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<p>This study evaluates the performance of artificial intelligence based weather forecasting model, namely, Pangu-Weather in predicting the tropical cyclones Dana and Remal over the Bay of Bengal. These cyclones occurred during the post-monsoon (22–26 Oct) and pre-monsoon (24–28 May) seasons of 2024, respectively. The Pangu-Weather model demonstrates high accuracy in forecasting the intensity as well as track of the tropical cyclones. The winds, mean sea level pressure, and geopotential height during the different phases of cyclones are correctly predicted by the model. The influence of model initialization time on cyclone forecast accuracy is also examined by carrying out different sensitivity experiments.</p>

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Evaluating the performance of Pangu-Weather model for Dana and Remal tropical cyclones over the Bay of Bengal

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Alok Kumar Mishra,
  • Suneet Dwivedi,
  • Shivam Kesarwani

摘要

This study evaluates the performance of artificial intelligence based weather forecasting model, namely, Pangu-Weather in predicting the tropical cyclones Dana and Remal over the Bay of Bengal. These cyclones occurred during the post-monsoon (22–26 Oct) and pre-monsoon (24–28 May) seasons of 2024, respectively. The Pangu-Weather model demonstrates high accuracy in forecasting the intensity as well as track of the tropical cyclones. The winds, mean sea level pressure, and geopotential height during the different phases of cyclones are correctly predicted by the model. The influence of model initialization time on cyclone forecast accuracy is also examined by carrying out different sensitivity experiments.