On the relation of CMIP6 GCMs errors at RCM driving boundary condition zones and inner domain for Central Europe region

Abstract

Global climate models (GCMs) are important tools for studying the climate system and climate change projections. Due to their coarse spatial resolution, downscaling is necessary on regional scale. Regional climate models (RCMs) represent a common solution for this issue. Nevertheless, outputs of RCMs are influenced by the boundary conditions provided by GCMs. This study evaluates CMIP6 GCMs regarding the variables relevant as RCM boundary conditions. Special focus is on the simulation of CNRM-ESM2-1, which is being used as a driving model for convection-permitting Aladin-Climate/CZ RCM, used as one source feeding new Czech climate change scenarios. The analysis is conducted over the boundaries and inside the RCM integration domain. Firstly, an evaluation of CFSR and ERA5 reanalyses against radiosondes is performed in order to choose an appropriate reference dataset for upper air variables. Revealed high correlation between both reanalysis and radiosondes slightly decreases at the most upper tropospheric levels. ERA5 is then chosen as the reference for the boundary analysis. Over the inner domain, simulated mean annual cycle of impact-relevant variables is validated against E-OBS. The CNRM-ESM2-1 performs well in terms of near-surface variables over the Czech Republic, but it exhibits larger errors along the boundaries, especially for air temperature and specific humidity. Weak statistical relationship between the GCM performance over the boundaries in the upper levels and over the inner domain suggests that the nested RCM simulation does not necessarily have to be influenced by the biases in the driving data.