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Remote sensing of suspended particulate matter, SPM, from space has long been used to assess its spatio-temporal variability in various coastal areas. The associated algorithms were generally site specific or developed over a relatively narrow range of concentration, which make them inappropriate for global applications (or at least over broad SPM range). In the frame of the GlobCoast project, a large in situ data set of SPM and remote sensing reflectance, Rrs(λ), has been built gathering together measurements from various coastal areas around Europe, French Guiana, North Canada, Vietnam, and China. This data set covers various contrasting coastal environments diversely affected by different biogeochemical and physical processes such as sediment resuspension, phytoplankton bloom events, and rivers discharges (Amazon, Mekong, Yellow river, MacKenzie, etc.). The SPM concentration spans about four orders of magnitude, from 0.15 to 2626 g·m−3. Different empirical and semi-analytical approaches developed to assess SPM from Rrs(λ) were tested over this in situ data set. As none of them provides satisfactory results over the whole SPM range, a generic semi-analytical approach has been developed. This algorithm is based on two standard semi-analytical equations calibrated for low-to-medium and highly turbid waters, respectively. A mixing law has also been developed for intermediate environments. Sources of uncertainties in SPM retrieval such as the bio-optical variability, atmospheric correction errors, and spectral bandwidth have been evaluated. The coefficients involved in these different algorithms have been calculated for ocean color (SeaWiFS, MODIS-A/T, MERIS/OLCI, VIIRS) and high spatial resolution (LandSat8-OLI, and Sentinel2-MSI) sensors. The performance of the proposed algorithm varies only slightly from one sensor to another demonstrating the great potential applicability of the proposed approach over global and contrasting coastal waters.

Ocean colour (OC) remote sensing is an important tool for monitoring phytoplankton in the global ocean. In optically complex waters such as the Baltic Sea, relatively efficient light absorption by substances other than phytoplankton increases product uncertainty. Sentinel-3 OLCI-A, Suomi-NPP VIIRS and MODIS-Aqua OC radiometric products were assessed using Baltic Sea in situ remote sensing reflectance (Rrs) from ferry tracks (Alg@line) and at two Aerosol Robotic Network for Ocean Colour (AERONET-OC) sites from April 2016 to September 2018. A range of atmospheric correction (AC) processors for OLCI-A were evaluated. POLYMER performed best with <23 relative % difference at 443, 490 and 560 nm compared to in situ Rrs and 28% at 665 nm, suggesting that using this AC for deriving Chl a will be the most accurate. Suomi-VIIRS and MODIS-Aqua underestimated Rrs by 35, 29, 22 and 39% and 34, 22, 17 and 33% at 442, 486, 560 and 671 nm, respectively. The consistency between different AC processors for OLCI-A and MODIS-Aqua and VIIRS products was relatively poor. Applying the POLYMER AC to OLCI-A, MODIS-Aqua and VIIRS may produce the most accurate Rrs and Chl a products and OC time series for the Baltic Sea.

After the exponential growth phase, variability in the scattering efficiency of phytoplankton cells over their complete life cycle is not well characterised. Bulk measurements are impacted by senescent cells and detritrus. Thus the analysis of the evolution of the optical properties thanks to their morphological and/or intra-cellular variations remains poorly studied. Using the Cytosense flow cytometer (CytoBuoy b.v., NL), the temporal course of the forward and sideward efficiencies of two phytoplankton species (Thalassiosira pseudonana and Chlamydomonas concordia) were analyzed during a complete life-cycle. These two species differ considerably from a morphological point of view. Over the whole experiment, the forward and sideward efficiencies of Thalassiosira pseudonana were, on average, respectively 2.2 and 1.6 times higher than the efficiencies of Chlamydomonas concordia. Large intra-species variability of the efficiencies were observed over the life cycle of the considered species. It highlights the importance of considering the optical properties of phytoplankton cells as a function of the population growth stage of the considered species. Furthermore, flow cytometry measurements were combined with radiative transfer simulations and biogeochemical and optical measurements. Results showed that the real refractive index of the chloroplast is a key parameter driving the sideward signal and that a simplistic two-layered model (cytoplasm-chloroplast) seems particularly appropriate to represent the phytoplankton cells.

The bulk backscattering ratio ( b b p ˜ ) is commonly used as a descriptor of the bulk real refractive index of the particulate assemblage in natural waters. Based on numerical simulations, we analyze the impact of modeled structural heterogeneity of phytoplankton cells on b b p ˜ . b b p ˜ is modeled considering viruses, heterotrophic bacteria, phytoplankton, organic detritus, and minerals. Three case studies are defined according to the relative abundance of the components. Two case studies represent typical situations in open ocean, oligotrophic waters, and phytoplankton bloom. The third case study is typical of coastal waters with the presence of minerals. Phytoplankton cells are modeled by a two-layered spherical geometry representing a chloroplast surrounding the cytoplasm. The b b p ˜ values are higher when structural heterogeneity is considered because the contribution of coated spheres to light backscattering is higher than homogeneous spheres. The impact of heterogeneity is; however, strongly conditioned by the hyperbolic slope ξ of the particle size distribution. Even if the relative abundance of phytoplankton is small (<1%), b b p ˜ increases by about 58% (for ξ = 4 and for oligotrophic waters), when the heterogeneity is taken into account, in comparison with a particulate population composed only of homogeneous spheres. As expected, heterogeneity has a much smaller impact (about 12% for ξ = 4 ) on b b p ˜ in the presence of suspended minerals, whose increased light scattering overwhelms that of phytoplankton.

The influences of physico-chemical and biological processes on dimethylsulfide (DMS) dynamics in the most oligotrophic subtropical zones of the global ocean were investigated. As metrics for the dynamics of DMS and the so-called 'summer DMS paradox' of elevated summer concentrations when surface chlorophyll a (Chl) and particulate organic carbon (POC) levels are lowest, we used the DMS-to-Chl and DMS-to-POC ratios in the context of three independent and complementary approaches. Firstly, field observations of environmental variables (such as the solar radiation dose, phosphorus limitation of phytoplankton and bacterial growth) were used alongside discrete DMS, Chl and POC estimates extracted from global climatologies (i.e., a 'station based' approach). We then used monthly climatological data for DMS, Chl, and POC averaged over the biogeographic province wherein a given oligotrophic subtropical zone resides (i.e., a 'province based' approach). Finally we employed sensitivity experiments with a new DMS module coupled to the ocean general circulation and biogeochemistry model PISCES to examine the influence of various processes in governing DMS dynamics in oligotrophic regions (i.e., a 'model based' approach). We find that the 'station based' and 'province based' approaches yield markedly different results. Interestingly, the 'province based' approach suggests the presence of a 'summer DMS paradox' in most all of the oligotrophic regions we studied. In contrast, the 'station based' approach suggests that the 'summer DMS paradox' is only present in the Sargasso Sea and eastern Mediterranean. Overall, we found the regional differences in the absolute and relative concentrations of DMS between 5 of the most oligotrophic regions of the world's oceans were better accounted for by their nutrient dynamics (specifically phosphorus limitation) than by physical factors often invoked, e.g., the solar radiation dose. Our 'model based' experiments suggest that it is the limitation of phytoplankton/bacterial production and bacterial consumption of DMS by pervasive phosphorus limitation that is responsible for the 'summer DMS paradox'.

Over the past years, a large number of new approaches in the domain of ocean-color have been developed, leading to a variety of innovative descriptors for phytoplankton communities. One of these methods, named PHYSAT, currently allows for the qualitative detection of five main phytoplankton groups from ocean-color measurements. Even though PHYSAT products are widely used in various applications and projects, the approach is limited by the fact it identifies only dominant phytoplankton groups. This current limitation is due to the use of biomarker pigment ratios for establishing empirical relationships between in-situ information and specific ocean-color radiance anomalies in open ocean waters. However, theoretical explanations of PHYSAT suggests that it could be possible to detect more than dominance cases but move more towards phytoplanktonic assemblage detection. Thus, to evaluate the potential of PHYSAT for the detection of phytoplankton assemblages, we took advantage of the Continuous Plankton Recorder (CPR) survey, collected in both the English Channel and the North Sea. The available CPR dataset contains information on diatom abundance in two large areas of the North Sea for the period 1998-2010. Using this unique dataset, recurrent diatom assemblages were retrieved based on classification of CPR samples. Six diatom assemblages were identified in-situ, blueeach having indicators taxa or species. Once this first step was completed, the in-situ analysis was used to empirically associate the diatom assemblages with specific PHYSAT spectral anomalies. This step was facilitated by the use of previous classifications of regional radiance anomalies in terms of shape and amplitude, coupled with phenological tools. Through a matchup exercise, three CPR assemblages were associated bluewith specific radiance anomalies. The maps of detection of these specific radiances anomalies are in close agreement with current in-situ ecological knowledge.

Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of its biomass and dynamics will help to understand ocean ecosystems and refine global climate models. Relevant data sets of phytoplankton defined at a functional level and on a sub-meso- and daily scale are thus required. In order to achieve this, an automated, high-frequency, dedicated scanning flow cytometer (SFC, Cytobuoy b.v., the Netherlands) has been developed to cover the entire size range of phytoplankton cells whilst simultaneously taking pictures of the largest of them. This cytometer was directly connected to the water inlet of a PocketFerryBox during a cruise in the North Sea, 08–12 May 2011 (DYMAPHY project, INTERREG IV A \"2 Seas\"), in order to identify the phytoplankton community structure of near surface waters (6 m) with a high spatial resolution basis (2.2 ± 1.8 km). Ten groups of cells, distinguished on the basis of their optical pulse shapes, were described (abundance, size estimate, red fluorescence per unit volume). Abundances varied depending on the hydrological status of the traversed waters, reflecting different stages of the North Sea blooming period. Comparisons between several techniques analysing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. For the first time, the community structure observed from the automated flow cytometry data set was compared with PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high-frequency in situ sampling and remote sensing was found to be more than 2 times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the 2 days for which matchups were available suggest that it is possible to label PHYSAT anomalies using automated flow cytometry to resolve not only dominant groups but also community structure.

The variability of inherent optical properties is investigated in the ultra-oligotrophic waters of the Mediterranean Sea sampled during the BOUM experiment performed during early summer 2008. Bio-optical relationships found for ultra-oligotrophic waters of the three anticyclonic gyres sampled significantly depart from the mean standard relationships provided for the global ocean, confirming the peculiar character of these Mediterranean waters. These optical anomalies are diversely related to the specific biological and environmental conditions occurring in the studied ecosystem. Specifically, the surface specific phytoplankton absorption coefficient exhibits values lower than those expected from the general relationships mainly in relation with a high contribution of relatively large sized phytoplankton. Conversely, the particulate backscattering coefficient, bbp, values are much higher than the mean standard values for a given chlorophyll-a concentration, TChl-a. This feature can presumably be related to the relevant influence of highly refractive submicrometer particles of Saharan origin in the surface layer of the water column. The present measurements also show that the Mediterranean Sea is greener than TChl-a alone indicates, as already stressed in previous studies. This color anomaly is partly explained by the estimated colored dissolved organic matter and submicrometer particles absorption coefficients, and to a greater extent by the high bbp/TChl-a values assuming that these particles backscatter light similarly in the green and blue parts of the visible spectrum. The diel variation of both the particulate matter attenuation and backscattering coefficients were also investigated specifically. Despite some differences in the timing and the magnitude of the daily oscillations found for these optical parameters, potential for the backscattering coefficient daily oscillation to be used, similarly to that for the attenuation coefficient, as a proxy for estimating carbon community production budget has been highlighted for the first time. This result is particularly relevant for present and future geostationary spatial ocean color missions.

The diffuse attenuation coefficient, Kd(λ) is a fundamental radiometric parameter that is used to assess the light availability in the water column. A neural network approach is developed to assess Kd(λ) at any visible wavelengths from the remote sensing reflectances as measured by the SeaWiFS satellite sensor. The neural network (NN) inversion is trained using a combination of simulated and in‐situ data sets covering a broad range ofKd(λ), between 0.0073 m−1 at 412 nm and 12.41 m−1at 510 nm. The performance of the retrieval is evaluated against two data sets, one consisting of mainly synthetic data while the other one contains in‐situ data only and is compared to those obtained with previous published empirical (NASA, Morel and Maritorena (2001) and Zhang and Fell (2007)) and semi‐analytical (Lee et al., 2005b) algorithms. On the in‐situ data set from the COASTLOOC campaign, the retrieval accuracy of the present algorithm is quite similar to published algorithms for oligotrophic and mesotrophic ocean waters. But for Kd(490) > 0.25 m−1, the NN approach allows to retrieve Kd(490) with a much better accuracy than the four other methods. The results are consistent when compared with other SeaWiFS wavelengths. This new inversion is as suitable in the open ocean waters as in the turbid waters. The work here is straightforwardly applicable to the MERIS sensor and with few changes to the MODIS‐AQUA sensor. The algorithm in matlab and C code is provided as auxiliary material. Key Points Diffuse attenuation coefficient retrieval using neural network inversion This new empirical inversion is suitable for open and coastal waters It is wavelength and Sun‐zenith angle independent

Major patterns of temporal variability associated with marine particulate backscattering coefficient at 490 nm (bbp(490), an indicator of the particulate organic carbon concentration) and particle backscattering spectral dependency γ (a proxy for the relative proportion between small and large particles) are investigated with a 10‐year SeaWiFS series. Generally, the contribution of the seasonal cycle to the series variance has a similar spatial pattern for γ and the chlorophyll a concentration (Chla). The spatial distribution of significant monotonic changes for γ and Chla (reaching up to ±5% yr−1) is also comparable with opposite signs of the slope, indicating that inter‐annual changes in Chla and average particle size are often positively correlated. Conversely, spatial patterns of seasonality and trend found for bbp(490) often differ from those of Chla and γ. Particularly, large seasonal signals for bbp(490) are seen poleward of 45° while high seasonality for Chla and γ is found in two mid‐latitude zonal belts (∼20°–40° latitude). Significant changes in bbp(490) over the considered decade are much fewer and usually not significant in areas where strong positive or negative changes in Chla have been detected. This suggests that the changes in phytoplankton have not been translated in terms of overall particle stock.