Stochastic downscaling of precipitation in complex orography: a simple method to reproduce a realistic fine-scale climatology

摘要

Stochastic rainfall downscaling methods usually do not take into account orographic effects or local precipitation features at spatial scales finer than those resolved by the large-scale input field. For this reason they may be less reliable in areas with complex topography or with sub-grid surface heterogeneities. Here we test a simple method to introduce realistic fine-scale precipitation patterns into the downscaled fields, with the objective of producing downscaled data more suitable for climatological and hydrological applications as well as for extreme event studies. The proposed method relies on the availability of a reference fine-scale precipitation climatology from which corrective weights for the downscaled fields are derived. We demonstrate the method by applying it to the Rainfall Filtered Autoregressive Model (RainFARM) stochastic rainfall downscaling algorithm.