@article{66ab1d785f26449287f34d2231d51bf9,
title = "Development of the Regional Arctic System Model (RASM): Near-surface atmospheric climate sensitivity",
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.",
keywords = "Arctic, Atmosphere-land interaction, Atmosphere-ocean interaction, Regional models, Sea ice",
author = "Cassano, {John J.} and Alice DuVivier and Andrew Roberts and Mimi Hughes and Mark Seefeldt and Michael Brunke and Anthony Craig and Brandon Fisel and William Gutowski and Joseph Hamman and Matthew Higgins and Wieslaw Maslowski and Bart Nijssen and Robert Osinski and Xubin Zeng",
note = "Funding Information: This work was funded by the United States Department of Energy Grants DE-FG02-07ER64462 and DE-SC0006178 (University of Colorado), DE-FG02-07ER64460 and DE-SC0006856 (University ofWashington), DE-FG02-07ER64463 (Iowa State University), DESC0006693 (University of Arizona) and National Science Foundation Grants PLR-1107788 and PLR-1417818 (University of Colorado). Computing resources were provided via aChallenge Grant fromtheU.S. Department of Defense as part of theHigh Performance ComputingModernization Program(HPCMP).Observationally based data used in this studywere supplied by theU.S. National Snow and IceData Center, the European Centre for Medium-Range Weather Forecasts, the National Center for Atmospheric Research, and the Jet Propulsion Laboratory of the National Aeronautics and Space Administration. ERA-Interim data were accessed from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. RASM data are archived at theDoD-HPCMP center.We thank the four anonymous reviewers and the editor for their time and useful comments which helped improve thismanuscript. Publisher Copyright: {\textcopyright} 2017 American Meteorological Society.",
year = "2017",
month = aug,
day = "1",
doi = "10.1175/JCLI-D-15-0775.1",
language = "English (US)",
volume = "30",
pages = "5729--5753",
journal = "Journal of Climate",
issn = "0894-8755",
publisher = "American Meteorological Society",
number = "15",
}