Preprints
https://doi.org/10.5194/essd-2026-388
https://doi.org/10.5194/essd-2026-388
14 Jul 2026
 | 14 Jul 2026
Status: this preprint is currently under review for the journal ESSD.

An ERA5-derived mesovortex tracking framework for investigating tropical cyclogenesis

Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong

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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
Share
Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong

Status: open (until 20 Aug 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong

Data sets

ERA5-derived mesovortex tracking dataset for tropical cyclogenesis Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong https://doi.org/10.5281/zenodo.18145741

Model code and software

Source code for the Mesovortex Analysis of Structure and Tracking (MAST) framework Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong https://doi.org/10.5281/zenodo.18145741

Jianqiao Fan, Liguang Wu, Haikun Zhao, and Zhenyuan Dong
Metrics will be available soon.
Latest update: 14 Jul 2026
Download
Short summary
Predicting how tropical cyclones form is difficult. We developed a new tracking method using forty years of historical data to monitor early storm positions. Our tool successfully detects ninety-six percent of developing tropical cyclones—often two days in advance—by tracking how their layers align vertically. This open tool provides vital data to train artificial intelligence weather models, which will significantly improve early warning systems for extreme weather and help protect communities.
Share
Altmetrics