The Importance of Lateral Boundaries, Surface Forcing and Choice of Domain Size for Dynamical Downscaling of Global Climate Simulations

Abstract: Dynamical downscaling by atmospheric Regional Climate Models (RCMs) forced with low-resolution data should produce climate details and add quality and value to the low-resolution data. The aim of this study was to explore the importance of (i) the oceanic surface forcing (sea-surface temperature (SST) and sea-ice), (ii) the lateral boundary condition data, and (iii) the size of the integration domain with respect to improved quality and value in dynamically downscaled data. Experiments addressing the three aspects were performed and the results were investigated for mean sea level pressure (mslp), 2 m air temperature (T2m) and daily precipitation. Although changes in SST gave a clear response locally, changes in the lateral boundary data and the size of the integration domain turned out to be more important with our geographical scope being Norway. The T2m turned out less sensitive to the changes in lateral forcing and the size of the integration domain than mslp and precipitation. The sensitivity for all three variables differed between Norwegian regions; northern parts of Norway were the most sensitive. Even though the sensitivities found in this study might be different in other regions and for other RCMs, these results call for careful consideration when choosing integration domain and driving lateral boundary data when performing dynamical downscaling.