Abstract
In order to retrieve geophysical satellite products in coastal waters with high coloured dissolved organic matter (CDOM), models and processors require parameterization with regional specific inherent optical properties (sIOPs). The sIOPs of the Baltic Sea were evaluated and compared to a global NOMAD/COLORS Reference Data Set (RDS), covering a wide range of optical provinces. Ternary plots of relative absorption at 442 nm showed CDOM dominance over phytoplankton and non-algal particle absorption (NAP). At 670 nm, the distribution of Baltic measurements was not different from case 1 waters and the retrieval of Chl a was shown to be improved by red-ratio algorithms. For correct retrieval of CDOM from Medium Resolution Imaging Spectrometer (MERIS) data, a different CDOM slope over the Baltic region is required. The CDOM absorption slope, SCDOM, was significantly higher in the northwestern Baltic Sea: 0.018 (±0.002) compared to 0.016 (±0.005) for the RDS. Chl a-specific absorption and ad [SPM]*(442) and its spectral slope did not differ significantly. The comparison to the MERIS Reference Model Document (RMD) showed that the SNAP slope was generally much higher (0.011 ± 0.003) than in the RMD (0.0072 ± 0.00108), and that the SPM scattering slope was also higher (0.547 ± 0.188) vs. 0.4. The SPM-specific scattering was much higher (1.016 ± 0.326 m2 g−1) vs. 0.578 m2 g−1 in RMD. SPM retrieval could be improved by applying the local specific scattering. A novel method was implemented to derive the phase function (PF) from AC9 and VSF-3 data. b ˜ was calculated fitting a Fournier–Forand PF to the normalized VSF data. b ˜ was similar to Petzold, but the PF differed in the backwards direction. Some of the sIOPs showed a bimodal distribution, indicating different water types—e.g., coastal vs. open sea. This seems to be partially caused by the distribution of inorganic particles that fall out relatively close to the coast. In order to improve remote sensing retrieval from Baltic Sea data, one should apply different parameterization to these distinct water types, i.e., inner coastal waters that are more influenced by scattering of inorganic particles vs. open sea waters that are optically dominated by CDOM absorption.
Highlights
The aim of this study is to (i) improve the optical characterization of the Baltic Sea in order to improve the parameterization for remote sensing inversion models for coastal waters with high coloured dissolved organic matter (CDOM) absorption; and to (ii) identify which of the optical properties differ significantly from other seas and oceans; and to (iii) compare the optical properties of the Baltic Sea to those implemented in the European Space Agency (ESA) Medium Resolution Imaging Spectrometer (MERIS) reference model document (RMD) [55]
For the global Reference Data Set (RDS), the median [chlorophyll a (Chl a)] was 0.73 μg L−1. [suspended particulate matter (SPM)] had a median of 1.31 g m−3 in the Baltic and 1.88 g m−3 for the global RDS. aCDOM had a median value of 0.42 m−1 in this study, which is relatively high when compared to other seas and oceans
The specific inherent optical properties (sIOPs) comparison here shows that the Baltic Sea differs significantly in several sIOPs from the global data set, and from the parameterization in the MERIS Reference Document which can be improved
Summary
The high freshwater input from land combined with the relatively low input of saline bottom waters from the North Sea cause a strong halocline with saline waters at the bottom and brackish water at the top. A stable halocline is situated at about 40–70 m depth in the Baltic proper and acts as density barrier between the saline deep waters and the brackish surface waters. The deep-water salinity is about 10–13 in the Baltic Sea proper and 3–7 in the Gulf of Bothnia. Surface salinity ranges from about 1.8–3.9 in the inner Bothnian Bay, 3.8–6.6 in the Gulf of Bothnia, 5.0–11.3 in the Baltic proper, and 5.0–7.5 in the Western Gotland Sea. The renewal time for the Baltic Sea is estimated in the range of about 30–40 years [2]
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