Evaluation of Dynamical Downscaling in a Fully Coupled Regional Earth System Model Provisionally Accepted

Mark W. Seefeldt^{1, 2*} John J. Cassano^{1, 2, 3} Younjoo Lee⁴ Wieslaw Maslowski`⁴ Anthony P. Craig⁵ Robert Osinski⁶

• ¹National Snow and Ice Data Center, University of Colorado Boulder, United States
• ²Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, United States
• ³Department of Atmospheric and Oceanic Sciences, College of Arts and Sciences, University of Colorado Boulder, United States
• ⁴Department of Oceanography, Naval Postgraduate School, United States
• ⁵Independent researcher, United States
• ⁶Institute of Oceanology, Polish Academy of Sciences, Poland

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere -land -ocean -sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.