Investigation of Physical Processes Leading to the Genesis of Tropical Cyclones over the North Indian Ocean: An Integrated Study of Wave Dynamics, Energy Conversion, and Advanced Tracking Methods

This research investigates the complex dynamics of tropical cyclone (TC) formation over the North Indian Ocean (NIO), focusing on equatorial wave influences, cyclogenesis mechanisms, barotropic energy conversion, and pre-genesis evolution through high-resolution modeling. Using the severe cyclonic storm Mora (2017) as a primary case study, the research demonstrates that tropical waves play a crucial role in cyclogenesis, particularly through the interaction between Madden-Julian Oscillation (MJO) and Equatorial Rossby (ER) waves. Analysis reveals that MJO provides essential mid-level moisture while ER waves initiate low-level circulation, leading to low formation. A comprehensive composite analysis of tropical cyclones from 2017-2022 further establishes that cyclogenesis predominantly occurs during the interaction of MJO phases 2-3 and ER phases 5-7, while non-developing systems typically involve single wave or no wave interaction. The study investigates the barotropic energy conversion processes within the wave interactions, revealing how eddy kinetic energy is transferred from the mean flow to the disturbances during cyclogenesis. This energy conversion analysis provides crucial insights into why some systems develop into tropical cyclones while others remain as non-developing lows. It is observed that developing systems exhibit stronger barotropic energy conversion rates, particularly during the interaction of MJO and ER waves, contributing to the intensification of the initial disturbance.

Further, to address the challenges in early detection of tropical cyclones, this study introduces a novel stream function-based methodology for tracking quasi-closed circulation (QCC) systems before low formation. Traditional approaches using mean sea level pressure have proven insufficient for early detection. The newly developed method successfully tracked the evolution of cyclone Mora and was subsequently automated and validated across multiple seasons from 2017 onwards. This tracking algorithm demonstrates remarkable accuracy in distinguishing between developing and non-developing lows based on stream function values and amplitude differences, along with total precipitable water, achieving high accuracy. Machine learning approach is further addressed to distinguish between developing and non-developing tropical lows to tropical cyclones irrespective of different numerical model’s data.

The research extends into high-resolution numerical modeling simulation using the Model for Prediction Across Scales (MPAS-A) at 3km spatial resolution. Utilizing ERA5 initial conditions and NOAA interpolated SST data, simulations were conducted for SCS Mora over Bay of Bengal, Indian ocean. The non-hydrostatic model successfully captured pre-vortex formations and accurately simulated wind speeds and reflectivity patterns prior to low formation, providing valuable insights into the pre-genesis phase of tropical cyclones.

This comprehensive study advances our understanding of tropical cyclone formation over the NIO by establishing the critical role of wave interactions and barotropic energy conversion in cyclogenesis, developing an innovative tracking methodology, and validating high-resolution modeling approaches. The findings have significant implications for improving tropical cyclone forecasting and early warning systems in the region, particularly in identifying and tracking potential cyclonic developments prior to low pressure area formation.