Copula-based statistical refinement of precipitation in RCM simulations over complex terrain

摘要

This paper presents a new Copula-based method for further downscalingregional climate simulations. It is developed, applied and evaluated forselected stations in the alpine region of Germany. Apart from the common wayto use Copulas to model the extreme values, a strategy is proposed whichallows to model continuous time series. As the conceptof Copulas requires independent and identically distributed(iid) random variables, meteorological fields are transformed usingan ARMA-GARCH time series model. In this paper, we focus on thepositive pairs of observed and modelled (RCM) precipitation.According to the empirical copulas, significant upper and lower tail dependencebetween observed and modelled precipitation can be observed.These dependence structures are further conditioned on the prevailing large-scaleweather situation.Based on the derived theoretical Copula models, stochastic rainfall simulations are performed, finally allowing for bias correctedand locally refined RCM simulations.