145 research outputs found

    Precipitation Modeling over the Greenland and Antarctic Ice Sheets and the Relationship to the Surface Mass Balance and Climate

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    Atmospheric numerical simulation and dynamic retrieval method with atmospheric numerical analyses are used to assess the spatial and temporal variability of Antarctic precipitation for the last two decades. First, the Polar MM5 has been run over Antarctica to study the Antarctic precipitation. With a horizontal resolution of 60km, the Polar MM5 has been run for the period of July 1996 through June 1999 in a series of short-term forecasts from initial and boundary conditions provided by the ECMWF operational analyses. In comparison with climatological maps, the major features of the spatial distribution of Antarctic precipitation are well captured by the Polar MM5. Drift snow effects on redistribution of surface accumulation over Antarctica are also assessed with surface wind fields from Polar MM5 in this study. There are complex divergence and convergence patterns of drift snow transport over Antarctica, especially along the coast. It is found that areas with large drift snow transport convergence and divergence are located around escarpment areas where there is large katabatic wind acceleration. In addition, areas with large snow transport divergence are generally accompanied by areas with large snow transport convergence nearby, indicating that drift snow transport is of local importance for the redistribution of the snowfal

    Large‐scale hydro‐climatology of the terrestrial Arctic drainage system

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    The large‐scale hydro‐climatology of the terrestrial Arctic drainage system is examined, focusing on the period 1960 onward. Special attention is paid to the Ob, Yenisey, Lena, and Mackenzie watersheds, which provide the bulk of freshwater discharge to the Arctic Ocean. Station data are used to compile monthly gridded time series of gauge‐corrected precipitation (P). Gridded time series of precipitation minus evapotranspiration (P−ET) are calculated from the moisture flux convergence using NCEP reanalysis data. Estimates of ET are obtained as a residual. Runoff (R) is obtained from available discharge records. For long‐term water‐year means, P−ET for the Yenisey, Lena, and Mackenzie watersheds is 16–20% lower than the observed runoff. In the Ob watershed, the two values agree within 9%. Given the uncertainties in P−ET, we consider the atmospheric and surface water budgets to be reasonably closed. Compared to the other three basins, the mean runoff ratio (R/P) is lower in the Ob watershed, consistent with the high fraction of annual precipitation lost through ET. All basins exhibit summer maxima in P and minima in P−ET. Summer P−ET in the Ob watershed is negative due to high ET rates. For large domains in northern Eurasia, about 25% of July precipitation is associated with the recycling of water vapor evapotranspirated within each domain. This points to a significant effect of the land surface on the hydrologic regime. Variability in P and P−ET has generally clear associations with the regional atmospheric circulation. A strong link with the Urals trough is documented for the Ob. Relationships with indices of the Arctic Oscillation and other teleconnections are generally weak. Water‐year time series of runoff and P−ET are strongly correlated in the Lena watershed only, reflecting extensive permafrost. Cold‐season runoff has increased in the Yenisey and Lena watersheds. This is most pronounced in the Yenisey watershed, where runoff has also increased sharply in spring, decreased in summer, but has increased for the year as a whole. The mechanisms for these changes are not entirely clear. While they fundamentally relate to higher air temperatures, increased winter precipitation, and strong summer drying, we speculate links with changes in active layer thickness and thawing permafrost

    Extreme Warming in the Kara Sea and Barents Sea during the Winter Period 2000–16

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    The regional climate model COSMOin Climate Limited-AreaMode (COSMO-CLM or CCLM) is used with a high resolution of 15km for the entire Arctic for all winters 2002/03–2014/15. The simulations show a high spatial and temporal variability of the recent 2-m air temperature increase in the Arctic. The maximum warming occurs north of Novaya Zemlya in the Kara Sea and Barents Sea between March 2003 and 2012 and is responsible for up to a 208C increase. Land-based observations confirm the increase but do not cover the maximum regions that are located over the ocean and sea ice.Also, the 30-km version of theArctic SystemReanalysis (ASR) is used to verify the CCLM for the overlapping time period 2002/03–2011/12. The differences between CCLM and ASR 2-m air temperatures vary slightly within 18C for the ocean and sea ice area. Thus,ASR captures the extreme warming as well. The monthly 2-m air temperatures of observations and ERA-Interim data show a large variability for the winters 1979–2016. Nevertheless, the air temperature rise since the beginning of the twenty-first century is up to 8 times higher than in the decades before. The sea ice decrease is identified as the likely reason for the warming. The vertical temperature profiles show that the warming has a maximum near the surface, but a 0.58Cyr21 increase is found up to 2 km. CCLM, ASR, and also the coarser resolved ERA-Interim data show that February and March are the months with the highest 2-m air temperature increases, averaged over the ocean and sea ice area north of 708N; for CCLM the warming amounts to an average of almost 58C for 2002/03–2011/12

    Modeled Antarctic Precipitation. Part I: Spatial and Temporal Variability*

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    Surface snow accumulation is the primary mass input to the Antarctic ice sheets. As the dominant term among various components of surface snow accumulation (precipitation, sublimation/deposition, and snow drift), pre-cipitation is of particular importance in helping to assess the mass balance of the Antarctic ice sheets and their contribution to global sea level change. The Polar MM5, a mesoscale atmospheric model based on the fifth-generation Pennsylvania State University– NCAR Mesoscale Model, has been run for the period of July 1996 through June 1999 to evaluate the spatial and temporal variability of Antarctic precipitation. Drift snow effects on the redistribution of surface snow over Antarctica are also assessed with surface wind fields from Polar MM5 in this study. It is found that areas with large drift snow transport convergence and divergence are located around escarpment areas where there is considerable katabatic wind acceleration. It is also found that the drift snow transport generally diverges over most areas of East and West Antarctica with relatively small values. The use of the dynamic retrieval method (DRM) to calculate precipitation has been developed and verified for the Greenland ice sheet. The DRM is also applied to retrieve the precipitation over Antarctica from 1979 to 1999 in this study. Most major features in the spatial distribution of Antarctic accumulation are well capture

    The Effect of Atmospheric Forcing Resolution on Delivery of Ocean Heat to the Antarctic Floating Ice Shelves

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    Oceanic melting at the base of the floating Antarctic ice shelves is now thought to be a more significant cause of mass loss for the Antarctic ice sheet than iceberg calving. In this study, a 10-km horizontal-resolution circum-Antarctic ocean–sea ice–ice shelf model [based on the Regional Ocean Modeling System (ROMS)] is used to study the delivery of ocean heat to the base of the ice shelves. The atmospheric forcing comes from the ERA-Interim reanalysis (;80-km resolution) and from simulations using the polar-optimized Weather Re- search and Forecasting Model (30-km resolution), where the upper atmosphere was relaxed to the ERA- Interim reanalysis. The modeled total basal ice shelf melt is low compared to observational estimates but increases by 14% with the higher-resolution winds and just 3% with both the higher-resolution winds and atmospheric surface temperatures. The higher-resolution winds lead to more heat being delivered to the ice shelf cavities from the adjacent ocean and an increase in the efficiency of heat transfer between the water and the ice. The higher-resolution winds also lead to changes in the heat delivered from the open ocean to the continental shelves as well as changes in the heat lost to the atmosphere over the shelves, and the sign of these changes varies regionally. Addition of the higher-resolution temperatures to the winds results in lowering, primarily during summer, the wind-driven increase in heat advected into the ice shelf cavities due to colder summer air temperatures near the coast

    Summer Drivers of Atmospheric Variability Affecting Ice Shelf Thinning in the Amundsen Sea Embayment, West Antarctica

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    Satellite data and a 35-year hindcast of the Amundsen Sea Embayment summer climate using the Weather Research and Forecasting model are used to understand how regional and large-scale atmospheric variability affects thinning of ice shelves in this sector of West Antarctica by melting from above and below (linked to intrusions of warm water caused by anomalous westerlies over the continental shelf edge). El Nino episodes are associated with an increase in surface melt but do not have a statistically significant impact on westerly winds over the continental shelf edge. The location of the Amundsen Sea Low and the polarity of the Southern Annular Mode (SAM) have negligible impact on surface melting, although a positive SAM and eastward shift of the Amundsen Sea Low cause anomalous westerlies over the continental shelf edge. The projected future increase in El Nino episodes and positive SAM could therefore increase the risk of disintegration of West Antarctic ice shelves
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