Towards explainable marine heatwaves forecasts

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.