Data assimilation of wave spectra observations and its impact on sea state predictions

General Information

DAWN aims to explore the beneficial impact of wave spectra assimilation on the predictability of wave forecast systems and the potential improvement to the sea state. Scientific evaluation of the new implementations into the wave model WAM will demonstrate the added value in improving the open ocean and coastal/regional seas’ forecasts. Furthermore, assessments of prediction skills relevant for delivery and integrations into the Copernicus Marine Environment Monitoring Service (CMEMS) will be performed. State-of-the-art machine learning (ML) techniques will be applied to global wave model simulations, providing new opportunities to improve the forecasting capabilities. We also propose new methodologies for spectral metrics and spectral validation that will be further implemented into the CMEMS product quality framework and will add value to the CMEMS forecast products. This will be done in close collaboration with CMEMS Monitoring Forecasting Centres (MFCs). The project brings together a consortium with complementary competence on wave modelling, artificial intelligence, and data assimilation. The improved WAM code including spectral data assimilation will be made publicly available enabling its use for other MFCs.

EU-Programme Acronym and Subprogramme Area	COPERNICUS Ocean (CMEMS)
Project Type	COPERNICUS Tender
Contract Number	23138-COP-INNO SCI-9000 – Lot nr. 1
Co-ordinator	Hereon (DE)

Funding for the Project (€)	Funding for Hereon (€)
130,000 €	130,000 €

Contact Person at Hereon

Dr. Marcel Ricker, Coastal Systems - Analysis and Modeling Hydrodynamics and Data Assimilation, KSD, phone: +49 (0)4152 87-1506 E-mail contact

Participants

Météo France, Centre de Recherches Météorologiques (FR)

Last Update: 18. October 2024