Atmospheric mesoscale dynamics over the North Atlantic: climatology based on Coherent Vortex Structures identification

Atmospheric mesoscale processes play a significant role in weather formation on different scales and in ocean dynamics on a larger scale. Additionally, mesoscale vortices often fall into the category of extreme weather events (such as tropical cyclones, mesoscale convective complexes, bora, tornadoes, etc.). To date, many types of mesoscale processes are known, but they have generally been studied individually (case studies). Therefore, little is still known about their climatic characteristics: statistical conditions and regions of occurrence, recurrence, and potential climatic dynamics for each of these types, among others. In this study, we attempt to find answers to these questions. This requires solving several complex tasks: automatic detection of mesoscale phenomena in spatial (model) data, tracking each phenomenon over time, and determining their types.

Phenomenologically, atmospheric mesoscale processes are most often vortex structures. Therefore, we utilized a modern method for identifying coherent vortex structures (Rortex) and applied it to long-term high-resolution numerical modeling data and the ERA5 reanalysis dataset.

The main objectives of the research were: (1) to develop a robust algorithm for automatic identification and tracking of coherent vortex structures; (2) to obtain the climatology of various types of mesoscale processes over the North Atlantic region; (3) to identify long-term trends in the recurrence and intensity of mesoscale processes; (4) to derive the climatology of their impact on ocean-atmosphere boundary processes based on the characteristics of each type of mesoscale process.

By bridging the gap between theoretical fluid dynamics and applied meteorology, this work provides new insights into the role of coherent vortex structures in the climate system. The findings have direct implications for improving severe weather forecasting accuracy, enhancing climate risk assessment frameworks, and refining parameterizations of mesoscale processes in climate models. The developed methodology establishes a foundation for future investigations of atmospheric mesoscale dynamics.