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<p>Prolonged periods of anomalously high sea surface temperatures (SSTs) are becoming increasingly frequent and intense due to climate change and regional climate variability. Accurate seasonal prediction of marine heatwaves (MHWs) is crucial for developing early warning systems and ensuring sustainable management of marine resources. This study evaluates the prediction skill of MHWs in the Indian Ocean and surrounding basins using the Monsoon Mission Coupled Forecast System version 1 (MMCFSv1) for the period 1982–2017. MHWs are detected using the 90th percentile SST threshold from the full ensemble distribution across model members. Forecast skill is assessed using the Pearson correlation coefficient and Mean Squared Skill Score (MSSS) for various lead times and initial conditions. Results show that seasonal forecasts possess good forecast skill across key regions, including the Western Arabian Sea, the North Bay of Bengal, and the North-East Pacific, particularly during the March-April-May (MAM) and June-July-August (JJA) seasons. Ensemble-based thresholds better capture the spatial and temporal variability of MHWs. The highest skill is observed with initializations in February and March, while later months show a gradual decline in performance. This study highlights the importance of ensemble spread in capturing MHW extremes and provides a robust framework for enhancing seasonal MHW forecasts. The findings contribute to advancing climate-resilient planning and marine hazard mitigation strategies in the Indian Ocean basin.</p>

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Seasonal forecasts of marine heat waves using Monsoon Mission Climate ForecaSt system

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Ashish Alone,
  • Ankur Srivastava,
  • Suryachandra A. Rao,
  • Maheswar Pradhan,
  • Geetanjali S.,
  • Aarti Soni,
  • Sudheer Joseph

摘要

Prolonged periods of anomalously high sea surface temperatures (SSTs) are becoming increasingly frequent and intense due to climate change and regional climate variability. Accurate seasonal prediction of marine heatwaves (MHWs) is crucial for developing early warning systems and ensuring sustainable management of marine resources. This study evaluates the prediction skill of MHWs in the Indian Ocean and surrounding basins using the Monsoon Mission Coupled Forecast System version 1 (MMCFSv1) for the period 1982–2017. MHWs are detected using the 90th percentile SST threshold from the full ensemble distribution across model members. Forecast skill is assessed using the Pearson correlation coefficient and Mean Squared Skill Score (MSSS) for various lead times and initial conditions. Results show that seasonal forecasts possess good forecast skill across key regions, including the Western Arabian Sea, the North Bay of Bengal, and the North-East Pacific, particularly during the March-April-May (MAM) and June-July-August (JJA) seasons. Ensemble-based thresholds better capture the spatial and temporal variability of MHWs. The highest skill is observed with initializations in February and March, while later months show a gradual decline in performance. This study highlights the importance of ensemble spread in capturing MHW extremes and provides a robust framework for enhancing seasonal MHW forecasts. The findings contribute to advancing climate-resilient planning and marine hazard mitigation strategies in the Indian Ocean basin.