A Downscaling Intercomparison Study: The Representation of Slope- and Ridge-Scale Processes in Models of Different Complexity

Spatially distributed meteorological information at the slope scale is relevant for many processes in complex terrain, yet this sub-km spatial resolution difficult to obtain. While downscaling kilometer resolutions well described literature, moving beyond not. In work, we present a methodical comparison of three methods varying complexity, that are used downscale data from Numerical Weather Prediction model COSMO-1 1.1 km horizontal 250 and 50 m over domain highly terrain Swiss Alps. We compare WRF, dynamical atmospheric model; ICAR, intermediate complexity; TopoSCALE, an efficient topography-based scheme. Point-scale comparisons show similar results amongst all models w.r.t. mean-error statistics, but underlying dynamics different. Ridge-flow interactions reasonable agreement between WRF ICAR resolution. However, able simulate flow patterns cannot. Validation against Lidar suggests only capture preferential deposition snow. Based on these findings significant reduction computational costs, cost alternative TopoScale performs very point-scale comparisons, it unclear if can be attributed itself or forcing observations assimilated therein. Further study required quantify effect.