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<p>This study evaluates the performance of the Advanced Research version of Weather Research and Forecasting model at a cloud-resolving scale (0.8&#xa0;km horizontal resolution) in simulating three heavy rainfall events (HREs) Tamil Nadu flood in December 2015, Kerala floods in August 2018 and August 2019 over the coastal regions of South India. A total of 30 simulations were carried out using ten different cloud microphysical schemes (CMSs) to investigate their impact on three HREs. Results were validated using datasets from Doppler Weather Radar, Automatic Weather Stations, and the IMERG satellite precipitation product. The results show that no single CMS consistently outperformed for the simulation of all three HREs. The WSM6 and Thompson CMSs provided a better results for Tamil Nadu 2015 case and WSM6 CMS for the Kerala flood in 2018. However, none of the CMSs effectively captured the spatial rainfall patterns of the 2019 Kerala flood. The probability of detection using 24&#xa0;h accumulated rainfall at 32 locations with threshold exceeded 250&#xa0;mm was approximately 78% with WSM6 CMS and followed by NSSL 2-mom scheme with 68% for Tamil Nadu case. The correlation coefficient at NCSCM AWS location is about 0.99 with Thompson CMS and 0.96 with WSM6 CMS. The study also highlighted time-longitude Hovmöller diagrams, hydrometeor profiles, and relative humidity and vertical wind structures obtained from hourly simulated results.</p>

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Evaluating the role of microphysical schemes in a cloud-resolving scale on simulation of heavy rainfall events near the coastal region of southern India

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • Km Chanchal,
  • Kuvar Satya Singh

摘要

This study evaluates the performance of the Advanced Research version of Weather Research and Forecasting model at a cloud-resolving scale (0.8 km horizontal resolution) in simulating three heavy rainfall events (HREs) Tamil Nadu flood in December 2015, Kerala floods in August 2018 and August 2019 over the coastal regions of South India. A total of 30 simulations were carried out using ten different cloud microphysical schemes (CMSs) to investigate their impact on three HREs. Results were validated using datasets from Doppler Weather Radar, Automatic Weather Stations, and the IMERG satellite precipitation product. The results show that no single CMS consistently outperformed for the simulation of all three HREs. The WSM6 and Thompson CMSs provided a better results for Tamil Nadu 2015 case and WSM6 CMS for the Kerala flood in 2018. However, none of the CMSs effectively captured the spatial rainfall patterns of the 2019 Kerala flood. The probability of detection using 24 h accumulated rainfall at 32 locations with threshold exceeded 250 mm was approximately 78% with WSM6 CMS and followed by NSSL 2-mom scheme with 68% for Tamil Nadu case. The correlation coefficient at NCSCM AWS location is about 0.99 with Thompson CMS and 0.96 with WSM6 CMS. The study also highlighted time-longitude Hovmöller diagrams, hydrometeor profiles, and relative humidity and vertical wind structures obtained from hourly simulated results.