Development of the Regional Arctic System Model (RASM): Near-Surface Atmospheric Climate Sensitivity

Author:

Cassano John J.12,DuVivier Alice1,Roberts Andrew3,Hughes Mimi14,Seefeldt Mark1,Brunke Michael5,Craig Anthony3,Fisel Brandon6,Gutowski William6,Hamman Joseph7,Higgins Matthew1,Maslowski Wieslaw3,Nijssen Bart7,Osinski Robert8,Zeng Xubin5

Affiliation:

1. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado

2. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

3. Department of Oceanography, Naval Postgraduate School, Monterey, California

4. NOAA/Earth System Research Laboratory, Boulder, Colorado

5. Department of Atmospheric Sciences, University of Arizona, Tucson, Arizona

6. Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa

7. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

8. Institute of Oceanology, Sopot, Poland

Abstract

The near-surface climate, including the atmosphere, ocean, sea ice, and land state and fluxes, in the initial version of the Regional Arctic System Model (RASM) are presented. The sensitivity of the RASM near-surface climate to changes in atmosphere, ocean, and sea ice parameters and physics is evaluated in four simulations. The near-surface atmospheric circulation is well simulated in all four RASM simulations but biases in surface temperature are caused by biases in downward surface radiative fluxes. Errors in radiative fluxes are due to biases in simulated clouds with different versions of RASM simulating either too much or too little cloud radiative impact over open ocean regions and all versions simulating too little cloud radiative impact over land areas. Cold surface temperature biases in the central Arctic in winter are likely due to too few or too radiatively thin clouds. The precipitation simulated by RASM is sensitive to changes in evaporation that were linked to sea surface temperature biases. Future work will explore changes in model microphysics aimed at minimizing the cloud and radiation biases identified in this work.

Funder

U.S. Department of Energy

National Science Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science

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