Blocking representation in the ERA-Interim driven EURO-CORDEX RCMs

• Published in: Climate dynamics 2019-03, Vol.52 (5-6), p.3291-3306
• Main Authors: Jury, Martin Wolfgang, Herrera, Sixto, Gutiérrez, José Manuel, Barriopedro, David
• Format: Article
• Language: English
• Subjects: Air conditioners; Air temperature; Analysis; Anomalies; Atmospheric blocking; Atmospheric circulation; Atmospheric models; Bias; Climate; Climate models; Climatology; Computer simulation; Data; Data processing; Dynamic meteorology; Earth and Environmental Science; Earth Sciences; General circulation models; Geophysics/Geodesy; Numerical weather prediction; Oceanography; Precipitation; Precipitation (Meteorology); Precipitation rate; Public relations; Regional climate models; Regional climates; Representations; Surface temperature
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-018-4335-8

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.