Generation of super-resolution gap-free ocean colour satellite products using data-interpolating empirical orthogonal functions (DINEOF)

Alvera-Azcárate, Aida; Van der Zande, Dimitry; Barth, Alexander; Dille, Antoine; Massant, Joppe; Beckers, Jean-Marie

doi:https://doi.org/10.5194/os-21-787-2025

Articles | Volume 21, issue 2

https://doi.org/10.5194/os-21-787-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Special Issue for the 54th International Liège Colloquium...

https://doi.org/10.5194/os-21-787-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 2

Research article

|

16 Apr 2025

Research article |

| 16 Apr 2025

Generation of super-resolution gap-free ocean colour satellite products using data-interpolating empirical orthogonal functions (DINEOF)

Aida Alvera-Azcárate, Dimitry Van der Zande, Alexander Barth, Antoine Dille, Joppe Massant, and Jean-Marie Beckers

Supplement

https://doi.org/10.5194/os-21-787-2025-supplement

Data sets

Physical State of the Sea - Belgian Coastal Zone - COHERENS UKMO Royal Belgian Institute of Natural Sciences, Directorate Natural Environment, Marine Forecasting Centre https://erddap.naturalsciences.be/erddap/griddap/BCZ_HydroState_V1.html

Model code and software

aida-alvera/DINEOF: DINEOF v2.0.0 A. Alvera-Azcárate et al. https://doi.org/10.5281/zenodo.15187824

Short summary

This work presents an approach for increasing the spatial resolution of satellite data and interpolating gaps due to cloud cover, using a method called DINEOF (data-interpolating empirical orthogonal functions). The method is tested on turbidity and chlorophyll-a concentration data in the Belgian coastal zone and the North Sea. The results show that we are able to improve the spatial resolution of these data in order to perform analyses of spatial and temporal variability in coastal regions.