Internal variability versus multi-physics uncertainty in a regional climate model

Abstract

In a recent study, Coppola et al. assessed the ability of an ensemble of convection-permitting models (CPM) to simulate deep convection using three case studies. The ensemble exhibited strong discrepancies between models, which were attributed to various factors. In order to shed some light on the issue, we quantify in this article the uncertainty associated to different physical parameterizations from that of using different initial conditions, often referred to as the internal 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-m temperature and 10-m 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 multi-physics and the internal variability. Therefore, the general lesson of this study is that internal variability should be analysed in order to properly distinguish the impact of other sources of uncertainty, especially for short-term sensitivity simulations. ; This work is partially funded by the Spanish government through grant BES-2016-078158 and MINECO/ FEDER co-funded projects INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R). Universidad de Cantabria simulations have been carried out on the Altamira Supercomputer at the Instituto de F´ısica de Cantabria (IFCA-CSIC), member of the Spanish Supercomputing Network. EK and SK acknowledge the support of the Greek Research and Technology Network (GRNET) High Performance Computing (HPC) infrastructure for providing the computational resources of AUTH-simulations (under project ID pr003005) and the AUTH Scientific Computing Center for technical support. IPSL acknowledges the support from the EUCP project, funded by the European Union under H2020 Grant Agreement 776613, and from the IPSL mesocenter ESPRI facility which is supported by CNRS, UPMC, Labex L-IPSL, CNES and Ecole Polytechnique. IPSL simulations were granted access to the HPC resources of TGCC 19 under the allocation A0050106877 made by GENCI. The computational resources for NORCE/BCCR were provided by UNINETT Sigma2 (NN9280K, NS9001K), with funding from the Research Council of Norway's support for the strategic project on climate services. FZJ gratefully acknowledges the computing time granted by the John von Neumann Institute for Computing (NIC) and JARA-HPC provided on the supercomputer JURECA at J¨ulich Supercomputing Centre (JSC). We acknowledge the E-OBS dataset from the EU-FP6 project UERRA (https://www.uerra.eu) and the Copernicus Climate Change Service, and the data providers in the ECA&D project (https://eca.knmi.nl).