Internal variability vs multi‐physics uncertainty in a regional climate model

In a recent study, Coppola et al (2020) assessed the ability of an ensemble of convection‐permitting models (CPM) to simulate deep convection using three case studies. The ensemble exhibited strong dis crepancies between models, which were attributed to various factors. In order to shed some light on the issue, we quantify in this paper the uncertainty associated to different physical parameterizations from that of using different initial conditions, often referred to as the inter nal variability. For this purpose, we establish a framework to quantify both signals and we compare them for upper atmospheric circulation and near‐surface variables. The analysis is carried out in the context of the CORDEX Flagship Pilot Study on Convective phenomena at high resolution over Europe and the Mediterranean, in which the intermediate RCM WRF simulations that serve to drive the CPM are run several times with different parameterizations. For atmospheric circulation (geopotential height), the sensitivity induced by multi‐physics and the internal variability show comparable magnitudes and a similar spatial distribution pattern. For 2‐meter temperature and 10‐meter wind, the simulations with different parameterizations show larger differences than those launched with different initial conditions. The systematic effect over one year shows distinct patterns for the multiphysics and the internal variability. Therefore, the general lesson of this study is that internal variability should be analyzed in order to properly distinguish the impact of other sources of uncertainty, especially for short‐term sensitivity simulations.