Abstract
AbstractIn 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 1 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.
Highlights
The increasing resolution of Regional Climate Models (RCMs) has reached the so-called convection-permitting scale (Prein et al, 2015), by approaching resolutions of a few kilometers, typically used in Numerical Weather Prediction (NWP)
Since causation is difficult to address in a multi-model approach, we focus on the multi-physics ensemble within the FPS-Convection RCMs that serve to drive the convection-permitting models (CPM)
We explore the uncertainty associated to physical parameterizations by using multi-physics ensembles (MPE, hereafter) generated in the context of the FPS-Convection
Summary
The increasing resolution of Regional Climate Models (RCMs) has reached the so-called convection-permitting scale (Prein et al, 2015), by approaching resolutions of a few kilometers, typically used in Numerical Weather Prediction (NWP). Quite a few analyses tested the ability of different MPEs to encompass the regional climate in different areas (Fernandez et al, 2007; Evans et al, 2012; Solman and Pessacg, 2012; Jerez et al, 2013; Garcıa-Dıez et al, 2015; Katragkou et al, 2015; Stegehuis et al, 2015; Devanand et al, 2018) Some of these analyses mentioned internal variability as potential source of background noise that impacts the sensitivity to the physical parameterization schemes (Tourpali and Zanis, 2013; Stegehuis et al, 2015), though internal variability was not formally investigated.
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