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<p>Extreme rainfall during the 2019 Indian southwest monsoon caused widespread flooding and severe socio-economic impacts. Here, we integrate multi-spectral satellite observations (TRMM Precipitation Radar and INSAT-3D/Meteosat-8 infrared and water-vapour channels) to develop a high-resolution (0.1° × 0.1°) Rain Index (RI) for capturing short-duration, localized convective events. By correlating RI with in-situ radar measurements, we achieve a robust nonlinear model (correlation coefficient = 0.92; RMSE = 4.55&#xa0;mm&#xa0;h⁻<sup>1</sup>). Rainfall anomalies during July–August 2019 exceeded historical averages by 10% over northern, western, and central India, largely driven by a strong positive Indian Ocean Dipole (IOD) that partially offset a weak El Niño phase. Monthly anomaly maps reveal regions in Rajasthan, Kerala, and Assam experiencing rainfall surpluses of up to 20%. These findings demonstrate the utility of satellite-based remote sensing for real-time flood monitoring and underscore the critical role of ocean–atmosphere teleconnections (IOD/ENSO) in modulating monsoon extremes. Our approach provides a transferable framework for high-resolution precipitation estimation, offering actionable insights for disaster preparedness and water-resource management under a changing climate.</p>

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Satellite-based assessment of extreme rainfall during the 2019 Indian monsoon: climatic linkages to IOD and ENSO

  • 期刊论文

  • 发表日期：

    2025年6月23日

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  • Mohammad Suhail Meer,
  • Anoop Kumar Mishra,
  • Vanganuru Nagaraju,
  • Jayanta Das,
  • Aqil Tariq

摘要

Extreme rainfall during the 2019 Indian southwest monsoon caused widespread flooding and severe socio-economic impacts. Here, we integrate multi-spectral satellite observations (TRMM Precipitation Radar and INSAT-3D/Meteosat-8 infrared and water-vapour channels) to develop a high-resolution (0.1° × 0.1°) Rain Index (RI) for capturing short-duration, localized convective events. By correlating RI with in-situ radar measurements, we achieve a robust nonlinear model (correlation coefficient = 0.92; RMSE = 4.55 mm h⁻1). Rainfall anomalies during July–August 2019 exceeded historical averages by 10% over northern, western, and central India, largely driven by a strong positive Indian Ocean Dipole (IOD) that partially offset a weak El Niño phase. Monthly anomaly maps reveal regions in Rajasthan, Kerala, and Assam experiencing rainfall surpluses of up to 20%. These findings demonstrate the utility of satellite-based remote sensing for real-time flood monitoring and underscore the critical role of ocean–atmosphere teleconnections (IOD/ENSO) in modulating monsoon extremes. Our approach provides a transferable framework for high-resolution precipitation estimation, offering actionable insights for disaster preparedness and water-resource management under a changing climate.