Stochastic downscaling of precipitation to high-resolution scenarios in orographically complex regions: 1. Model evaluation

摘要

[1] The simulation of space-time precipitation has been studied since the late 1980s. However, there are still many open issues concerning the most appropriate approach to simulate it, specially in highly heterogeneous areas, such as in mountain environments. For this reason, we present here a comprehensive investigation of the Space-Time Neyman-Scott Rectangular Pulses model, with the purpose of analyzing its performance in a challenging Alpine environment of Switzerland and identifying weaknesses that can drive future improvements. The results point at the suitability of the model in reproducing not only the basic statistics at different temporal aggregations, but also the more challenging distributional and scaling properties. The intrinsic stationarity of the model in space, induced by the parameter estimation procedure, poses occasional limitations with regard to the accurate simulation of the variability of the observed climate characteristics, which are strongly influenced by local microclimates. However, the model is able, even in the complex Alpine environment, to preserve the spatial patterns observed in the actual precipitation process. The study allowed (ⅰ) to conclude about the robustness of the model and its suitability for multisite downscaling of precipitation estimated from climate model simulations, as reported in the companion paper, and (ⅱ) to put in evidence some limitations that require further consideration to improve space-time rainfall generation.