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<p>Cloudbursts are brief, intense rainfall occurrences that present significant risks to human life, infrastructure, and ecosystems, especially in the Indian Himalayan Region (IHR). Despite their damaging characteristics, predicting these events remains challenging due to their localized nature, the influence of complex terrain, and a lack of high-resolution observational data. Therefore, enhancing the simulation and comprehension of such occurrences is crucial for improved forecasting and disaster readiness. This research introduces a high-resolution computational modeling technique utilizing the Weather Research and Forecasting (WRF) model to replicate cloudburst events in the Indian Himalayan Region (IHR) during the monsoon season of 2022. These extreme weather phenomena, marked by intense and localized rainfall, are hard to forecast because of the region's complex terrain and convective dynamics. In this study six representative cloudburst events from Himachal Pradesh, Uttarakhand, and Jammu &amp; Kashmir were simulated at a resolution of 3&#xa0;km using six-hourly NCEP-FNL reanalysis data. The analysis concentrated on critical atmospheric mechanisms such as vorticity, convective instability (CAPE, CINE), moisture availability, and orographic lifting. The model outputs were validated against daily rainfall data from the India Meteorological Department (IMD), Global Precipitation Measurement Mission (GPM), and the CPC MORPHing technique (CMORPH). The model demonstrated a strong correlation with IMD data (correlation coefficient of 0.84 and RMSE of 45.07&#xa0;mm), although performance varied with satellite-based datasets. This study contributes to understanding the simulation of cloudburst events using high-resolution regional modeling and multiple observational validations.</p>

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Studying the dynamics of cloudburst events over Indian Himalayan region using model simulation

  • 期刊论文

  • 发表日期：

    2025年12月2日

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  • Payoshni Samantray,
  • Krushna Chandra Gouda

摘要

Cloudbursts are brief, intense rainfall occurrences that present significant risks to human life, infrastructure, and ecosystems, especially in the Indian Himalayan Region (IHR). Despite their damaging characteristics, predicting these events remains challenging due to their localized nature, the influence of complex terrain, and a lack of high-resolution observational data. Therefore, enhancing the simulation and comprehension of such occurrences is crucial for improved forecasting and disaster readiness. This research introduces a high-resolution computational modeling technique utilizing the Weather Research and Forecasting (WRF) model to replicate cloudburst events in the Indian Himalayan Region (IHR) during the monsoon season of 2022. These extreme weather phenomena, marked by intense and localized rainfall, are hard to forecast because of the region's complex terrain and convective dynamics. In this study six representative cloudburst events from Himachal Pradesh, Uttarakhand, and Jammu & Kashmir were simulated at a resolution of 3 km using six-hourly NCEP-FNL reanalysis data. The analysis concentrated on critical atmospheric mechanisms such as vorticity, convective instability (CAPE, CINE), moisture availability, and orographic lifting. The model outputs were validated against daily rainfall data from the India Meteorological Department (IMD), Global Precipitation Measurement Mission (GPM), and the CPC MORPHing technique (CMORPH). The model demonstrated a strong correlation with IMD data (correlation coefficient of 0.84 and RMSE of 45.07 mm), although performance varied with satellite-based datasets. This study contributes to understanding the simulation of cloudburst events using high-resolution regional modeling and multiple observational validations.