Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea

Abstract

Optical-biogeochemical relationships of particulate and dissolved organic matter are presented in support of remote sensing of the Baltic Sea pelagic. This system exhibits strong seasonality in phytoplankton community composition and wide gradients of chromophoric dissolved organic matter (CDOM), properties which are poorly handled by existing remote sensing algorithms. Absorption and scattering properties of particulate matter reflected the seasonality in biological (phytoplankton succession) and physical (thermal stratification) processes. Inherent optical properties showed much wider variability when normalized to the chlorophyll-a concentration compared to normalization to either total suspended matter dry weight or particulate organic carbon. The particle population had the largest optical variability in summer and was dominated by organic matter in both seasons. The geographic variability of CDOM and relationships with dissolved organic carbon (DOC) are also presented. CDOM dominated light absorption at blue wavelengths, contributing 81% (median) of the absorption by all water constituents at 400 nm and 63% at 442 nm. Consequentially, 90% of water-leaving radiance at 412 nm originated from a layer (z90) no deeper than approximately 1.0 m. With water increasingly attenuating light at longer wavelengths, a green peak in light penetration and reflectance is always present in these waters, with z90 up to 3.0–3.5 m depth, whereas z90 only exceeds 5 m at biomass < 5 mg Chla m-3. High absorption combined with a weakly scattering particle population (despite median phytoplankton biomass of 14.1 and 4.3 mg Chla m-3 in spring and summer samples, respectively), characterize this sea as a dark water body for which dedicated or exceptionally robust remote sensing techniques are required. Seasonal and regional optical-biogeochemical models, data distributions, and an extensive set of simulated remote-sensing reflectance spectra for testing of remote sensing algorithms are provided as supplementary data.

Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans

“…The exp{c} found in this study (0.532) was higher than the value found by Bricaud et al [45] of 0.0398; however, the MERIS RMD value used for conversion of from a p (442) is intermediate (0.0434); Simis et al [92] found an average value of 0.0555 across Baltic Sea basins and seasons.…”

“…Oligotrophic waters are usually dominated by picoplanktonic species that usually have stronger pigment packaging than microplankton-which with its relative low a p *(442) dominates the Baltic Sea. The observed value of (n − 1) −0.477 (R 2 = 0.4667) was higher than that of Bricaud et al [45] −0.339 (R 2 = 0.767) but considerably different from the value of −0.996 in the MERIS RMD; Simis et al [92] found a value of −0.307 (R 2 = 0.43). Their campaign covered both spring and summer seasons in different Baltic Sea basins, whereas the current study has a focus on the NW Baltic proper during the summer months.…”

Shifting Diatom—Dinoflagellate Dominance During Spring Bloom in the Baltic Sea and its Potential Effects on Biogeochemical Cycling

“…Kahru et al (2016) also reported that the summer community of phytoplankton is becoming more abundant than the spring community based on satellite observations of Chl a. However, the Chl a determination from remote sensing is difficult to estimate (Darecki and Stramski, 2004), and recent direct measurements of Chl a, covering large parts of the Baltic Sea, demonstrate that the Chl a concentration during spring is still much higher than during summer in the main basins of the Baltic Sea (Simis et al, 2017). FIGURE 1 | Spatial variability of the spring bloom peak biomass (wet weight, mg L −1 ) in the Baltic Sea.…”

Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument imagery in the Baltic Sea

“…Diatoms dominate the spring bloom that occurs after ice melt and cyanobacteria dominate during summer and early autumn. Optical properties of these two assemblages are so different that seasonal remote sensing algorithms may be needed [10,11]. There are also indications that the seasonality is changing [12,13].…”