Abstract
While Regional Climate Models (RCMs) have been shown to yield improved simulations compared to General Circulation Model (GCM), their representation of large-scale phenomena like atmospheric blocking has been hardly addressed. Here, we evaluate the ability of RCMs to simulate blocking situations present in their reanalysis driving data and analyse the associated impacts on anomalies and biases of European 2-m air temperature (TAS) and precipitation rate (PR). Five RCM runs stem from the EURO-CORDEX ensemble while three RCMs are WRF models with different nudging realizations, all of them driven by ERA-Interim for the period 1981–2010. The detected blocking systems are allocated to three sectors of the Euro-Atlantic region, allowing for a characterization of distinctive blocking-related TAS and PR anomalies. Our results indicate some misrepresentation of atmospheric blocking over the EURO-CORDEX domain, as compared to the driving reanalysis. Most of the RCMs showed fewer blocks than the driving data, while the blocking misdetection was negligible for RCMs strongly conditioned to the driving data. A higher resolution of the RCMs did not improve the representation of atmospheric blocking. However, all RCMs are able to reproduce the basic anomaly structure of TAS and PR connected to blocking. Moreover, the associated anomalies do not change substantially after correcting for the misrepresentation of blocking in RCMs. The overall model bias is mainly determined by pattern biases in the representations of surface parameters during non-blocking situations. Biases in blocking detections tend to have a secondary influence in the overall bias due to compensatory effects of missed blockings and non-blockings. However, they can lead to measurable effects in the presence of a strong blocking underestimation.
Highlights
Regional Climate Models (RCMs) are a common tool to generate relevant climate information on regional scales (e.g. Dickinson et al 1989; Giorgi and Bates 1989; Giorgi and Mearns 1991; Laprise 2008; Rummukainen 2010)
The free-running RCMs from EURO-CORDEX generally under-represent the blocking days throughout the year, especially in summer, when the simulated blocking frequency (BF) can drop to almost half of those in the ERA-Interim reanalysis
State-of-the-art EURO-CORDEX RCMs show a different representation of blockings than their driving data (ERAInterim) mainly in the center of the RCM domain, where the RCMs’ own dynamics are less constrained by the boundary conditions
Summary
Regional Climate Models (RCMs) are a common tool to generate relevant climate information on regional scales (e.g. Dickinson et al 1989; Giorgi and Bates 1989; Giorgi and Mearns 1991; Laprise 2008; Rummukainen 2010). There is the possibility that the RCM’s mean flow on the synoptic scale diverges from that of the GCM, especially if the regional domain is large enough (Jones et al 1995; Diaconescu and Laprise 2013) This may hold benefits, since a better representation of certain phenomena might overcome some aspects of the “garbage in, garbage out” problem (Diaconescu and Laprise 2013; Hall 2014). One aspect hardly addressed in newer large downscaling experiments, like the Coordinated Regional Climate Downscaling Experiment (CORDEX, Giorgi et al 2009; Evans 2011), is if the downscaling domain is large enough for RCMs to diverge from their driving GCMs, and, if so, whether RCMs better represent certain atmospheric phenomena or should be more strongly conditioned to their driving data Among these large-scale systems, blocking describes a situation where the westerly flow in the mid-latitudes is interrupted or deflected during several days to weeks by an anticyclonic high pressure system (Rex 1950). We further explore the contribution of blocking errors in RCMs to the climatological biases in surface variables, namely 2-m air temperature (TAS) and precipitation rate (PR)
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