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

Sensing the profile of particulate beam attenuation coefficient through a single-photon oceanic Raman lidar

A lidar technique has been proposed and demonstrated for remotely sensing particulate beam attenuation coefficient (cp) profiles using the Raman backscattered signal from water. In Raman lidar, the backscatter coefficient at 180° can be considered constant, allowing for the determination of the lidar attenuation coefficient (Klidar) from the Raman backscattered signal. This scheme has these features. 1) The bandwidth of the filter that used to extract the Raman component from the backscattered signal of the lidar was optimized to ensure sufficient lidar signal strength while minimizing the influence of chlorophyll fluorescence on inversion. 2) A receiving telescope with narrow field of view (FOV) and small aperture was utilized to suppress multi-scattering components in the backscattered signal. 3) A relationship between the beam attenuation coefficient (c) and Klidar was established after simulations via a semi-analytic Monto Carlo. 4) The value of cp was obtained by subtracting the attenuation coefficient of pure seawater (cw) from c. According to the theoretical analysis, the maximum relative error of cp is less than 15% for chlorophyll concentrations up to 10 mg/m3. Due to the water Raman backscattered signal being several orders of magnitude lower than the elastic backscattered signal, a single-photon detector is required to significantly improve the detection sensitivity to the single-photon level. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, and continuous subsurface profiles of cp were obtained. These measurements confirm the robustness and reliability of the oceanic single-photon Raman lidar system and the inversion method.

Phytoplankton dynamics based on satellite inherent optical properties and oceanographic conditions in a patagonian gulf frontal system in relation to the adjacent continental shelf waters

The dynamics of phytoplankton across a seasonal frontal system formed in San José Gulf (SJG, Patagonia Argentina) and in neighbouring shelf waters was assessed based on bio-optical satellite data (2003-2018) and spring and summer in situ samplings. Bio-optical properties of the water masses on the eastern (ED) and western (WD) domains of the seasonal frontal system of SJG showed clear differences: the year-round-vertically-mixed waters from the WD, strongly connected with the adjacent shelf waters, evidenced a brief and strong single phytoplankton bloom, while those from the ED, showing lower exchange with shelf waters and a strong vertical stratification during the warm season, displayed an earlier and long-lasting spring phytoplankton bloom, followed by a late-summer and autumn bloom, both associated with the development and erosion of the seasonal thermocline. Waters from the entire system are optically influenced by the absorption of coloured dissolved organic matter and detritus (cdom + detritus), suggesting a strong sediment load contribution from the continent and the seabed. To remark, a strong correlation between satellite chlorophyll-a (Chla-sat) and absorption by phytoplankton (aphy₄₄₃) in the outer shelf waters differs from the weak correlation of those variables in the gulf's water masses, whose optical parameters are more complex. In situ Chla records may indicate wind-driven upwelling and downwelling areas in the northern and southern coasts of the ED. Dissolved nitrogen was identified as the limiting macronutrient for phytoplankton growth in the ED during summer. This work contributes relevant ecological information that may support management actions on the SJG shellfish artisanal fishery.

Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements

The Sentinel-3 mission launched its first satellite Sentinel-3A in 2016 to be followed by Sentinel-3B and Sentinel-3C to provide long-term operational measurements over Earth. Sentinel-3A and 3B are in full operational status, allowing global coverage in less than two days, usable to monitor optical water quality and provide data for environmental studies. However, due to limited ground truth data, the product quality has not yet been analyzed in detail with the fiducial reference measurement (FRM) dataset. Here, we use the fully characterized ground truth FRM dataset for validating Sentinel-3A Ocean and Land Colour Instrument (OLCI) radiometric products over optically complex Estonian inland waters and Baltic Sea coastal areas. As consistency between satellite and local data depends on uncertainty in field measurements, filtering of the in situ data has been made based on the uncertainty for the final comparison. We have compared various atmospheric correction methods and found POLYMER (POLYnomial-based algorithm applied to MERIS) to be most suitable for optically complex waters under study in terms of product accuracy, amount of usable data and also being least influenced by the adjacency effect.

Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters

Monthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002–2012) were analysed along a horizontal transect from the inner Bråviken bay and out into the open sea. The CHL-a values were calibrated using an algorithm derived from Swedish lakes. Then, calibrated Chl-a and Secchi Depth (SD) estimates were extracted from MERIS data along the transect and compared to conventional monitoring data as well as to data from the Swedish Coastal zone Model (SCM), providing physico-biogeochemical parameters such as temperature, nutrients, Chlorophyll-a (CHL-a) and Secchi depth (SD). A high negative correlation was observed between satellite-derived CHL-a and SD (ρ = −0.91), similar to the in situ relationship established for several coastal gradients in the Baltic proper. We also demonstrate that the validated MERIS-based estimates and data from the SCM showed strong correlations for the variables CHL-a, SD and total nitrogen (TOTN), which improved significantly when analysed on a monthly basis across basins. The relationship between satellite-derived CHL-a and modelled TOTN was also evaluated on a monthly basis using least-square linear regression models. The predictive power of the models was strong for the period May-November (R2: 0.58–0.87), and the regression algorithm for summer was almost identical to the algorithm generated from in situ data in Himmerfjärden bay. The strong correlation between SD and modelled TOTN confirms that SD is a robust and reliable indicator to evaluate changes in eutrophication in the Baltic proper which can be assessed using remote sensing data. Amongst all three assessed methods, only MERIS CHL-a was able to correctly depict the pattern of phytoplankton phenology that is typical for the Baltic proper. The approach of combining satellite data and physio-biogeochemical models could serve as a powerful tool and value-adding complement to the scarcely available in situ data from national monitoring programs. In particular, satellite data will help to reduce uncertainties in long-term monitoring data due to its improved measurement frequency.

Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea

In this study, the Level-2 products of the Ocean and Land Colour Instrument (OLCI) data on Sentinel-3A are derived using the Case-2 Regional CoastColour (C2RCC) processor for the SentiNel Application Platform (SNAP) whilst adjusting the specific scatter of Total Suspended Matter (TSM) for the Baltic Sea in order to improve TSM retrieval. The remote sensing product “kd_z90max” (i.e., the depth of the water column from which 90% of the water-leaving irradiance are derived) from C2RCC-SNAP showed a good correlation with in situ Secchi depth (SD). Additionally, a regional in-water algorithm was applied to derive SD from the attenuation coefficient K_d(489) using a local algorithm. Furthermore, a regional in-water relationship between particle scatter and bench turbidity was applied to generate turbidity from the remote sensing product “iop_bpart” (i.e., the scattering coefficient of marine particles at 443 nm). The spectral shape of the remote sensing reflectance (R_rs) data extracted from match-up stations was evaluated against reflectance data measured in situ by a tethered Attenuation Coefficient Sensor (TACCS) radiometer. The L2 products were evaluated against in situ data from several dedicated validation campaigns (2016–2018) in the NW Baltic proper. All derived L2 in-water products were statistically compared to in situ data and the results were also compared to results for MERIS validation from the literature and the current S3 Level-2 Water (L2W) standard processor from EUMETSAT. The Chl-a product showed a substantial improvement (MNB 21%, RMSE 88%, APD 96%, n = 27) compared to concentrations derived from the Medium Resolution Imaging Spectrometer (MERIS), with a strong underestimation of higher values. TSM performed within an error comparable to MERIS data with a mean normalized bias (MNB) 25%, root-mean square error (RMSE) 73%, average absolute percentage difference (APD) 63% n = 23). Coloured Dissolved Organic Matter (CDOM) absorption retrieval has also improved substantially when using the product “iop_adg” (i.e., the sum of organic detritus and Gelbstoff absorption at 443 nm) as a proxy (MNB 8%, RMSE 56%, APD 54%, n = 18). The local SD (MNB 6%, RMSE 62%, APD 60%, n = 35) and turbidity (MNB 3%, RMSE 35%, APD 34%, n = 29) algorithms showed very good agreement with in situ data. We recommend the use of the SNAP C2RCC with regionally adjusted TSM-specific scatter for water product retrieval as well as the regional turbidity algorithm for Baltic Sea monitoring. Besides documenting the evaluation of the C2RCC processor, this paper may also act as a handbook on the validation of Ocean Colour data.

Detection of Phytoplankton Temporal Anomalies Based on Satellite Inherent Optical Properties: A Tool for Monitoring Phytoplankton Blooms

The baseline of a specific variable defines the average behavior of that variable and it must be built from long data series that represent its spatial and temporal variability. In coastal and marine waters, phytoplankton can produce blooms characterized by a wide range of total cells number or chlorophyll a concentration. Classifying a phytoplankton abundance increase as a bloom depends on the species, the study area and the season. The objective of this study was to define the baseline of satellite absorption coefficients in Todos Santos Bay (Baja California, Mexico) to determine the presence of phytoplankton blooms based on the satellite inherent optical properties index (satellite IOP index). Two field points were selected according to historical bloom reports. To build the baseline, the data of phytoplankton absorption coefficients ( a p h y , G I O P ) and detritus plus colored dissolved organic matter (CDOM) ( a d C D O M , G I O P ) from the generalized inherent optical property (GIOP) satellite model of the NASA moderate resolution imaging spectroradiometer (MODIS-Aqua) sensor was studied for the period 2003 to 2016. Field data taken during a phytoplankton bloom event on June 2017 was used to validate the use of satellite products. The association between field and satellite data had a significant positive correlation. The satellite baseline detected a trend change from high values to low values of the satellite IOP index since 2010. Improved wastewater treatment to waters discharged into the Bay, and increased aquaculture of filter-feeding mollusks could have been the cause. The methodology proposed in this study can be a supplementary tool for permanent in situ monitoring programs. This methodology offers several advantages: A complete spatial coverage of the specific coastal area under study, appropriate temporal resolution and a tool for building an objective baseline to detect deviation from average conditions during phytoplankton bloom events.

Monitoring Coastal Lagoon Water Quality Through Remote Sensing: The Mar Menor as a Case Study

The Mar Menor is a hypersaline coastal lagoon located in the southeast of Spain. This fragile ecosystem is suffering several human pressures, such as nutrient and sediment inputs from agriculture and other activities and decreases in salinity. Therefore, the development of an operational system to monitor its evolution is crucial to know the cause-effect relationships and preserve the natural system. The evolution and variability of the turbidity and chlorophyll-a levels in the Mar Menor water body were studied here through the joint use of remote sensing techniques and in situ data. The research was undertaken using Operational Land Imager (OLI) images on Landsat 8 and two SPOT images, because cloudy weather prevented the use of OLI images alone. This provided the information needed to perform a time series analysis of the lagoon. We also analyzed the processes that occur in the salt lagoon, characterizing the different spatio-temporal patterns of biophysical parameters. Special attention was given to the role of turbidity and chlorophyll-a levels in the Mar Menor ecosystem with regard to the programs of integral management of this natural space that receives maximum environmental protection. The objective of the work has been fulfilled by answering the questions of the managers: when did the water quality in the Mar Menor begin to change? What is happening in the lagoon? Is remote sensing useful for monitoring the water quality in the Mar Menor? The answers to these questions have allowed the generation of a methodology and monitoring system to track the water quality in the Mar Menor in real-time and space. The tracking system using satellite images is open to the incorporation of images provided by new multispectral sensors.