| 14 Jul 2026
An ERA5-derived mesovortex tracking framework for investigating tropical cyclogenesis
Abstract. Previous studies have suggested that the vertical mesovortex couple plays a critical role in tropical cyclogenesis. This couple consists of midlevel and low-level mesoscale vortices, whose formation is believed to result from different physical mechanisms. However, existing tropical cyclone datasets primarily document post-formation stages, and a substantial gap remains between the well-observed life cycles of mature tropical cyclones and the poorly documented mesoscale processes preceding formation. To address this gap, a flexible, objective detection and tracking framework was developed based on ERA5 reanalysis, termed the Mesovortex Analysis of Structure and Tracking (MAST), and a corresponding multi-decadal dataset was constructed for the western North Pacific (WNP) basin covering 1984–2023. Technical validation shows that MAST successfully detects 96 % of the mesovortex couple associated with observed tropical cyclogenesis events at the formation time, with more than 50 % of cases identifiable as early as 48 h prior to formation. A comparative analysis further reveals systematic differences in the vertical tilt evolution of the mesovortex couple: genesis cases exhibit a steady reduction in tilt with time, whereas non-genesis cases maintain a persistently large tilt of approximately 200 km. The MAST framework extends the long-term record of mesoscale vortex evolution during the pre-formation stage and provides a valuable resource for understanding tropical cyclogenesis, numerical model evaluation, and machine-learning-based genesis prediction.
This article provides a very useful dataset for mesoscale vortices prior to tropical cyclone genesis. The paper is well written, and the data processing steps are clearly described.
My only suggestion is to consider including vortex centers at additional pressure levels in the dataset. While vortices at 850 hPa and 500 hPa are indeed important, a more complete vertical representation—including levels such as 700 hPa, 600 hPa, and those above—would be valuable. Since vortex tilting is a continuous vertical structure, a more detailed sampling would provide richer information and likely increase the dataset's impact. Given that the algorithm is already in place, extending the analysis to additional levels should not be overly difficult.