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Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4
Authors:Steve Vavrus  Duane Waliser  Axel Schweiger  Jennifer Francis
Institution:1. Center for Climatic Research, University of Wisconsin-Madison, 1225?W. Dayton Street, Madison, WI, 53706, USA
2. Water and Carbon Cycles Group, Jet Propulsion Laboratory, MS 183-501, 4800 Oak Grove Drive, Pasadena, CA, 91109, USA
3. Polar Science Center, University of Washington, 1013 NE 40th Street, Seattle, WA, 98105, USA
4. J. J. Howard Marine Laboratory, Rutgers University, 74 Magrudor Road, Highlands, NJ, 07732, USA
Abstract:Simulations of late 20th and 21st century Arctic cloud amount from 20 global climate models (GCMs) in the Coupled Model Intercomparison Project phase 3 (CMIP3) dataset are synthesized and assessed. Under recent climatic conditions, GCMs realistically simulate the spatial distribution of Arctic clouds, the magnitude of cloudiness during the warmest seasons (summer–autumn), and the prevalence of low clouds as the predominant type. The greatest intermodel spread and most pronounced model error of excessive cloudiness coincides with the coldest seasons (winter–spring) and locations (perennial ice pack, Greenland, and the Canadian Archipelago). Under greenhouse forcing (SRES A1B emissions scenario) the Arctic is expected to become cloudier, especially during autumn and over sea ice, in tandem with cloud decreases in middle latitudes. Projected cloud changes for the late 21st century depend strongly on the simulated modern (late 20th century) annual cycle of Arctic cloud amount: GCMs that correctly simulate more clouds during summer than winter at present also tend to simulate more clouds in the future. The simulated Arctic cloud changes display a tripole structure aloft, with largest increases concentrated at low levels (below 700 hPa) and high levels (above 400 hPa) but little change in the middle troposphere. The changes in cloud radiative forcing suggest that the cloud changes are a positive feedback annually but negative during summer. Of potential explanations for the simulated Arctic cloud response, local evaporation is the leading candidate based on its high correlation with the cloud changes. The polar cloud changes are also significantly correlated with model resolution: GCMs with higher spatial resolution tend to produce larger future cloud increases.
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