Sub-seasonal prediction for global marine heatwaves and their implications for Biodiversity

Marine heatwaves (MHWs) are prolonged extreme ocean warming events with profound socioeconomic and ecological consequences. While accurate sub-seasonal MHW prediction is critical for proactive marine management, its achievable performance, particularly in global biodiversity hotspots vital to ecosystem-dependent economies, remains poorly understood. Here, we evaluate MHW sub-seasonal prediction skill across the global ocean using current state-of-the-art operational prediction models, emphasizing marine biodiversity hotspots. We show that MHWs are predictable up to two weeks in advance on average globally, with a twofold improvement potential under perfect-model assumptions. The prediction skill for MHWs is most notable as it approaches the model's upper limits in regions influenced by climate modes. However, in nearly two-thirds of marine biodiversity hotspots, the skill remains relatively low, lasting less than two weeks. La Niña conditions generally enhance prediction skill across most marine hotspot regions, primarily in the western Pacific Ocean, whereas El Niño conditions, although extending predictability up to six weeks in the tropical central-eastern Pacific and tropical western Indian Ocean, exhibit significant skills along the western coast of the Americas for global biological hotspot seas. These findings highlight the need for model refinements prioritizing biodiverse regions and leveraging specific climate events to develop more accurate MHW forecasts.