Relationship of tropical cyclone wind-field and cloud-band metrics with extreme rainfall events over Mexico

Abstract

Tropical cyclones (TCs) are the most important hydrometeorological phenomena affecting Mexico, accounting for approximately 86.5% of the country’s most costly disasters, where extreme rainfall is the main TC-associated hazard. This study analyzes two TC size metrics during the 2000–2024 period: R34, defined as the mean radius of 34-kt winds, and ROCLOUD, a satellite-derived metric that represents the spatial extent of TC cloud bands. These two TC size metrics are evaluated to determine their skill in capturing extreme precipitation events and TC-associated disaster records from CENAPRED. We use diverse databases for this study: IBTrACS, MSWEP (used to define the 95th percentile of daily precipitation from May to November and identify extreme rainfall events), and official disaster declarations from CENAPRED. We consider municipalities are affected by TCs when their locations are inside the spatial domain of R34 (ROCLOUD). In addition, the SIAT-CT (Early Warning System for Tropical Cyclones by its acronym in Spanish) hazard index is computed during the study period to evaluate its performance in capturing extreme precipitation events induced by TCs. Our results show that at least 70% of TC-related disaster records are associated with tropical storms and tropical depressions. Extreme rainfall events frequently occur at distances greater than 300 km from the TC center, and ROCLOUD captures them better than R34. Radial curves indicate that ROCLOUD adequately covers the extreme events up to 500 km from the TC center, whereas the R34 skill to cover these events decays rapidly beyond 300 km. The SIAT-CT index, mainly based on R34, classifies the most extreme precipitation events into low-hazard categories, revealing important limitations for issuing TC rainfall-related warnings. Therefore, we conclude that SIAT-CT requires both TC wind-based metrics and TC cloud-band extension metrics in order to provide accurate warnings of TC-induced hazards and thus strengthen disaster risk reduction strategies prior to TC landfall.