FORESEE - FOREcasting Sea statE Extremes

FORESEE has progressed on WP1 (metocean conditions) and WP2 (model development). The primary focus of WP1 was to explore the connection between large scale metocean conditions and extreme sea state events in the different mandate regions. Preliminary datasets were established containing such conditions (i.e. NAO, AO, ElNino, sea ice extent, ...) together with extreme sea state events for all considered regions (i.e. North Sea, Norwegian Sea, Barents Sea) for subsequent quantification and modelling attempts. A statistical model / workflow based on generalized additive models was developed for covariates season and direction. It is planned to extend this framework for the relevant metocean conditions. Validation of the NORA3 dataset is being performed using Triple Collocation. The implementation of this method at MET Norway was made public through a git repository (https://github.com/bohlinger/wavy) and is currently applied to our core datasets. To bring together all FORESEE members a 3-day workshop was held in Sotra (close to Bergen). There, first results were presented and everyone was briefed in statistics of extreme sea states. Two additional collaborations were established during this phase, one with KNMI (Netherlands) on model validation and triple collocation where a research visit is planned and one collaboration with Maynooth University (Ireland) on metocean precursors. In total, two PhD students were hired in the project were both started on a manuscript for their first results, one manuscript on metocean conditions and one manuscript on validation with triple collocation. Results from the project were presented at various conferences and workshops such as the 55th International Liège Colloquium on Ocean Dynamics, Topic Ocean Extremes. At this stage the described work is in line with the intended deliverables D1.1 (processed datasets containing extreme events), D1.2 (manuscript on involved metocean) conditions, and D2.1 (covariates for metocean conditions and build a statistical EVT model).

Extreme sea states have tremendous impact on marine structural design and offshore operations where high assets and human lives are at stake. It is of paramount importance to map and understand the physical processes leading to these extremes and to correctly estimate their probability and magnitude. We will focus on large scale metocean conditions associated with extreme sea states. For our three regions of interest, the Central North Sea, Norwegian Sea, and the Barents Sea, such metocean conditions have not yet been assessed systematically despite their immense value for improving return level estimates. Even though the predictive skill of forecasting synoptic scale meteorological conditions on sub-seasonal to seasonal time scales advanced greatly over the last decade, it has not been utilized to predict exceedance probabilities and return level estimates. Being able to answer a question like: ”What is the probability for exceeding 7 m SWH in the coming season” would make the long-term planning of offshore operations more reliable and precise and thus reduce risks and costs significantly. We plan to create a superior statistical extreme value model for our regions based on large wave hindcast datasets including the knowledge of metocean conditions connected to extreme sea states. Expanding this model to seasonal forecasts from the European Centre for Medium-Range Weather Forecasts will yield the first seasonal extreme sea state prediction system. This task will be achieved by combining strong interdisciplinary and international expertise on meteorology, ocean surface waves, and statistical modelling of environmental hazards. Our custom-fit dissemination plan will convey the knowledge and product to where it is needed.