Enhancing Severe Weather Prediction Over Myanmar Using INSAT-3D Sounder and Hyperspectral Satellite Observations

Abstract

This study investigates the application of INSAT-3D Sounder and hyperspectral sounders from polar-orbiting satellites (AIRS, IASI, and CrIS) in predicting severe weather over Myanmar, with a focus on two severe weather case studies from Rakhine State. Data on the stability index (Lifted Index, LI) and Total Precipitable Water (TPW) from INSAT-3D and hyperspectral sounders were analyzed following the methodology of Schmit et al. (2009). The workflow involved downloading data from various sources (MOSDAC, NCDC, Mirador) and generating LI and TPW images. Numerical values for specific stations were extracted, followed by time series analysis. Results demonstrated that increasing LI values, indicating atmospheric instability, and TPW values exceeding 50 mm were critical predictors of severe weather with a lead time of 3–4 hours. These findings suggest that LI and TPW are valuable indicators for nowcasting severe weather. However, the study also highlighted limitations in temporal resolution due to the observation gaps from polar-orbiting sounders. Future research aims to integrate Himawari-8/9 AHI data with hyperspectral sounder observations to improve nowcasting accuracy and the development of a robust tool for severe weather and thunderstorms in Myanmar.