Extremes in the marine environment: analysis of multi-temporal and multi-scale dynamics using observations, models, and machine learning techniques
Extremes in the marine environment: analysis of multi-temporal and multi-scale dynamics using observations, models, and machine learning techniques
Editor(s): Antonio Ricchi, Giovanni Liguori, Matjaz Licer, Milena Menna, Clea Denamiel, Aida Alvera-Azcárate, Joanna Staneva, and John C. Warner
Despite their socio-economic and environmental impacts, extreme events in the marine environment are generally poorly understood, simulated, or predicted. In particular, the dynamics of these events involve multiple temporal and spatial scales and can be driven by different mechanics and complex feedback involving the ocean and its interaction with the other spheres of the climate system. In response to climate change, the frequency and magnitude of these events could dramatically change, resulting in significant impacts on human life and property as well as on marine ecosystems. Hence, advancing our understanding of the dynamics leading to extremes in marine environments is crucial for improving their predictability, which, in turn, will help to achieve environmental and social sustainability. With this rationale, the special issue will focus on marine extremes at multiple temporal and spatial scales. Studies discussing ocean dynamics and air–sea interactions that can influence the evolution of marine extremes are particularly welcome; the inclusion of work using techniques ranging from in situ to remote-sensing observations and from numerical models to innovative artificial intelligence techniques (e.g. machine learning) is also encouraged. This diversity of topics will make for a highly multidisciplinary special issue, open to multiple applications in the field of marine extremes. Contributions related to the investigation of marine heat waves, marine storminess, storm surge and sea level rise, dense-water formation, deep-ocean extreme events, etc. are other examples of potential topics. The special issue has been stimulated by the EGU General Assembly 2023, session OS4.6, but all submissions on this topic are welcome, regardless of whether authors participated in the conference.

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Preprint under review for OS (discussion: final response, 2 comments)
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