A Climatological Perspective on Cyclones and Surface Impacts in the Eastern Mediterranean Using Potential Vorticity-Based Classification

Abstract. Eastern Mediterranean Cyclones (EMCs) are a major contributor to extreme weather in their region, including precipitation, strong winds, cold extremes or dust storms, significantly impacting the population and natural environment. Understanding the relationship between EMC variability and associated impacts is key to understanding their predictability and forecasting them accurately.  Various processes come together to govern the genesis and development of EMC, affecting eventual cyclone characteristics and impacts.  These processes have distinct signatures on the potential vorticity (PV) distribution. Existing approaches for EMC classification provide limited physical interpretations of cyclone variability, associated impacts and predictability. Here we classify EMCs based on their associated upper-tropospheric PV structures providing a novel process-based framework for EMC classification. Using Self-Organising Maps classification of ERA5 reanalysis data, we find 6 coherent PV patterns that typify cyclone clusters, each with its own signature precipitation pattern, which we quantify using ERA5 forecasts, IMERG and local station data. For each of the seasons, there are dominant clusters that lead to extreme precipitation and temperatures. In particular, two clusters with high PV values dominate the eastern Mediterranean's annual precipitation. Evidently, a strong ridge upstream of the PV trough has a greater impact on precipitation than the PV pattern with a weak ridge upstream. Temperature anomalies and extremes during cyclone passage were found to be strongly linked to upper-level PV patterns, with certain cyclones types causing significant near-surface hot or cold extremes (or both). While we found that the overall frequency of cyclones shows no significant trend, specific cyclone types display notable trends, with some increasing and others decreasing, which may suggest a rise in the frequency of drier cyclones if these trends continue, potentially indicating a shift toward drier conditions that could impact precipitation patterns. This classification approach enhances our understanding of the link between cyclones variability and their surface impacts in the region through processes reflected in upper-level PV distributions. These findings provide a framework for systematic evaluation of cyclones and their prediction, and could benefit strategies for managing the societal and environmental impacts of EMCs at weather and climate timescales.