DIVAnd: a free tool for HFR data gap-filling using SOCIB continuous observations

Researchers at the University of Liège-GHER and SOCIB publish a new study about the use of the DIVAnd (Data-Interpolating Variational Analysis, in n-dimensions) free tool for High-frequency radar (HFR) data gap-filling. In this study, DIVAnd has been applied to HFR radial current measurements from the Ibiza Channel.

DIVAnd, developed by the GeoHydrodynamics and Environment Research group (GHER), is a software to spatially interpolate in situ data, thus obtaining a gridded (continuous) field from sparse (discrete) data points. In this study, DIVAnd has been applied to HFR radial current measurements from the Ibiza Channel in order to achieve integrative applications with gap-free 2D surface currents. To that end, researchers have used various dynamic constraints relevant to ocean surface currents, such as the imposition of a zero normal velocity at the coastline, a low horizontal divergence of the surface currents, temporal coherence, and simplified dynamics based on the Coriolis force and the possibility of including a surface pressure gradient.

The impact of these constraints has been evaluated by cross-validation using SOCIB’s HFR and Lagrangian drifters ocean surface current observations of the Ibiza Channel. These observations have shown that dynamical information appears to be quite beneficial when analyzing ocean surface currents. The best results have been obtained using the Coriolis force and the ocean surface pressure gradient as a constraint. Furthermore, it has been shown that this constraint is able to improve the reconstruction from the Open-boundary Modal Analysis, a quite commonly used method to interpolate HFR observations, once multiple time instances are considered together.

Overall, the researchers have demonstrated that if large data gaps exist in space and/or time, using an interpolation algorithm able to leverage a priori information about the field to interpolate, such as dynamical constraints, can be beneficial and can avoid excessive smoothing when interpolating over large gaps. Now, the next steps to provide gap-filled HFR data on an operational basis, aligned with the roadmap of the EuroGOOS HFR Task Team, are: homogenize the methodology to be applied; define a common data and metadata model to standardize the data; and promote the ingestion and dissemination of these added-value products by means of the main European data portals (ie. CMEMS, EMODnet -Physics, Sea Data Net, etc.).

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