The objective of this project is to identify programs and research and development projects that improve the ability of responders to deal with accidental oil spills in fresh or salt-water marine environments where there is ice. This includes spills that occur on top of or underneath solid, stable ice extending out from shore (land-fast), into an area of drifting ice floes (pack ice), or onto an ice-covered shoreline.
This report summarizes conclusions reached by experts that met in 2004 to discuss Arctic marine transport, international marine safety, sea ice and climate change. The report includes a research agenda and identifies critical issues relevant to the future of Arctic shipping.
Since the 1950s, nuclear weapon testing and releases from the nuclear industry have introduced anthropogenic radionuclides into the sea, and in many instances their ultimate fate are the bottom sediments. The Arctic Ocean is one of the most polluted in this respect, because, in addition to global fallout, it is impacted by regional fallout from nuclear weapon testing, and indirectly by releases from nuclear reprocessing facilities and nuclear accidents. Sea-ice formed in the shallow continental shelves incorporate sediments with variable concentrations of anthropogenic radionuclides that are transported through the Arctic Ocean and are finally released in the melting areas. In this work, we present the results of anthropogenic radionuclide analyses of sea-ice sediments (SIS) collected on five cruises from different Arctic regions and combine them with a database including prior measurements of these radionuclides in SIS. The distribution of (137)Cs and (239,240)Pu activities and the (240)Pu/(239)Pu atom ratio in SIS showed geographical differences, in agreement with the two main sea ice drift patterns derived from the mean field of sea-ice motion, the Transpolar Drift and Beaufort Gyre, with the Fram Strait as the main ablation area. A direct comparison of data measured in SIS samples against those reported for the potential source regions permits identification of the regions from which sea ice incorporates sediments. The (240)Pu/(239)Pu atom ratio in SIS may be used to discern the origin of sea ice from the Kara-Laptev Sea and the Alaskan shelf. However, if the (240)Pu/(239)Pu atom ratio is similar to global fallout, it does not provide a unique diagnostic indicator of the source area, and in such cases, the source of SIS can be constrained with a combination of the (137)Cs and (239,240)Pu activities. Therefore, these anthropogenic radionuclides can be used in many instances to determine the geographical source area of sea-ice.
The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades—a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B ‘business as usual’ scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979–2008 satellite record of ice extent and seasonality.
At the end of the 21st century (2090–2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement among models. High agreement also accompanies projections that the Chukchi Sea will be completely ice covered during February, March, and April at the end of the century. Large uncertainties, however, are associated with the timing and amount of partial ice cover during the intervening periods of melt and freeze. For the Bering Sea, median March ice extent is projected to be about 25 percent less than the 1979–1988 average by mid-century and 60 percent less by the end of the century. The ice-free season in the Bering Sea is projected to increase from its contemporary average of 5.5 months to a median of about 8.5 months by the end of the century. A 3-month longer ice- free season in the Bering Sea is attained by a 1-month advance in melt and a 2-month delay in freeze, meaning the ice edge typically will pass through the Bering Strait in May and January at the end of the century rather than June and November as presently observed.
The minimum of Arctic sea ice extent in the summer of 2007 was unprecedented in the historical record. A coupled ice-ocean model is used to determine the state of the ice and ocean over the past 29 years to investigate the causes of this ice extent minimum within a historical perspective. It is found that even though the 2007 ice extent was strongly anomalous, the loss in total ice mass was not. Rather, the 2007 ice mass loss is largely consistent with a steady decrease in ice thickness that began in 1987. Since then, the simulated mean September ice thickness within the Arctic Ocean has declined from 3.7 to 2.6 m at a rate of -0.57 m/decade. Both the area coverage of thin ice at the beginning of the melt season and the total volume of ice lost in the summer have been steadily increasing. The combined impact of these two trends caused a large reduction in the September mean ice concentration in the Arctic Ocean. This created conditions during the summer of 2007 that allowed persistent winds to push the remaining ice from the Pacific side to the Atlantic side of the basin and more than usual into the Greenland Sea. This exposed large areas of open water, resulting in the record ice extent anomaly.
Background: Over the past century, the air and water temperatures in Alaska have warmed considerably faster than in the rest of the United States. Because Alaska is the only Arctic state in the Nation, Alaskans are likely to face some climate change challenges that will be different
than those encountered in other states. For example, permafrost currently underlies 80% of Alaska and provides a stable foundation for the physical infrastructure of many Alaska communities. As has already been seen in numerous villages, the groundcover that overlies permafrost is vulnerable to sinking or caving if the permafrost thaws, resulting in costly damage to physical infrastructure. The reliance on subsistence resources is another contrast to many other states. Many Alaskans depend upon subsistence harvests of fish and wildlife resources for food and to
support their way of life. Some Alaskans report that the changing environment has already impacted their traditional practices.
Many past efforts to characterize the potential impacts of climate change in Alaska have focused primarily on describing expected changes to the physical environment and the ecosystem, and less on
describing how these changes, in addition to changes in animal and environmental health, could affect human health. Thus, a careful analysis of how climate change could affect the health of people living in Alaska is warranted. The Alaska Division of Public Health has conducted such an assessment using the Health Impact Assessment (HIA) framework; the assessment is based on the current National Climate Assessment (NCA) predictions for Alaska.
The document is intended to provide a broad overview of the potential adverse human health impacts of climate change in Alaska and to present examples of adaptation strategies for communities to consider when planning their own response efforts. This document does not present a new model for climate change in Alaska, and it does not offer a critique of the NCA predictions for Alaska.
Low-level temperature inversions are a common feature of the wintertime troposphere in the Arctic and Antarctic. Inversion strength plays an important role in regulating atmospheric processes including air pollution, ozone destruction, cloud formation, and negative longwave feedback mechanisms that shape polar climate response to anthropogenic forcing. The Atmospheric Infrared Sounder (AIRS) instrument provides reliable measures of spatial patterns in mean wintertime inversion strength when compared with available radiosonde observations and reanalysis products. Here, we examine the influence of sea ice concentration on inversion strength in the Arctic and Antarctic. Correlation of inversion strength with mean annual sea ice concentration, likely a surrogate for the effective thermal conductivity of the wintertime ice pack, yields strong, linear relationships in the Arctic (r = 0.88) and Antarctic (r = 0.86). We find a substantially greater (stronger) linear relationship between sea ice concentration and surface air temperature than with temperature at 850 hPa, lending credence to the idea that sea ice controls inversion strength through modulation of surface heat fluxes. As such, declines in sea ice in either hemisphere may imply weaker mean inversions in the future. Comparison of mean inversion strength in AIRS and global climate models (GCMs) suggests that many GCMs poorly characterize mean inversion strength at high latitudes.