Atmospheric Drivers of North Atlantic Marine Heatwaves: Event‑Scale Detection and Links to Climate Modes Variability

Marine Heatwaves (MHWs), defined as prolonged periods of anomalously warm ocean temperatures, have gained increasing scientific attention due to their significant ecological and socioeconomic consequences. Despite advances in MHW detection and characterisation, the mechanisms driving their onset and evolution remain an active area of research. As part of the Horizon Europe ObsSea4Clim project, this study investigates the influence of atmospheric circulation and climate modes of variability on MHWs in the North Atlantic basin. Preliminary findings underscore the critical role of large-scale atmospheric circulation, particularly the positioning and intensity of high-pressure systems, in modulating air–sea heat flux anomalies. These circulation patterns suppress wind speeds, enhance oceanic heat absorption, and consequently influence the spatial distribution, intensity, and duration of MHWs. To better capture the spatiotemporal coherence of these events, we advance from a pixel-wise to an event-based detection framework, enabling the labelling and ranking of spatially organised, scale-dependent MHWs. Enhancements to the spatial filtering and labelling algorithm further improve the detection of event structure and propagation pathways. Building on previous analyses, we apply non-linear statistical techniques, including Spearman’s rank correlation and Mutual Information, to more robustly quantify relationships between MHW characteristics and atmospheric drivers. Composite analyses for positive and negative phases of the North Atlantic Oscillation (NAO) are refined using a monthly NAO index and complemented with the Eastern Atlantic (EA) index, allowing for a more detailed representation of temporal variability. Furthermore, the statistical significance of these results is tested. Together, these advances deepen understanding of the atmospheric drivers of North Atlantic MHWs and enhance the potential for improved prediction of extreme ocean temperature events.