Correcting surface winds by assimilating high-frequency radar surface currents in the German Bight

• Published in: Ocean dynamics Vol. 61; no. 5; pp. 599 - 610
• Main Authors: Barth, Alexander, Alvera-Azcárate, Aida, Beckers, Jean-Marie, Staneva, Joanna, Stanev, Emil V., Schulz-Stellenfleth, Johannes
• Format: Journal Article Web Resource
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.05.2011; Springer Nature B.V; Springer Science & Business Media B.V
• Subjects: Atmospheric Sciences; Boundary conditions; Data assimilation; Data collection; Earth and Environmental Science; Earth Sciences; Earth sciences & physical geography; Fluid- and Aerodynamics; Geophysics/Geodesy; German Bight; In situ measurement; Mean square errors; Monitoring/Environmental Analysis; ocean modelling; Oceanography; Physical, chemical, mathematical & earth Sciences; Physique, chimie, mathématiques & sciences de la terre; Radar; Sciences de la terre & géographie physique; Sea surface temperature; Studies; Surface circulation; Topical Collection on Multiparametric observation and analysis of the Sea; Weather; Weather forecasting; Wind; Wind speed; Ensemble simulation; High-frequency radar; Surface currents; Data assimilation
• ISSN: 1616-7341; 1616-7228; 1616-7228
• DOI: 10.1007/s10236-010-0369-0

Surface winds are crucial for accurately modeling the surface circulation in the coastal ocean. In the present work, high-frequency radar surface currents are assimilated using an ensemble scheme which aims to obtain improved surface winds taking into account European Centre for Medium-Range Weather Forecasts winds as a first guess and surface current measurements. The objective of this study is to show that wind forcing can be improved using an approach similar to parameter estimation in ensemble data assimilation. Like variational assimilation schemes, the method provides an improved wind field based on surface current measurements. However, the technique does not require an adjoint, and it is thus easier to implement. In addition, it does not rely on a linearization of the model dynamics. The method is validated directly by comparing the analyzed wind speed to independent in situ measurements and indirectly by assessing the impact of the corrected winds on model sea surface temperature (SST) relative to satellite SST.