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  • 1.
    Claremar, Bjorn
    et al.
    Uppsala Univ, Dept Earth Sci, S-75236 Uppsala, Sweden..
    Obleitner, Friedrich
    Univ Innsbruck, Inst Meteorol & Geophys, A-6020 Innsbruck, Austria..
    Reijmer, Carleen
    Univ Utrecht, Inst Marine & Atmospher Res, NL-3508 TC Utrecht, Netherlands..
    Pohjola, Veijo
    Uppsala Univ, Dept Earth Sci, S-75236 Uppsala, Sweden..
    Waxegard, Anna
    Uppsala Univ, Dept Earth Sci, S-75236 Uppsala, Sweden..
    Karner, Florian
    Univ Innsbruck, Inst Meteorol & Geophys, A-6020 Innsbruck, Austria..
    Rutgersson, Anna
    Uppsala Univ, Dept Earth Sci, S-75236 Uppsala, Sweden..
    Applying a Mesoscale Atmospheric Model to Svalbard Glaciers2012In: Advances in Meteorology, ISSN 1687-9309, E-ISSN 1687-9317, article id 321649Article in journal (Refereed)
    Abstract [en]

    The mesoscale atmospheric model WRF is used over three Svalbard glaciers. The simulations are done with a setup of the model corresponding to the state-of-the-art model for polar conditions, Polar WRF, and it was validated using surface observations. The ERA-Interim reanalysis was used for boundary forcing and the model was used with three nested smaller domains, 24 and 8 km, and 2.7 km resolution. The model was used for a two-year period as well as for a more detailed study using 3 summer and winter months. In addition sensitivity tests using finer horizontal and vertical resolution in the boundary layer and using different physics schemes were performed. Temperature and incoming short- and long-wave radiation were skillfully simulated, with lower agreement between measured and modelled wind speed. Increased vertical resolution improved the frequency distributions of the wind speed and the temperature. The choice of different physics schemes only slightly changed the model results. The polar-optimized microphysics scheme outperformed a slightly simpler microphysics scheme, but the two alternative and more sophisticated PBL schemes improved the model score. A PBL scheme developed for very stable stratifications (QNSE) proved to be better in the winter.

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