Long Term Assimilation of Directional Wave Data From CFOSAT in the Wave Prediction Model MFWAM

Assimilation à long terme des données de vagues directionnelles de CFOSAT dans le modèle de prévision des vagues MFWAM

Bedossa, Emma ; Aouf, Lofti ; Hauser, D. ; Dalphinet, Alice ; Giordani, Hervé ; Collard, F.

Année de publication
2026

Recently, satellite wave observations have stepped forward with the innovative measurements from the wave scatterometer SWIM of the CFOSAT mission which provides both the significant wave height (SWH) along-track at nadir look and the directional wave spectra on off-nadir incidence angle. This work aims at evaluating the impact of the assimilation of SWIM wave observations on the wave forecast, and at analyzing the improvement of estimating wave properties. Runs of the MFWAM model with and without assimilation of SWIM data have been performed for a long period from 2019 to 2022. SWIM wave data is used with the improved level 2 processing version 6, operational since June 2023. The validation of model runs is performed against independent SWH from independent altimeters and against drifting wave buoys parameters provided by the SOFAR network during the year 2021. The results show an improvement of integrated wave parameters induced by the assimilation compared with observations, especially when wavenumbers and SWH are assimilated jointly. The scatter index of SWH when assimilation of wave heights from SWIM is activated is improved by 15%, globally and 9.5% in the tropics. This impact increases to 18% for the Southern ocean, known for severe storms and long swell dominant sea state. In this study we also show that the assimilation of directional wave spectra is more efficient to reduce the bias and scatter index on the peak period, than the assimilation of significant wave height only, and we discuss the improvement of the assimilation scheme in the MFWAM model.</div>

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