Land Surface Climate in the Regional Arctic System Model

Joseph Hamman Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Bart Nijssen Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Michael Brunke Department of Atmospheric Sciences, The University of Arizona, Tucson, Arizona

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John Cassano Cooperative Institute for Research in Environmental Sciences, and Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado

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Anthony Craig Department of Oceanography, Naval Postgraduate School, Monterey, California

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Alice DuVivier Cooperative Institute for Research in Environmental Sciences, and Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado

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Mimi Hughes Cooperative Institute for Research in Environmental Sciences, and Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado
National Oceanic and Atmospheric Administration, Earth Science Research Laboratory, Physical Sciences Division, Boulder, Colorado

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Dennis P. Lettenmaier Department of Geography, University of California, Los Angeles, Los Angeles, California

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Wieslaw Maslowski Department of Oceanography, Naval Postgraduate School, Monterey, California

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Robert Osinski Polish Institute of Oceanology, Sopot, Poland

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Andrew Roberts Department of Oceanography, Naval Postgraduate School, Monterey, California

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Xubin Zeng Department of Atmospheric Sciences, The University of Arizona, Tucson, Arizona

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Abstract

The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979–2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are local biases that exceed 6°C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-15-0415.s1.

Corresponding author address: Bart Nijssen, Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195-2700. E-mail: nijssen@uw.edu

Abstract

The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979–2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are local biases that exceed 6°C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-15-0415.s1.

Corresponding author address: Bart Nijssen, Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195-2700. E-mail: nijssen@uw.edu

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