Description: We have examined several approaches for estimating the surface concentration of particulate organic carbon, POC, from optical measurements of spectral remote-sensing reflectance, Rrs(Lambda), using field data collected in tropical and subtropical waters of the eastern South Pacific and eastern Atlantic Oceans. These approaches include a direct empirical relationship between POC and the blue-to-green band ratio of reflectance, Rrs(Lambda B)/Rrs(555), and two-step algorithms that consist of relationships linking reflectance to an inherent optical property IOP (beam attenuation or backscattering coefficient) and POC to the IOP. We considered two-step empirical algorithms that exclusively include pairs of empirical relationships and two-step hybrid algorithms that consist of semianalytical models and empirical relationships. The surface POC in our data set ranges from about 10 mg/m**3 within the South Pacific Subtropical Gyre to 270 mg/m**3 in the Chilean upwelling area, and ancillary data suggest a considerable variation in the characteristics of particulate assemblages in the investigated waters. The POC algorithm based on the direct relationship between POC and Rrs(Lambda B)/Rrs(555) promises reasonably good performance in the vast areas of the open ocean covering different provinces from hyperoligotrophic and oligotrophic waters within subtropical gyres to eutrophic coastal upwelling regimes characteristic of eastern ocean boundaries. The best error statistics were found for power function fits to the data of POC vs. Rrs(443)/Rrs(555) and POC vs. Rrs(490)/Rrs(555). For our data set that includes over 50 data pairs, these relationships are characterized by the mean normalized bias of about 2% and the normalized root mean square error of about 20%. We recommend that these algorithms be implemented for routine processing of ocean color satellite data to produce maps of surface POC with the status of an evaluation data product for continued work on algorithm development and refinements. The two-step algorithms also deserve further attention because they can utilize various models for estimating IOPs from reflectance, offer advantages for developing an understanding of bio-optical variability underlying the algorithms, and provide flexibility for regional or seasonal parameterizations of the algorithms.

Description: The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Description: The relationship between phytoplankton assemblages and the associated optical properties of the water body is important for the further development of algorithms for large-scale remote sensing of phytoplankton biomass and the identification of phytoplankton functional types (PFTs), which are often representative for different biogeochemical export scenarios. Optical in-situ measurements aid in the identification of phytoplankton groups with differing pigment compositions and are widely used to validate remote sensing data. In this study we present results from an interdisciplinary cruise aboard the RV Polarstern along a north-to-south transect in the eastern Atlantic Ocean in November 2008. Phytoplankton community composition was identified using a broad set of in-situ measurements. Water samples from the surface and the depth of maximum chlorophyll concentration were analyzed by high performance liquid chromatography (HPLC), flow cytometry, spectrophotometry and microscopy. Simultaneously, the above- and underwater light field was measured by a set of high spectral resolution (hyperspectral) radiometers. An unsupervised cluster algorithm applied to the measured parameters allowed us to define bio-optical provinces, which we compared to ecological provinces proposed elsewhere in the literature. As could be expected, picophytoplankton was responsible for most of the variability of PFTs in the eastern Atlantic Ocean. Our bio-optical clusters agreed well with established provinces and thus can be used to classify areas of similar biogeography. This method has the potential to become an automated approach where satellite data could be used to identify shifting boundaries of established ecological provinces or to track exceptions from the rule to improve our understanding of the biogeochemical cycles in the ocean.

Description: We present a data set on particulate absorption line height at 676 and surface Chl-a concentration using underway spectrophotometry (Wetlabs AC-s instrument) and collocated discrete water sampling (measured by High Pressure Liquid Chromatography, HPLC, and Quantitative Filtration Technique) during two summer cruises PS93.2 and PS99.2 in the Fram Strait. Additionally we present for the discrete water samples the fraction of different phytoplankton groups on the total biomass, approximated by the chl-a concentration, which are derived from phytoplankton marker pigments also measured by HPLC.

Description: The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., 〈 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Description: We present data sets on: 1) the concentrations of various phytoplankton pigments (unit: mg/m³) from discrete samples measured using High Pressure Liquid Chromatography (HPLC); 2) the concentrations of various phytoplankton pigments (unit: mg/m³) estimated from underway AC-S particulate absorption data (Fucoxanthin, 19'-hexanoyloxyfucoxanthin and Diadinoxanthin are estimated using SVD-NNLS-9 matrix inversion method; total Chlorophyll a, b, Chlorophyll c1+2, photosynthetic and photoprotective carotenoids are estimated using Gaussian decomposition); and 3) the spectral particulate absorption and attenuation coefficients and their standard deviation (unit: 1/m) derived from underway AC-S measurements during the cruises PS93.2, PS99.2 and PS107 on R/V POLARSTERN in the Fram Strait.

Description: Lake Süßer See is a eutrophic to hypertrophic medium-sized lake (max. depth 8.2 m, mean depth 4.3 m; volume 11.6 Mio. m³, surface area 268 ha) which receives water from the south-eastern foothills of the Harz Mountains and a former mining area for copper shale (Mansfelder Land) by the stream “Böse Sieben” (Becker et al. 2001; Lewandowski et al. 2003). The lake basin represents a sinkhole that has been formed by dissolution of underlying Permian evaporates (Wennrich et al. 2007). High P load by the inflows are a result of extensive fertilizer application in the catchment further supporting the high trophic state of the lake. Although phosphorus removal by aluminum sulfate application between 1976 and 1992 reduced internal P loading from the sediments high external, diffuse-source TP loads prevented substantial water quality improvements (TPlake about 200 µg/L) and annually occurring algae blooms of cyanobacteria persist. This publication series includes datasets collected on Lake Süßer See during the Inland Water Remote Sensing Validation Campaign 2017 (Bumberger et al. 2023).

Description: Kelbra Reservoir is a shallow lowland reservoir (approx. 35 Mio. m³ volume; max. depth 5,5 m, mean depth 3.5 m; surface area 600 ha), which was constructed 1962-1966 for flood protection for the downstream reaches of the river “Helme” and came into operation 1969. It is also used for irrigation and recreational purposes. Until the beginning of the 1990s, the production of carp was also initiated and played an important role (Ziemann 1986). Immediately after commissioning, the reservoir became an important resting place for diverse migrating birds (Görner et al. 1983; Scheuer 2003). In the last 30 years, cranes, during their migration from Scandinavia to Africa, occurred in high numbers (up to 10,000 individuals; Höpfner 2003; Scheuer et al. 2019) so that bird protection measures became a vital component of the reservoir management. During winter, the reservoir is emptied to have its full capacity for flood protection. The highest floods occur in river “Helme” typically from December through March (LHW 2016). Kelbra Reservoir has been highly eutrophic from the very beginning (Ziemann 1986) until now although waste water treatment was improved and carp production was stopped in the 1990s. Still, external and internal phosphorus loading is at a high level. Due to very high total phosphorous concentrations cyanobacterial blooms appear regularly in summer time and the trophic state can be characterized to be hypertrophic. This publication series includes datasets collected on Kelbra Reservoir during the Inland Water Remote Sensing Validation Campaign 2017 (Bumberger et al. 2023).

Description: Lake Geiseltal is the largest lake of Saxony-Anhalt and the largest artificial lake of Germany (max. depth 78 m; mean depth 22.8 m; volume 423 Mio. m³; surface area 1853 ha) and can be classified as oligotrophic. It was created by the excavation of lignite in several former surface mines starting at industrial scale in 1906 (formerly only small-scale mining dated back to 1698; Knochenhauer 1996). Mining stopped 1993 after 1.4*109 tons of lignite and the same mass of overburden were excavated. To stabilize the slopes of the residual mine pits and to avoid acidification from mine drainage, a planned, large scale flooding of the residual mine pits started in 2003 by pumping water from River Saale that was cleaned up by sand filtration before (Fritz et al. 2001). In 2011, the flooding of the lake was completed (LMBV 2018). Algal productivity in the lake is low and water transparency high, the littoral compartments along the shores harbor large stocks of submerged macrophytes. This publication series includes datasets collected on Lake Geiseltal during the Inland Water Remote Sensing Validation Campaign 2017 (Bumberger et al. 2023).

Description: On Aug. 29, 2017, the central intercalibration campaign was conducted on Lake Süßer See, in which all groups were participating that had been involved in the field measurements included in the overall project campaigns. The main goal of this intercalibration campaign was to realise a direct comparison of all involved field and lab sensors/analysis in order to assess their accuracy, comparability, and reproducibility. For this purpose, all used instruments were used simultaneously at the measuring point on Lake Süßer See. This fully parallel application enabled us to directly compare the results under identical in-situ conditions and to detect and quantify instrumental deviations.