A 3-decade advancements in prediction of tropical cyclones and other severe weather over India: A recap
DOI:
https://doi.org/10.54302/mausam.v76i4.7271Keywords:
Weather forecasting, Machine learning, Deep learning, Neural networks, Polar weather data, Data scienceAbstract
India has been witnessing frequent and deadly extreme weather events in recent years. These events are becoming increasingly complex due to the compound effects of climate change, urbanization, and land-use land-cover changes, making their accurate prediction a major challenge for both research and operational communities. Numerical Weather Prediction (NWP) has been a vital tool in providing the early warnings, thereby helping to reduce the damage to properties, minimize adverse impact on human life, and limits the country’s economic losses. This review summarizes progress in NWP research over the past three decades, with a focus on improving forecasts of weather extremes (tropical cyclones and associated storm surge, thunderstorms, heatwaves, and urban rainfall) affecting India. These advancements have been made possible through continuous R&D efforts and the support of India Meteorological Department (IMD) in increasing the observational network, severe weather monitoring, and providing timely assistance to the research community in advancing NWP capabilities and reached satisfactory prediction skills that enhanced the reliability in the decision support systems.
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