Yearly evolution of Euro-Atlantic weather regimes and of their sub-seasonal predictability

Nicola Cortesi,Andrea Manrique-Suñén,Verónica Torralba,Francisco J Doblas-Reyes,Albert Soret,Llorenç Lledó,Nube Gonzalez-Reviriego

doi:10.1007/s00382-021-05679-y

Abstract

It is often assumed that weather regimes adequately characterize atmospheric circulation variability. However, regime classifications spanning many months and with a low number of regimes may not satisfy this assumption. The first aim of this study is to test such hypothesis for the Euro-Atlantic region. The second one is to extend the assessment of sub-seasonal forecast skill in predicting the frequencies of occurrence of the regimes beyond the winter season. Two regime classifications of four regimes each were obtained from sea level pressure anomalies clustered from October to March and from April to September respectively. Their spatial patterns were compared with those representing the annual cycle. Results highlight that the two regime classifications are able to reproduce most part of the patterns of the annual cycle, except during the transition weeks between the two periods, when patterns of the annual cycle resembling Atlantic Low regime are not also observed in any of the two classifications. Forecast skill of Atlantic Low was found to be similar to that of NAO+, the regime replacing Atlantic Low in the two classifications. Thus, although clustering yearly circulation data in two periods of 6 months each introduces a few deviations from the annual cycle of the regime patterns, it does not negatively affect sub-seasonal forecast skill. Beyond the winter season and the first ten forecast days, sub-seasonal forecasts of ECMWF are still able to achieve weekly frequency correlations of r = 0.5 for some regimes and start dates, including summer ones. ECMWF forecasts beat climatological forecasts in case of long-lasting regime events, and when measured by the fair continuous ranked probability skill score, but not when measured by the Brier skill score. Thus, more efforts have to be done yet in order to achieve minimum skill necessary to develop forecast products based on weather regimes outside winter season.

Highlights

One of the key areas where progresses are expected in this decade is that of forecasts of weather regimes (WRs) from two to four weeks, a time range until recently considered a ”predictability desert” (Vitart et al 2012)
The aim of this study was to highlight the limits of extended WR classifications in characterizing atmospheric circulation variability, and to validate sub-seasonal forecast skill in predicting the frequencies of WRs beyond the winter season
Two extended WR classifications of four WRs each were classified, both based on k-means clustering of daily sea level pressure (SLP) fields from October to March and from April to September 1979–2017 respectively

Summary

Introduction

One of the key areas where progresses are expected in this decade is that of forecasts of weather regimes (WRs) from two to four weeks, a time range until recently considered a ”predictability desert” (Vitart et al 2012). As WRs represent long-lasting and recurrent weather conditions over extended regions, they are useful to predict large-scale events with a strong impact on society, such as droughts (Lavaysse et al 2018), heat waves (Alvarez-Castro et al 2018), cold spells (Ferranti et al 2018) and wind power fluctuations (Grams et al 2017). WRs were identified in less studied areas, like Asia (Gerlitz et al 2018; Wang et al 2019), Australia (Wilson et al 2013) and Africa (Fauchereau et al 2009).

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Discussion

Conclusion