EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Towards explainable marine heatwaves forecasts

Ayush Prasad1 and Swarnalee Mazumder2
Ayush Prasad and Swarnalee Mazumder
  • 1Faculty of Science, University of Helsinki, Helsinki, Finland (
  • 2School of Integrated Climate System Science, University of Hamburg, Hamburg, Germany (

In recent years, both the intensity and extent of marine heatwaves have increased across the world. Anomalies in sea surface temperature have an effect on the health of marine ecosystems, which are crucial to the Earth's climate system. Marine Heatwaves' devastating impacts on aquatic life have been increasing steadily in recent years, harming aquatic ecosystems and causing a tremendous loss of marine life. Early warning systems and operational forecasting that can foresee such events can aid in designing effective and better mitigation techniques. Recent studies have shown that machine learning and deep learning-based approaches can be used for forecasting the occurrence of marine heatwaves up to a year in advance. However, these models are black box in nature and do not provide an understanding of the factors influencing MHWs. In this study, we used machine learning methods to forecast marine heatwaves. The developed models were tested across four historical Marine Heatwave events around the world. Explainable AI methods were then used to understand and analyze the relationships between the drivers of these events.

How to cite: Prasad, A. and Mazumder, S.: Towards explainable marine heatwaves forecasts, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13622,, 2023.