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- Author or Editor: James Maslanik x
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Abstract
Analysis of weekly sea ice charts produced by the U.S. National Ice Center from 1976 to 2007 indicates large interannual variations in the averaged winter landfast ice extent around the Arctic Basin. During the 32-yr period of the record, landfast ice cover was relatively extensive from the early to mid-1980s but since then has declined in many coastal regions of the Arctic, particularly after the early 1990s. While the Barents, Baltic, and Bering Seas show increases in landfast ice area, the overall change for the Northern Hemisphere is negative, about −12.27 (±2.8) × 103 km2 yr−1, or −7 (±1.5)% decade−1 relative to the long-term mean. Except in a few coastal regions, the seasonal duration of landfast ice is shorter overall, particularly in the Laptev, East Siberian, and Chukchi Seas. The decreased winter landfast ice extent is associated with some notable changes in ice growth and melt patterns, in particular the slowed landfast ice expansion during fall and early winter since 1990. The observed changes in Arctic landfast ice could have profound impacts on the Arctic coasts. The challenge is to understand and project the responses of the whole coastal ecosystem to changing ice cover and Arctic warming.
Abstract
Analysis of weekly sea ice charts produced by the U.S. National Ice Center from 1976 to 2007 indicates large interannual variations in the averaged winter landfast ice extent around the Arctic Basin. During the 32-yr period of the record, landfast ice cover was relatively extensive from the early to mid-1980s but since then has declined in many coastal regions of the Arctic, particularly after the early 1990s. While the Barents, Baltic, and Bering Seas show increases in landfast ice area, the overall change for the Northern Hemisphere is negative, about −12.27 (±2.8) × 103 km2 yr−1, or −7 (±1.5)% decade−1 relative to the long-term mean. Except in a few coastal regions, the seasonal duration of landfast ice is shorter overall, particularly in the Laptev, East Siberian, and Chukchi Seas. The decreased winter landfast ice extent is associated with some notable changes in ice growth and melt patterns, in particular the slowed landfast ice expansion during fall and early winter since 1990. The observed changes in Arctic landfast ice could have profound impacts on the Arctic coasts. The challenge is to understand and project the responses of the whole coastal ecosystem to changing ice cover and Arctic warming.
Abstract
Measurements from the Russian “North Pole” series of drifting stations, the United States drifting stations“T-3” and “Arlis II,” land stations, and, where necessary, over the northern North Atlantic and coastal Greenland, empirically derived values from earlier Russian studies are used to compile a new gridded monthly climatology of global (downwelling shortwave) radiation for the region north of 65°N. Spatio-temporal patterns of fluxes and effective cloud transmittance are examined and comparisons are made with fields from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and those derived from the International Satellite Cloud Climatology Project (ISCCP) C2 (monthly) cloud product.
All months examined (March–October) show peak fluxes over the Greenland ice sheet. March, September, and October feature a strong zonal component. Other months exhibit an asymmetric pattern related to cloud fraction and optical depth, manifested by an Atlantic side flux minimum. For June, the month of maximum insolation, fluxes increase from less than 200 W m−2 in the Norwegian and Barents seas to more than 300 W m−2 over the Pacific side of central Arctic Ocean extending into the Beaufort Sea. June fluxes of more than 340 W m−2 are found over the Greenland ice sheet. Effective cloud transmittance, taken as the ratio of the observed flux to the modeled clear sky flux, is examined for April–September. Values for the Atlantic sector range from 0.50–0.60, contrasting with the central Arctic Ocean where values peak in April at 0.75–0.80, falling to 0.60–0.65 during late summer and early autumn. A relative Beaufort Sea maximum is well expressed during June. The NCEP–NCAR and ISCCP products capture 50%–60% of the observed spatial variance in global radiation during most months. However, the NCEP–NCAR fluxes are consistently high, with Arctic Ocean errors in excess of 60 W m−2 during summer, reflecting problems in modeled cloud cover. ISCCP fluxes compare better in terms of magnitude.
Abstract
Measurements from the Russian “North Pole” series of drifting stations, the United States drifting stations“T-3” and “Arlis II,” land stations, and, where necessary, over the northern North Atlantic and coastal Greenland, empirically derived values from earlier Russian studies are used to compile a new gridded monthly climatology of global (downwelling shortwave) radiation for the region north of 65°N. Spatio-temporal patterns of fluxes and effective cloud transmittance are examined and comparisons are made with fields from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis and those derived from the International Satellite Cloud Climatology Project (ISCCP) C2 (monthly) cloud product.
All months examined (March–October) show peak fluxes over the Greenland ice sheet. March, September, and October feature a strong zonal component. Other months exhibit an asymmetric pattern related to cloud fraction and optical depth, manifested by an Atlantic side flux minimum. For June, the month of maximum insolation, fluxes increase from less than 200 W m−2 in the Norwegian and Barents seas to more than 300 W m−2 over the Pacific side of central Arctic Ocean extending into the Beaufort Sea. June fluxes of more than 340 W m−2 are found over the Greenland ice sheet. Effective cloud transmittance, taken as the ratio of the observed flux to the modeled clear sky flux, is examined for April–September. Values for the Atlantic sector range from 0.50–0.60, contrasting with the central Arctic Ocean where values peak in April at 0.75–0.80, falling to 0.60–0.65 during late summer and early autumn. A relative Beaufort Sea maximum is well expressed during June. The NCEP–NCAR and ISCCP products capture 50%–60% of the observed spatial variance in global radiation during most months. However, the NCEP–NCAR fluxes are consistently high, with Arctic Ocean errors in excess of 60 W m−2 during summer, reflecting problems in modeled cloud cover. ISCCP fluxes compare better in terms of magnitude.
Abstract
The Climate System Model (CSM) consists of atmosphere, ocean, land, and sea-ice components linked by a flux coupler, which computes fluxes of energy and momentum between components. The sea-ice component consists of a thermodynamic formulation for ice, snow, and leads within the ice pack, and ice dynamics using the cavitating-fluid ice rheology, which allows for the compressive strength of ice but ignores shear viscosity.
The results of a 300-yr climate simulation are presented, with the focus on sea ice and the atmospheric forcing over sea ice in the polar regions. The atmospheric model results are compared to analyses from the European Centre for Medium-Range Weather Forecasts and other observational sources. The sea-ice concentrations and velocities are compared to satellite observational data.
The atmospheric sea level pressure (SLP) in CSM exhibits a high in the central Arctic displaced poleward from the observed Beaufort high. The Southern Hemisphere SLP over sea ice is generally 5 mb lower than observed. Air temperatures over sea ice in both hemispheres exhibit cold biases of 2–4 K. The precipitation-minus-evaporation fields in both hemispheres are greatly improved over those from earlier versions of the atmospheric GCM.
The simulated ice-covered area is close to observations in the Southern Hemisphere but too large in the Northern Hemisphere. The ice concentration fields show that the ice cover is too extensive in the North Pacific and subarctic North Atlantic Oceans. The interannual variability of the ice area is similar to observations in both hemispheres. The ice thickness pattern in the Antarctic is realistic but generally too thin away from the continent. The maximum thickness in the Arctic occurs against the Bering Strait, not against the Canadian Archipelago as observed. The ice velocities are stronger than observed in both hemispheres, with a consistently greater turning angle (to the left) in the Southern Hemisphere. They produce a northward ice transport in the Southern Hemisphere that is 3–4 times the satellite-derived value. Sensitivity tests with the sea-ice component show that both the pattern of wind forcing in CSM and the air-ice drag parameter used contribute to the biases in thickness, drift speeds, and transport. Plans for further development of the ice model to incorporate a viscous-plastic ice rheology are presented.
In spite of the biases of the sea-ice simulation, the 300-yr climate simulation exhibits only a small degree of drift in the surface climate without the use of flux adjustment. This suggests a robust stability in the simulated climate in the presence of significant variability.
Abstract
The Climate System Model (CSM) consists of atmosphere, ocean, land, and sea-ice components linked by a flux coupler, which computes fluxes of energy and momentum between components. The sea-ice component consists of a thermodynamic formulation for ice, snow, and leads within the ice pack, and ice dynamics using the cavitating-fluid ice rheology, which allows for the compressive strength of ice but ignores shear viscosity.
The results of a 300-yr climate simulation are presented, with the focus on sea ice and the atmospheric forcing over sea ice in the polar regions. The atmospheric model results are compared to analyses from the European Centre for Medium-Range Weather Forecasts and other observational sources. The sea-ice concentrations and velocities are compared to satellite observational data.
The atmospheric sea level pressure (SLP) in CSM exhibits a high in the central Arctic displaced poleward from the observed Beaufort high. The Southern Hemisphere SLP over sea ice is generally 5 mb lower than observed. Air temperatures over sea ice in both hemispheres exhibit cold biases of 2–4 K. The precipitation-minus-evaporation fields in both hemispheres are greatly improved over those from earlier versions of the atmospheric GCM.
The simulated ice-covered area is close to observations in the Southern Hemisphere but too large in the Northern Hemisphere. The ice concentration fields show that the ice cover is too extensive in the North Pacific and subarctic North Atlantic Oceans. The interannual variability of the ice area is similar to observations in both hemispheres. The ice thickness pattern in the Antarctic is realistic but generally too thin away from the continent. The maximum thickness in the Arctic occurs against the Bering Strait, not against the Canadian Archipelago as observed. The ice velocities are stronger than observed in both hemispheres, with a consistently greater turning angle (to the left) in the Southern Hemisphere. They produce a northward ice transport in the Southern Hemisphere that is 3–4 times the satellite-derived value. Sensitivity tests with the sea-ice component show that both the pattern of wind forcing in CSM and the air-ice drag parameter used contribute to the biases in thickness, drift speeds, and transport. Plans for further development of the ice model to incorporate a viscous-plastic ice rheology are presented.
In spite of the biases of the sea-ice simulation, the 300-yr climate simulation exhibits only a small degree of drift in the surface climate without the use of flux adjustment. This suggests a robust stability in the simulated climate in the presence of significant variability.
Abstract
To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.
Abstract
To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.
