Multivariate stochastic downscaling model for generating daily precipitation series based on atmospheric circulation

The goal of the paper is to present a model for generating daily precipitation time series and its applications to two climatologically different areas. The rainfall is modeled as stochastic process coupled to atmospheric circulation. Rainfall is linked to the circulation patterns using conditional model parameters. Any kind of circulation pattern classification can be used for this purpose. In this study a new fuzzy rule based method of circulation patterns classification was used. The advantage of this classification technique is the fact that in contrast to common circulation patterns classifications its objective is to explain the variability of local precipitation. It means that the circulation patterns explain the relation between large-scale atmospheric circulation and surface climate (precipitation). Therefore the circulation patterns obtained by this classification method are suitable as input for the subsequent precipitation downscaling. The model was successfully applied in two regions with different climate conditions: Central Europe (Germany) and Eastern Mediterranean (Greece). Several tests like comparison of mean seasonal cycles, comparison of mean values and deviations of yearly totals and other standard diagnostics showed that simulated values agree fairly well with historical data.