Physics Parameterization Selection in RCM and ESM Simulations Revisited: New Supporting Approach Based on Empirical Copulas

Abstract

This study aims at a new supplementary approach to identify optimal configurationsof physics parameterizations in regional climate models (RCMs) and earth system models (ESMs).Traditional approaches separately evaluate variable performance, which may lead to an inappropriateselection of physics parameterization combinations. Besides traditional approaches, we suggest anadditional selection approach by considering the joint dependence structure (covariance structure)between key meteorological variables, i.e., precipitation P and temperature T. This is accomplishedby empirical P and T copula functions and the χ2-test, and is demonstrated in two locationsin Kenya with different major precipitation processes. It is shown that the selection based ontraditional approaches alone may lead to nonoptimal decisions in terms of joint dependence structurebetween P and T. It was found that the copula-based approach may reduce the need for complexmultivariate bias correction, as demonstrated using local intensity scaling for P and linear scaling forT. The new approach may contribute to improving RCM and ESM simulations and climate-impactstudies worldwide.

Keywords

• physics parameterization
• regional climate models
• earth system models
• performance evaluation
• empirical copula
• χ2-test
• bias correction