline

SONG Mirong; WEI Lixin; WANG Zhenzhan

2016-01-01

Arctic sea ice extent has been declining in recent decades. There is ongoing debate on the contribution of natural internal variability to recent and future Arctic sea ice changes. In this study, we contrast the trends in the forced and unforced simulations of carefully selected global climate models with the extended observed Arctic sea ice records. The results suggest that the natural variability explains no more than 42.3% of the observed September sea ice extent trend during 35 a (1979–2013) satellite observations, which is comparable to the results of the observed sea ice record extended back to 1953 (61 a, less than 48.5% natural variability). This reinforces the evidence that anthropogenic forcing plays a substantial role in the observed decline of September Arctic sea ice in recent decades. The magnitude of both positive and negative trends induced by the natural variability in the unforced simulations is slightly enlarged in the context of increasing greenhouse gases in the 21st century. However, the ratio between the realizations of positive and negative trends change has remained steady, which enforces the standpoint that external forcing will remain the principal determiner of the decreasing Arctic sea ice extent trend in the future.

17. The effect of changing sea ice on the physical vulnerability of Arctic coasts

K. R. Barnhart

2014-09-01

Full Text Available Sea ice limits the interaction of the land and ocean water in the Arctic winter and influences this interaction in the summer by governing the fetch. In many parts of the Arctic, the open-water season is increasing in duration and summertime sea-ice extents are decreasing. Sea ice provides a first-order control on the physical vulnerability of Arctic coasts to erosion, inundation, and damage to settlements and infrastructures by ocean water. We ask how the changing sea-ice cover has influenced coastal erosion over the satellite record. First, we present a pan-Arctic analysis of satellite-based sea-ice concentration specifically along the Arctic coasts. The median length of the 2012 open-water season, in comparison to 1979, expanded by between 1.5 and 3-fold by Arctic Sea sector, which allows for open water during the stormy Arctic fall. Second, we present a case study of Drew Point, Alaska, a site on the Beaufort Sea, characterized by ice-rich permafrost and rapid coastal-erosion rates, where both the duration of the open-water season and distance to the sea-ice edge, particularly towards the northwest, have increased. At Drew Point, winds from the northwest result in increased water levels at the coast and control the process of submarine notch incision, the rate-limiting step of coastal retreat. When open-water conditions exist, the distance to the sea ice edge exerts control on the water level and wave field through its control on fetch. We find that the extreme values of water-level setup have increased consistently with increasing fetch.

18. Arctic energy budget in relation to sea-ice variability on monthly to annual time scales

Krikken, Folmer; Hazeleger, Wilco

2015-04-01

The strong decrease in Arctic sea-ice in recent years has triggered a strong interest in Arctic sea-ice predictions on seasonal to decadal time scales. Hence, it is key to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. The authors report on an analysis of natural variability of Arctic sea-ice from an energy budget perspective, using 15 CMIP5 climate models, and comparing these results to atmospheric and oceanic reanalyses data. We quantify the persistence of sea ice anomalies and the cross-correlation with the surface and top energy budget components. The Arctic energy balance components primarily indicate the important role of the seasonal sea-ice albedo feedback, in which sea-ice anomalies in the melt season reemerge in the growth season. This is a robust anomaly reemergence mechanism among all 15 climate models. The role of ocean lies mainly in storing heat content anomalies in spring, and releasing them in autumn. Ocean heat flux variations only play a minor role. The role of clouds is further investigated. We demonstrate that there is no direct atmospheric response of clouds to spring sea-ice anomalies, but a delayed response is evident in autumn. Hence, there is no cloud-ice feedback in late spring and summer, but there is a cloud-ice feedback in autumn, which strengthens the ice-albedo feedback. Anomalies in insolation are positively correlated with sea-ice variability. This is primarily a result of reduced multiple-reflection of insolation due to an albedo decrease. This effect counteracts the sea-ice albedo effect up to 50%. ERA-Interim and ORAS4 confirm the main findings from the climate models.

19. Winter spring dynamics in sea-ice carbon cycling in the coastal Arctic Ocean

Riedel, Andrea; Michel, Christine; Gosselin, Michel; LeBlanc, Bernard

2008-12-01

An understanding of microbial interactions in first-year sea ice on Arctic shelves is essential for identifying potential responses of the Arctic Ocean carbon cycle to changing sea-ice conditions. This study assessed dissolved and particulate organic carbon (DOC, POC), exopolymeric substances (EPS), chlorophyll a, bacteria and protists, in a seasonal (24 February to 20 June 2004) investigation of first-year sea ice and associated surface waters on the Mackenzie Shelf. The dynamics of and relationships between different sea-ice carbon pools were investigated for the periods prior to, during and following the sea-ice-algal bloom, under high and low snow cover. A predominantly heterotrophic sea-ice community was observed prior to the ice-algal bloom under high snow cover only. However, the heterotrophic community persisted throughout the study with bacteria accounting for, on average, 44% of the non-diatom particulate carbon biomass overall the study period. There was an extensive accumulation of sea-ice organic carbon following the onset of the ice-algal bloom, with diatoms driving seasonal and spatial trends in particulate sea-ice biomass. DOC and EPS were also significant sea-ice carbon contributors such that sea-ice DOC concentrations were higher than, or equivalent to, sea-ice-algal carbon concentrations prior to and following the algal bloom, respectively. Sea-ice-algal carbon, DOC and EPS-carbon concentrations were significantly interrelated under high and low snow cover during the algal bloom ( r values ≥ 0.74, p algae are primarily responsible for the large pools of DOC and EPS-carbon and that similar stressors and/or processes could be involved in regulating their release. This study demonstrates that DOC can play a major role in organic carbon cycling on Arctic shelves.

20. Are Recent Arctic Sea Ice Changes a Fingerprint of Greenhouse Warming?

Vavrus, S. J.

2002-12-01

Arctic sea ice has undergone significant reductions in thickness and extent in recent decades, leading to speculation that the ice pack is already showing signs of greenhouse warming. The decline in ice cover is not uniform across the Arctic Ocean, but instead shows a distinct spatial pattern of maximum reductions in the eastern (European) sector and minimum decreases in the western (North American) sector. This dipole spatial pattern has been dubbed the "East-West Arctic Anomaly Pattern" (EWAAP) and is consistent with recent trends in high-latitude atmospheric circulation, which in turn are driven by the well-known decrease in Arctic sea level pressure. Climate simulations using an AGCM coupled to a mixed-layer ocean (GENESIS) are presented to show that enhanced greenhouse forcing causes the model to produce the EWAAP and its associated anomalous cyclonic circulation pattern. Paleoclimate simulations of orbitally forced warm periods in the Arctic (mid-Holocene and last interglacial) show similar changes of sea ice cover and surface winds, suggesting that the recent anomalies may be a signature of warmer Arctic climates. The consistent EWAAP response to warm external forcings is caused by two dynamical mechanisms. First, the flow of Arctic sea ice in the modern climate produces ice divergence (convergence) and more (less) open water in the eastern (western) Arctic Ocean, thus favoring (hindering) melting in the eastern (western) sector under warmer conditions. Second, because warmer climates promote a decrease in Arctic sea level pressure, anomalous surface winds blow across the Arctic Ocean from Eurasia toward North America and thus enhance the spatial dipole pattern of ice coverage.

1. Changing Arctic ecosystems: sea ice decline, permafrost thaw, and benefits for geese

Flint, Paul; Whalen, Mary; Pearce, John M.

2014-01-01

Through the Changing Arctic Ecosystems (CAE) initiative, the U.S. Geological Survey (USGS) strives to inform resource management decisions for Arctic Alaska by providing scientific information on current and future ecosystem response to a warming climate. A key area for the USGS CAE initiative has been the Arctic Coastal Plain of northern Alaska. This region has experienced a warming trend over the past 30 years, leading to reductions in sea ice and thawing of permafrost. Loss of sea ice has increased ocean wave action, leading to erosion and salt water inundation of coastal habitats. Saltwater tolerant plants are now thriving in these areas and this appears to be a positive outcome for geese in the Arctic. This finding is contrary to the deleterious effects that declining sea ice is having on habitats of ice-dependent animals, such as polar bear and walrus.

2. Sea Ice

Perovich, D.; Gerland, S.; Hendricks, S.; Meier, Walter N.; Nicolaus, M.; Richter-Menge, J.; Tschudi, M.

2013-01-01

During 2013, Arctic sea ice extent remained well below normal, but the September 2013 minimum extent was substantially higher than the record-breaking minimum in 2012. Nonetheless, the minimum was still much lower than normal and the long-term trend Arctic September extent is -13.7 per decade relative to the 1981-2010 average. The less extreme conditions this year compared to 2012 were due to cooler temperatures and wind patterns that favored retention of ice through the summer. Sea ice thickness and volume remained near record-low levels, though indications are of slightly thicker ice compared to the record low of 2012.

3. The Role of Sea Ice for Vascular Plant Dispersal in the Arctic

Geirsdottir, A.; Alsos, I. G.; Seidenkrantz, M. S.; Bennike, O.; Kirchhefer, A.; Ehrich, D.

2015-12-01

Plant species adapted to arctic environments are expected to go extinct at their southern margins due to climate warming whereas they may find suitable habitats on arctic islands if they are able to disperse there. Analyses of species distribution and phylogenetic data indicate both that the frequency of dispersal events is higher in the arctic than in other regions, and that the dispersal routes often follow the routes of sea surface currents. Thus, it has been hypothesised that sea ice has played a central role in Holocene colonisation of arctic islands. Here we compile data on the first Holocene occurrence of species in East Greenland, Iceland, the Faroe Islands, and Svalbard. We then combine these records with interpretations of dispersal routes inferred from genetic data and data on geographical distributions, reconstructions of Holocene sea ice extent, and records of driftwood to evaluate the potential role sea ice has played in past colonisation events.

4. Estimation of Arctic Sea Ice Freeboard and Thickness Using CryoSat-2

Lee, S.; Im, J.; Kim, J. W.; Kim, M.; Shin, M.

2014-12-01

Arctic sea ice is one of the significant components of the global climate system as it plays a significant role in driving global ocean circulation. Sea ice extent has constantly declined since 1980s. Arctic sea ice thickness has also been diminishing along with the decreasing sea ice extent. Because extent and thickness, two main characteristics of sea ice, are important indicators of the polar response to on-going climate change. Sea ice thickness has been measured with numerous field techniques such as surface drilling and deploying buoys. These techniques provide sparse and discontinuous data in spatiotemporal domain. Spaceborne radar and laser altimeters can overcome these limitations and have been used to estimate sea ice thickness. Ice Cloud and land Elevation Satellite (ICEsat), a laser altimeter provided data to detect polar area elevation change between 2003 and 2009. CryoSat-2 launched with Synthetic Aperture Radar (SAR)/Interferometric Radar Altimeter (SIRAL) in April 2010 can provide data to estimate time-series of Arctic sea ice thickness. In this study, Arctic sea ice freeboard and thickness between 2011 and 2014 were estimated using CryoSat-2 SAR and SARIn mode data that have sea ice surface height relative to the reference ellipsoid WGS84. In order to estimate sea ice thickness, freeboard, i.e., elevation difference between the top of sea ice surface should be calculated. Freeboard can be estimated through detecting leads. We proposed a novel lead detection approach. CryoSat-2 profiles such as pulse peakiness, backscatter sigma-0, stack standard deviation, skewness and kurtosis were examined to distinguish leads from sea ice. Near-real time cloud-free MODIS images corresponding to CryoSat-2 data measured were used to visually identify leads. Rule-based machine learning approaches such as See5.0 and random forest were used to identify leads. The proposed lead detection approach better distinguished leads from sea ice than the existing approaches

5. Characterization of sea-ice kinematic in the Arctic outflow region using buoy data

Ruibo Lei

2016-01-01

Full Text Available Data from four ice-tethered buoys deployed in 2010 were used to investigate sea-ice motion and deformation from the Central Arctic to Fram Strait. Seasonal and long-term changes in ice kinematics of the Arctic outflow region were further quantified using 42 ice-tethered buoys deployed between 1979 and 2011. Our results confirmed that the dynamic setting of the transpolar drift stream (TDS and Fram Strait shaped the motion of the sea ice. Ice drift was closely aligned with surface winds, except during quiescent conditions, or during short-term reversal of the wind direction opposing the TDS. Meridional ice velocity south of 85°N showed a distinct seasonal cycle, peaking between late autumn and early spring in agreement with the seasonality of surface winds. Inertia-induced ice motion was strengthened as ice concentration decreased in summer. As ice drifted southward into the Fram Strait, the meridional ice speed increased dramatically, while associated zonal ice convergence dominated the ice-field deformation. The Arctic atmospheric Dipole Anomaly (DA influenced ice drift by accelerating the meridional ice velocity. Ice trajectories exhibited less meandering during the positive phase of DA and vice versa. From 2005 onwards, the buoy data exhibit high Arctic sea-ice outflow rates, closely related to persistent positive DA anomaly. However, the long-term data from 1979 to 2011 do not show any statistically significant trend for sea-ice outflow, but exhibit high year-to-year variability, associated with the change in the polarity of DA.

6. Sediment-Laden sea ice in the Arctic Ocean: Implications for climate, environment and sedimentation

Sediments in sea ice were first described by F. Nansen during his famous Fram expedition (1893-1896). Many researchers observed and recorded sediment-laden or dirty sea ice in the Central Arctic, but the origin and incorporation mechanisms are poorly understood and were never the object of detailed studies. Sea ice-rafted sediments are important factors for the albedo and for the ecology and productivity of marine organisms, because of the absorption of solar radiation and lowered light transmission. Beginning in 1987 in the Eastern Arctic Basin and continuing in 1988, 1989 and 1990 in Fram Strait, Barents Sea and Greenland Sea the authors conducted a multi-disciplinary sea ice project on the role and importance of sea ice-rafted sediments for sedimentation in the Arctic Ocean. During the field work very high sediment accumulations were observed and sampled (up to 560 g sediment/kg ice). Most of the material was concentrated in small patches of 1-10 m in diameter, but in some areas, especially in the Eastern Arctic, they covered up to 80% of the ice surface and formed layers of pure mud, 2-3 cm thick. First estimations of the observed concentrations, the annual ice flow through Fram Strait, and the average sedimentation rate in this area show that the necessary sediment flux can be obtained only by sea ice. Thus, sea ice-rafting seems to be the most important input mechanism of fine grained terrigenous (biogenic and terrigenic) sediment into the ice-covered deep sea regions

7. Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

Miao, X.; Xie, H.; Li, Z.; Lei, R.

2013-12-01

The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture

8. Monitoring Arctic sea ice phenology change using hypertemporal remotely sensed data: 1989-2010

Tan, Wenxia; LeDrew, Ellsworth

2016-07-01

Arctic sea ice has undergone a significant decline in recent years. Previous studies have demonstrated that the annual sea ice cycle has experienced earlier melt and later freeze up, leading to a significant reduction in minimum sea ice extents and the lengthening of the melting season. The Arctic is being transformed into a regime of widespread seasonal ice with a large loss of old and thick multiyear ice in recent years. However, the sea ice change exhibits considerable interannual and regional variability at different spatial and temporal scales. In this study, we present a new method for hypertemporal sea ice data change detection based on the annual sea ice concentration (SIC) profile for the melt months of each year. A decision tree-based classification is adopted to group pixels with similar annual SIC profiles, and a phenology map of each year is generated for visualization. The phenoregion map visualizes the spatial and temporal configurations of ice melt process for a year. The change detection objective is achieved by comparing the phenoregion number of the same pixel in different years. The algorithm further leads to interpretation of anomalies to obtain change maps at the pixel level. Compared to previous sea ice studies that mainly focused on a particular spatial region and commonly use time period averages, the proposed pixel-based approach has the potential to map sea ice data change both temporally and spatially.

9. Numerical model of the ice cover evolution in Arctic Seas for the operational forecasting

S. V. Klyachkin

2015-01-01

Full Text Available The dynamic-thermodynamic model of the ice cover evolution is used for operational 5‑day ice forecasts in the Russian Arctic seas and to obtain some statistical estimates of the ice cover state. The model is a numerical realization of the heat budget and the motion balance equations for sea and ice cover with appropriate boundary conditions. The statistical processing of the data resulted in revealing characteristics of seasonal and spatial variability of the ice compressionin the Barents and Kara Seas.

10. A sea ice free summer Arctic within 30 years: An update from CMIP5 models

Wang, Muyin; Overland, James E.

2012-09-01

Three years ago we proposed that the summer Arctic would be nearly sea ice free by the 2030s; “nearly” is interpreted as sea ice extent less than 1.0 million km2. We consider this estimate to be still valid based on projections of updated climate models (CMIP5) and observational data. Similar to previous models (CMIP3), CMIP5 still shows a wide spread in hindcast and projected sea ice loss among different models. Further, there is no consensus in the scientific literature for the cause of such a spread in results for CMIP3 and CMIP5. While CMIP5 model mean sea ice extents are closer to observations than CMIP3, the rates of sea ice reduction in most model runs are slow relative to recent observations. All CMIP5 models do show loss of sea ice due to increased anthropogenic forcing relative to pre-industrial control runs. Applying the same technique of model selection and extrapolation approach to CMIP5 as we used in our previous paper, the interval range for a nearly sea ice free Arctic is 14 to 36 years, with a median value of 28 years. Relative to a 2007 baseline, this suggests a nearly sea ice free Arctic in the 2030s.

11. A study of Arctic sea ice freeboard heights, gravity anomalies and dynamic topography from ICESat measurementes

Skourup, Henriette

used to estimate the sea ice freeboard, and shows good qualitative correlation to QuikSCAT scatterometer data. As the method depends on the presence of open water, the method is underestimating the sea ice freeboard heights, when compared to coincident high resolution airborne lidar measurements in...... Arctic is a combination of sea ice and open water. The sea surface height is found by a "lowest-level" filtering procedure, originally developed for airborne lidar measurements, which assumes that the lowest levels measured represent the open water in the ice pack. The sea surface obtained this way is...... are investigated. The ICESat gravity grid shows all the major tectonic features of the Arctic Ocean at high resolution. The results show that the laser altimetry data provides excellent gravity results comparable to open ocean altimetry even over the most heavy ice conditions. Subtracting a geoid...

12. Modelling the mass balance and salinity of Arctic and Antarctic sea ice

Vancoppenolle, Martin

2008-01-01

Ice formed from seawater, called sea ice, is both an important actor in and a sensitive indicator of climate change. Covering 7% of the World Ocean, sea ice damps the atmosphere-ocean exchanges of heat, radiation and momentum in polar regions. It also affects the oceanic circulation at a global scale. Recent satellite and submarine observations systems indicate a sharp decrease in the extent and volume of Arctic sea ice over the last 30 years. In addition, climate models project drastic sea i...

13. Impact of a Reduced Arctic Sea Ice Cover on Ocean and Atmospheric Properties

Sedláček, Jan; Knutti, Reto; Martius, Olivia; Beyerle, Urs

2012-01-01

The Arctic sea ice cover declined over the last few decades and reached a record minimum in 2007, with a slight recovery thereafter. Inspired by this the authors investigate the response of atmospheric and oceanic properties to a 1-yr period of reduced sea ice cover. Two ensembles of equilibrium and transient simulations are produced with the Community Climate System Model. A sea ice change is induced through an albedo change of 1 yr. The sea ice area and thickness recover in both ensembles a...

14. Impacts of Organic Macromolecules, Chlorophyll and Soot on Arctic Sea Ice

Ogunro, O. O.; Wingenter, O. W.; Elliott, S.; Flanner, M.; Dubey, M. K.

2014-12-01

Recent intensification of Arctic amplification can be strongly connected to positive feedback relating black carbon deposition to sea ice surface albedo. In addition to soot deposition on the ice and snow pack, ice algal chlorophyll is likely to compete as an absorber and redistributor of energy. Hence, solar radiation absorption by chlorophyll and some components of organic macromolecules in/under the ice column is currently being examined to determine the level of influence on predicted rate of ice loss. High amounts of organic macromolecules and chlorophyll are produced in global sea ice by the bottom microbial community and also in vertically distributed layers where substantial biological activities take place. Brine channeling in columnar ice can allow for upward flow of nutrients which leads to greater primary production in the presence of moderate light. Modeling of the sea-ice processes in tandem with experiments and field observations promises rapid progress in enhancing Arctic ice predictions. We are designing and conducting global climate model experiments to determine the impact of organic macromolecules and chlorophyll on Arctic sea ice. Influences on brine network permeability and radiation/albedo will be considered in this exercise. Absorption by anthropogenic materials such as soot and black carbon will be compared with that of natural pigments. We will indicate areas of soot and biological absorption dominance in the sense of single scattering, then couple into a full radiation transfer scheme to attribute the various contributions to polar climate change amplification. The work prepares us to study more traditional issues such as chlorophyll warming of the pack periphery and chemical effects of the flow of organics from ice internal communities. The experiments started in the Arctic will broaden to include Antarctic sea ice and shelves. Results from the Arctic simulations will be presented.

15. SONARC: A Sea Ice Monitoring and Forecasting System to Support Safe Operations and Navigation in Arctic Seas

Stephenson, S. R.; Babiker, M.; Sandven, S.; Muckenhuber, S.; Korosov, A.; Bobylev, L.; Vesman, A.; Mushta, A.; Demchev, D.; Volkov, V.; Smirnov, K.; Hamre, T.

2015-12-01

Sea ice monitoring and forecasting systems are important tools for minimizing accident risk and environmental impacts of Arctic maritime operations. Satellite data such as synthetic aperture radar (SAR), combined with atmosphere-ice-ocean forecasting models, navigation models and automatic identification system (AIS) transponder data from ships are essential components of such systems. Here we present first results from the SONARC project (project term: 2015-2017), an international multidisciplinary effort to develop novel and complementary ice monitoring and forecasting systems for vessels and offshore platforms in the Arctic. Automated classification methods (Zakhvatkina et al., 2012) are applied to Sentinel-1 dual-polarization SAR images from the Barents and Kara Sea region to identify ice types (e.g. multi-year ice, level first-year ice, deformed first-year ice, new/young ice, open water) and ridges. Short-term (1-3 days) ice drift forecasts are computed from SAR images using feature tracking and pattern tracking methods (Berg & Eriksson, 2014). Ice classification and drift forecast products are combined with ship positions based on AIS data from a selected period of 3-4 weeks to determine optimal vessel speed and routing in ice. Results illustrate the potential of high-resolution SAR data for near-real-time monitoring and forecasting of Arctic ice conditions. Over the next 3 years, SONARC findings will contribute new knowledge about sea ice in the Arctic while promoting safe and cost-effective shipping, domain awareness, resource management, and environmental protection.

16. Arctic Sea Ice Charts from Danish Meteorological Institute, 1893 - 1956

National Oceanic and Atmospheric Administration, Department of Commerce — From 1893 to 1956, the Danish Meteorological Institute (DMI) created charts of observed and inferred sea ice extent for each summer month. These charts are based on...

17. Sea Ice Melt Pond Data from the Canadian Arctic

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains observations of albedo, depth, and physical characteristics of melt ponds on sea ice, taken during the summer of 1994. The melt ponds studied...

18. Late winter biogeochemical conditions under sea ice in the Canadian High Arctic

Helen S. Findlay

2015-12-01

Full Text Available With the Arctic summer sea-ice extent in decline, questions are arising as to how changes in sea-ice dynamics might affect biogeochemical cycling and phenomena such as carbon dioxide (CO2 uptake and ocean acidification. Recent field research in these areas has concentrated on biogeochemical and CO2 measurements during spring, summer or autumn, but there are few data for the winter or winter–spring transition, particularly in the High Arctic. Here, we present carbon and nutrient data within and under sea ice measured during the Catlin Arctic Survey, over 40 days in March and April 2010, off Ellef Ringnes Island (78° 43.11′ N, 104° 47.44′ W in the Canadian High Arctic. Results show relatively low surface water (1–10 m nitrate (<1.3 µM and total inorganic carbon concentrations (mean±SD=2015±5.83 µmol kg−1, total alkalinity (mean±SD=2134±11.09 µmol kg−1 and under-ice pCO2sw (mean±SD=286±17 µatm. These surprisingly low wintertime carbon and nutrient conditions suggest that the outer Canadian Arctic Archipelago region is nitrate-limited on account of sluggish mixing among the multi-year ice regions of the High Arctic, which could temper the potential of widespread under-ice and open-water phytoplankton blooms later in the season.

19. Spatial and temporal variations in the age structure of Arctic sea ice

Belchansky, G.I.; Douglas, D.C.; Platonov, N.G.

2005-01-01

Spatial and temporal variations in the age structure of Arctic sea ice are investigated using a new reverse chronology algorithm that tracks ice-covered pixels to their location and date of origin based on ice motion and concentration data. The Beaufort Gyre tends to harbor the oldest (>10 years old) sea ice in the western Arctic while direct ice advection pathways toward the Transpolar Drift Stream maintain relatively young (10 years old (10+ year age class) were observed during 1989-2003. Since the mid-1990s, losses to the 10+ year age class lacked compensation by recruitment due to a prior depletion of all mature (6-10 year) age classes. Survival of the 1994 and 1996-1998 sea ice generations reestablished most mature age classes, and thereby the potential to increase extent of the 10+ year age class during the mid-2000s.

20. Insights on Arctic Sea Ice Processes from New Seafloor and Coastline Mapping

Nghiem, S. V.; Hall, D. K.; Rigor, I. G.; Clemente-Colon, P.; Li, P.; Neumann, G.

2014-12-01

The seafloor can exert a significant control on Arctic sea ice patterns by guiding the distribution of ocean water masses and river discharge in the Arctic Ocean. Satellite observations of sea ice and surface temperature are used together with bathymetry data to understand dynamic and thermodynamic processes of sea ice. In particular, data from satellite radars, including scatterometer and synthetic aperture radar (SAR) instruments, are used to identify and map sea ice with different spatial and temporal resolutions across the Arctic. Data from a satellite spectroradiometer, such as MODIS, are used to accurately measure surface temperature under clear sky conditions. For seafloor measurements, advances have been made with new observations surveyed to modern standards in different regions of the Arctic, enabling the production of an improved bathymetry dataset, such as the International Bathymetric Chart of the Arctic Ocean Version 3.0 (IBCAO 3.0) released in 2012. The joint analyses of these datasets reveal that the seafloor can govern warm- and cold-water distribution and thereby dictate sea ice patterns on the sea surface from small local scales to a large regional scale extending over thousands of km. Satellite results show that warm river waters can intrude into the Arctic Ocean and affect sea ice melt hundreds of km away from the river mouths. The Arctic rivers bring significant heat as their waters come from sources across vast watersheds influenced by warm continental climate effects in summertime. In the case of the Mackenzie River, results from the analysis with the new IBCAO 3.0 indicated that the formation and break-up of landfast sea ice is related to the depth and not the slope of the seafloor. In turn, such ice processes can impact the discharge and distribution of warm river waters and influence the melting of sea ice. Animations of satellite observations of sea ice overlaid on both the old and new versions of IBCAO will be presented to illustrate

1. Temporal and spatial variability in sea-ice carbon:nitrogen ratios on Canadian Arctic shelves

Andrea Niemi

2015-12-01

Full Text Available Abstract To enhance the accuracy of carbon cycling models as applied to sea ice in the changing Arctic, we analyzed a large data set of particulate organic carbon (POC and nitrogen (PON measurements in first-year bottom sea ice (n = 257 from two Arctic shelves, the Canadian Arctic Archipelago and Beaufort Sea shelf, including dark winter and spring seasonal measurements. Wide ranges of sea-ice POC:PON ratios were observed during both the dark winter (12–46 mol:mol and spring (3–24 mol:mol periods. Sea-ice POC:PON ratios and chlorophyll a concentrations were significantly higher in the Archipelago versus the Beaufort Sea shelf (p < 0.01, yet there was a highly significant relationship between sea-ice POC and PON during spring for both shelves (r2 = 0.94. POC:PON ratios were not consistent over the range of measured POC and PON concentrations, justifying the use of a power function model to best describe the relationship between POC and PON. Distinct relationships between POC:PON ratios and chlorophyll-based biomass were observed for the dark winter and the spring: dark winter sea-ice POC:PON ratios decreased with increasing sea-ice biomass whereas spring POC:PON ratios increased with increasing sea-ice biomass. The transition from the dark period to the spring growth period in first-year sea ice represented a distinct stoichiometric shift in POC:PON ratios. Our results demonstrate that the Redfield ratio has limited applicability over the four-order of magnitude range of biomass concentrations observed in first-year sea ice on Arctic shelves. This study emphasizes the need for variable POC:PON stoichiometry in sea-ice biogeochemical models and budget estimates, in particular at high biomass concentrations and when considering seasonality outside of the spring period in first year ice. The use of a power function model for POC:PON relationships in sea ice is also recommended to better constrain carbon estimates in biogeochemical sea-ice models.

2. Does ocean coupling matter for the northern extratropical response to projected Arctic sea ice loss?

Deser, Clara; Sun, Lantao; Tomas, Robert A.; Screen, James

2016-03-01

The question of whether ocean coupling matters for the extratropical Northern Hemisphere atmospheric response to projected late 21st century Arctic sea ice loss is addressed using a series of experiments with Community Climate System Model version 4 at 1° spatial resolution under different configurations of the ocean model component: no interactive ocean, thermodynamic slab ocean, and full-depth (dynamic plus thermodynamic) ocean. Ocean-atmosphere coupling magnifies the response to Arctic sea ice loss but does not change its overall structure; however, a slab ocean is inadequate for inferring the role of oceanic feedbacks. The westerly winds along the poleward flank of the eddy-driven jet weaken in response to Arctic sea ice loss, accompanied by a smaller-magnitude strengthening on the equatorward side, with largest amplitudes in winter. Dynamical and thermodynamic oceanic feedbacks amplify this response by approximately 50%. Air temperature, precipitation, and sea level pressure responses also show sensitivity to the degree of ocean coupling.

3. Arctic sea ice variability during the last deglaciation: a biomarker approach

Müller, J.; Stein, R. H.

2014-12-01

The last transition from full glacial to current interglacial conditions was accompanied by distinct short-term climate fluctuations caused by changes in the global ocean circulation system. Most palaeoceanographic studies focus on the documentation of the behaviour of the Atlantic Meridional Overturning Circulation (AMOC) during the last deglaciation in response to freshwater forcing events. In this respect, the role of Arctic sea ice remained relatively unconsidered - primarily because of the difficulty of its reconstruction. Here we present new proxy data on late glacial (including the Last Glacial Maximum; LGM) and deglacial sea ice variability in the Arctic Ocean and its main gateway - the Fram Strait - and how these changes in sea ice coverage contributed to AMOC perturbations observed during Heinrich Event 1 and the Younger Dryas. Recurrent short-term advances and retreats of sea ice in Fram Strait, prior and during the LGM, are in line with a variable (or intermittent) North Atlantic heat flow along the eastern corridor of the Nordic Seas. Possibly in direct response to the initial freshwater discharge from melting continental ice-sheets, a permanent sea ice cover established only at about 19 ka BP (i.e. post-LGM) and lasted until 17.6 ka BP, when an abrupt break-up of this thick ice cover and a sudden discharge of huge amounts of sea ice and icebergs through Fram Strait coincided with the weakening of the AMOC during Heinrich Event 1. Similarly, another sea ice maximum at about 12.8 ka BP is associated with the slowdown of the AMOC during the Younger Dryas. The new data sets clearly highlight the important role of Arctic sea ice for the re-organisation of the oceanographic setting in the North Atlantic during the last deglaciation. Further studies and sensitivity experiments to identify crucial driving (and feedback) mechanisms within the High Latitude ice-ocean-atmosphere system will contribute the understanding of rapid climate changes.

4. A Possible Feedback Mechanism Involving the Arctic Freshwater,the Arctic Sea Ice, and the North Atlantic Drift

Odd Helge OTTER(A); Helge DRANGE

2004-01-01

Model studies point to enhanced warming and to increased freshwater fluxes to high northern latitudes in response to global warming. In order to address possible feedbacks in the ice-ocean system in response to such changes, the combined effect of increased freshwater input to the Arctic Ocean and Arctic warming--the latter manifested as a gradual melting of the Arctic sea ice--is examined using a 3-D isopycnic coordinate ocean general circulation model. A suite of three idealized experiments is carried out: one control integration, one integration with a doubling of the modern Arctic river runoff, and a third more extreme case, where the river runoff is five times the modern value. In the two freshwater cases, the sea ice thickness is reduced by 1.5-2 m in the central Arctic Ocean over a 50-year period. The modelled ocean response is qualitatively the same for both perturbation experiments: freshwater propagates into the Atlantic Ocean and the Nordic Seas, leading to an initial weakening of the North Atlantic Drift.Furthermore, changes in the geostrophic currents in the central Arctic and melting of the Arctic sea ice lead to an intensified Beaufort Gyre, which in turn increases the southward volume transport through the Canadian Archipelago. To compensate for this southward transport of mass, more warm and saline Atlantic water is carried northward with the North Atlantic Drift. It is found that the increased transport of salt into the northern North Atlantic and the Nordic Seas tends to counteract the impact of the increased freshwater originating from the Arctic, leading to a stabilization of the North Atlantic Drift.

5. Frost flowers on young Arctic sea ice: The climatic, chemical, and microbial significance of an emerging ice type

Barber, D.; Ehn, J.; Pucko, M.;

2014-01-01

Ongoing changes in Arctic sea ice are increasing the spatial and temporal range of young sea ice types over which frost flowers can occur, yet the significance of frost flowers to ocean-sea ice-atmosphere exchange processes remains poorly understood. Frost flowers form when moisture from seawater...... formed. The new ice and frost flowers dramatically changed the radiative and thermal environment. The frost flowers were about 5°C colder than the brine surface, with an approximately linear temperature gradient from their base to their upper tips. Salinity and δ18O values indicated that frost flowers...

6. A Low Order Theory of Arctic Sea Ice Stability

Moon, W

2011-01-01

We analyze the stability of a low-order coupled sea ice and climate model and extract the essential physics governing the time scales of response as a function of greenhouse gas forcing. Under present climate conditions the stability is controlled by longwave radiation driven heat conduction. However, as greenhouse gas forcing increases and the ice cover decays, the destabilizing influence of ice-albedo feedback acts on equal footing with longwave stabilization. Both are seasonally out of phase and as the system warms towards a seasonal ice state these effects, which underlie the bifurcations between climate states, combine to extend the intrinsic relaxation time scale from ~ 2 yr to 5 yr.

7. Observational determination of albedo decrease caused by vanishing Arctic sea ice.

Pistone, Kristina; Eisenman, Ian; Ramanathan, V

2014-03-01

The decline of Arctic sea ice has been documented in over 30 y of satellite passive microwave observations. The resulting darkening of the Arctic and its amplification of global warming was hypothesized almost 50 y ago but has yet to be verified with direct observations. This study uses satellite radiation budget measurements along with satellite microwave sea ice data to document the Arctic-wide decrease in planetary albedo and its amplifying effect on the warming. The analysis reveals a striking relationship between planetary albedo and sea ice cover, quantities inferred from two independent satellite instruments. We find that the Arctic planetary albedo has decreased from 0.52 to 0.48 between 1979 and 2011, corresponding to an additional 6.4 ± 0.9 W/m(2) of solar energy input into the Arctic Ocean region since 1979. Averaged over the globe, this albedo decrease corresponds to a forcing that is 25% as large as that due to the change in CO2 during this period, considerably larger than expectations from models and other less direct recent estimates. Changes in cloudiness appear to play a negligible role in observed Arctic darkening, thus reducing the possibility of Arctic cloud albedo feedbacks mitigating future Arctic warming. PMID:24550469

8. Observational uncertainty of Arctic sea-ice concentration significantly affects seasonal climate forecasts

Bunzel, Felix; Notz, Dirk; Baehr, Johanna; Müller, Wolfgang; Fröhlich, Kristina

2016-04-01

We examine how the choice of a particular satellite-retrieved sea-ice concentration dataset used for initialising seasonal climate forecasts impacts the prediction skill of Arctic sea-ice area and Northern hemispheric 2-meter air temperatures. To do so, we performed two assimilation runs with the Max Planck Institute Earth System Model (MPI-ESM) from 1979 to 2012, where atmospheric and oceanic parameters as well as sea-ice concentration were assimilated using Newtonian relaxation. The two assimilation runs differ only in the sea-ice concentration dataset used for assimilating sea ice. In the first run, we use sea-ice concentrations as derived by the NASA-Team algorithm, while in the second run we use sea-ice concentrations as derived from the Bootstrap algorithm. A major difference between these two sea-ice concentration data products involves the treatment of melt ponds. While for both products melt ponds appear as open water in the raw satellite data, the Bootstrap algorithm more strongly attempts to offset this systematic bias by synthetically increasing the retrieved ice concentration during summer months. For each year of the two assimilation runs we performed a 10-member ensemble of hindcast experiments starting on 1 May and 1 November with a hindcast length of 6 months. For hindcasts started in November, initial differences in Arctic sea-ice area and surface temperature decrease rapidly throughout the freezing period. For hindcasts started in May, initial sea-ice area differences increase over time. By the end of the melting period, this causes significant differences in 2-meter air temperature of regionally more than 3°C. Hindcast skill for surface temperatures over Europe and North America is higher with Bootstrap initialization during summer and with NASA Team initialisation during winter. This implies that the choice of the sea-ice data product and, thus, the observational uncertainty also affects forecasts of teleconnections that depend on Northern

9. Sea-ice hazards, associated risks and implications for human activities in the Arctic

Eicken, Hajo; Mahoney, Andrew; Jones, Joshua

2014-05-01

Polar sea ice serves important functions in the Earth system, including as climate regulator, habitat for diverse biological communities, or substrate and platform for a range of human activities. Subsumed under the concept of sea-ice services, polar ice covers are associated with benefits and risks of harm to ecosystems and people. Recent changes in Arctic ice extent, thickness and mobility have transformed services derived from sea ice. We summarize how these changes have diminished some benefits derived from the ice cover, while increasing others. More important, growing maritime activities in the North and a changing ice cover drive a need for better understanding of sea-ice hazards and the risk they represent in the context of human activities in the Arctic. Three major aspects of this problem are: (1) Broader risks associated with a rapid reduction in summer ice extent, such as geographic shifts in marine ecosystems and warming of submarine permafrost and adjacent land; (2) hazards resulting from changes in sea ice extent and dynamics such as increased coastal erosion and threats to infrastructure; and (3) risks derived from the combination of sea-ice hazards and human activities such as shipping or offshore resource development. Problem (1) is typically seen as a slow-onset hazard that requires a response in the form of mitigation and adaptation. At the same time, the importance of linkages between summer sea-ice reduction to processes outside of the Arctic has only recently emerged (such as atmospheric circulation patterns and extreme weather events) and remains difficult to quantify. Hazards and risks subsumed under (2) and (3) are more localized but with potentially major ecological and socio-economic consequences beyond the Arctic. Drawing on examples from our research in Alaska, we review and illustrate key aspects of sea-ice hazards in terms of risks to ecosystems, people and infrastructure in the coastal zone and Arctic shelf seas. In the Pacific

10. Sensitivity of the Arctic sea ice concentration forecasts to different atmospheric forcing：a case study

YANG Qinghua; LIU Jiping; ZHANG Zhanhai; SUI Cuijuan; XING Jianyong; LI Ming; LI Chunhua; ZHAO Jiechen; ZHANG Lin

2014-01-01

A regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MIT-gcm) is used as the coupled ice-ocean model for forecasting sea ice conditions in the Arctic Ocean at the Na-tional Marine Environmental Forecasting Center of China (NMEFC), and the numerical weather prediction from the National Center for Environmental Prediction Global Forecast System (NCEP GFS) is used as the atmospheric forcing. To improve the sea ice forecasting, a recently developed Polar Weather Research and Forecasting model (Polar WRF) model prediction is also tested as the atmospheric forcing. Their forecasting performances are evaluated with two different satellite-derived sea ice concentration products as initializa-tions: (1) the Special Sensor Microwave Imager/Sounder (SSMIS) and (2) the Advanced Microwave Scanning Radiometer for EOS (AMSR-E). Three synoptic cases, which represent the typical atmospheric circulations over the Arctic Ocean in summer 2010, are selected to carry out the Arctic sea ice numerical forecasting experiments. The evaluations suggest that the forecasts of sea ice concentrations using the Polar WRF atmo-spheric forcing show some improvements as compared with that of the NCEP GFS.

11. Skill improvement of seasonal Arctic sea ice forecasts using bias-correction and ensemble calibration

Krikken, Folmer; Hazeleger, Wilco; Vlot, Willem; Schmeits, Maurice; Guemas, Virginie

2016-04-01

We explore the standard error and skill of dynamical seasonal sea ice forecasts of the Arctic using different bias-correction and ensemble calibration methods. The latter is often used in weather forecasting, but so far has not been applied to Arctic sea ice forecasts. We use seasonal predictions of Arctic sea ice of a 5-member ensemble forecast using the fully coupled GCM EC-Earth, with model initial states obtained by nudging towards ORAS4 and ERA-Interim. The raw model forecasts contain large biases in total sea ice area, especially during the summer months. This is mainly caused by a difference in average seasonal cycle between EC-Earth and observations, which translates directly into the forecasts yielding large biases. Further errors are introduced by the differences in long term trend between the observed sea ice, and the uninitialised EC-earth simulation. We find that extended logistic regression (ELR) and heteroscedastic extended logistic regression (HELR) both prove viable ensemble calibration methods, and improve the forecasts substantially compared to standard bias correction techniques. No clear distinction between ELR and HELR is found. Forecasts starting in May have higher skill (CRPSS > 0 up to 5 months lead time) than forecasts starting in August (2-3 months) and November (2-3 months), with trend-corrected climatology as reference. Analysis of regional skill in the Arctic shows distinct differences, where mainly the Arctic ocean and the Kara and Barents sea prove to be one of the more predictable regions with skilful forecasts starting in May up to 5-6 months lead time. Again, forecasts starting in August and November show much lower regional skill. Overall, it is still difficult to beat relative simple statistical forecasts, but by using ELR and HELR we are getting reasonably close to skilful seasonal forecasts up to 12 months lead time. These results show there is large potential, and need, for using ensemble calibration in seasonal forecasts of

12. Future Arctic sea ice loss reduces severity of cold air outbreaks in midlatitudes

Ayarzagüena, Blanca; Screen, James A.

2016-03-01

The effects of Arctic sea ice loss on cold air outbreaks (CAOs) in midlatitudes remain unclear. Previous studies have defined CAOs relative to the present-day climate, but changes in CAOs, defined in such a way, may reflect changes in mean climate and not in weather variability, and society is more sensitive to the latter. Here we revisit this topic but applying changing temperature thresholds relating to climate conditions of the time. CAOs do not change in frequency or duration in response to projected sea ice loss. However, they become less severe, mainly due to advection of warmed polar air, since the dynamics associated with the occurrence of CAOs are largely not affected. CAOs weaken even in midlatitude regions where the winter mean temperature decreases in response to Arctic sea ice loss. These results are robustly simulated by two atmospheric models prescribed with differing future sea ice states and in transient runs where external forcings are included.

13. Arctic climate change: observed and modelled temperature and sea-ice variability

Johannessen, Ola M.; BENGTSSON, LENNART; MILES, MARTIN W.; Kuzmina, Svetlana I.; Semenov, Vladimir A.; Alekseev, Genrikh V.; NAGURNYI, ANDREI P.; Zakharov, Victor F.; Bobylev, Leonid P.; Pettersson, Lasse H.; HASSELMANN, KLAUS; Cattle, Howard P.

2004-01-01

Changes apparent in the arctic climate system in recent years require evaluation in a century-scale perspective in order to assess the Arctic's response to increasing anthropogenic greenhouse-gas forcing. Here, a new set of century- and multidecadal-scale observational data of surface air temperature (SAT) and sea ice is used in combination with ECHAM4 and HadCM3 coupled atmosphere-ice-ocean global model simulations in order to better determine and understand arctic climate variability. We sh...

14. In situ expression of eukaryotic ice-binding proteins in microbial communities of Arctic and Antarctic sea ice.

Uhlig, Christiane; Kilpert, Fabian; Frickenhaus, Stephan; Kegel, Jessica U; Krell, Andreas; Mock, Thomas; Valentin, Klaus; Beszteri, Bánk

2015-11-01

Ice-binding proteins (IBPs) have been isolated from various sea-ice organisms. Their characterisation points to a crucial role in protecting the organisms in sub-zero environments. However, their in situ abundance and diversity in natural sea-ice microbial communities is largely unknown. In this study, we analysed the expression and phylogenetic diversity of eukaryotic IBP transcripts from microbial communities of Arctic and Antarctic sea ice. IBP transcripts were found in abundances similar to those of proteins involved in core cellular processes such as photosynthesis. Eighty-nine percent of the IBP transcripts grouped with known IBP sequences from diatoms, haptophytes and crustaceans, but the majority represented novel sequences not previously characterized in cultured organisms. The observed high eukaryotic IBP expression in natural eukaryotic sea ice communities underlines the essential role of IBPs for survival of many microorganisms in communities living under the extreme conditions of polar sea ice. PMID:25885562

15. Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations

Kauker, F.; Kaminski, T.; Ricker, R.; Toudal-Pedersen, L.; Dybkjaer, G.; Melsheimer, C.; Eastwood, S.; Sumata, H.; Karcher, M.; Gerdes, R.

2015-10-01

The recent thinning and shrinking of the Arctic sea ice cover has increased the interest in seasonal sea ice forecasts. Typical tools for such forecasts are numerical models of the coupled ocean sea ice system such as the North Atlantic/Arctic Ocean Sea Ice Model (NAOSIM). The model uses as input the initial state of the system and the atmospheric boundary condition over the forecasting period. This study investigates the potential of remotely sensed ice thickness observations in constraining the initial model state. For this purpose it employs a variational assimilation system around NAOSIM and the Alfred Wegener Institute's CryoSat-2 ice thickness product in conjunction with the University of Bremen's snow depth product and the OSI SAF ice concentration and sea surface temperature products. We investigate the skill of predictions of the summer ice conditions starting in March for three different years. Straightforward assimilation of the above combination of data streams results in slight improvements over some regions (especially in the Beaufort Sea) but degrades the over-all fit to independent observations. A considerable enhancement of forecast skill is demonstrated for a bias correction scheme for the CryoSat-2 ice thickness product that uses a spatially varying scaling factor.

16. Airborne lidar measurements of surface ozone depletion over Arctic sea ice

Seabrook, J. A.; Whiteway, J. A.; Gray, L. H.; Staebler, R.; A. Herber

2013-01-01

A differential absorption lidar (DIAL) for measurement of atmospheric ozone concentration was operated aboard the Polar 5 research aircraft in order to study the depletion of ozone over Arctic sea ice. The lidar measurements during a flight over the sea ice north of Barrow, Alaska, on 3 April 2011 found a surface boundary layer depletion of ozone over a range of 300 km. The photochemical destruction of surface level ozone was strongest at the most northern point of the flight, and steadily de...

17. Sea ice melt onset dynamics in the northern Canadian Arctic Archipelago from RADARSAT

Mahmud, M. S.; Howell, S.; Geldsetzer, T.; Yackel, J.

2015-12-01

Sea ice melt onset, the appearance of liquid water in its snow cover, decreases surface albedo which increases shortwave absorption and thereby accelerates snow and sea ice melting. Earlier melt onset leads to the earlier formation of open water which enhances the ice-albedo feedback. Sea ice melt onset timing and duration vary considerably, both spatially and temporally, owing to variability in atmospheric forcing; this in turn influences the September sea ice extent. Sea ice melt onset variability has been investigated using coarse resolution passive microwave observation in Canadian Arctic Archipelago (CAA); however, this does not provide sufficient information about sea ice melt dynamics. We developed a new melt onset algorithm using high resolution synthetic aperture radar (SAR) images from RADARSAT to better understand sea ice melt onset dynamics in northern Canadian Arctic Archipelago (fig 1) from 1997 to 2014. The algorithm is based on the temporal evolution of the SAR backscatter coefficient (σo), using separate thresholds for seasonal first-year ice and multi-year ice. Results indicated that the mean annual average melt onset date in the northern CAA was on year day 164 (mid-June) with a standard deviation of 4 days over the 18 year period. No significant trend for melt onset date was found over the 18 year period (fig: 2) but extreme early melt onset was detected in 1998 and 2012 associated with anomalous atmospheric forcing. Spatially, sea ice onset over the entire northern CAA varied from a 10-day minimum in 2007, to a 35-day maximum in 2011 and exhibited negative correlation (r=0.70) with the rate of increase in surface air temperature (fig 3) derived from Extended AVHRR Polar Pathfinder (APP-x) dataset. An earlier (later) melt onset also results in light (heavier) September sea ice area in the northern CAA (fig 4).

18. Changes in Arctic and Antarctic Sea Ice as a Microcosm of Global Climate Change

Parkinson, Claire L.

2014-01-01

Polar sea ice is a key element of the climate system and has now been monitored through satellite observations for over three and a half decades. The satellite observations reveal considerable information about polar ice and its changes since the late 1970s, including a prominent downward trend in Arctic sea ice coverage and a much lesser upward trend in Antarctic sea ice coverage, illustrative of the important fact that climate change entails spatial contrasts. The decreasing ice coverage in the Arctic corresponds well with contemporaneous Arctic warming and exhibits particularly large decreases in the summers of 2007 and 2012, influenced by both preconditioning and atmospheric conditions. The increasing ice coverage in the Antarctic is not as readily explained, but spatial differences in the Antarctic trends suggest a possible connection with atmospheric circulation changes that have perhaps been influenced by the Antarctic ozone hole. The changes in the polar ice covers and the issues surrounding those changes have many commonalities with broader climate changes and their surrounding issues, allowing the sea ice changes to be viewed in some important ways as a microcosm of global climate change.

19. Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles – variability and change

V. A. Semenov; Martin, T.; Behrens, L. K.; M Latif

2015-01-01

The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the model results exhibit considerable spread. The last generation of climate models from World Climate Research ...

20. Surface water mass composition changes captured by cores of Arctic land-fast sea ice

Smith, I. J.; Eicken, H.; Mahoney, A. R.; Van Hale, R.; Gough, A. J.; Fukamachi, Y.; Jones, J.

2016-04-01

In the Arctic, land-fast sea ice growth can be influenced by fresher water from rivers and residual summer melt. This paper examines a method to reconstruct changes in water masses using oxygen isotope measurements of sea ice cores. To determine changes in sea water isotope composition over the course of the ice growth period, the output of a sea ice thermodynamic model (driven with reanalysis data, observations of snow depth, and freeze-up dates) is used along with sea ice oxygen isotope measurements and an isotopic fractionation model. Direct measurements of sea ice growth rates are used to validate the output of the sea ice growth model. It is shown that for sea ice formed during the 2011/2012 ice growth season at Barrow, Alaska, large changes in isotopic composition of the ocean waters were captured by the sea ice isotopic composition. Salinity anomalies in the ocean were also tracked by moored instruments. These data indicate episodic advection of meteoric water, having both lower salinity and lower oxygen isotopic composition, during the winter sea ice growth season. Such advection of meteoric water during winter is surprising, as no surface meltwater and no local river discharge should be occurring at this time of year in that area. How accurately changes in water masses as indicated by oxygen isotope composition can be reconstructed using oxygen isotope analysis of sea ice cores is addressed, along with methods/strategies that could be used to further optimize the results. The method described will be useful for winter detection of meteoric water presence in Arctic fast ice regions, which is important for climate studies in a rapidly changing Arctic. Land-fast sea ice effective fractionation coefficients were derived, with a range of +1.82‰ to +2.52‰. Those derived effective fractionation coefficients will be useful for future water mass component proportion calculations. In particular, the equations given can be used to inform choices made when

1. Assessing the controllability of Arctic sea ice extent by sulfate aerosol geoengineering

Jackson, L. S.; Crook, J. A.; Jarvis, A.; Leedal, D.; Ridgwell, A.; Vaughan, N.; Forster, P. M.

2015-02-01

In an assessment of how Arctic sea ice cover could be remediated in a warming world, we simulated the injection of SO2 into the Arctic stratosphere making annual adjustments to injection rates. We treated one climate model realization as a surrogate "real world" with imperfect "observations" and no rerunning or reference to control simulations. SO2 injection rates were proposed using a novel model predictive control regime which incorporated a second simpler climate model to forecast "optimal" decision pathways. Commencing the simulation in 2018, Arctic sea ice cover was remediated by 2043 and maintained until solar geoengineering was terminated. We found quantifying climate side effects problematic because internal climate variability hampered detection of regional climate changes beyond the Arctic. Nevertheless, through decision maker learning and the accumulation of at least 10 years time series data exploited through an annual review cycle, uncertainties in observations and forcings were successfully managed.

2. Circumpolar Arctic greening: Relationships to summer sea-ice concentrations, land temperatures and disturbance regimes

Walker, D. A.; Bhatt, U. S.; Epstein, H. E.; Raynolds, M. K.; Frost, G. V.; Leibman, M. O.; Khomutov, A.; Jia, G.; Comiso, J. C.; Pinzon, J. E.; Tucker, C. J.; Webber, P. J.; Tweedie, C. E.

2009-12-01

The global distribution of Arctic tundra vegetation is closely tied to the presence of summer sea ice. Models predict that the reduction of sea ice will cause large changes to summer land-surface temperatures. Warming combined with increased natural and anthropogenic disturbance are expected to greatly increase arctic tundra productivity. To examine where tundra productivity is changing most rapidly, we studied 1982-2008 trends of sea-ice concentrations, summer warmth index (SWI) and the annual Maximum Normalized Difference Vegetation Index (MaxNDVI). We summarize the results according to the tundra adjacent to 14 Arctic seas. Sea-ice concentrations have declined and summer land temperatures have increased in all parts of the Arctic coast. The overall percentage increase in Arctic MaxNDVI was +7%. The trend was much greater in North America (+11%) than in Eurasia (+4%). Large percentage increases of MaxNDVI occurred inland from Davis Straight (+20%), Baffin Bay (+18%), Canadian Archipelago (+14%), Beaufort Sea (+12%), and Laptev Sea (+8%). Declines occurred in the W. Chukchi (-6%) and E. Bering (-5%) seas. The changes in NDVI are strongly correlated to changes in summer ground temperatures. Two examples from a 900-km north-south Arctic transect in Russia and long-term observations at a High Arctic site in Canada provide insights to where the changes in productivity are occurring most rapidly. At tree line near Kharp in northwest Siberia, alder shrubs are expanding vigorously in fire-disturbed areas; seedling establishment is occurring primarily in areas with disturbed mineral soils, particularly nonsorted circles. In the Low Arctic tundra areas of the central Yamal Peninsula greening is concentrated in riparian areas and upland landslides associated with degrading massive ground ice, where low-willow shrublands replace the zonal sedge, dwarf-shrub tundra growing on nutrient-poor sands. In polar desert landscapes near the Barnes Ice Cap, Baffin Island, Canada

3. Advancing the understanding of variations of Arctic sea ice optical and thermal behaviors through an international research and mobility project

Marcel Nicolaus; LEI Ruibo; LI Qun; LU Peng; Caixin Wang; Sebastian Gerland; LI Na; LI Zhijun; Bin Cheng; Don K Perovich; Mats A Granskog; SHI Liqiong

2015-01-01

In recent decades, significant changes of Arctic sea ice have taken place. These changes are expected to influence the surface energy balance of the ice-covered Arctic Ocean. To quantify this energy balance and to increase our understanding of mechanisms leading to observed changes in the Arctic sea ice, the project“Advancing Modelling and Observing solar Radiation of Arctic sea ice—understanding changes and processes (AMORA)”was initiated and conducted from 2009 to 2013. AMORA was funded and organized under a frame of Norway-China bilateral collaboration program with partners from Finland, Germany, and the USA. The primary goal of the project was achieved by developing an autonomous spectral radiation buoy, deploying it on drifting sea ice close to the North Pole, and receiving a high-resolution time series of spectral radiation over and under sea ice from spring (before melt onset) to autumn (after freeze-up) 2012. Beyond this, in-situ sea ice data were collected during several ifeld campaigns and simulations of snow and sea ice thermodynamics were performed. More autonomous measurements are available through deployments of sea ice mass balance buoys. These new observational data along with numerical model studies are helping us to better understand the key thermodynamic processes of Arctic sea ice and changes in polar climate. A strong scientiifc, but also cultural exchange between Norway, China, and the partners from the USA and Europe initiated new collaborations in Arctic reseach.

4. Atmospheric response in summer linked to recent Arctic sea ice loss

Petrie, Ruth E.; Shaffrey, Len C.; Sutton, Rowan T.

2015-01-01

Since 2007 a large decline in Arctic sea ice has been observed. The large-scale atmospheric circulation response to this decline is investigated in ERA-Interim reanalyses and HadGEM3 climate model experiments. In winter, post-2007 observed circulation anomalies over the Arctic, North Atlantic and Eurasia are small compared to interannual variability. In summer, the post-2007 observed circulation is dominated by an anticyclonic anomaly over Greenland which has a large signal-to-noise ratio. Cl...

5. Cyclone impact on sea ice in the central Arctic Ocean: a statistical study

A. Kriegsmann

2013-03-01

Full Text Available This study investigates the impact of cyclones on the Arctic Ocean sea ice for the first time in a statistical manner. We apply the coupled ice–ocean model NAOSIM which is forced by the ECMWF analyses for the period 2006–2008. Cyclone position and radius detected in the ECMWF data are used to extract fields of wind, ice drift, and concentration from the ice–ocean model. Composite fields around the cyclone centre are calculated for different cyclone intensities, the four seasons, and different regions of the Arctic Ocean. In total about 3500 cyclone events are analyzed. In general, cyclones reduce the ice concentration on the order of a few percent increasing towards the cyclone centre. This is confirmed by independent AMSR-E satellite data. The reduction increases with cyclone intensity and is most pronounced in summer and on the Siberian side of the Arctic Ocean. For the Arctic ice cover the impact of cyclones has climatologic consequences. In winter, the cyclone-induced openings refreeze so that the ice mass is increased. In summer, the openings remain open and the ice melt is accelerated via the positive albedo feedback. Strong summer storms on the Siberian side of the Arctic Ocean may have been important reasons for the recent ice extent minima in 2007 and 2012.

6. Snow and sea ice thermodynamics in the Arctic: Model validation and sensitivity study against SHEBA data

CHENG Bin; Timo Vihma; ZHANG Zhan-hai; LI Zhi-jun; WU Hui-ding

2008-01-01

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model (HIGHTSI). Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution.The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedhack processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parametetization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

7. Sensitivity of Pliocene Arctic climate to orbital forcing, atmospheric CO2 and sea ice albedo parameterisation

Howell, Fergus W.; Haywood, Alan M.; Dowsett, Harry J.; Pickering, Steven J.

2016-05-01

General circulation model (GCM) simulations of the mid-Pliocene Warm Period (mPWP, 3.264 to 3.025 Myr ago) do not reproduce the magnitude of Northern Hemisphere high latitude surface air and sea surface temperature (SAT and SST) warming that proxy data indicate. There is also large uncertainty regarding the state of sea ice cover in the mPWP. Evidence for both perennial and seasonal mPWP Arctic sea ice is found through analyses of marine sediments, whilst in a multi-model ensemble of mPWP climate simulations, half of the ensemble simulated ice-free summer Arctic conditions. Given the strong influence that sea ice exerts on high latitude temperatures, an understanding of the nature of mPWP Arctic sea ice would be highly beneficial. Using the HadCM3 GCM, this paper explores the impact of various combinations of potential mPWP orbital forcing, atmospheric CO2 concentrations and minimum sea ice albedo on sea ice extent and high latitude warming. The focus is on the Northern Hemisphere, due to availability of proxy data, and the large data-model discrepancies in this region. Changes in orbital forcings are demonstrated to be sufficient to alter the Arctic sea ice simulated by HadCM3 from perennial to seasonal. However, this occurs only when atmospheric CO2 concentrations exceed 300 ppm. Reduction of the minimum sea ice albedo from 0.5 to 0.2 is also sufficient to simulate seasonal sea ice, with any of the combinations of atmospheric CO2 and orbital forcing. Compared to a mPWP control simulation, monthly mean increases north of 60°N of up to 4.2 °C (SST) and 9.8 °C (SAT) are simulated. With varying CO2, orbit and sea ice albedo values we are able to reproduce proxy temperature records that lean towards modest levels of high latitude warming, but other proxy data showing greater warming remain beyond the reach of our model. This highlights the importance of additional proxy records at high latitudes and ongoing efforts to compare proxy signals between sites.

8. Robust seasonal cycle of Arctic sea ice area through tipping point in amplitude

Ditlevsen, Peter D

2012-01-01

The variation in the Arctic sea ice is dominated by the seasonal cycle with little inter-annual correlation. Though the mean sea ice area has decreased steadily in the period of satellite observations, a dramatic transition in the dynamics was initiated with the record low September ice area in 2007. The change is much more pronounced in the amplitude of the seasonal cycle than in the annual mean ice area. The shape of the seasonal cycle is surprisingly constant for the whole observational record despite the general decline. A simple explanation, independent of the increased greenhouse warming, for the shape of the seasonal cycle is offered. Thus the dramatic climate change in arctic ice area is seen in the amplitude of the cycle and to a lesser extend the annual mean and the summer ice extend. The reason why the climate change is most pronounced in the amplitude is related to the rapid reduction in perennial ice and thus a thinning of the ice. The analysis shows that a tipping point for the arctic ice area w...

9. Arctic sea ice and atmospheric circulation under the abrupt4xCO2 scenario

YU Xiaoyong; Annette Rinke; JI Duoying; CUI Xuefeng; John C Moore

2014-01-01

We analyze sea ice changes from eight different earth system models that have conducted experiment abrupt4xCO2 of the Coupled Model Intercomparison Project Phase 5 (CMIP5). In response to abrupt quadrupling of CO2 from preindustrial levels, Arctic temperatures dramatically rise by about 10°C—16°C in winter and the seasonal sea ice cycle and sea ice concentration are signiifcantly changed compared with the pre-industrial control simulations (piControl). Changes of Arctic sea ice concentration are spatially correlated with temperature patterns in all seasons and highest in autumn. Changes in sea ice are associated with changes in atmospheric circulation patterns at heights up to the jet stream. While the pattern of sea level pressure changes is generally similar to the surface air temperature change pattern, the wintertime 500 hPa circulation displays a positive Paciifc North America (PNA) anomaly under abrupt4xCO2-piControl. This large scale teleconnection may contribute to, or feedback on, the simulated sea ice cover change and is associated with an intensiifcation of the jet stream over East Asia and the north Paciifc in winter.

10. The delivery of organic contaminants to the Arctic food web: Why sea ice matters

Pucko, M.; Stern, Gary; Macdonald, Robie;

2015-01-01

For decades sea ice has been perceived as a physical barrier for the loading of contaminants to the Arctic Ocean. We show that sea ice, in fact, facilitates the delivery of organic contaminants to the Arctic marine food web through processes that: 1) are independent of contaminant physical......–chemical properties (e.g. 2–3-fold increase in exposure to brine-associated biota), and 2) depend on physical–chemical properties and, therefore, differentiate between contaminants (e.g. atmospheric loading of contaminants to melt ponds over the summer, and their subsequent leakage to the ocean). We estimate...... the concentrations of legacy organochlorine pesticides (OCPs) and current-use pesticides (CUPs) in melt pond water in the Beaufort Sea, Canadian High Arctic, in 2008, at near-gas exchange equilibriumbased on Henry's lawconstants (HLCs), air concentrations and exchange dynamics. CUPs currently present the highest...

11. Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network

A. Rösel

2012-04-01

Full Text Available Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (MODIS using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs.

Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from R2=0.28 to R2=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N.

Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave

12. Arctic Sea Ice Export Through Fram Strait and Atmospheric Planetary Waves

Cavalieri, Donald J.; Koblinsky, Chester (Technical Monitor)

2001-01-01

A link is found between the variability of Arctic sea ice export through Ram Strait and the phase of the longest atmospheric planetary wave (zonal wave 1) in SLP for the period 1958-1997. Previous studies have identified a link between From Strait ice export and the North Atlantic Oscillation (NAO), but this link has been described as unstable because of a lack of consistency over time scales longer than the last two decades. Inconsistent and low correlations are also found between From Strait ice export and the Arctic Oscillation (AD) index. This paper shows that the phase of zonal wave 1 explains 60% - 70% of the simulated From Strait ice export variance over the Goodyear period 1958 - 1997. Unlike the NAB and AD links, these high variances are consistent for both the first and second halves of the Goodyear period. This consistency is attributed to the sensitivity of the wave I phase at high latitudes to the presence of secondary low pressure systems in the Barents Sea that serve to drive sea ice southward through From Strait. These results provide further evidence that the phase of zonal wave 1 in SLP at high latitudes drives regional as well as hemispheric low frequency Arctic Ocean and sea ice variability.

13. On the influence of model physics on simulations of Arctic and Antarctic sea ice

F. Massonnet

2011-09-01

Full Text Available Two hindcast (1983–2007 simulations are performed with the global, ocean-sea ice models NEMO-LIM2 and NEMO-LIM3 driven by atmospheric reanalyses and climatologies. The two simulations differ only in their sea ice component, while all other elements of experimental design (resolution, initial conditions, atmospheric forcing are kept identical. The main differences in the sea ice models lie in the formulation of the subgrid-scale ice thickness distribution, of the thermodynamic processes, of the sea ice salinity and of the sea ice rheology. To assess the differences in model skill over the period of investigation, we develop a set of metrics for both hemispheres, comparing the main sea ice variables (concentration, thickness and drift to available observations and focusing on both mean state and seasonal to interannual variability. Based upon these metrics, we discuss the physical processes potentially responsible for the differences in model skill. In particular, we suggest that (i a detailed representation of the ice thickness distribution increases the seasonal to interannual variability of ice extent, with spectacular improvement for the simulation of the recent observed summer Arctic sea ice retreats, (ii the elastic-viscous-plastic rheology enhances the response of ice to wind stress, compared to the classical viscous-plastic approach, (iii the grid formulation and the air-sea ice drag coefficient affect the simulated ice export through Fram Strait and the ice accumulation along the Canadian Archipelago, and (iv both models show less skill in the Southern Ocean, probably due to the low quality of the reanalyses in this region and to the absence of important small-scale oceanic processes at the models' resolution (~1°.

14. An analytical model for wind-driven Arctic summer sea ice drift

Park, H.-S.; Stewart, A. L.

2016-01-01

The authors present an analytical model for wind-driven free drift of sea ice that allows for an arbitrary mixture of ice and open water. The model includes an ice-ocean boundary layer with an Ekman spiral, forced by transfers of wind-input momentum both through the sea ice and directly into the open water between the ice floes. The analytical tractability of this model allows efficient calculation of the ice velocity provided that the surface wind field is known and that the ocean geostrophic velocity is relatively weak. The model predicts that variations in the ice thickness or concentration should substantially modify the rotation of the velocity between the 10 m winds, the sea ice, and the ocean. Compared to recent observational data from the first ice-tethered profiler with a velocity sensor (ITP-V), the model is able to capture the dependencies of the ice speed and the wind/ice/ocean turning angles on the wind speed. The model is used to derive responses to intensified southerlies on Arctic summer sea ice concentration, and the results are shown to compare closely with satellite observations.

15. Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations

Melia, N.; Haines, K.; Hawkins, E.

2015-07-01

Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 Global Climate Models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various spatial and temporal biases when compared with the Pan-Arctic Ice Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT to narrow projection uncertainty via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the uncertainty in projections of SIT and reveals the significant contributions of sea ice internal variability in the first half of the century and of scenario uncertainty from mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to narrow uncertainty in climate projections more generally.

16. Environmental Working Group Joint U.S.-Russian Arctic Sea Ice Atlas

National Oceanic and Atmospheric Administration, Department of Commerce — Note: The Russian chart component of this product has been replaced and updated by Sea Ice Charts of the Russian Arctic in Gridded Format, 1933-2006 and the U.S...

17. Does Change in the Arctic Sea Ice Indicate Climate Change? A Lesson Using Geospatial Technology

Bock, Judith K.

2011-01-01

The Arctic sea ice has not since melted to the 2007 extent, but annual summer melt extents do continue to be less than the decadal average. Climate fluctuations are well documented by geologic records. Averages are usually based on a minimum of 10 years of averaged data. It is typical for fluctuations to occur from year to year and season to…

18. Influence of projected Arctic sea ice loss on polar stratospheric ozone and circulation in spring

The impact of projected Arctic sea ice loss on the stratosphere is investigated using the Whole Atmosphere Community Climate Model (WACCM), a state-of-the-art coupled chemistry climate model. Two 91-year simulations are conducted: one with a repeating seasonal cycle of Arctic sea ice for the late twentieth-century, taken from the fully coupled WACCM historical run; the other with Arctic sea ice for the late twenty-first century, obtained from the fully coupled WACCM RCP8.5 run. In response to Arctic sea ice loss, polar cap stratospheric ozone decreases by 13 DU (34 DU at the North Pole) in spring, confirming the results of Scinocca et al (2009 Geophys. Res. Lett. 36 L24701). The ozone loss is dynamically initiated in March by a suppression of upward-propagating planetary waves, possibly related to the destructive interference between the forced wave number 1 and its climatology. The diminished upward wave propagation, in turn, weakens the Brewer–Dobson circulation at high latitudes, strengthens the polar vortex, and cools the polar stratosphere. The ozone reduction persists until the polar vortex breaks down in late spring. (letter)

19. Ship-borne electromagnetic induction sounding of sea ice thickness in the Arctic during summer 2003

Shirasawa,Kunio /Tateyama,Kazutaka /Takatsuka,Toru /Kawamura,Toshiyuki /Uto,Shotaro

2006-01-01

Measurements of ice thickness were carried out by a ship-borne electromagnetic induction instrument mounted on the R/V Xuelong during the Second Chinese National Arctic Research Expedition (CHINARE-2003) in summer 2003 in the Chukchi Sea. A 1-D multi-layer model, consisting of three layers of snow, ice and seawater, was used to calculate the total thickness of snow and sea ice. The time series of total thickness from 24 August to 7 September 2003 indicates that deformed and second-/multi-year...

20. Modeling the 20th century Arctic Ocean/Sea ice system: Reconstruction of surface forcing

Kauker, Frank; KöBerle, Cornelia; Gerdes, Rüdiger; Karcher, Michael

2008-09-01

The ability to simulate the past variability of the sea ice-ocean system is of fundamental interest for the identification of key processes and the evaluation of scenarios of future developments. To achieve this goal atmospheric surface fields are reconstructed by statistical means for the period 1900 to 1997 and applied to a coupled sea ice-ocean model of the North Atlantic/Arctic Ocean. We devised a statistical model using a redundancy analysis to reconstruct the atmospheric fields. Several sets of predictor and predictand fields are used for reconstructions on different time scales. The predictor fields are instrumental records available as gridded or station data sets of sea level pressure and surface air temperature. The predictands are surface fields from the NCAR/NCEP reanalysis. Spatial patterns are selected by maximizing predictand variance during a "learning" period. The reliability of these patterns is tested in a validation period. The ensemble of reconstructions is checked for robustness by mutual comparison and an "optimal" reconstruction is selected. Results of the simulations with the sea ice-ocean model are compared with historical sea ice extent observations for the Arctic and Nordic Seas. The results obtained with the "optimal" reconstruction are shown to be highly consistent with these historical data. An analysis of simulated trends of the "early 20th century warming" and the recent warming in the Arctic complete the manuscript.

1. Arctic sea ice freeboard from AltiKa and comparison with CryoSat-2 and Operation IceBridge

Armitage, Thomas W. K.; Ridout, Andy L.

2015-08-01

Satellite radar altimeters have improved our knowledge of Arctic sea ice thickness over the past decade. The main sources of uncertainty in sea ice thickness retrievals are associated with inadequate knowledge of the snow layer depth and the radar interaction with the snow pack. Here we adapt a method of deriving sea ice freeboard from CryoSat-2 to data from the AltiKa Ka band radar altimeter over the 2013-14 Arctic sea ice growth season. AltiKa measures basin-averaged freeboards between 4.4 cm and 6.9 cm larger than CryoSat-2 in October and March, respectively. Using airborne laser and radar measurements from spring 2013 and 2014, we estimate the effective scattering horizon for each sensor. While CryoSat-2 echoes penetrate to the ice surface over first-year ice and penetrate the majority (82 ± 3%) of the snow layer over multiyear ice, AltiKa echoes are scattered from roughly the midpoint (46 ± 5%) of the snow layer over both ice types.

2. Sea Ice Deformation Rates in the Arctic: from Wind-Driven Synoptic Variability to Seasonal Trends

Glowacki, O.; Herman, A.

2012-12-01

Deformation mechanisms of the Arctic Ocean ice sheet are characterized by high spatial and temporal variability, in which ice ridges and leads tend to be concentrated in elongated, narrow zones. Present state-of-the-art numerical models, especially those based on various versions of viscous-plastic rheology, are still far from perfection in terms of reproducing localized and intermittent characteristics of sea ice deformation. In this study, the relationship (and its variability) between scaling properties of sea ice deformation and 10-m wind speed is analyzed. We used NCEP-DOE Reanalysis 2 data to determine area-averaged atmospheric drag force. Gridded sea ice total deformation rates from Radarsat Geophysical Processor System (RGPS) data were obtained from the NASA Jet Propulsion Laboratory, with a time resolution of 3 days and a spatial resolution of 12.55 km. Our analysis covers 11 winter seasons from 1996/1997 to 2007/2008. We calculated the moments mq, L of probability distribution functions (pdfs) of total sea ice deformation rates for a range of spatial scales L. The logarithms of the moments are significantly correlated with basin-scale wind forcing, especially for low values of q (with Pearson correlation coefficient reaching 0.7). It can be well-described by simplified momentum equations and a very general rheology model. Furthermore, the strength of this relationship varies seasonally and reaches its minimum in March, due to changeable thickness and consolidation of the Arctic Ocean ice sheet. This effect is clearly seen in comparison with trend lines of time-varying values of moments. Finally, there is a positive trend in seasonally-averaged power of correlation, which is probably associated with decreasing area of the multi-year ice. As a result, the course of sea ice deformation process in the Arctic is a possible indicator of climate change.

3. Snow thickness retrieval over thick Arctic sea ice using SMOS satellite data

N. Maaß

2013-12-01

Full Text Available The microwave interferometric radiometer of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS mission measures at a frequency of 1.4 GHz in the L-band. In contrast to other microwave satellites, low frequency measurements in L-band have a large penetration depth in sea ice and thus contain information on the ice thickness. Previous ice thickness retrievals have neglected a snow layer on top of the ice. Here, we implement a snow layer in our emission model and investigate how snow influences L-band brightness temperatures and whether it is possible to retrieve snow thickness over thick Arctic sea ice from SMOS data. We find that the brightness temperatures above snow-covered sea ice are higher than above bare sea ice and that horizontal polarisation is more affected by the snow layer than vertical polarisation. In accordance with our theoretical investigations, the root mean square deviation between simulated and observed horizontally polarised brightness temperatures decreases from 20.9 K to 4.7 K, when we include the snow layer in the simulations. Although dry snow is almost transparent in L-band, we find brightness temperatures to increase with increasing snow thickness under cold Arctic conditions. The brightness temperatures' dependence on snow thickness can be explained by the thermal insulation of snow and its dependence on the snow layer thickness. This temperature effect allows us to retrieve snow thickness over thick sea ice. For the best simulation scenario and snow thicknesses up to 35 cm, the average snow thickness retrieved from horizontally polarised SMOS brightness temperatures agrees within 0.1 cm with the average snow thickness measured during the IceBridge flight campaign in the Arctic in spring 2012. The corresponding root mean square deviation is 5.5 cm, and the coefficient of determination is r2 = 0.58.

4. Monitoring Sea Ice Conditions and Use in Arctic Alaska to Enhance Community Adaptation to Change

Druckenmiller, M. L.; Eicken, H.

2010-12-01

Sea ice changes in the coastal zone, while less conspicuous in relation to the dramatic thinning and retreat of perennial Arctic sea ice, can be more readily linked to local impacts. Shorefast ice is a unique area for interdisciplinary research aimed at improving community adaptation to climate through local-scale environmental observations. Here, geophysical monitoring, local Iñupiat knowledge, and the documented use of ice by the Native hunting community of Barrow, Alaska are combined to relate coastal ice processes and morphologies in the Chukchi Sea to ice stability and community adaption strategies for travel, hunting, and risk assessment. A multi-year effort to map and survey the community’s seasonal ice trails, alongside a detailed record of shorefast ice conditions, provides insight into how hunters evaluate the evolution of ice throughout winter and spring. Various data sets are integrated to relate the annual accretion history of the local ice cover to both measurements of ice thickness and topography and hunter observations of ice types and hazards. By relating changes in the timing of shorefast ice stabilization, offshore ice conditions, and winter wind patterns to ice characteristics in locations where spring bowhead whaling occurs, we are working toward an integrated scientific product compatible with the perspective of local ice experts. A baseline for assessing future change and community climate-related vulnerabilities may not be characterized by single variables, such as ice thickness, but rather by how changes in observable variables manifest in impacts to human activities. This research matches geophysical data to ice-use to establish such a baseline. Documenting human-environment interactions will allow future monitoring to illustrate how strategies for continued community ice-use are indicative of or responsive to change, and potentially capable of incorporating science products as additional sources of useable information.

5. Analysis of an Arctic sea ice loss model in the limit of a discontinuous albedo

Hill, Kaitlin; Silber, Mary

2015-01-01

As Arctic sea ice extent decreases with increasing greenhouse gases, there is a growing interest in whether there could be a bifurcation associated with its loss, and whether there is significant hysteresis associated with that bifurcation. A challenge in answering this question is that the bifurcation behavior of certain Arctic energy balance models have been shown to be sensitive to how ice-albedo feedback is parameterized. We analyze an Arctic energy balance model in the limit as a smoothing parameter associated with ice-albedo feedback tends to zero, which makes the system piecewise-smooth. Our analysis provides a case study where we use the piecewise-smooth system to explore bifurcation behavior of the smooth system. In this case study, we demonstrate that certain qualitative bifurcation behaviors of the smooth system can have nonsmooth counterparts. We use this perspective to systematically search parameter space. For example, we uncover parameter sets for which the largest transition, with increasing g...

6. Atmospheric response to the autumn sea-ice free Arctic and its detectability

Suo, Lingling; Gao, Yongqi; Guo, Dong; Liu, Jiping; Wang, Huijun; Johannessen, Ola M.

2016-04-01

We have used an Atmospheric General Circulation Model with a large ensemble (300) to explore the atmospheric responses during the autumn-winter (September to February) to the projected sea-ice free Arctic in autumn (September to November). The detectability of the responses against the internal variability has also been studied. Three ensemble experiments have been performed, the control (CONT) forced by the simulated present-day Arctic sea-ice concentration (SIC) and sea surface temperature (SST), the second forced by the projected autumn Arctic SIC free and present-day SSTs (SENSICE) and the third forced by the projected autumn Arctic SIC free and projected SSTs (SENS). The results show that the disappearance of autumn Arctic sea-ice can cause significant synchronous near-surface warming and increased precipitation over the regions where the sea-ice is removed. The changes in autumn surface heat flux (sensible plus latent), surface air temperature (SAT) and precipitation averaged over the sea-ice reduction region between the SENS and the CONT are about 46, 43 and 50 % more respectively than the changes between the SENSICE and the CONT, which is consistent with the prescribed boundary setting: the surface temperature warming averaged over the sea-ice reduction region in the SENS relative to the CONT is 48 % higher than that in the SENSICE relative to the CONT. The response shows a significant negative Arctic Oscillation (AO) in the troposphere during autumn and December. However, the negative AO does not persist into January-February (JF). Instead, 500 hPa geopotential height (GH) response presents a wave train like pattern in JF which is related to the downstream propagation of the planetary wave perturbations during November-December. The SAT increases over northern Eurasia in JF in accordance with the atmosphere circulation changes. The comparison of the atmosphere response with the atmosphere internal variability (AIV) shows that the responses of SAT and

7. Interplay between linear, dissipative and permanently critical mechanical processes in Arctic sea ice

A. Chmel

2010-08-01

Full Text Available Mechanical processes in the Arctic ice pack result in fragmented sea ice cover, the regular geometry of which could be described in main features in terms of the conventional mechanics. However, the size distribution of sea ice floes does not exhibit the random (poissonian-like statistics and follows the power law typical for self-similar (fractal structures. The analysis of ice floe oscillations in the frequency range specific for cracking, shearing and stick-slip motion evidences the self-organized dynamics of sea ice fracturing, which manifests itself in scaling distributions of both the discrete energy discharges in fracture events and the recurrence times between that one. So determined space-time-energy self-similarity characterises the ice pack as the non-equilibrium, nonlinear thermodynamic system where the synergic relations are established through conventional long propagating wave/oscillations. The presented experimental data were collected at the Russian ice-research camp "North Pole 35" drifting on the Arctic ice pack in 2008.

8. Projected polar bear sea ice habitat in the Canadian Arctic Archipelago.

Stephen G Hamilton

Full Text Available Sea ice across the Arctic is declining and altering physical characteristics of marine ecosystems. Polar bears (Ursus maritimus have been identified as vulnerable to changes in sea ice conditions. We use sea ice projections for the Canadian Arctic Archipelago from 2006 - 2100 to gain insight into the conservation challenges for polar bears with respect to habitat loss using metrics developed from polar bear energetics modeling.Shifts away from multiyear ice to annual ice cover throughout the region, as well as lengthening ice-free periods, may become critical for polar bears before the end of the 21st century with projected warming. Each polar bear population in the Archipelago may undergo 2-5 months of ice-free conditions, where no such conditions exist presently. We identify spatially and temporally explicit ice-free periods that extend beyond what polar bears require for nutritional and reproductive demands.Under business-as-usual climate projections, polar bears may face starvation and reproductive failure across the entire Archipelago by the year 2100.

9. Recent and future changes in Arctic sea ice simulated by the HadCM3 AOGCM

Gregory, J. M.; Stott, P. A.; Cresswell, D. J.; Rayner, N. A.; Gordon, C.; Sexton, D. M. H.

2002-12-01

The HadCM3 AOGCM has been used to undertake an ensemble of four integrations from 1860 to 1999 with forcings due to all major anthropogenic and natural climate factors. The simulated decreasing trend in average Arctic sea ice extent for 1970-1999 (-2.5% per decade) is very similar to observations. HadCM3 indicates that internal variability and natural forcings (solar and volcanic) of the climate system are very unlikely by themselves to have caused a trend of this size. The simulated decreasing trend in Arctic sea ice volume (-3.4% per decade for 1961-1998) is less than some recent observationally based estimates. Extending the integrations into the 21st century, Arctic sea ice area and volume continue to decline. Area decreases linearly as global-average temperature rises (by 13% per K), and volume diminishes more rapidly than area. By the end of the century, in some scenarios, the Arctic is ice-free in late summer.

10. Determination of Sea Ice Freeboard in Arctic from ICESat: Case Study of 2005—2006

Chen, Guodong; Li, Jiancheng; CHU Yonghai; Li, Dawei

2015-01-01

Based on variation characters of sea surface height and parameters of ICESat return pulse waveform, a method is proposed for estimating Arctic sea ice freeboard with ICESat observation. This proposed method is compared with the common ‘lowest-level’ method. The results show that the lowest-level method is vulnerable to gross errors and present systematic errors in spatial distribution of freeboard. But the proposed method is more reliable than the lowest-level method. The lowest-level method ...

11. Real-Time Observations of Optical Properties of Arctic Sea Ice with an Autonomous System

Wang, C.; Gerland, S.; Nicolaus, M.; Granskog, M. A.; Hudson, S. R.; Perovich, D. K.; Karlsen, T. I.; Fossan, K.

2012-12-01

The recent drastic changes in the Arctic sea ice cover have altered the interaction of solar radiation and sea ice. To improve our understanding of this interaction, a Spectral Radiation Buoy (SRB) for measuring sea ice optical properties was developed, based on a system used during the last International Polar Year at the drift of "Tara" across the Arctic Ocean. A first version of the SRB was deployed on drifting ice in the high Arctic in April 2012. It includes three Satlantic spectral radiometers (two in air, one under ice), covering the wavelength range from 347 nm to 804 nm with 3.3 nm spectral resolution, a bio-shutter to protect the under-ice radiometer, a data logger to handle and store collected data, and an Iridium satellite modem to transfer data in real-time. The under-ice radiometer is mounted on an adjustable under-ice arm, and the other instruments are mounted on a triangular frame frozen into the ice. The SRB measures simultaneously, autonomously and continuously the spectral fluxes of incident and reflected solar radiation, as well as under-ice irradiance, water temperature and water pressure every hour. So far, between mid April and early August 2012, the system has drifted about 600 km, from the starting position near the North Pole towards the Fram Strait. The data collected during this deployment, so far, already demonstrate that this system is suitable for autonomous and long-term observations over and under sea ice in harsh conditions. Along with the SRB, commercially available Ice Mass Balance buoys (IMB) were deployed on the same ice floe. In the vicinity of the site, manned baseline measurements of snow and sea ice physical properties have been carried out during the SRB deployment. The combined datasets allow description of the evolution of the ice floe during seasonal melt. With snow melt, the spectral surface albedo decreased and the transmittance through the snow and ice increased after mid-April, especially when melt ponds started to

12. Impact Studies of a 2 C Global Warming on the Arctic Sea Ice Cover

Comiso, Josefino C.

2004-01-01

The possible impact of an increase in global temperatures of about 2 C, as may be caused by a doubling of atmospheric CO2, is studied using historical satellite records of surface temperatures and sea ice from late 1970s to 2003. Updated satellite data indicate that the perennial ice continued to decline at an even faster rate of 9.2 % per decade than previously reported while concurrently, the surface temperatures have steadily been going up in most places except for some parts of northern Russia. Surface temperature is shown to be highly correlated with sea ice concentration in the seasonal sea ice regions. Results of regression analysis indicates that for every 1 C increase in temperature, the perennial ice area decreases by about 1.48 x 10(exp 6) square kilometers with the correlation coefficient being significant but only -0.57. Arctic warming is estimated to be about 0.46 C per decade on average in the Arctic but is shown to be off center with respect to the North Pole, and is prominent mainly in the Western Arctic and North America. The length of melt has been increasing by 13 days per decade over sea ice covered areas suggesting a thinning in the ice cover. The length of melt also increased by 5 days per decade over Greenland, 7 days per decade over the permafrost areas of North America but practically no change in Eurasia. Statistically derived projections indicate that the perennial sea ice cover would decline considerably in 2025, 2035, and 2060 when temperatures are predicted by models to reach the 2 C global increase.

13. Shifting El Niño inhibits summer Arctic warming and Arctic sea-ice melting over the Canada Basin

Hu, Chundi; Yang, Song; Wu, Qigang; Li, Zhenning; Chen, Junwen; Deng, Kaiqiang; Zhang, Tuantuan; Zhang, Chengyang

2016-06-01

Arctic climate changes include not only changes in trends and mean states but also strong interannual variations in various fields. Although it is known that tropical-extratropical teleconnection is sensitive to changes in flavours of El Niño, whether Arctic climate variability is linked to El Niño, in particular on interannual timescale, remains unclear. Here we demonstrate for the first time a long-range linkage between central Pacific (CP) El Niño and summer Arctic climate. Observations show that the CP warming related to CP El Niño events deepens the tropospheric Arctic polar vortex and strengthens the circumpolar westerly wind, thereby contributing to inhibiting summer Arctic warming and sea-ice melting. Atmospheric model experiments can generally capture the observed responses of Arctic circulation and robust surface cooling to CP El Niño forcing. We suggest that identification of the equator-Arctic teleconnection, via the `atmospheric bridge', can potentially contribute to improving the skill of predicting Arctic climate.

14. Linkages between Arctic sea ice cover, large-scale atmospheric circulation, and weather and ice conditions in the Gulf of Bothnia, Baltic Sea

Timo Vihma; Bin Cheng; Petteri Uotila; WEI Lixin; QIN Ting

2014-01-01

During years 1980/1981–2012/2013, inter-annual variations in sea ice and snow thickness in Kemi, in the northern coast of the Gulf of Bothnia, Baltic Sea, depended on the air temperature, snow fall, and rain. Inter-annual variations in the November—April mean air temperature, accumulated total precipitation, snow fall, and rain, as well as ice and snow thickness in Kemi and ice concentration in the Gulf of Bothnia correlated with inter-annual variations of the Paciifc Decadal Oscillation (PDO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Scandinavian Pattern (SCA), and Polar / Eurasian Pattern (PEU). The strong role of PDO is a new ifnding. In general, the relationships with PDO were approximately equally strong as those with AO, but rain and sea ice concentration were better correlated with PDO. The correlations with PDO were, however, not persistent; for a study period since 1950 the correlations were much lower. During 1980/1981—2012/2013, also the Paciifc / North American Pattern (PNA) and El Nino–Southern Oscillation (ENSO) had statistical connections with the conditions in the Gulf of Bothnia, revealed by analyzing their effects combined with those of PDO and AO. A reduced autumn sea ice area in the Arctic was related to increased rain and total precipitation in the following winter in Kemi. This correlation was signiifcant for the Pan-Arctic sea ice area in September, October, and November, and for the November sea ice area in the Barents / Kara seas.

15. National Ice Center Arctic Sea Ice Charts and Climatologies in Gridded Format

National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. National Ice Center (NIC) is an inter-agency sea ice analysis and forecasting center comprised of the Department of Commerce/NOAA, the Department of...

16. Differences between the bacterial community structures of first- and multi-year Arctic sea ice in the Lincoln Sea.

Hatam, I.; Beckers, J. F.; Haas, C.; Lanoil, B. D.

2014-12-01

The Arctic sea ice composition is shifting from predominantly thick perennial ice (multiyear ice -MYI) to thinner, seasonal ice (first year ice -FYI). The effects of the shift on the Arctic ecosystem and macro-organisms of the Arctic Ocean have been the focus of many studies and have also been extensively debated in the public domain. The effect of this shift on the microbial constituents of the Arctic sea ice has been grossly understudied, although it is a vast habitat for a microbial community that plays a key role in the biogeochemical cycles and energy flux of the Arctic Ocean. MYI and FYI differ in many chemical and physical attributes (e.g. bulk salinity, brine volume, thickness and age), therefore comparing and contrasting the structure and composition of microbial communities from both ice types will be crucial to our understanding of the challenges that the Arctic Ocean ecosystem faces as MYI cover continues to decline. Here, we contend that due to the differences in abiotic conditions, differences in bacterial community structure will be greater between samples from different ice types than within samples from the same ice type. We also argue that since FYI is younger, its community structure will be closer to that of the surface sea water (SW). To test this hypotheses, we extracted DNA and used high throughput sequencing to sequence V1-V3 regions of the bacterial 16s rRNA gene from 10 sea ice samples (5 for each ice type) and 4 surface sea water (SW) collected off the shore of Northern Ellesmere Island, NU, CAN, during the month of May from 2010-2012. Our results showed that observed richness was higher in FYI than MYI. FYI and MYI shared 26% and 36% of their observed richness respectively. While FYI shared 23% of its observed richness with SW, MYI only shared 17%. Both ice types showed similar levels of endemism (61% of the observed richness). This high level of endemism results in the grouping of microbial communities from MYI, FYI, and SW to three

17. Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice

M. Zygmuntowska

2013-08-01

Full Text Available Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat-2 was launched in 2010 carrying a Ku-band radar altimeter (SIRAL designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300 m along track. In this study, airborne Ku-band radar altimeter data over different sea ice types have been analyzed. A set of parameters has been defined to characterize the differences in strength and width of the returned power waveforms. With a Bayesian-based method, it is possible to classify about 80% of the waveforms from three parameters: maximum of the returned power waveform, the trailing edge width and pulse peakiness. Furthermore, the maximum of the power waveform can be used to reduce the number of false detections of leads, compared to the widely used pulse peakiness parameter. For the pulse peakiness the false classification rate is 12.6% while for the power maximum it is reduced to 6.5%. The ability to distinguish between different ice types and leads allows us to improve the freeboard retrieval and the conversion from freeboard into sea ice thickness, where surface type dependent values for the sea ice density and snow load can be used.

18. Waveform analysis of airborne synthetic aperture radar altimeter over Arctic sea ice

M. Zygmuntowska

2013-03-01

Full Text Available Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat was launched in 2010 carrying a Ku-band Radar Altimeter (SIRAL designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300 m along track. In this study, airborne Ku-band radar altimeter data over different sea ice types has been analyzed. A set of parameters has been defined to characterize the difference in strength and width of the returned power waveforms. With a Bayesian based method it is possible to classify about 80% of the waveforms by three parameters: maximum of the returned power echo, the trailing edge width and pulse peakiness. Furthermore, the radar power echo maximum can be used to minimize the rate of false detection of leads compared to the widely used Pulse Peakiness parameter. The possibility to distinguish between different ice types and open water allows to improve the freeboard retrieval and the conversion into sea ice thickness where surface type dependent values for the sea ice density and snow load can be used.

19. Summer Arctic sea fog

2001-01-01

Synchronous or quasi-synchronous sea-land-air observations were conducted using advanced sea ice, atmospheric and marine instruments during China' s First Arctic Expedition. Based on the Precious data from the expedition, it was found that in the Arctic Ocean, most part of which is covered with ice or is mixed with ice, various kinds of sea fog formed such as advection fog, radiation fog and vapor fog. Each kind has its own characteristic and mechanics of creation. In the southern part of the Arctic Ocean, due to the sufficient warm and wet flow there, it is favorable for advection fog to form,which is dense and lasts a long time. On ice cap or vast floating ice, due to the strong radiation cooling effect, stable radiating fog is likely to form. In floating ice area there forms vapor fog with the appearance of masses of vapor from a boiling pot, which is different from short-lasting land fog. The study indicates that the reason why there are many kinds of sea fog form in the Arctic Ocean is because of the complicated cushion and the consequent sea-air interaction caused by the sea ice distribution and its unique physical characteristics. Sea fog is the atmospheric phenomenon of sea-air heat exchange. Especially, due to the high albedo of ice and snow surface, it is diffcult to absorb great amount of solar radiation during the polar days. Besides, ice is a poor conductor of heat; it blocks the sea-air heat exchange.The sea-air exchange is active in floating ice area where the ice is broken. The sea sends heat to the atmosphere in form of latent heat; vapor fog is a way of sea-air heat exchange influencing the climate and an indicator of the extent of the exchange. The study also indicates that the sea also transports heat to the atmosphere in form of sensible heat when vapor fog occurs.

20. Fluctuations and seasonality in the Arctic sea ice area: A sudden regime shift in 2007?

Ditlevsen, Peter D

2013-01-01

Since the beginning of satellite observations, the Arctic sea ice extent has shown a downward trend. The decline has been weaker in the March maximum than in the September minimum and masked by inter-annual fluctuations. One of the less understood aspects of the sea ice response is the persistence times for fluctuations, which could indicate the dominant physical processes behind the sea ice decline. To determine the fluctuation persistence times, however, it is necessary to first filter out the dominant effect of the seasonal cycle. In the current study, we thus develop a statistical model, which accurately decomposes the ice area changes into: (1) a variable seasonal cycle component with a constant shape and (2) a residual (short term) fluctuation. We find the persistence time of fluctuations to be only about three weeks, independently from season, which is substantially shorter than previously reported. Such short time scale points to the dominance of atmospheric forcing. The shape of the seasonal cycle is...

1. TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic

P. Sakov

2012-08-01

Full Text Available We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003–2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation in the North Atlantic and the sea-ice variability in the Arctic. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates – a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in-situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed several flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level.

2. Upwelling of Arctic pycnocline associated with shear motion of sea ice

McPhee, M. G.; Kwok, R.; Robins, R.; Coon, M.

2006-01-01

High-resolution radar imagery shows that the dynamic response of winter sea ice to gradients in large-scale surface wind stress is often localized along quasi-linear fractures hundreds of kilometers long. Relative shearing motion across these narrow fractures can exceed 10 cm/s. In one event recorded during the drift of the SHEBA ice camp, we observed an intense zone of pycnocline upwelling (approx.14 m) associated with significant shear motion near the camp, while upward turbulent heat flux in the ocean boundary layer reached nearly 400 W/sq m, an order of magnitude greater than at any other time during the year-long drift. We attribute the upwelling to Ekman pumping associated with concentrated ice shear. Over the entire Arctic Ocean sea ice cover, this process could be responsible for significant heat exchange between the cold surface layer and warmer subsurface water at the ubiquitous fractures resulting from large-scale atmosphere-ice interactions.

3. A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

St.Germain, Karen; Cavalieri, Donald J.; Markus, Thorsten

1997-01-01

Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations.

4. Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations

Melia, N.; Haines, K.; Hawkins, E.

2015-12-01

Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various biases when compared with the Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the spread in projections of SIT and reveals the significant contributions of climate internal variability in the first half of the century and of scenario uncertainty from the mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to reduce spread in climate projections more generally.

5. Intensified Arctic warming under greenhouse warming by vegetation–atmosphere–sea ice interaction

Observations and modeling studies indicate that enhanced vegetation activities over high latitudes under an elevated CO2 concentration accelerate surface warming by reducing the surface albedo. In this study, we suggest that vegetation-atmosphere-sea ice interactions over high latitudes can induce an additional amplification of Arctic warming. Our hypothesis is tested by a series of coupled vegetation-climate model simulations under 2xCO2 environments. The increased vegetation activities over high latitudes under a 2xCO2 condition induce additional surface warming and turbulent heat fluxes to the atmosphere, which are transported to the Arctic through the atmosphere. This causes additional sea-ice melting and upper-ocean warming during the warm season. As a consequence, the Arctic and high-latitude warming is greatly amplified in the following winter and spring, which further promotes vegetation activities the following year. We conclude that the vegetation-atmosphere-sea ice interaction gives rise to additional positive feedback of the Arctic amplification. (letter)

6. Increased Arctic Sea Ice Drift Alters Polar Bear Movements and Energetics

Douglas, D. C.; Durner, G. M.; Albeke, S. E.; Whiteman, J. P.; Amstrup, S. C.; Richardson, E.; Wilson, R. R.; Ben-David, M.

2015-12-01

Recent thinning of Arctic sea ice has increased its drift from currents and winds. Increased ice drift could affect movements and energy balance of polar bears (Ursus maritimus) which rely, almost exclusively, on this substrate for hunting seals. Foraging by polar bears is a relatively sedentary behavior, as they typically capture their main prey by waiting at breathing holes, where seals haul-out along leads, or by short-distance stalking. We examined the response of polar bears to ice drift in the Beaufort (BS) and Chukchi (CS) seas, and between two periods with different sea ice characteristics: 1987-1998 and 1999-2013. We used satellite-tracked adult female polar bear locations, standardized by a continuous-time correlated random walk, coupled with modeled ice drift, to estimate displacement and drift-corrected bear movements along east-west and north-south axes. Sea ice drift in both regions increased with greater westward and more extreme northward and southward rates from 1987-1998 to 1999-2013. Polar bears responded with greater eastward movements and, in the CS greater movements north and south. We show that efforts by polar bears to compensate for greater westward ice drift in recent years translated into a model-derived estimate of 5.7-7.2% increase in energy expenditure. We also estimated that polar bears increased their travel time 18-20% between the two time periods, suggesting time allocated to foraging was reduced. Increased energetic costs and travel time resulting from greater ice drift, in conjunction with ongoing habitat loss, suggest that recent changes to Arctic sea ice may affect movements and energy balance of polar bears.

7. Phylogenetic analysis of bacteria in sea ice brine sampled from the Canada Basin, Arctic Ocean

2006-01-01

Bacterial diversity in sea ice brine samples which collected from four stations located at the Canada Basin, Arctic Ocean was analyzed by PCR-DGGE. Twenty-three 16S rDNA sequences of bacteria obtained from DGGE bands were cloned and sequenced. Phylogenetic analysis clustered these sequences within γ-proteobacteria, Cytophaga-Flexibacter-Bacteroides (CFB) group, Firmicutes and Actinobacteria. The phylotype of Pseudoalteromonas in the γ-proteobacteria was predominant and members of the CFB group and γ-proteobacteria were highly abundant in studied sea ice brine samples.

8. Ku-Band radar penetration into Snow over Arctic Sea Ice

Hendricks, Stefan; Stenseng, Lars; Helm, Veit;

is the snow/air interface, whereas radar waves interact with the variable physical properties of the snow cover on the Arctic sea ice. In addition, radar elevation measurements may vary for different retracker algorithms, which determine the track point of the scattered echo power distribution. Since accurate...... knowledge of the reflection horizon is critical for sea ice thickness retrieval, validation data is necessary to investigate the penetration of radar waves into the snow for the upcoming CryoSat-2 mission. Furthermore, the combination of both optical and RF wavelengths might be used to derive snow thickness...

9. CBSIT 2009: Airborne Validation of Envisat Radar Altimetry and In Situ Ice Camp Measurements Over Arctic Sea Ice

Connor, Laurence; Farrell, Sinead; McAdoo, David; Krabill, William; Laxon, Seymour; Richter-Menge, Jacqueline; Markus, Thorsten

2010-01-01

The past few years have seen the emergence of satellite altimetry as valuable tool for taking quantitative sea ice monitoring beyond the traditional surface extent measurements and into estimates of sea ice thickness and volume, parameters that arc fundamental to improved understanding of polar dynamics and climate modeling. Several studies have now demonstrated the use of both microwave (ERS, Envisat/RA-2) and laser (ICESat/GLAS) satellite altimeters for determining sea ice thickness. The complexity of polar environments, however, continues to make sea ice thickness determination a complicated remote sensing task and validation studies remain essential for successful monitoring of sea ice hy satellites. One such validation effort, the Arctic Aircraft Altimeter (AAA) campaign of2006. included underflights of Envisat and ICESat north of the Canadian Archipelago using NASA's P-3 aircraft. This campaign compared Envisat and ICESat sea ice elevation measurements with high-resolution airborne elevation measurements, revealing the impact of refrozen leads on radar altimetry and ice drift on laser altimetry. Continuing this research and validation effort, the Canada Basin Sea Ice Thickness (CBSIT) experiment was completed in April 2009. CBSIT was conducted by NOAA. and NASA as part of NASA's Operation Ice Bridge, a gap-filling mission intended to supplement sea and land ice monitoring until the launch of NASA's ICESat-2 mission. CBIST was flown on the NASA P-3, which was equipped with a scanning laser altimeter, a Ku-band snow radar, and un updated nadir looking photo-imaging system. The CB5IT campaign consisted of two flights: an under flight of Envisat along a 1000 km track similar to that flown in 2006, and a flight through the Nares Strait up to the Lincoln Sea that included an overflight of the Danish GreenArc Ice Camp off the coast of northern Greenland. We present an examination of data collected during this campaign, comparing airborne laser altimeter measurements

10. MEaSUREs Arctic Sea Ice Characterization Daily 25km EASE-Grid 2.0 V001

National Aeronautics and Space Administration — This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides a daily record of Arctic sea ice...

11. Relating the Age of Arctic Sea Ice to its Thickness, as Measured during NASA’s ICESat and IceBridge Campaigns

Mark A. Tschudi; Stroeve, Julienne C.; J. Scott Stewart

2016-01-01

Recent satellite observations yield estimates of the distribution of sea ice thickness across the entire Arctic Ocean. While these sensors were only placed in operation within the last few years, information from other sensors may assist us with estimating the distribution of sea ice thickness in the Arctic beginning in the 1980s. A previous study found that the age of sea ice is correlated to sea ice thickness from 2003 to 2006, but an extension of the temporal analysis is needed to better q...

12. The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

A. A. Marks

2013-07-01

Full Text Available The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g−1, in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g−1 of black carbon causes a decrease to 98.7% of the original albedo for first-year sea ice compared to a decrease to 99.7% for the albedo of multi-year sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g−1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2–5 cm snow layer (less than the e-folding depth of snow is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

13. Late Quaternary sea-ice history of northern Fram Strait/Arctic Ocean

Kremer, Anne; Stein, Rüdiger; Fahl, Kirsten; Matthießen, Jens; Forwick, Matthias; O'Regan, Matt

2016-04-01

One of the main characteristics of the Arctic Ocean is its seasonal to perennial sea-ice cover. Variations of sea-ice conditions affect the Earth's albedo, primary production, rate of deep-water etc.. During the last decades, a drastic decrease in sea ice has been recorded, and the causes of which, i.e., natural vs. anthropogenic forcings, and their relevance within the global climate system, are subject of intense scientific and societal debate. In this context, records of past sea-ice conditions going beyond instrumental records are of major significance. These records may help to better understand the processes controlling natural sea-ice variability and to improve models for forecasts of future climatic conditions. During RV Polarstern Cruise PS92 in summer 2015, a 860 cm long sediment core (PS92/039-2) was recovered from the eastern flank of Yermak Plateau north of the Svalbard archipelago (Peeken, 2015). Based on a preliminary age model, this sediment core probably represents the time interval from MIS 6 to MIS 1. This core, located close to the modern summer ice edge, has been selected for reconstruction of past Arctic sea-ice variability based on specific biomarkers. In this context, we have determined the ice-algae-derived sea-ice proxy IP25 (Belt et al., 2007), in combination with other biomarkers indicative for open-water conditions (cf., Müller et al., 2009, 2011). Furthermore, organic carbon fluxes were differentiated using specific biomarkers indicative for marine primary production (brassicasterol, dinosterol) and terrigenous input (campesterol, β-sitosterol). In this poster, preliminary results of our organic-geochemical and sedimentological investigations are presented. Distinct fluctuations of these biomarkers indicate several major, partly abrupt changes in sea-ice cover in the Yermak Plateau area during the late Quaternary. These changes are probably linked to changes in the inflow of Atlantic Water along the western coastline of Svalbard into

14. Radar and infrared remote sensing of terrain, water resources, arctic sea ice, and agriculture

Biggs, A. W.

1983-01-01

15. The delivery of organic contaminants to the Arctic food web: why sea ice matters.

Pućko, Monika; Stern, Gary A; Macdonald, Robie W; Jantunen, Liisa M; Bidleman, Terry F; Wong, Fiona; Barber, David G; Rysgaard, Søren

2015-02-15

For decades sea ice has been perceived as a physical barrier for the loading of contaminants to the Arctic Ocean. We show that sea ice, in fact, facilitates the delivery of organic contaminants to the Arctic marine food web through processes that: 1) are independent of contaminant physical-chemical properties (e.g. 2-3-fold increase in exposure to brine-associated biota), and 2) depend on physical-chemical properties and, therefore, differentiate between contaminants (e.g. atmospheric loading of contaminants to melt ponds over the summer, and their subsequent leakage to the ocean). We estimate the concentrations of legacy organochlorine pesticides (OCPs) and current-use pesticides (CUPs) in melt pond water in the Beaufort Sea, Canadian High Arctic, in 2008, at near-gas exchange equilibrium based on Henry's law constants (HLCs), air concentrations and exchange dynamics. CUPs currently present the highest risk of increased exposures through melt pond loading and drainage due to the high ratio of melt pond water to seawater concentration (Melt pond Enrichment Factor, MEF), which ranges from 2 for dacthal to 10 for endosulfan I. Melt pond contaminant enrichment can be perceived as a hypothetical 'pump' delivering contaminants from the atmosphere to the ocean under ice-covered conditions, with 2-10% of CUPs annually entering the Beaufort Sea via this input route compared to the standing stock in the Polar Mixed Layer of the ocean. The abovementioned processes are strongly favored in first-year ice compared to multi-year ice and, therefore, the dynamic balance between contaminant inventories and contaminant deposition to the surface ocean is being widely affected by the large-scale icescape transition taking place in the Arctic. PMID:25437762

16. In-situ calibration and validation of Cryosat-2 observations over arctic sea ice north of Svalbard

Gerland, Sebastian; Renner, Angelika H. H.; Spreen, Gunnar;

CryoSat-2's radar altimeter allows to observe the panArctic sea ice thickness up to 88°N on a monthly basis. However, calibration and validation are crucial to assess limitations and accuracy of the altimeter, and to better quantify the uncertainties involved in converting sea ice freeboard to...

17. Autotrophic and heterotrophic activity in Arctic first-year sea-ice: Seasonal study from Marlene Bight, SW Greenland

Søgaard, Dorte Haubjerg; Kristensen, Morten; Rysgaard, Søren;

2010-01-01

We present a study of autotrophic and heterotrophic activities of Arctic sea ice (Malene Bight, SW Greenland) as measured by 2 different approaches: (1) standard incubation techniques ((HCO3-)-C-14 and [H-3] thymidine incubation) on sea ice cores brought to the laboratory and (2) cores incubated ...

18. Arctic Sea Ice Freeboard from Icebridge Acquisitions in 2009: Estimates and Comparisons with ICEsat

Kwok, R.; Cunningham, Glenn F.; Manizade, S. S.; Krabill, W. B.

2012-01-01

During the spring of 2009, the Airborne Topographic Mapper (ATM) system on the IceBridge mission acquired cross-basin surveys of surface elevations of Arctic sea ice. In this paper, the total freeboard derived from four 2000 km transects are examined and compared with those from the 2009 ICESat campaign. Total freeboard, the sum of the snow and ice freeboards, is the elevation of the air-snow interface above the local sea surface. Prior to freeboard retrieval, signal dependent range biases are corrected. With data from a near co-incident outbound and return track on 21 April, we show that our estimates of the freeboard are repeatable to within 4 cm but dependent locally on the density and quality of sea surface references. Overall difference between the ATM and ICESat freeboards for the four transects is 0.7 (8.5) cm (quantity in bracket is standard deviation), with a correlation of 0.78 between the data sets of one hundred seventy-eight 50 km averages. This establishes a level of confidence in the use of ATM freeboards to provide regional samplings that are consistent with ICESat. In early April, mean freeboards are 41 cm and 55 cm over first year and multiyear sea ice (MYI), respectively. Regionally, the lowest mean ice freeboard (28 cm) is seen on 5 April where the flight track sampled the large expanse of seasonal ice in the western Arctic. The highest mean freeboard (71 cm) is seen in the multiyear ice just west of Ellesmere Island from 21 April. The relatively large unmodeled variability of the residual sea surface resolved by ATM elevations is discussed.

19. New Visualizations Highlight New Information on the Contrasting Arctic and Antarctic Sea-Ice Trends Since the Late 1970s

Parkinson, Claire L.; DiGirolamo, Nicolo E.

2016-01-01

Month-by-month ranking of 37 years (1979-2015) of satellite-derived sea-ice extents in the Arctic and Antarctic reveals interesting new details in the overall trends toward decreasing sea-ice coverage in the Arctic and increasing sea-ice coverage in the Antarctic. The Arctic decreases are so definitive that there has not been a monthly record high in Arctic sea-ice extents in any month since 1986, a time period during which there have been 75 monthly record lows. The Antarctic, with the opposite but weaker trend toward increased ice extents, experienced monthly record lows in 5 months of 1986, then 6 later monthly record lows scattered through the dataset, with the last two occurring in 2006, versus 45 record highs since 1986. However, in the last three years of the 1979-2015 dataset, the downward trends in Arctic sea-ice extents eased up, with no new record lows in any month of 2013 or 2014 and only one record low in 2015,while the upward trends in Antarctic ice extents notably strengthened, with new record high ice extents in 4 months (August-November) of 2013, in 6 months (April- September) of 2014, and in 3 months (January, April, and May) of 2015. Globally, there have been only 3 monthly record highs since 1986 (only one since 1988), whereas there have been 43 record lows, although the last record lows (in the 1979-2015 dataset) occurred in 2012.

20. Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations

R. Lindsay

2014-08-01

Full Text Available Sea ice thickness is a fundamental climate state variable that provides an integrated measure of changes in the high-latitude energy balance. However, observations of ice thickness have been sparse in time and space making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness and each observational source likely has different and poorly characterized measurement and sampling biases. Observational sources include upward looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Here we use a curve-fitting approach to evaluate the systematic differences between eight different observation systems in the Arctic Basin. The approach determines the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month and the primary time period analyzed is 2000–2013 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compared to the five. The trend in annual mean ice thickness over the Arctic Basin is −0.58 ± 0.07 m decade−1 over the period 2000–2013, while the annual mean ice thickness for the central Arctic Basin alone (the SCICEX Box has decreased from 3.45 m in 1975 to 1.11 m in 2013, a 68% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational confirmation of substantial sea ice losses found in model analyses.

1. Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic

Geilfus, Nicolas-Xavier; Galley, R.J.; Crabeck, O.;

2014-01-01

of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However......, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring...... the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget....

2. Rapidly changing distribution of velocity and suspended materials under the drifting Arctic sea ice

Ha, Ho Kyung; Im, Jungho; Kim, Yong Hoon; Yae Son, Eun; Lee, Sanggyun

2015-04-01

In two summer seasons of 2011 and 2014, the short-term (1-4 days) ice-camp study has been conducted on the drifting Arctic sea ice. In particular, in 2014, the international collaboration with the Marginal Ice Zone program (sponsored by Office of Naval Research) has been integrated. The mooring package comprises the acoustic Doppler velocity profiler, holographic imaging camera, and conductivity-temperature-depth profiler, which are used to understand the dynamic behavior of sea ice and spatial-temporal variation of mixing layer (ML) and suspended particulate matters under the sea ice. Mooring data clearly shows the mixing and entrainment pattern in the upper ML in the marginal ice zone. When ice floes drift toward the pack ice, the upward entrainment from the seasonal pycnocline to sea ice-water boundary was induced by shear across ML and seasonal pycnocline. The entrainment speed was in the range of 0.25-2 m/hr, which matches well with thickening and thinning rate of ML during the near-inertial period (~12 hr). When ice floes drift toward the open ocean, the turbulent wakes at the advancing edge of ice were combined with the entrainment caused by near-inertial motion, which results in a complex mixing pattern of both upward and downward fluxes in the ML. Also, the acoustic backscatter observed by the acoustic Doppler current profiler and beam attenuation from transmissometer revealed the increased concentration of suspended particulate materials in the ML, which can be direct evidence visualizing the mixing pattern. Results suggest that the mixing and entrainment found in our study sustain particulate matters in suspension within the upper ML for a few months.

3. Convective forcing of mercury and ozone in the Arctic boundary layer induced by leads in sea ice

Moore, Christopher W.; Obrist, Daniel; Steffen, Alexandra; Staebler, Ralf M.; Douglas, Thomas A.; Richter, Andreas; Nghiem, Son V.

2014-02-01

The ongoing regime shift of Arctic sea ice from perennial to seasonal ice is associated with more dynamic patterns of opening and closing sea-ice leads (large transient channels of open water in the ice), which may affect atmospheric and biogeochemical cycles in the Arctic. Mercury and ozone are rapidly removed from the atmospheric boundary layer during depletion events in the Arctic, caused by destruction of ozone along with oxidation of gaseous elemental mercury (Hg(0)) to oxidized mercury (Hg(II)) in the atmosphere and its subsequent deposition to snow and ice. Ozone depletion events can change the oxidative capacity of the air by affecting atmospheric hydroxyl radical chemistry, whereas atmospheric mercury depletion events can increase the deposition of mercury to the Arctic, some of which can enter ecosystems during snowmelt. Here we present near-surface measurements of atmospheric mercury and ozone from two Arctic field campaigns near Barrow, Alaska. We find that coastal depletion events are directly linked to sea-ice dynamics. A consolidated ice cover facilitates the depletion of Hg(0) and ozone, but these immediately recover to near-background concentrations in the upwind presence of open sea-ice leads. We attribute the rapid recoveries of Hg(0) and ozone to lead-initiated shallow convection in the stable Arctic boundary layer, which mixes Hg(0) and ozone from undepleted air masses aloft. This convective forcing provides additional Hg(0) to the surface layer at a time of active depletion chemistry, where it is subject to renewed oxidation. Future work will need to establish the degree to which large-scale changes in sea-ice dynamics across the Arctic alter ozone chemistry and mercury deposition in fragile Arctic ecosystems.

4. The Arctic Amplification and inter-relation between Arctic Sea-Ice, cloud greenhouse heating and atmospheric circulation in ERA-Interim and EC-Earth

Willen, Ulrika; Bintanja, Richard; Sedlar, Joseph; Königk, Torben

2014-05-01

The Arctic is warming faster than the global average especially in autumn and winter and substantial reductions in summer and winter sea-ice have been observed recently. It is also the part of the globe where climate model scenarios show the largest spread. The impact of clouds on sea ice and Arctic amplification is not well understood even though an increase in clouds in winter is expected to have a warming effect due to the initial small amounts of cloud condensate and especially in liquid form. Many recent observational data sets report significant amounts of mixed-phase clouds over the Arctic in all seasons. The frequent occurrence of Arctic mixed-phase clouds has important implications for the cloud radiative forcing at the surface, since mixed-phase clouds tend to be optically thicker than ice-only clouds and emit more downward long-wave flux which increases the surface temperature and sea-ice melt. A number of studies have shown that models underestimate the amount of cloud water in Arctic mixed-phase clouds. In this study we investigate how cloudiness affect the Arctic warming and sea-ice retreat in the global coupled climate model EC-Earth for AMIP and transient experiments. We also investigate how the cloud-radiation and sea-ice interactions affect the circulation in EC-Earth and in ERA-Interim reanalysis data.

5. The influence of regional Arctic sea-ice decline on stratospheric and tropospheric circulation

McKenna, Christine; Bracegirdle, Thomas; Shuckburgh, Emily; Haynes, Peter

2016-04-01

Arctic sea-ice extent has rapidly declined over the past few decades, and most climate models project a continuation of this trend during the 21st century in response to greenhouse gas forcing. A number of recent studies have shown that this sea-ice loss induces vertically propagating Rossby waves, which weaken the stratospheric polar vortex and increase the frequency of sudden stratospheric warmings (SSWs). SSWs have been shown to increase the probability of a negative NAO in the following weeks, thereby driving anomalous weather conditions over Europe and other mid-latitude regions. In contrast, other studies have shown that Arctic sea-ice loss strengthens the polar vortex, increasing the probability of a positive NAO. Sun et al. (2015) suggest these conflicting results may be due to the region of sea-ice loss considered. They find that if only regions within the Arctic Circle are considered in sea-ice projections, the polar vortex weakens; if only regions outwith the Arctic Circle are considered, the polar vortex strengthens. This is because the anomalous Rossby waves forced in the former/latter scenario constructively/destructively interfere with climatological Rossby waves, thus enhancing/suppressing upward wave propagation. In this study, we investigate whether Sun et al.'s results are robust to a different model. We also divide the regions of sea-ice loss they considered into further sub-regions, in order to examine the regional differences in more detail. We do this by using the intermediate complexity climate model, IGCM4, which has a well resolved stratosphere and does a good job of representing stratospheric processes. Several simulations are run in atmosphere only mode, where one is a control experiment and the others are perturbation experiments. In the control run annually repeating historical mean surface conditions are imposed at the lower boundary, whereas in each perturbation run the model is forced by SST perturbations imposed in a specific

6. The influence of Arctic sea ice variability on the summer North Atlantic Oscillation (SNAO)

Linderholm, H. W.; Folland, C. K.; Ou, T.; Jeong, J. H.; Wilson, R.; Rydval, M.; Chen, D.; Kim, B. M.

2015-12-01

The summer North Atlantic Oscillation (SNAO), which is strongly related to changes in Atlantic and European summer storm tracks and the latitudinal position of the jet stream, exerts a strong influence on rainfall, temperature, and cloudiness and is related to summer extremes, such as droughts and floods, mainly in Europe. Reconstructions suggest that the SNAO was mainly negative during the last several centuries until the mid-twentieth century when it entered a positive phase, and climate model projections have suggested a predominantly positive SNAO under future global warming. However, during the recent decade, the SNAO has mainly been in a negative phase, along with a southerly shift in the jet stream, accompanied by wet and cool summers in northwest Europe. Sea surface temperatures in the North Atlantic (related to the Atlantic Multidecadal Oscillation, AMO) strongly influence the SNAO, and the current positive phase of the AMO has likely played some role in the recent downturn of the SNAO. Additionally, we found a consistent association between winter/spring Arctic sea ice concentration (SIC), particularly in the Labrador and Nordic seas, and the SNAO over the last decades based on observations. However, since the 1990s the strength of the correlations with the regional SIC has changed, weakening over the Labrador Sea and strengthening over Barents Sea. This is particularly evident during the last decade. Possibly this is a response to the rapid changes in Arctic sea ice. To test this, a new tree-ring based reconstruction of the SNAO as well as CMIP5 model runs are used to examine the influence of Arctic sea ice on the summer atmospheric circulation over northwestern Europe in a long-term context.

7. History of sea ice in the Arctic basin: Lessons from the past for future

I. I. Borzenkova

2016-01-01

Full Text Available The process of the sea ice formation in the Arctic Ocean is analyzed for the period of the last 65 million years, i.e. from the Paleocene to the present time. Appearance of sea ice in the high latitudes is demonstrated to be caused by the negative trend in global temperatures due to decreasing of the CO2 concentration in the ancient atmosphere. Formation of seasonal and perennial ice cover in the limited area near the Pole could take place during the mid-Neogene period, about 12–13 Ma ago. However, areas of the sea icing could be obviously changed for this time during periods of the climate warming and cooling. Permanent sea ice had been formed in the early Pleistocene, i.e. about 2.0–1.8 Ma ago only. Paleoclimatic reconstructions, based on the indirect data and modeling simulation for the Holocene optimum (10–6 ka ago and for the Last Interglacial period (the isotopic substage in the marine cross-section 5e, about 125–127 ka ago had shown that rising of global temperatures by 1.0–1.5 °C resulted in strong decreasing of the sea ice area, and the perennial ice cover became the seasonal one. Relatively small changes in the incoming solar radiation originating during the spring-summer time due to the orbital factors played the role of a trigger for onset of the melting process. Further on, the process could be enhanced owing to difference in the albedo between the ice cover and open water. Recently, the rapid shortening of the sea ice area is noted, and in some parts of the Arctic Ocean the area is twice cut down as compared with the normal. In 2015, the record low area of the winter sea ice was observed, and therewith the maximum of the ice area shifted to the earlier period (by 15 days as compared with the period of 1981–2010. The winter fluctuations of the sea ice areas are as much important as the summer ones, since they are the best indicators of the present-day global warming. Thus, it can be supposed that some

8. Large, omega-3 rich, pelagic diatoms under Arctic sea ice: sources and implications for food webs.

Duerksen, Steven W; Thiemann, Gregory W; Budge, Suzanne M; Poulin, Michel; Niemi, Andrea; Michel, Christine

2014-01-01

Pelagic primary production in Arctic seas has traditionally been viewed as biologically insignificant until after the ice breakup. There is growing evidence however, that under-ice blooms of pelagic phytoplankton may be a recurrent occurrence. During the springs of 2011 and 2012, we found substantial numbers (201-5713 cells m-3) of the large centric diatom (diameter >250 µm) Coscinodiscus centralis under the sea ice in the Canadian Arctic Archipelago near Resolute Bay, Nunavut. The highest numbers of these pelagic diatoms were observed in Barrow Strait. Spatial patterns of fatty acid profiles and stable isotopes indicated two source populations for C. centralis: a western origin with low light conditions and high nutrients, and a northern origin with lower nutrient levels and higher irradiances. Fatty acid analysis revealed that pelagic diatoms had significantly higher levels of polyunsaturated fatty acids (mean ± SD: 50.3 ± 8.9%) compared to ice-associated producers (30.6 ± 10.3%) in our study area. In particular, C. centralis had significantly greater proportions of the long chain omega-3 fatty acid, eicosapentaenoic acid (EPA), than ice algae (24.4 ± 5.1% versus 13.7 ± 5.1%, respectively). Thus, C. centralis represented a significantly higher quality food source for local herbivores than ice algae, although feeding experiments did not show clear evidence of copepod grazing on C. centralis. Our results suggest that C. centralis are able to initiate growth under pack ice in this area and provide further evidence that biological productivity in ice-covered seas may be substantially higher than previously recognized. PMID:25473949

9. Migration phenology and seasonal fidelity of an Arctic marine predator in relation to sea ice dynamics.

Cherry, Seth G; Derocher, Andrew E; Thiemann, Gregory W; Lunn, Nicholas J

2013-07-01

Understanding how seasonal environmental conditions affect the timing and distribution of synchronized animal movement patterns is a central issue in animal ecology. Migration, a behavioural adaptation to seasonal environmental fluctuations, is a fundamental part of the life history of numerous species. However, global climate change can alter the spatiotemporal distribution of resources and thus affect the seasonal movement patterns of migratory animals. We examined sea ice dynamics relative to migration patterns and seasonal geographical fidelity of an Arctic marine predator, the polar bear (Ursus maritimus). Polar bear movement patterns were quantified using satellite-linked telemetry data collected from collars deployed between 1991-1997 and 2004-2009. We showed that specific sea ice characteristics can predict the timing of seasonal polar bear migration on and off terrestrial refugia. In addition, fidelity to specific onshore regions during the ice-free period was predicted by the spatial pattern of sea ice break-up but not by the timing of break-up. The timing of migration showed a trend towards earlier arrival of polar bears on shore and later departure from land, which has been driven by climate-induced declines in the availability of sea ice. Changes to the timing of migration have resulted in polar bears spending progressively longer periods of time on land without access to sea ice and their marine mammal prey. The links between increased atmospheric temperatures, sea ice dynamics, and the migratory behaviour of an ice-dependent species emphasizes the importance of quantifying and monitoring relationships between migratory wildlife and environmental cues that may be altered by climate change. PMID:23510081

10. Greenland sea ice anomalies during 1901-1984 and their relation to an interdecadal arctic climate cycle

Two ice data sets from the Greenland and neighboring seas have been analyzed to determine interannual and decadal time scale sea ice extent anomalies during this century. Sea ice concentration data on a 1 degree x 1 degree grid for 1953-1984 revealed the presence of a large positive anomaly in the Greenland Sea during the 1960s which coincided with the Great Salinity Anomaly, a low-salinity water mass that traveled cyclonically around the northern North Atlantic during 1968-1982. The two anomalies propagated into the Labrador Sea with a typical travel time of 3-5 years. Spring and summer ice-limit data obtained from Danish Meteorological Institute charts for 1901-1956 indicated the presence of heavy ice conditions in the Greenland Sea during 1902-1920 and in the late 1940s, and generally light ice conditions during the 1920s and 1930s. Only limited evidence of propagation of Greenland Sea ice anomalies into the Labrador Sea was observed, however. On the other hand, several large ice anomalies in the Greenland Sea occurred 2-3 years after large runoffs from northern Canada into the western Arctic Ocean. Similarly, a large runoff into the Arctic preceded the large Greenland Sea ice anomaly of the 1960s. These facts, together with recent evidence of climatic jumps in the Northern Hemisphere tropospheric circulation, suggest the existence of an interdecadal, self-sustained climate cycle in the Arctic which is described in terms of a negative feed-back loop. In the Greenland Sea this cycle is characterized by a state of large sea ice extent overlying a layer of cool freshwater that does not convectively overturn, which alternates with a state of small sea ice extent and warm saline surface water that frequently overturns

11. Summer sea ice characteristics and morphology in the Pacific Arctic sector as observed during the CHINARE 2010 cruise

H. Xie

2013-07-01

Full Text Available In the summer of 2010, atmosphere–ice–ocean interaction was studied aboard the icebreaker R/V Xuelong during the Chinese National Arctic Research Expedition (CHINARE, in the sea ice zone of the Pacific Arctic sector between 150° W and 180° W up to 88.5° N. The expedition lasted from 21 July to 28 August and comprised of ice observations and measurements along the cruise track, 8 short-term stations and one 12-day drift station. Ship-based observations of ice thickness and concentration are compared with ice thickness measured by an electromagnetic induction device (EM31 mounted off the ship's side and ice concentrations obtained from AMSR-E. It is found that the modal thickness from ship-based visual observations matches well with the modal thickness from the mounted EM31. A grid of 8 profiles of ice thickness measurements (four repeats was conducted at the 12-day drift station in the central Arctic (~ 86°50´ N–87°20´ N and an average melt rate of 2 cm day−1, primarily bottom melt, was found. As compared with the 2005 data from the Healy/Oden Trans-Arctic Expedition (HOTRAX for the same sector but ~ 20 days later (9 August to 10 September, the summer 2010 was first-year ice dominant (vs. the multi-year ice dominant in 2005, 70% or less in mean ice concentration (vs. 90% in 2005, and 94–114 cm in mean ice thickness (vs. 150 cm in 2005. Those changes suggest the continuation of ice thinning, less concentration, and younger ice for the summer sea ice in the sector since 2007 when a record minimum sea ice extent was observed. Overall, the measurements provide a valuable dataset of sea ice morphological properties over the Arctic Pacific Sector in summer 2010 and can be used as a benchmark for measurements of future changes.

12. Arctic climate response to forcing from light-absorbing particles in snow and sea ice in CESM

N. Goldenson

2012-09-01

Full Text Available The presence of light-absorbing aerosol particles deposited on arctic snow and sea ice influences the surface albedo, causing greater shortwave absorption, warming, and loss of snow and sea ice, lowering the albedo further. The Community Earth System Model version 1 (CESM1 now includes the radiative effects of light-absorbing particles in snow on land and sea ice and in sea ice itself. We investigate the model response to the deposition of black carbon and dust to both snow and sea ice. For these purposes we employ a slab ocean version of CESM1, using the Community Atmosphere Model version 4 (CAM4, run to equilibrium for year 2000 levels of CO2 and fixed aerosol deposition. We construct experiments with and without aerosol deposition, with dust or black carbon deposition alone, and with varying quantities of black carbon and dust to approximate year 1850 and 2000 deposition fluxes. The year 2000 deposition fluxes of both dust and black carbon cause 1–2 °C of surface warming over large areas of the Arctic Ocean and sub-Arctic seas in autumn and winter and in patches of Northern land in every season. Atmospheric circulation changes are a key component of the surface-warming pattern. Arctic sea ice thins by on average about 30 cm. Simulations with year 1850 aerosol deposition are not substantially different from those with year 2000 deposition, given constant levels of CO2. The climatic impact of particulate impurities deposited over land exceeds that of particles deposited over sea ice. Even the surface warming over the sea ice and sea ice thinning depends more upon light-absorbing particles deposited over land. For CO2 doubled relative to year 2000 levels, the climate impact of particulate impurities in snow and sea ice is substantially lower than for the year 2000 equilibrium simulation.

13. Arctic sea ice bordering on the North Atlantic and intera- nnual climate variations

2001-01-01

Variations of winter Arctic sea ice bordering on the North Atlantic are closely related to climate variations in the same region. When winter North Atlantic Oscillation (NAO) index is positive (negative) anomaly phase, Icelandic Low is obviously deepened and shifts northwards (southwards). Simultaneously, the Subtropical High over the North Atlantic is also intensified, and moves northwards (south-wards). Those anomalies strengthen (weaken) westerly be-tween Icelandic Low and the Subtropical High, and further result in positive (negative) sea surface temperature (SST) anomalies in the mid-latitude of the North Atlantic, and increase (decrease) the warm water transportation from the mid-latitude to the Barents Sea, which causes positive (nega-tive) mixed-layer water temperature anomalies in the south part of the Barents Sea. Moreover, the distribution of anom-aly air temperature clearly demonstrates warming (cooling) in northern Europe and the subarctic regions (including the Barents Sea) and cooling (warming) in Baffin Bay/ Davis Strait. Both of distributions of SST and air temperature anomalies directly result in sea ice decrease (increase) in the Barents/Kara Seas, and sea ice increase (decrease) in Baffin Bay/Davis Strait.

14. Optimization of a sea ice model using basinwide observations of Arctic sea ice thickness, extent, and velocity

Miller, Paul A.; Laxon, Seymour W.; FELTHAM, DANIEL L.; Cresswell, Douglas J.

2006-01-01

A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Su...

15. Arctic layer salinity controls heat loss from deep Atlantic layer in seasonally ice-covered areas of the Barents Sea

Lind, Sigrid; Ingvaldsen, Randi B.; Furevik, Tore

2016-05-01

In the seasonally ice-covered northern Barents Sea an intermediate layer of cold and relatively fresh Arctic Water at ~25-110 m depth isolates the sea surface and ice cover from a layer of warm and saline Atlantic Water below, a situation that resembles the cold halocline layer in the Eurasian Basin. The upward heat flux from the Atlantic layer is of major concern. What causes variations in the heat flux and how is the Arctic layer maintained? Using observations, we found that interannual variability in Arctic layer salinity determines the heat flux from the Atlantic layer through its control of stratification and vertical mixing. A relatively fresh Arctic layer effectively suppresses the upward heat flux, while a more saline Arctic layer enhances the heat flux. The corresponding upward salt flux causes a positive feedback. The Arctic layer salinity and the water column structures have been remarkably stable during 1970-2011.

16. The distribution of radiocesium and plutonium in sea ice-entrained arctic sediments in relation to potential sources and sinks

Gamma counting of a range of grain size fractions of sediments entrained in Arctic Ocean sea ice indicate that the wide range of radiocesium activities that are observed in bulk samples are primarily a function of the geographical origin of the sediment, rather than mineral composition, or physical processes that increase the content of fine clays in sediments. Plutonium isotope ratios (240Pu:239Pu) of sea ice sediments are consistent with an ultimate origin of the plutonium from bomb fallout (240Pu:239Pu=similar0·18), and these sediment ratios differ significantly in plutonium isotope ratios from deep sea sediments of the Arctic Ocean. Much lower plutonium activities were observed in deep sea sediments relative to the sea ice entrained sediments. These differences in isotopic ratios indicate that on decadal scales, sedimentation of bomb fallout plutonium is not the sole source of plutonium to deep Arctic Ocean sediments. The large differences in total plutonium activity between some of the sea ice entrained sediments and all of the deep Arctic Ocean sediments also suggest that the total flux of plutonium from sea ice entrained sediments to the deep sea may be relatively small. Radiocesium activity in the sea ice entrained sediments is well correlated with total plutonium abundance, but the best-fit regression line does not pass through the origin, indicating that a small secondary source of cesium (3 to 9 Bq kg-1 dry weight) that is free of plutonium may contribute to the radiocesium activity observed in sediments entrained in Arctic Ocean sea ice. Based upon observations of carbon:nitrogen weight/weight ratios in excess of 20 in the organic carbon fraction, together with δ13C values less than -23%, several of the sea ice entrained sediments show indications of estuarine origin. However, these specific samples typically have low radionuclide burdens. Consideration of the low smectite content (sea ice sediments and prevailing

17. Arctic sea ice melt, the Polar vortex, and mid-latitude weather: Are they connected?

Vihma, Timo; Overland, James; Francis, Jennifer; Hall, Richard; Hanna, Edward; Kim, Seong-Joong

2015-04-01

The potential of recent Arctic changes to influence broader hemispheric weather is a difficult and controversial topic with considerable skepticism, as time series of potential linkages are short (relative to chaotic weather events is small. A way forward is through further understanding of potential atmospheric dynamic mechanisms. Although not definitive of change in a statistical or in a causality sense, the exceptionally warm Arctic winters since 2007 do contain increased variability according to some climate indices, with six negative (and two positive) Arctic Oscillation atmospheric circulation index events that created meridional flow reaching unusually far north and south. High pressure anomalies developed east of the Ural Mountains in Russia in response to sea-ice loss in the Barents/Kara Seas, which initiated eastward-propagating wave trains of high and low pressure that advected cold air over central and eastern Asia. Increased Greenland blocking and greater geopotential thickness related to low-level temperatures increases led to northerly meridional flow into eastern North America, inducing persistent cold periods. Arctic connections in Europe and western North America are less clear. The quantitative impact of potential Arctic change on mid-latitude weather will not be resolved within the foreseeable future, yet new approaches to high-latitude atmospheric dynamics can contribute to improved extended range forecasts as outlined by the WMO/Polar Prediction Program and other international activities.

18. The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: A model study

Martin, Torge; Tsamados, Michel; Schroeder, David; Feltham, Daniel L.

2016-03-01

The Arctic sea ice cover is thinning and retreating, causing changes in surface roughness that in turn modify the momentum flux from the atmosphere through the ice into the ocean. New model simulations comprising variable sea ice drag coefficients for both the air and water interface demonstrate that the heterogeneity in sea ice surface roughness significantly impacts the spatial distribution and trends of ocean surface stress during the last decades. Simulations with constant sea ice drag coefficients as used in most climate models show an increase in annual mean ocean surface stress (0.003 N/m2 per decade, 4.6%) due to the reduction of ice thickness leading to a weakening of the ice and accelerated ice drift. In contrast, with variable drag coefficients our simulations show annual mean ocean surface stress is declining at a rate of -0.002 N/m2 per decade (3.1%) over the period 1980-2013 because of a significant reduction in surface roughness associated with an increasingly thinner and younger sea ice cover. The effectiveness of sea ice in transferring momentum does not only depend on its resistive strength against the wind forcing but is also set by its top and bottom surface roughness varying with ice types and ice conditions. This reveals the need to account for sea ice surface roughness variations in climate simulations in order to correctly represent the implications of sea ice loss under global warming.

19. Tracking and responding to a changing Arctic sea-ice cover: How ice users can help the scientific community design better observing systems (Louis Agassiz Medal Lecture)

Eicken, Hajo

2010-05-01

The Arctic sea-ice cover is undergoing a major transformation, with substantial reductions in summer ice extent reflecting changes in ice thickness, age, and circulation. These changes are impacting Arctic ecosystems and a range of human activities. Anticipating and responding to such impacts, exacerbated by increasing economic activity in parts of the Arctic, requires a foundation of environmental observations and model predictions. Recent increases in industrial activities such as shipping and resource development in parts of the Arctic have further highlighted the need for an integrated observing system. In the case of a changing sea-ice cover, how would one best design and optimize such a system? One of the challenges is to meet the information needs of the scientific community in furthering fundamental understanding of the Arctic system, as well as those of key stakeholders and society, helping them to prepare for and respond to Arctic change. This presentation focuses on how the concept of sea-ice system services, i.e., the uses and benefits (or harm) derived from sea ice, may help guide the implementation of an effective observing system. Principal service categories are (1) sea ice as climate regulator, marine hazard, and coastal buffer; (2) transportation and use of ice as a platform; (3) cultural services obtained from the "icescape"; and (4) support of food webs and biological diversity by sea ice. An analysis of the different ice services provided to different user groups can help prioritize different types of observations and determine optimal measurement strategies. Moreover, the focus on different uses of the ice cover may also help synthesize fundamental and applied research to help Arctic communities adapt in a changing environment. Alaska has experienced some of the most substantial changes in sea-ice conditions throughout the Arctic over the past three decades and is used to illustrate the concepts discussed above. Specifically, we have examined

20. Loss of Arctic sea ice causing punctuated change in sightings of killer whales (Orcinus orca) over the past century.

Higdon, Jeff W; Ferguson, Steven H

2009-07-01

Killer whales (Orcinus orca) are major predators that may reshape marine ecosystems via top-down forcing. Climate change models predict major reductions in sea ice with the subsequent expectation for readjustments of species' distribution and abundance. Here, we measure changes in killer whale distribution in the Hudson Bay region with decreasing sea ice as an example of global readjustments occurring with climate change. We summarize records of killer whales in Hudson Bay, Hudson Strait, and Foxe Basin in the eastern Canadian Arctic and relate them to an historical sea ice data set while accounting for spatial and temporal autocorrelation in the data. We find evidence for "choke points," where sea ice inhibits killer whale movement, thereby creating restrictions to their Arctic distribution. We hypothesize that a threshold exists in seasonal sea ice concentration within these choke points that results in pulses in advancements in distribution of an ice-avoiding predator. Hudson Strait appears to have been a significant sea ice choke point that opened up .approximately 50 years ago allowing for an initial punctuated appearance of killer whales followed by a gradual advancing distribution within the entire Hudson Bay region. Killer whale sightings have increased exponentially and are now reported in the Hudson Bay region every summer. We predict that other choke points will soon open up with continued sea ice melt producing punctuated predator-prey trophic cascades across the Arctic. PMID:19688941

1. Where to Forage in the Absence of Sea Ice? Bathymetry As a Key Factor for an Arctic Seabird.

Françoise Amélineau

Full Text Available The earth is warming at an alarming rate, especially in the Arctic, where a marked decline in sea ice cover may have far-ranging consequences for endemic species. Little auks, endemic Arctic seabirds, are key bioindicators as they forage in the marginal ice zone and feed preferentially on lipid-rich Arctic copepods and ice-associated amphipods sensitive to the consequences of global warming. We tested how little auks cope with an ice-free foraging environment during the breeding season. To this end, we took advantage of natural variation in sea ice concentration along the east coast of Greenland. We compared foraging and diving behaviour, chick diet and growth and adult body condition between two years, in the presence versus nearby absence of sea ice in the vicinity of their breeding site. Moreover, we sampled zooplankton at sea when sea ice was absent to evaluate prey location and little auk dietary preferences. Little auks foraged in the same areas both years, irrespective of sea ice presence/concentration, and targeted the shelf break and the continental shelf. We confirmed that breeding little auks showed a clear preference for larger copepod species to feed their chick, but caught smaller copepods and nearly no ice-associated amphipod when sea ice was absent. Nevertheless, these dietary changes had no impact on chick growth and adult body condition. Our findings demonstrate the importance of bathymetry for profitable little auk foraging, whatever the sea-ice conditions. Our investigations, along with recent studies, also confirm more flexibility than previously predicted for this key species in a warming Arctic.

2. Where to Forage in the Absence of Sea Ice? Bathymetry As a Key Factor for an Arctic Seabird

Amélineau, Françoise; Grémillet, David; Bonnet, Delphine; Le Bot, Tangi; Fort, Jérôme

2016-01-01

The earth is warming at an alarming rate, especially in the Arctic, where a marked decline in sea ice cover may have far-ranging consequences for endemic species. Little auks, endemic Arctic seabirds, are key bioindicators as they forage in the marginal ice zone and feed preferentially on lipid-rich Arctic copepods and ice-associated amphipods sensitive to the consequences of global warming. We tested how little auks cope with an ice-free foraging environment during the breeding season. To this end, we took advantage of natural variation in sea ice concentration along the east coast of Greenland. We compared foraging and diving behaviour, chick diet and growth and adult body condition between two years, in the presence versus nearby absence of sea ice in the vicinity of their breeding site. Moreover, we sampled zooplankton at sea when sea ice was absent to evaluate prey location and little auk dietary preferences. Little auks foraged in the same areas both years, irrespective of sea ice presence/concentration, and targeted the shelf break and the continental shelf. We confirmed that breeding little auks showed a clear preference for larger copepod species to feed their chick, but caught smaller copepods and nearly no ice-associated amphipod when sea ice was absent. Nevertheless, these dietary changes had no impact on chick growth and adult body condition. Our findings demonstrate the importance of bathymetry for profitable little auk foraging, whatever the sea-ice conditions. Our investigations, along with recent studies, also confirm more flexibility than previously predicted for this key species in a warming Arctic. PMID:27438790

3. Review: Potential catastrophic reduction of sea ice in the western Arctic Ocean: Its impact on biogeochemical cycles and marine ecosystems

2016-01-01

The reduction of sea ice in the Arctic Ocean, which has progressed more rapidly than previously predicted, has the potential to cause multiple environmental stresses, including warming, acidification, and strengthened stratification of the ocean. Observational studies have been undertaken to detect the impacts on biogeochemical cycles and marine ecosystems of these environmental stresses in the Arctic Ocean. Satellite analyses show that the reduction of sea ice has been especially great in the western Arctic Ocean. Observations and model simulations have both helped to clarify the impact of sea-ice reductions on the dynamics of ecosystem processes and biogeochemical cycles. In this review, I focus on the western Arctic Ocean, which has experienced the most rapid retreat of sea ice in the Arctic Ocean and, very importantly, has a higher rate of primary production than any other area of the Arctic Ocean owing to the supply of nutrient-rich Pacific water. I report the impact of the current reduction of sea ice on marine biogeochemical cycles in the western Arctic Ocean, including lower-trophic-level organisms, and identify the key mechanism of changes in the biogeochemical cycles, based on published observations and model simulations. The retreat of sea ice has enhanced primary production and has increased the frequency of appearance of mesoscale anticyclonic eddies. These eddies enhance the light environment and replenish nutrients, and they also represent a mechanism that can increase the rate of the biological pump in the Arctic Ocean. Various unresolved issues that require further investigation, such as biological responses to environmental stressors such as ocean acidification, are also discussed.

4. Air-sea-ocean interaction processes and impacts on polynya formation and sea ice production in the Laptev Sea of the Siberian Arctic

Heinemann, Günther; Schröder, David; Willmes, Sascha; Ebner, Lars; Adams, Susanne; Ernsdorf, Thomas; Helbig, Alfred; Timmermann, Ralph

2010-01-01

Processes of the exchange of energy and momentum at the sea ice-ocean-atmosphere interface are key processes for the polar climate system. Heat and moisture fluxes are strongly modulated by open water fractions associated with polynyas, having important consequences for the atmosphere, ocean processes, ice formation, brine release, gas exchange and biology. Our paper aims at the study of atmospheric processes forcing and maintaining polynyas in the Laptev Sea of the Siberian Arctic. This regi...

5. The 2013 Arctic Field Season of the NRL Sea-Ice Measurement Program

Gardner, J. M.; Brozena, J. M.; Ball, D.; Hagen, R. A.; Liang, R.; Stoudt, C.

2013-12-01

The U.S. Naval Research Laboratory (NRL) is conducting a five year study of the changing Arctic with a particular focus on ice thickness and distribution variability with the intent of optimizing state-of-the-art computer models which are currently used to predict sea ice changes. An important part of our study is to calibrate/validate CryoSat2 ice thickness data prior to its incorporation into new ice forecast models. NRL Code 7420 collected coincident data with the CryoSat2 satellite in 2011 and 2012 using a LiDAR (Riegl Q560) to measure combined snow and ice thickness and a 10 GHz pulse-limited precision radar altimeter to measure sea-ice freeboard. This field season, LiDAR data was collected using the Riegl Q680 which permitted higher density operation and data collection. Concident radar data was collected using an improved version of the NRL 10 GHz pulse limited radar that was used for the 2012 fieldwork. 8 coincident tracks of CryoSat2 satellite data were collected. Additionally a series of grids (7 total) of adjacent tracks were flown coincident with Cryosat2 satellite overpass. These grids cover the approximate satellite footprint of the satellite on the ice as it passes overhead. Data from these grids are shown here and will be used to examine the relationship of the tracked satellite waveform data to the actual surface across the footprint. We also coordinated with the Seasonal Ice Zone Observing Network (SIZONet) group who conducted surface based ice thickness surveys using a Geonics EM-31 along hunter trails on the landfast ice near Barrow as well as on drifting ice offshore during helicopter landings. On two sorties, a twin otter carrying the NRL LiDAR and radar altimeter flew in tandem with the helicopter carrying the EM-31 to achieve synchronous data acquisition. Data from these flights are shown here along with a digital elevation map.

6. Species of Thaumatomastix (Thaumatomastigidae, Protista incertae sedis) from the Arctic sea ice biota (North-East Water Polynya, NE Greenland)

Thomsen, Helge Abildhauge; Ikävalko, Johanna

1997-01-01

The sea ice biota of polar regions contains numerous heterotrophic flagellates very few of which have been properly identified. The whole mount technique for transmission electron microscopy enables the identification of loricate and scaly forms. A survey of Arctic ice samples (North-East Water Polynya, NE Greenland) revealed the presence of ca. 12 taxa belonging to the phagotrophic genus Thaumatomastix (Protista incertae sedis). Species of Thaumatomastix possess siliceous body scales and one naked and one scale-covered flagellum. The presence in both Arctic samples and sea ice material previously examined from the Antarctic indicates that this genus is most likely ubiquitous in polar sea ice and may be an important component in sea ice biota microbial activities.

7. EASE-Grid Sea Ice Age

National Aeronautics and Space Administration — This data set provides weekly estimates of sea ice age for the Arctic Ocean from remotely sensed sea ice motion and sea ice extent. The ice age data are derived...

8. Arctic Sea Ice in Transformation: A Review of Recent Observed Changes and Impacts on Biology and Human Activity

Meier, Walter N.; Hovelsrud, Greta K.; van Oort, Bob E. H.; Key, Jeffrey R.; Kovacs, Kit M.; Michel, Christine; Haas, Christian; Granskog, Mats A.; Gerland, Sebastian; Perovich, Donald K.; Makshtas, Alexander; Reist, James D.

2014-01-01

Sea ice in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal extent has declined over 30, and all months show statistically significant declining trends. New satellite missions and techniques have greatly expanded information on sea ice thickness, but many uncertainties remain in the satellite data and long-term records are sparse. However, thickness observations and other satellite-derived data indicate a 40 decline in thickness, due in large part to the loss of thicker, older ice cover. The changes in sea ice are happening faster than models have projected. With continued increasing temperatures, summer ice-free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea ice decreases. The changes in Arctic sea ice are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting peoples living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction.

9. Sea Ice, Hydrocarbon Extraction, Rain-on-Snow and Tundra Reindeer Nomadism in Arctic Russia

Forbes, B. C.; Kumpula, T.; Meschtyb, N.; Laptander, R.; Macias-Fauria, M.; Zetterberg, P.; Verdonen, M.

2015-12-01

It is assumed that retreating sea ice in the Eurasian Arctic will accelerate hydrocarbon development and associated tanker traffic along Russia's Northern Sea Route. However, oil and gas extraction along the Kara and Barents Sea coasts will likely keep developing rapidly regardless of whether the Northwest Eurasian climate continues to warm. Less certain are the real and potential linkages to regional biota and social-ecological systems. Reindeer nomadism continues to be a vitally important livelihood for indigenous tundra Nenets and their large herds of semi-domestic reindeer. Warming summer air temperatures over the NW Russian Arctic have been linked to increases in tundra productivity, longer growing seasons, and accelerated growth of tall deciduous shrubs. These temperature increases have, in turn, been linked to more frequent and sustained summer high-pressure systems over West Siberia, but not to sea ice retreat. At the same time, winters have been warming and rain-on-snow (ROS) events have become more frequent and intense, leading to record-breaking winter and spring mortality of reindeer. What is driving this increase in ROS frequency and intensity is not clear. Recent modelling and simulation have found statistically significant near-surface atmospheric warming and precipitation increases during autumn and winter over Arctic coastal lands in proximity to regions of sea-ice loss. During the winter of 2013-14 an extensive and lasting ROS event led to the starvation of 61,000 reindeer out of a population of ca. 300,000 animals on Yamal Peninsula, West Siberia. Historically, this is the region's largest recorded mortality episode. More than a year later, participatory fieldwork with nomadic herders during spring-summer 2015 revealed that the ecological and socio-economic impacts from this extreme event will unfold for years to come. There is an urgent need to understand whether and how ongoing Barents and Kara Sea ice retreat may affect the region's ancient

10. Impact of rapid sea-ice reduction in the Arctic Ocean on the rate of ocean acidification

A. Yamamoto

2012-06-01

Full Text Available The largest pH decline and widespread undersaturation with respect to aragonite in this century due to uptake of anthropogenic carbon dioxide in the Arctic Ocean have been projected. The reductions in pH and aragonite saturation state in the Arctic Ocean have been caused by the melting of sea ice as well as by an increase in the concentration of atmospheric carbon dioxide. Therefore, future projections of pH and aragonite saturation in the Arctic Ocean will be affected by how rapidly the reduction in sea ice occurs. The observed recent Arctic sea-ice loss has been more rapid than projected by many of the climate models that contributed to the Intergovernmental Panel on Climate Change Fourth Assessment Report. In this study, the impact of sea-ice reduction rate on projected pH and aragonite saturation state in the Arctic surface waters was investigated. Reductions in pH and aragonite saturation were calculated from the outputs of two versions of an Earth system model with different sea-ice reduction rates under similar CO2 emission scenarios. The newer model version projects that Arctic summer ice-free condition will be achieved by the year 2040, and the older version predicts ice-free condition by 2090. The Arctic surface water was projected to be undersaturated with respect to aragonite in the annual mean when atmospheric CO2 concentration reaches 513 (606 ppm in year 2046 (2056 in new (old version. At an atmospheric CO2 concentration of 520 ppm, the maximum differences in pH and aragonite saturation state between the two versions were 0.1 and 0.21 respectively. The analysis showed that the decreases in pH and aragonite saturation state due to rapid sea-ice reduction were caused by increases in both CO2 uptake and freshwater input. Thus, the reductions in pH and aragonite saturation state in the Arctic surface waters are significantly affected by the difference in future projections for sea-ice

11. Relationships linking primary production, sea ice melting, and biogenic aerosol in the Arctic

Becagli, S.; Lazzara, L.; Marchese, C.; Dayan, U.; Ascanius, S. E.; Cacciani, M.; Caiazzo, L.; Di Biagio, C.; Di Iorio, T.; di Sarra, A.; Eriksen, P.; Fani, F.; Giardi, F.; Meloni, D.; Muscari, G.; Pace, G.; Severi, M.; Traversi, R.; Udisti, R.

2016-07-01

This study examines the relationships linking methanesulfonic acid (MSA, arising from the atmospheric oxidation of the biogenic dimethylsulfide, DMS) in atmospheric aerosol, satellite-derived chlorophyll a (Chl-a), and oceanic primary production (PP), also as a function of sea ice melting (SIM) and extension of the ice free area in the marginal ice zone (IF-MIZ) in the Arctic. MSA was determined in PM10 samples collected over the period 2010-2012 at two Arctic sites, Ny Ålesund (78.9°N, 11.9°E), Svalbard islands, and Thule Air Base (76.5°N, 68.8°W), Greenland. PP is calculated by means of a bio-optical, physiologically based, semi-analytical model in the potential source areas located in the surrounding oceanic regions (Barents and Greenland Seas for Ny Ålesund, and Baffin Bay for Thule). Chl-a peaks in May in the Barents sea and in the Baffin Bay, and has maxima in June in the Greenland sea; PP follows the same seasonal pattern of Chl-a, although the differences in absolute values of PP in the three seas during the blooms are less marked than for Chl-a. MSA shows a better correlation with PP than with Chl-a, besides, the source intensity (expressed by PP) is able to explain more than 30% of the MSA variability at the two sites; the other factors explaining the MSA variability are taxonomic differences in the phytoplanktonic assemblages, and transport processes from the DMS source areas to the sampling sites. The taxonomic differences are also evident from the slopes of the correlation plots between MSA and PP: similar slopes (in the range 34.2-36.2 ng m-3of MSA/(gC m-2 d-1)) are found for the correlation between MSA at Ny Ålesund and PP in Barents Sea, and between MSA at Thule and PP in the Baffin Bay; conversely, the slope of the correlation between MSA at Ny Ålesund and PP in the Greenland Sea in summer is smaller (16.7 ng m-3of MSA/(gC m-2 d-1)). This is due to the fact that DMS emission from the Barents Sea and Baffin Bay is mainly related to the MIZ

12. Biological and physical processes influencing sea ice, under-ice algae, and dimethylsulfoniopropionate during spring in the Canadian Arctic Archipelago

Galindo, V.; Levasseur, M.; Mundy, C. J.; Gosselin, M.; Tremblay, J.-É.; Scarratt, M.; Gratton, Y.; Papakiriakou, T.; Poulin, M.; Lizotte, M.

2014-06-01

This study presents temporal variations in concentrations of chlorophyll a (Chl a), particulate and dissolved dimethylsulfoniopropionate (DMSPp and DMSPd) in the sea ice and underlying water column in the Canadian Arctic Archipelago during the spring of 2010 and 2011. During both years, bottom ice Chl a, DMSPp and DMSPd concentrations were high (up to 1328 µg L-1, 15,082 nmol L-1, and 6110 nmol L-1, respectively) in May and decreased thereafter. The release of bottom ice algae and DMSPp in the water column was gradual in 2010 and rapid (8 days) in 2011. Bottom brine drainage during the presnowmelt period in 2010 and a rapid loss of the snow cover in 2011 coinciding with rain events explain most of the difference between the 2 years. During both years, less than 13% of the DMSPd lost from the ice was detected in the water column, suggesting a rapid microbial consumption. An under-ice diatom bloom developed in both years. In 2010, the bloom was dominated by centric diatoms while in 2011 pennates dominated, likely reflecting seeding by ice algae following the faster snowmelt progression induced by rainfall events in 2011. Both under-ice blooms were associated with high DMSPp concentrations (up to 185 nmol L-1), but pennate diatoms showed DMSPp/Chl a ratios twice higher than centrics. These results highlight the key role of snowmelt and precipitation on the temporal pattern of ice-DMSP release to the water column and on the timing, taxonomic composition, and DMSP content of phytoplankton under-ice blooms in the Arctic.

13. Variability of scaling time series in the Arctic sea-ice drift dynamics

A. Chmel

2010-02-01

Full Text Available The motion of an individual ice floe in the Arctic Ocean was monitored at the Russian research station North Pole 35 established on the ice pack in 2008. The ice floe speed (V was found to be correlated with wind speed (v in main features, such as the positions of maxima and minima of V and v. However, the fine structure of the V-variation cannot be explained by the wind forcing alone. There were periods of time when the floe drift was affected by the interactions of ice floes between each other or by the periodical forcing due to either the Coriolis inertia effect or the tidal activity. These data were compared with the "waiting times" statistics that are the distributions of time intervals between subsequent, sufficiently strong changes in the kinetic energy of drifting ice floe. These distributions were measured in several time windows differing in the average wind speed and wind direction, and/or in the mechanical state of the ice pack. The distribution functions N (t>τ, where N is the number of successive events of energy change separated by the time interval t that exceeds τ, constructed in different time windows demonstrate fractal or a multifractal nature of the time series during motion in the consolidated ice pack but were truly random when the ice floe drifted in the highly fragmented sea ice. The latter result shows the existence of a relationship between the long-range mechanical interactions in the pack and long-term memory (time scaling behaviour of the sea-ice motion.

14. Fluctuating Arctic Sea ice thickness changes estimated by an in situ learned and empirically forced neural network model

Belchansky, G.I.; Douglas, D.C.; Platonov, N.G.

2008-01-01

Sea ice thickness (SIT) is a key parameter of scientific interest because understanding the natural spatiotemporal variability of ice thickness is critical for improving global climate models. In this paper, changes in Arctic SIT during 1982-2003 are examined using a neural network (NN) algorithm trained with in situ submarine ice draft and surface drilling data. For each month of the study period, the NN individually estimated SIT of each ice-covered pixel (25-km resolution) based on seven geophysical parameters (four shortwave and longwave radiative fluxes, surface air temperature, ice drift velocity, and ice divergence/convergence) that were cumulatively summed at each monthly position along the pixel's previous 3-yr drift track (or less if the ice was <3 yr old). Average January SIT increased during 1982-88 in most regions of the Arctic (+7.6 ?? 0.9 cm yr-1), decreased through 1996 Arctic-wide (-6.1 ?? 1.2 cm yr-1), then modestly increased through 2003 mostly in the central Arctic (+2.1 ?? 0.6 cm yr-1). Net ice volume change in the Arctic Ocean from 1982 to 2003 was negligible, indicating that cumulative ice growth had largely replaced the estimated 45 000 km3 of ice lost by cumulative export. Above 65??N, total annual ice volume and interannual volume changes were correlated with the Arctic Oscillation (AO) at decadal and annual time scales, respectively. Late-summer ice thickness and total volume varied proportionally until the mid-1990s, but volume did not increase commensurate with the thickening during 1996-2002. The authors speculate that decoupling of the ice thickness-volume relationship resulted from two opposing mechanisms with different latitudinal expressions: a recent quasi-decadal shift in atmospheric circulation patterns associated with the AO's neutral state facilitated ice thickening at high latitudes while anomalously warm thermal forcing thinned and melted the ice cap at its periphery. ?? 2008 American Meteorological Society.

15. Recent ice cap snowmelt in Russian High Arctic and anti-correlation with late summer sea ice extent

Glacier surface melt dynamics throughout Novaya Zemlya (NovZ) and Severnaya Zemlya (SevZ) serve as a good indicator of ice mass ablation and regional climate change in the Russian High Arctic. Here we report trends of surface melt onset date (MOD) and total melt days (TMD) by combining multiple resolution-enhanced active and passive microwave satellite datasets and analyze the TMD correlations with local temperature and regional sea ice extent. The glacier surface snowpack on SevZ melted significantly earlier (−7.3 days/decade) from 1992 to 2012 and significantly longer (7.7 days/decade) from 1995 to 2011. NovZ experienced large interannual variability in MOD, but its annual mean TMD increased. The snowpack melt on NovZ is more sensitive to temperature fluctuations than SevZ in recent decades. After ruling out the regional temperature influence using partial correlation analysis, the TMD on both archipelagoes is statistically anti-correlated with regional late summer sea ice extent, linking land ice snowmelt dynamics to regional sea ice extent variations. (letter)

16. Using records from submarine, aircraft and satellite to evaluate climate model simulations of Arctic sea ice thickness

J. Stroeve

2014-04-01

Full Text Available Arctic sea ice thickness distributions from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 are evaluated against observations from submarines, aircraft and satellites. While it's encouraging that the mean thickness distributions from the models are in general agreement with observations, the spatial patterns of sea ice thickness are poorly represented in most models. The poor spatial representation of thickness patterns is associated with a failure of models to represent details of the mean atmospheric circulation pattern that governs the transport and spatial distribution of sea ice. The climate models as a whole also tend to underestimate the rate of ice volume loss from 1979 to 2013, though the multi-model ensemble mean trend remains within the uncertainty of that from the Pan-Arctic Ice Ocean Modeling and Assimilation System. These results raise concerns regarding the ability of CMIP5 models to realistically represent the processes driving the decline of Arctic sea ice and project the timing of when a seasonally ice-free Arctic may be realized.

17. Wind-driven interannual variability of sea ice algal production over the western Arctic Chukchi Borderland

E. Watanabe

2015-05-01

Full Text Available Seasonal and interannual variability in sinking flux of biogenic particles was reported by the multi-year bottom-tethered sediment trap measurements in the Northwind Abyssal Plain (Station NAP: 75° N, 162° W, 1975 m water depth of the western Arctic Chukchi Borderland. Whereas the trapped particle flux had an obvious peak with the dominance of sea ice-related diatom valve in August 2011, the observed particle flux was considerably suppressed throughout the summer season in 2012. In the present study, response of ice algal production and biomass to wind-driven changes in physical environments was addressed using a pan-Arctic sea ice–ocean modeling approach. Sea ice ecosystem with ice algae was newly incorporated into the lower-trophic marine ecosystem model, which was previously coupled with a high-resolution (i.e., horizontal grid size of 5 km ocean general circulation model. Seasonal experiments covering two year-long mooring periods indicated that primary productivity of ice algae around the Chukchi Borderland depended on basin-scale wind pattern through various processes. Easterly wind in the southern part of distinct Beaufort High supplied high abundance of nutrient for euphotic zones of the NAP region via both surface Ekman transport of Chukchi shelf water and vertical turbulent mixing with underlying nutricline water as in 2011. In contrast, northwesterly wind flowing in the northern part of extended Siberian High transported oligotrophic water within the Beaufort Gyre circulation toward the NAP region as in 2012. The modeled ice algal biomass during the summer season certainly reflected the differences in nutrient distribution. The sinking flux of Particulate Organic Nitrogen (PON was comparable with the time series obtained from the sediment trap data in summer 2011. On the other hand, lateral advection of shelf-origin ice algal patch during a great cyclone event might have caused a model bias on the PON flux in 2012. The extension

18. Rising sea surface temperature: towards ice-free Arctic summers and a changing marine food chain Document Actions

Coppini, Giovanni; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Bologna, Bologna, Italia; Christiansen, Trine; European Environment Agency

2009-01-01

Global sea surface temperature is approximately 1 degree C higher now than 140 years ago, and is one of the primary physical impacts of climate change. Sea surface temperature in European seas is increasing more rapidly than in the global oceans. Projections show the temperature increases will persist throughout this century. Ice-free summers are expected in the Arctic by the end of this century, if not earlier. Already, there is evidence that many marine ecosystems in European seas are affec...

19. Ikaite crystals in melting sea ice - implications for pCO(2) and pH levels in Arctic surface waters

Rysgaard, Søren; Glud, Ronnie N.; Lennert, K.;

2012-01-01

A major issue of Arctic marine science is to understand whether the Arctic Ocean is, or will be, a source or sink for air-sea CO2 exchange. This has been complicated by the recent discoveries of ikaite (a polymorph of CaCO3 center dot 6H(2)O) in Arctic and Antarctic sea ice, which indicate that m...

20. Ikaite crystals in melting sea ice – implications for pCO2 and pH levels in Arctic surface waters

Rysgaard, Søren; Glud, R.N.; Lennert, K.;

2012-01-01

A major issue of Arctic marine science is to understand whether the Arctic Ocean is, or will be, a source or sink for air-sea CO 2 exchange. This has been complicated by the recent discoveries of ikaite (a polymorph of CaCO 3•6H 2O) in Arctic and Antarctic sea ice, which indicate that multiple ch...

1. Arctic Ocean gravity, geoid and sea-ice freeboard heights from ICESat and GRACE

Forsberg, René; Skourup, Henriette

2005-01-01

coverage of multi-year sea-ice; however, comparison to an airborne lidar underflight north of Greenland shows that the lowest-level filtering scheme may introduce a bias. We finally use the ICESat and GRACE results to derive new gravity anomalies by Fourier inversion. The satellite-only gravity field shows...... all major tectonic features of the Arctic Ocean, and has an accuracy of 6 mGal compared to recent airborne gravity data, illustrating the usefulness of ICESat data for gravity field determination....

2. A closer investigation of associations between Autumn Arctic sea ice and central and east Eurasian winter climate

Wang, Shaoyin; Liu, Jiping

2016-04-01

Whether recent Arctic sea ice loss is responsible for recent severe winters over mid-latitude continents has emerged as a major debate among climate scientists owing to short records of observations and large internal variability in mid- and high-latitudes. In this study, we divide the evolution of autumn Arctic sea ice extent during 1979-2014 into three epochs, 1979-1986 (high), 1987-2006 (moderate) and 2007-2014 (low), using a regime shift identification method. We then compare the associations between autumn Arctic sea ice and winter climate anomalies over central and eastern Eurasia for the three epochs with focus not only on the mean state, but also the extreme events. The results show robust and detectable signals of sea ice loss in weather and climate over western Siberia and East Asia. For the mean state, anomalous low sea ice extent is associated with a strengthening of the Siberian high pressure, a weakening of westerly winds over north Asia, leading to cold anomalies in central Asia and northern China. For the extreme events, the latitude (speed) of the jet stream shifts southward (reduces), the wave extent amplifies, blocking high events increase over Ural Mountains, leading to increased frequency of cold air outbreaks extending from central Asia to northeast China. These associations bear a high degree of similarity to the observed atmospheric anomalies during the low sea ice epoch. By contrast, the patterns of atmospheric anomalies for the high sea ice epoch are different from those congruent with sea ice variability, which is related to the persistent negative phase of the Arctic Oscillation. We also found that the ENSO plays a minor role in the determination of the observed atmospheric anomalies for the three epochs. Support for these observational analysis is largely corroborated by independent atmospheric model simulations.

3. Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness

J. Stroeve; Barrett, A; Serreze, M.; Schweiger, A

2014-01-01

Arctic sea ice thickness distributions from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5) are evaluated against observations from submarines, aircraft and satellites. While it is encouraging that the mean thickness distributions from the models are in general agreement with observations, the spatial patterns of sea ice thickness are poorly represented in most models. The poor spatial representation of thick...

4. Archival and Analysis of Sea Ice Thickness in the Arctic Ocean Based on On-Ice In Situ Historical Measurements

Holt, B.; Melocik, K.

2009-12-01

A largely unexplored sea ice data record consists of in situ thickness measurements derived from drill holes, cores, gauges, thermistor strings, and surface electromagnetic induction. By compiling these often disparate and scattered but generally highly accurate measurements into a single database, a long-term record is being developed, that will expand and extend in time and space the thickness record obtained from the submarine ice draft record as well as the developing satellite, helicopter EM, and sonar and mass balance buoys measurements. From journal articles, reports, on-line databases, and direct contact with sea ice investigators, we assembled measurements from many types of expeditions, large and small, with the earliest data so far from 1928 to the most recent from 2007. Many of the field expeditions are in regions outside of the central Arctic region that submarines are able to sample, thereby expanding the spatial extent of the sea ice record. We will discuss the preliminary analysis of these records, as a means to improving the understanding of thickness changes in relation to climate change.

5. Improvement in Simulation of Eurasian Winter Climate Variability with a Realistic Arctic Sea Ice Condition in an Atmospheric GCM

Lim, Young-Kwon; Ham, Yoo-Geun; Jeong, Jee-Hoon; Kug, Jong-Seong

2012-01-01

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988-2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI). Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to approx. 0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated.

6. Improvement in simulation of Eurasian winter climate variability with a realistic Arctic sea ice condition in an atmospheric GCM

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988–2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI). Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to ∼0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated. (letter)

7. Impact of rapid sea-ice reduction in the Arctic Ocean on the rate of ocean acidification

A. Yamamoto

2011-10-01

Full Text Available The largest pH decline and widespread undersaturation with respect to aragonite in this century due to uptake of anthropogenic carbon dioxide in the Arctic Ocean have been projected. The reductions in pH and aragonite saturation state have been caused primarily by an increase in the concentration of atmospheric carbon dioxide. However, in a previous study, simulations with and without warming showed that these reductions in the Arctic Ocean also advances due to the melting of sea ice caused by global warming. Therefore, future projections of pH and aragonite saturation in the Arctic Ocean will be affected by how rapidly the reduction in sea ice occurs. In this study, the impact of sea-ice reduction rate on projected pH and aragonite saturation state in the Arctic surface waters was investigated. Reductions in pH and aragonite saturation were calculated from the outputs of two versions of an earth system model (ESM with different sea-ice reduction rates under similar CO2 emission scenarios. The newer model version projects that Arctic summer ice-free condition will be achieved by the year 2040, and the older version predicts ice-free condition by 2090. The Arctic surface water was projected to be undersaturated with respect to aragonite in the annual mean when atmospheric CO2 concentration reached 480 (550 ppm in year 2040 (2048 in new (old version. At an atmospheric CO2 concentration of 520 ppm, the maximum differences in pH and aragonite saturation state between the two versions were 0.08 and 0.15, respectively. The analysis showed that the decreases in pH and aragonite saturation state due to rapid sea-ice reduction were caused by increases in both CO2 uptake and freshwater input. Thus, the reductions in pH and aragonite saturation state in the Arctic surface waters are significantly affected by the difference in future projections for sea-ice reduction rate. The critical CO2 concentration

8. Arctic sea-ice melting: Effects on hydroclimatic variability and on UV-induced carbon cycling

Sulzberger, Barbara

2016-04-01

Since 1980 both the perennial and the multiyear central Arctic sea ice areas have declined by approximately 13 and 15% per decade, respectively (IPCC, 2013). Arctic sea-ice melting has led to an increase in the amplitude of the Northern Hemisphere jet stream and, as a consequence, in more slowly moving Rossby waves which results in blocking of weather patterns such as heat waves, droughts, cold spells, and heavy precipitation events (Francis and Vavrus, 2012). Changing Rossby waves account for more than 30% of the precipitation variability over several regions of the northern middle and high latitudes, including the US northern Great Plains and parts of Canada, Europe, and Russia (Schubert et al., 2011). From 2007 to 2013, northern Europe experienced heavy summer precipitation events that were unprecedented in over a century, concomitant with Arctic sea ice loss (Screen, 2013). Heavy precipitation events tend to increase the runoff intensity of terrigenous dissolved organic matter (tDOM) (Haaland et al., 2010). In surface waters tDOM is subject to UV-induced oxidation to produce atmospheric CO2. Mineralization of DOM also occurs via microbial respiration. However, not all chemical forms of DOM are available to bacterioplankton. UV-induced transformations generally increase the bioavailability of tDOM (Sulzberger and Durisch-Kaiser, 2009). Mineralization of tDOM is an important source of atmospheric CO2 and this process is likely to contribute to positive feedbacks on global warming (Erickson et al., 2015). However, the magnitudes of these potential feedbacks remain unexplored. This paper will discuss the following items: 1.) Links between Arctic sea-ice melting, heavy precipitation events, and enhanced tDOM runoff. 2.) UV-induced increase in the bioavailability of tDOM. 3.) UV-mediated feedbacks on global warming. References Erickson, D. J. III, B. Sulzberger, R. G. Zepp, A. T. Austin (2015), Effects of stratospheric ozone depletion, solar UV radiation, and climate

9. Could massive Arctic sea ice export to the North Atlantic be the real cause of abrupt climate change during the last deglaciation?

Coletti, A. J.; Condron, A.

2015-12-01

Using a coupled ocean-sea ice model (MITgcm), we investigate whether the break-up and mobilization of thick, multiyear, Arctic sea ice might have supplied enough freshwater to the Nordic Seas to reduce North Atlantic Deep Water (NADW) formation and weaken the Atlantic Meridional Overturning Circulation (AMOC). Numerical simulations of a Last Glacial Maximum (LGM) environment show the potential for sea ice to grow to ~30m thick, storing ~1.41x105 km3 of freshwater as sea ice in the Arctic (this is ~10 times the volume of freshwater stored in the modern-day Arctic). Releasing this volume of sea ice from the Arctic in 1-yr is equivalent to a high-latitude freshwater forcing of ~4.5 Sv, which is comparable (or larger) in magnitude to most meltwater floods emanating from land-based glacial lakes (e.g. Agassiz) during the last deglaciation. Opening of the Bering Strait and Barents Sea are two plausible mechanisms that may have initiated sea ice mobilization. Opening Bering Strait increases sea ice transport through the Fram Strait by 7% and results in a 22% weakening of AMOC for 2000 years and a >3°C warming in the Arctic basin at 800 m depth. Opening Barents Sea to simulate a collapse of the Fennoscandian ice sheet has little impact on Arctic sea ice and freshwater export to the North Atlantic, but weakens AMOC ~8%. In a simulation with both straits open there is a transition to near-modern sea ice circulation pattern and a 24% reduction in AMOC. Experiments with the Bering Strait open and sea ice artificially capped to 10 m show barely any difference to those when sea ice can grow to ~30m, suggesting that changes in topography have a much greater impact on AMOC than the freshwater forcing from sea ice melting in the Nordic Seas.

10. Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation

Ricker, R.; Hendricks, S.; V. Helm; H. Skourup; M. Davidson

2014-01-01

In the context of quantifying Arctic ice-volume decrease at global scale, the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku band synthetic aperture radar altimeter SIRAL (Synthetic Aperture Interferometric Radar Altimeter), which we use to derive sea-ice freeboard defined as the height of the ice surface above the sea level. Accurate CryoSat-2 range measurements over open water and the ice surface of the order of centimetres are necessary to achieve...
{"extraction_info": {"found_math": true, "script_math_tex": 0, "script_math_asciimath": 0, "math_annotations": 0, "math_alttext": 0, "mathml": 0, "mathjax_tag": 0, "mathjax_inline_tex": 1, "mathjax_display_tex": 0, "mathjax_asciimath": 0, "img_math": 0, "codecogs_latex": 0, "wp_latex": 0, "mimetex.cgi": 0, "/images/math/codecogs": 0, "mathtex.cgi": 0, "katex": 0, "math-container": 0, "wp-katex-eq": 0, "align": 0, "equation": 0, "x-ck12": 0, "texerror": 0, "math_score": 0.734341025352478, "perplexity": 4147.844188190565}, "config": {"markdown_headings": false, "markdown_code": true, "boilerplate_config": {"ratio_threshold": 0.18, "absolute_threshold": 10, "end_threshold": 15, "enable": true}, "remove_buttons": true, "remove_image_figures": true, "remove_link_clusters": true, "table_config": {"min_rows": 2, "min_cols": 3, "format": "plain"}, "remove_chinese": true, "remove_edit_buttons": true, "extract_latex": true}, "warc_path": "s3://commoncrawl/crawl-data/CC-MAIN-2016-44/segments/1476988720845.92/warc/CC-MAIN-20161020183840-00056-ip-10-171-6-4.ec2.internal.warc.gz"}