Perspectives on Arctic Hydroclimatology from General Circulation Models
As a region that is currently experiencing rapid change, the Arctic is of growing concern in the climate sciences. Potential changes in Arctic hydrology are of particular concern, because (a) there is significant potential for the Arctic freshwater cycle to change under amplified greenhouse conditions, and (b) these changes may have a profound impact on global climate through interactions with sea ice and global ocean circulation. General circulation models (GCMs) are well suited to the study of these issues, providing self-consistent and relatively complete data sets, as well as a platform for climate experimentation. The series of studies presented here assesses the simulation of Arctic hydroclimatology in GCMs, and examines the system's response to anthropogenic climate change. Model performance has been assessed in terms of regional synoptic climatologies created using the method of self-organizing maps. This approach reveals several biases in simulated Arctic circulation, including significant biases in the location and intensity of climatological storm tracks. However, these biases have relatively little impact on simulated precipitation. Instead, large-scale precipitation biases in the regions studied appear to be primarily the result of systematic errors in simulated precipitation processes, perhaps related to parameterization schemes. With this in mind, the models have then been used to examine hydroclimatological change. GCMs universally project an intensification of the Arctic hydrologic cycle under enhanced greenhouse conditions, with increases in both evapotranspiration (E) and precipitation (P) over both the Arctic Ocean and the surrounding terrestrial drainage area. P increases more than E over both regions in all GCMs examined, leading to a net increase in freshwater delivery to the Arctic Ocean. The largest increases in net precipitation (P-E) occur over the Arctic drainage area, driven by substantial increases in cold season (September through May) precipitation. By combining a cyclone identification algorithm with a means of isolating cyclone-associated precipitation systems, it is shown that this cold season trend is due to an increase in the mean precipitation produced by individual storms. Over mid-latitudes this increase is partially offset by a decrease in storm frequency, while over the Arctic a slight increase in storm frequency further enhances precipitation trends.
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21st century annual cycles anticyclones Arctic drainage Arctic freshwater cycle Arctic Ocean atmospheric circulation atmospheric moisture autumn averaged Beaufort High Beaufort Sea bias Cassano CCSM3 climate change climate system coastal cyclones cold season precipitation cyclone activity cyclone frequency cyclone intensity cyclone-associated precipitation daily data sets decreases drainage area dynamic error ECHAM5/MPI-OM ensemble mean Eurasian evapotranspiration extratropical cyclones feature Figure flux GCM ensemble greenhouse gas Gulf of Alaska high latitude Holland hydrologic hydrologic cycle increase influence Kattsov Lena Mackenzie River Mackenzie River Basin mean precipitation meridional mid-latitude MIROC3.2(hires model physics MRB precipitation NCAR NCAR CCSM3 node frequencies North America North Atlantic North Pacific observations output P-ET precipitation biases precipitation error precipitation events precipitation regimes process error produce reference vectors relative sea ice sea level pressure Serreze shifts significant simulations SLP field storm track study regions summer synoptic climatology terrestrial drainage thermodynamic trends troposphere values variability winter Yenisey