Process-based classification of Mediterranean cyclones using potential vorticity

Cyclones handle extreme weather events across the Mediterranean and its neighboring continents, affecting the lives of hundreds of millions. Despite many studies addressing Mediterranean cyclones (MCs) in the last decades, their correct simulation and prediction remain a significant challenge to the present day. This may be attributed to the large variability between MCs, which differ greatly from each other in many aspects.Past classifications of MCs are primarily based on geographical and seasonal separations, yet recent advances and the appearance of Medicanes devastating tropical-like Mediterranean cyclones - emphasize the need for a dynamical classification, focusing on the cyclone deepening mechanisms. A variety of processes alternately govern Mediterranean cyclones' evolution, including diabatic and adiabatic processes, topographic influences, surface temperature anomalies, and land-sea contrasts. Fortunately, each process bears a distinct signature on the potential vorticity (PV) field.Therefore, a PV perspective is called upon to distinguish among the driving mechanisms of the different types of Mediterranean cyclones. Here, a combined cyclone tracking algorithm is used to detect and track Mediterranean cyclones in ECMWF ERA5 from 1979-2020. Cyclone-centered, upper-level isentropic PV structures in the peak time of each cyclone track are classified using the Self Organizing Map (SOM). The SOM analysis reveals 9 classes of Mediterranean cyclones, with distinctcyclone characteristics, lifecycles, associated hazards, and long-term trends. Though classified by upper-level flow structures, each class shows different flow structures down to the surface. Unique synoptic, thermal, dynamical, seasonal, and geographical features indicate dominant processes in the evolution of each Mediterranean cyclone subset. Furthermore, the tropopause-surface coupling is explored and reveals the importance of topographically induced Rossby-wave breaking to the generation of the most intense Mediterranean cyclones. These results enhance our understanding of Mediterranean cyclones' predictability, by linking predictable large-scale Rossby wave formations and life cycles to under-predicted cyclonic variability and associated hazards.