Process-based classification of Mediterranean cyclones using potential vorticity

Abstract

Abstract. Mediterranean cyclones (MCs) govern extreme weather events across the Euro-African Basin, affecting the lives of hundreds of millions. Despite many studies addressing MCs in the last few decades, their correct simulation and prediction remain a significant challenge to the present day, which may be attributed to the large variability among MCs. Past classifications of MCs are primarily based on geographical and/or seasonal separations; however, here we focus on cyclone genesis and deepening mechanisms. A variety of processes combine to govern MC genesis and evolution, including adiabatic and diabatic processes, topographic influences, land–sea contrasts, and local temperature anomalies. As each process bears a distinct signature on the potential vorticity (PV) field, a PV approach is used to distinguish among different “types” of MCs. Here, a combined cyclone-tracking algorithm is used to detect 3190 Mediterranean cyclone tracks in ECMWF ERA5 from 1979–2020. Cyclone-centered, upper-level isentropic PV structures in the peak time of each cyclone track are classified using a self-organizing map (SOM). The SOM analysis reveals nine classes of Mediterranean cyclones, with distinct Rossby-wave-breaking patterns, discernible in corresponding PV structures. Although classified by upper-level PV structures, each class shows different contributions of lower-tropospheric PV and flow structures down to the surface. Unique cyclone life cycle characteristics, associated hazards (precipitation, winds, and temperature anomalies), and long-term trends, as well as synoptic, thermal, dynamical, seasonal, and geographical features of each cyclone class, indicate dominant processes in their evolution. Among others, the classification reveals the importance of topographically induced Rossby wave breaking to the generation of the most extreme Mediterranean cyclones. These results enhance our understanding of MC predictability by linking the large-scale Rossby wave formations and life cycles to coherent classes of under-predicted cyclone aspects.