Identifying Mediterranean cyclones in GCM simulations – validation and future predictions

Mid-latitude cyclones play a significant role in shaping the weather and climate of Europe. Cyclones forming in the Mediterranean region and its neighbouring areas – known as Mediterranean cyclones –, typically have shorter life spans and lower pressure at their centres than their Atlantic counterparts. This study uses ERA5 reanalysis data and general circulation model (GCM) outputs of the CMIP6 project to identify potential cyclone centres during the period of 1950–2014. First, the identification algorithm locates local minima in the mean sea level pressure values, which are regridded to a spatial resolution of 1°, and are available in the main synoptic times (6-hour temporal frequency). The potential cyclone centres are then connected through subsequent timesteps to produce cyclone trajectories. The frequency of cyclones and the characteristics of these trajectories are analysed and are validated by comparing the results of reanalysis and CMIP6-simulation data. For the best performing models future trends are assessed across different Shared Socioeconomic Pathway (SSP) scenarios – representing different anthropogenic impacts and mitigation efforts. Mediterranean cyclones affect other parts of Europe, including Hungary and its vicinity. Our ultimate goal is to analyse what portion of the annual precipitation is connected to Mediterranean cyclones and their frontal systems, and how it will change in the future. For this purpose, we use precipitation data from the above-mentioned databases. The outcome of this study is important for future impact assessments. Results can serve as input for decision-makers and stakeholders as they formulate long-term strategies for their respective sectors.

Acknowledgements: The study contributes to the COST CA19109 action (MEDCYCLONES). Research leading to this study has been supported by the following sources: the Hungarian National Research, Development and Innovation Fund (under grant K-129162), and the National Multidisciplinary Laboratory for Climate Change (RRF-2.3.1-21-2022-00014).