Unravelling the dynamical characteristics of tropical cyclones: Amphan and Nisarga using ERA5 reanalysis - Kumar, Subodh; Verma, Saurabh; Lodh, Abhishek (Frontiers in Environmental Science, 2025)
Tropical cyclone (TC) is a rapidly intensifying storm over warm water of oceans, critically studied for its potential to inflict severe damage and pose life-threatening hazards. The present study focuses on exploring the pre- and post-cyclone characteristics of TC Amphan and Nisarga using ECMWF Reanalysis v5 (ERA5) reanalysis. Our analysis reveals that the TC features, such as its intensity, life cycle, wind circulations, the warm-core structure evolution, and the related environmental factors, are consistent with India Meteorological Department observations. The presented results have indicated that maximum sustainable wind speed, central sea level pressure, lower troposphere temperature and lower stratosphere temperature along the radius from the TC center create a favourable condition that eventually leads to the formation and intensification of super and severe cyclonic storms, for example, Amphan and Nisarga, respectively. The analysis suggests that the atmospheric instability, TC formation, development, and energy for intensification are controlled mainly by the warmer-than-average Arabian Sea and Bay of Bengal basin sea surface temperature anomalies in the Indian Ocean region. The results indicated that the TC genesis and movement are well captured by ERA5, close to the observed best tracks provided by the India Meteorological Department, with an RMSE of ∼31 km. The vorticity budget analysis illustrates that in the developing and mature stages of TC, the tilting term converts horizontal vorticity into vertical vorticity via upward motion. During the dissipation phase, the tilting term reverses, resulting in a fall in vertical vorticity, which weakens or dissipates the TC intensity. Overall, the circulation pattern appears to reproduce most of the essential characteristics of the mature stage of TCs, like the eye and eyewall, highlighting the importance of near real-time high-resolution reanalysis datasets for exploring the details of extreme events.