Euro-Atlantic weather Regimes in the PRIMAVERA coupled climate simulations: impact of resolution and mean state biases on model performance

• Published in: Climate Dynamics
• Main Authors: Fabiano, F., Christensen, H. M., Strommen, K., Athanasiadis, P., Baker, A., Schiemann, R., Corti, S.
• Other Authors: Horizon 2020 Framework Programme, Natural Environment Research Council
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2020
• Subjects: Atmospheric Science; North Atlantic
• Online Access: http://dx.doi.org/10.1007/s00382-020-05271-w; https://link.springer.com/content/pdf/10.1007/s00382-020-05271-w.pdf; https://link.springer.com/article/10.1007/s00382-020-05271-w/fulltext.html

Abstract Recently, much attention has been devoted to better understand the internal modes of variability of the climate system. This is particularly important in mid-latitude regions like the North-Atlantic, which is characterized by a large natural variability and is intrinsically difficult to predict. A suitable framework for studying the modes of variability of the atmospheric circulation is to look for recurrent patterns, commonly referred to as Weather Regimes. Each regime is characterized by a specific large-scale atmospheric circulation pattern, thus influencing regional weather and extremes over Europe. The focus of the present paper is the study of the Euro-Atlantic wintertime Weather Regimes in the climate models participating to the PRIMAVERA project. We analyse here the set of coupled historical simulations (hist-1950), which have been performed both at standard and increased resolution, following the HighresMIP protocol. The models’ performance in reproducing the observed Weather Regimes is assessed in terms of different metrics, focussing on systematic biases and on the impact of resolution. We also analyse the connection of the Weather Regimes with the Jet Stream latitude and blocking frequency over the North-Atlantic sector. We find that—for most models—the regime patterns are better represented in the higher resolution version, for all regimes but the NAO-. On the other side, no clear impact of resolution is seen on the regime frequency of occurrence and persistence. Also, for most models, the regimes tend to be more tightly clustered in the increased resolution simulations, more closely resembling the observed ones. However, the horizontal resolution is not the only factor determining the model performance, and we find some evidence that biases in the SSTs and mean geopotential field might also play a role.