Poster Session P1.20 Sensitivity of Antarctic Precipitation to Sea Ice Concentrations in a General Circulation Model

Tuesday, 15 May 2001
John W. Weatherly, Cold Regions Research and Engineering Lab, Hanover, NH

Handout (69.2 kB)

Antarctic ice sheet precipitation and accumulation has the potential to increase significantly as global temperatures increase and sea ice cover decreases. The sensitivity of Antarctic precipitation to variations in surrounding sea-ice concentrations is investigated using the NCAR Community Climate Model version 3 (CCM3) global atmospheric general circulation model (GCM). Sea ice concentrations from passive-microwave satellite data from 1979 to 1991 are used as boundary conditions. The GCM is run at spectral resolution T42 (approximately 2.8 by 2.8 degrees). An ensemble of five GCM simulations of 1979-1991 has been performed with monthly ice concentrations (and different initial conditions). The ensemble results are averaged to separate the model’s response (the signal) from the large natural variability (the noise). A pair of 25-year simulations with both maximum and minimum ice concentrations is also being performed to diagnose the difference between these cases.

CCM3 simulates Antarctic precipitation that is more similar in magnitude and spatial pattern to observational analyses than previous CCM versions have simulated. The gradient in precipitation at the sharp coastal topographic boundary is weakened in CCM3, due to the grid resolution used. No elevation-based adjustment for ice-sheet accumulation is employed in this study, so accumulation rates are not considered here. The near-surface air temperatures over the Antarctic sea ice exhibit interannual and monthly anomalies as created by the sea-ice concentration patterns, mostly in the region from 60S to 65S. The sea level pressures exhibits some sensitivity to the sea ice and temperature changes in this region. The changes in Antarctic precipitation in response to the interannual sea-ice variations, in only preliminary analysis of the GCM results, are smaller in magnitude, and require consideration of their statistical significance in relation to the natural variability.

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