Thunderstorms, associated with lightning and heavy rain, are a weather hazard causing human deaths, urban floods and damage to crops. Current work attempted to study the thunderstorms over Andhra Pradesh, coastal state in southeast India, using multiple satellite datasets, gridded rainfall, Doppler Radar Images and Advanced Research Weather Research and Forecasting (ARW) model simulations during the pre-monsoon seasons of 2017 and 2018. Thermodynamic stability indices computed using INSAT-3D/3DR satellite data were used to identify precursors and lead time of prediction. India Meteorological Department (IMD) daily gridded rainfall data were used to identify the thunderstorm occurrence days, and Doppler Radar Images and INSAT imagery were conjointly used to fix the location. Eight severe thunderstorm cases were analyzed to assess the precursors and the predictability. Further, ARW model predictions for two thunderstorm cases were performed and stability indices computed using model output were compared with satellite-based indices for evaluation. Statistical metrics had shown good agreement of ARW model-based stability indices with satellite-based stability indices. Model had simulated rainfall and cloud properties associated with thunderstorm activity. The results illustrated the predictability of the location and intensity of thunderstorms with 3–4 hrs lead time, which would find usefulness in the real-time prediction of thunderstorms.
$\bullet$ Occurrence of thunderstorms using satellite and radar imagery.
$\bullet$ Identification of thunderstorm occurrences using daily rainfall data.
$\bullet$ Emphasizing the use of thermodynamic stability indices in the prediction of thunderstorms.
$\bullet$ Numerical model predictability of thunderstorms.
$\bullet$ Predictability of thunderstorms collocating satellite and model experiments.
Volume 131, 2022
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