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International audience; We present a three-step inverse model (3SAA) for estimating the inherent optical properties (IOPs) of surface waters from the remote sensing reflectance spectra, Rrs(λ). The derived IOPs include the total (a(λ)), phytoplankton (aphy(λ)), and colored detrital matter (acdm(λ)), absorption coefficients, and the total (bb(λ)) and particulate (bbp(λ)) backscattering coefficients. The first step uses an improved neural network approach to estimate the diffuse attenuation coefficient of downwelling irradiance from Rrs. a(λ) and bbp(λ) are then estimated using the LS2 model (Loisel et al., 2018), which does not require spectral assumptions on IOPs and hence can assess a(λ) and bb(λ) at any wavelength at which Rrs(λ) is measured. Then, an inverse optimization algorithm is combined with an optical water class (OWC) approach to assess aphy(λ) and acdm(λ) from anw(λ).The proposed model is evaluated using an in situ dataset collected in open oceanic, coastal, and inland waters. Comparisons with other standard semi-analytical algorithms (QAA and GSM), as well as match-up exercises, have also been performed. The applicability of the algorithm on OLCI observations was assessed through the analysis of global IOPs spatial patterns derived from 3SAA and GSM. The good performance of 3SAA is manifested by median absolute percentage differences (MAPD) of 13%, 23%, 34% and 34% for bbp(443), anw(443), aphy(443) and acdm(443), respectively for oceanic waters. Due to the absence of spectral constraints on IOPs in the inversion of total IOPs, and the adoption of an OWC-based approach, the performance of 3SAA is only slightly degraded in bio-optical complex inland waters.

The proxy for phytoplankton biomass, Chlorophyll a (Chl a), is an important variable to assess the health and state of the oceans which are under increasing anthropogenic pressures. Prior to the operational use of satellite ocean-colour Chl a to monitor the oceans, rigorous assessments of algorithm performance are necessary to select the most suitable products. Due to their inaccessibility, the oligotrophic open-ocean gyres are under-sampled and therefore under-represented in global in situ data sets. The Atlantic Meridional Transect (AMT) campaigns fill the sampling gap in Atlantic oligotrophic waters. In-water underway spectrophotometric data were collected on three AMT field campaigns in 2016, 2017 and 2018 to assess the performance of Sentinel-3A (S3-A) and Sentinel-3B (S3-B) Ocean and Land Colour Instrument (OLCI) products. Three Chl a algorithms for OLCI were compared: Processing baseline (pb) 2, which uses the ocean colour 4 band ratio algorithm (OC4Me); pb 3 (OL_L2M.003.00) which uses OC4Me and a colour index (CI); and POLYMER v4.8 which models atmosphere and water reflectance and retrieves Chl a as a part of its spectral matching inversion. The POLYMER Chl a for S-3A OLCI performed best. The S-3A OLCI pb 2 tended to under-estimate Chl a especially at low concentrations, while the updated OL_L2M.003.00 provided significant improvements at low concentrations. OLCI data were also compared to MODIS-Aqua (R2018 processing) and Suomi-NPP VIIRS standard products. MODIS-Aqua exhibited good performance similar to OLCI POLYMER whereas Suomi-NPP VIIRS exhibited a slight under-estimate at higher Chl a values. The reasons for the differences were that S-3A OLCI pb 2 Rrs were over-estimated at blue bands which caused the under-estimate in Chl a. There were also some artefacts in the Rrs spectral shape of VIIRS which caused Chl a to be under-estimated at values >0.1 mg m-3. In addition, using in situ Rrs to compute Chl a with OC4Me we found a bias of 25% for these waters, related to the implementation of the OC4ME algorithm for S-3A OLCI. By comparison, the updated OLCI processor OL_L2M.003.00 significantly improved the Chl a retrievals at lower concentrations corresponding to the AMT measurements. S-3A and S-3B OLCI Chl a products were also compared during the Sentinel-3 mission tandem phase (the period when S-3A and S-3B were flying 30 sec apart along the same orbit). Both S-3A and S-3B OLCI pb 2 under-estimated Chl a especially at low values and the trend was greater for S-3A compared to S-3B. The performance of OLCI was improved by using either OL_L2M.003.00 or POLYMER Chl a. Analysis of coincident satellite images for S-3A OLCI, MODIS-Aqua and VIIRS as composites and over large areas illustrated that OLCI POLYMER gave the highest Chl a concentrations and percentage (%) coverage over the north and south Atlantic gyres, and OLCI pb 2 produced the lowest Chl a and % coverage.

Spatio-temporal patterns of suspended particulate matter, SPM, in coastal waters under the Mekong's influence are examined through remote sensing data collected from January 2003 to April 2012 by the MEdium Resolution Imaging Spectrometer (MERIS) at full spatial resolution (300 × 300 m2). The first SPM climatology over this region is provided and the SPM temporal variation schemes (irregular variability, seasonal variability, and long term trend) are described using the Census-X-11 time series decomposition method. The different spatio-temporal patterns are then analyzed with regard to regional oceanographic and hydrologic conditions. The origin of the processes controlling the seasonality of the Mekong Delta plume is characterized. The increase of turbidity observed from June to December, starts with the Mekong sediment inputs which are maximum during the summer monsoon (the water discharge reaches its maximum in September/October). While the Mekong water discharge decreases, the concentration of suspended sediment keeps increasing in coastal waters during the following two/three months (November to January). This increase is explained by resuspension effects occurring in the shallow coastal areas. Due to higher wave energy and oblique orientation of the waves breaking near the coast, the winter monsoon triggers a high level of agitation and high value of resuspended material concentration which are submitted to a longshore current directed towards the South–West. Deposition (in front of the Delta) and erosion (northern and southern areas of the delta) areas are identified in good agreement with recent results obtained from a prognostic model. While the temporal variability is strongly dominated by the seasonal component, a long term trend of about − 5% SPM concentration per year is observed in the pro-delta area and is attributed to the decrease of the Mekong river sediment output during the high flow season.

International audience; The composition of marine ecosystems is determined by spatial and temporal patterns of global biogeochemical cycles. Shifts in marine ecosystem composition driven by changes in climate can in turn affect biogeochemical cycles, especially through their impact on air-sea fluxes of CO2 and trace gas concentrations in the atmosphere. However, the response of marine ecosystems to climate is difficult to assess at global scale due to the scarcity of large-scale in-situ biological monitoring programmes. Here, we combine and analyse remote-sensing observations, in-situ observations, and a global ocean biogeochemistry model to gain insight into interactions between marine ecosystem composition and climate variability over the last decade, in the North Atlantic and in the Southern Ocean. Our results show large-scale shifts in the dominance of diatoms, with mean anomalies 63.3% higher during extreme positive phases of North Atlantic Oscillation index compared to its extreme negative phases and with mean anomalies 134% higher during extreme positive phases of Southern Annular Mode in the Southern Ocean over the period 1998-2008. Significant changes in the frequency of diatom dominance are detected concurrently in the three data sources studied. Model outputs indicate that this increase is driven by nutrient supply from deep waters during windier and more turbulent climate conditions.