Version 1
: Received: 2 May 2023 / Approved: 4 May 2023 / Online: 4 May 2023 (10:01:07 CEST)
How to cite:
Mondal, U.; Kumar, A.; Panda, S.K.; Sharma, D.; Das, S. Comprehensive Study of Thunderstorm Indices Threshold Favorable for Thunderstorms During Monsoon Season Using WRF-ARW Model and ERA5 Over India. Preprints2023, 2023050251. https://doi.org/10.20944/preprints202305.0251.v1
Mondal, U.; Kumar, A.; Panda, S.K.; Sharma, D.; Das, S. Comprehensive Study of Thunderstorm Indices Threshold Favorable for Thunderstorms During Monsoon Season Using WRF-ARW Model and ERA5 Over India. Preprints 2023, 2023050251. https://doi.org/10.20944/preprints202305.0251.v1
Mondal, U.; Kumar, A.; Panda, S.K.; Sharma, D.; Das, S. Comprehensive Study of Thunderstorm Indices Threshold Favorable for Thunderstorms During Monsoon Season Using WRF-ARW Model and ERA5 Over India. Preprints2023, 2023050251. https://doi.org/10.20944/preprints202305.0251.v1
APA Style
Mondal, U., Kumar, A., Panda, S.K., Sharma, D., & Das, S. (2023). Comprehensive Study of Thunderstorm Indices Threshold Favorable for Thunderstorms During Monsoon Season Using WRF-ARW Model and ERA5 Over India. Preprints. https://doi.org/10.20944/preprints202305.0251.v1
Chicago/Turabian Style
Mondal, U., Devesh Sharma and Someshwar Das. 2023 "Comprehensive Study of Thunderstorm Indices Threshold Favorable for Thunderstorms During Monsoon Season Using WRF-ARW Model and ERA5 Over India" Preprints. https://doi.org/10.20944/preprints202305.0251.v1
Abstract
: This study investigates the use of various thunderstorm indices in predicting severe thunderstorms events during the monsoon season in four different regions in India. The research evaluates the performance of the prediction model using a model skill score and utilizes the Weather Research and Forecasting (WRF) model with the double moment microphysics scheme to simulate model cases. It also compares fifteen thunderstorm indices derived from the ERA5 dataset to identify the most effective index for predicting severe thunderstorms events. The results of this study show that in-corporating thunderstorm indices with model skill scores improves severe thunderstorms fore-casting in the monsoon season in India. The result revealed that determining the optimal threshold for each index is crucial in achieving accurate predictions. The study also highlights the importance of considering multiple indices rather than relying on a single index to predict severe thunderstorms events. The advance indices such as Energy Helicity Index (EHI), Supercell Composite Parameter (SCP), mainly works well with extreme severe thunderstorms. The simplistic indices can predict the weak or severe thunderstorm easily. The use of multiple thunderstorm indices can also help mete-orologists to make more accurate predictions, which can further enhance public safety. In conclu-sion, this study demonstrates the potential of incorporating thunderstorm indices with model skill scores like HSS and TSS and combinations of different skill scores in severe thunderstorms fore-casting during the monsoon season in India. Future research can build upon the findings of this study to develop more accurate and reliable severe weather forecasting models.
Keywords
Thunderstorm Indices; WRF-ARW; Lightning; Optimal Threshold; Model Skill Score
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
