Preprints
https://doi.org/10.5194/essd-2025-443
https://doi.org/10.5194/essd-2025-443
08 Aug 2025
 | 08 Aug 2025
Status: this preprint is currently under review for the journal ESSD.

Optical complexity of North Sea, Baltic Sea, and adjacent coastal and inland waters derived from satellite data

Martin Hieronymi, Daniel Behr, Shun Bi, and Rüdiger Röttgers

Abstract. Despite advances in remote sensing, consistent monitoring of water quality across freshwater-marine systems remains challenging due to methodological fragmentation. Here, we provide an overview of an exemplary dataset on water quality characteristics in inland waters, coasts, and the open sea estimated from optical satellite data. Specifically, this is Sentinel-3 OLCI data for the entire North Sea and Baltic Sea region for the period June to September 2023. The dataset includes daily aggregated observational data with a spatial resolution of approximately 300 m of reflectance at the top-of-atmosphere and for cloud-free water areas remote-sensing reflectance, inherent optical properties of the water, and an estimation of the concentrations of water constituents, e.g. related to the aquatic carbon content. These are the results of the novel A4O atmospheric correction and the ONNS water algorithm. The dataset serves as a prototype for understanding the processing chain and interdependencies, but also for developing a high degree of connectivity for answering various scientific questions; we do not perform an actual validation of the 73 individual parameters in the dataset. The aim is to show how fragmentation in water quality monitoring along the aquatic continuum from lakes, rivers to the sea can be overcome by applying an optical water type-specific and neural network-based processing scheme for Copernicus satellite data. Emphasis of this work is on analysing the optical complexity of remote-sensing reflectance in the North Sea, Baltic Sea, coastal, and inland waters. Results of a new optical water type classification show that almost all (99.7 %) remote-sensing reflectances delivered by A4O are classifiable and that the region exhibits the full range of optical water diversity. The dataset can serve as a blueprint for a holistic view of the aquatic environment and is a step towards an observation-based digital twin component of the complex system.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Martin Hieronymi, Daniel Behr, Shun Bi, and Rüdiger Röttgers

Status: open (until 14 Sep 2025)

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Martin Hieronymi, Daniel Behr, Shun Bi, and Rüdiger Röttgers

Data sets

Sentinel-3 OLCI daily averaged earth observation data of water constituents Martin Hieronymi et al. https://doi.org/10.26050/WDCC/AquaINFRA_Sentinel3

Martin Hieronymi, Daniel Behr, Shun Bi, and Rüdiger Röttgers

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Short summary
We provide scientific descriptions of a Copernicus satellite-based dataset and its novel processing chain. The data include water quality properties of lakes, rivers, coasts, as well as the entire North Sea and Baltic Sea. Moreover, the data include a novel estimate of organic carbon in diverse waters and results of a new optical water type classification. The dataset and algorithm behind offers many links to future oceanographic-limnological analysis.
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