Analyzing Variability and Threshold Values of Thermodynamic Indices in the Context of Climate Change for Predicting Pre-monsoon Season Thunderstorms in Sylhet, Bangladesh

Thunderstorms (TS) occurring during the pre-monsoon season (March–May) pose significant challenges across the Eastern and Northeastern Indian subcontinent, leading to the loss of life and property. To predict the occurrence of these TS events and to understand the associated changes in the thermodynamic structure of the atmosphere, our study integrates in-situ surface meteorological variables (temperature and rainfall) and TS activity information from 1956–2016 over Sylhet, Bangladesh, to identify TS days. The study utilised radiosonde measurements for 2016–2017 and ERA5 (the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis) reanalysis datasets for six decades, 1956–2016. The study attempts to check the influence of changing climate over the thermodynamic indices for Sylhet by taking six decades of data. These datasets were employed to assess the atmosphere's stability: conditional, convective, and potential characteristics and to analyse thermodynamic fluctuations during TS. Combining these two data sets provides valuable insights into atmospheric conditions and changes during TS events over the study period. To examine the influence of climate change over the study region, we established threshold values for the thermodynamic indices for 5-year intervals. By observing the long-term variations of these indices, we identified indicators that signify the climate change impact on TS variability. The research findings provide valuable insights into the complex relationship between climate change and TS in Sylhet, Bangladesh. Establishing threshold values for thermodynamic indices not only aids in predicting TS events but also highlights the crucial role of atmospheric stability in their formation. This study contributes to a better understanding of regional weather patterns. It could assist in formulating effective mitigation strategies to minimise the impact of severe TS on vulnerable communities and infrastructure.