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5 pages, 3 figures, Radiometric water products from the neural network (NNv2) in the alternative atmospheric correction (AAC) processing chain of Ocean and Land Colour Instrument (OLCI) data were assessed over different marine regions. These products, not included among the operational ones, were custom-produced from Copernicus Sentinel-3 OLCI Baseline Collection 3. The assessment benefitted of in situ reference data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) from sites representative of different water types. These included clear waters in the Western Mediterranean Sea, optically complex waters characterized by varying concentrations of total suspended matter and chromophoric dissolved organic matter (CDOM) in the northern Adriatic Sea, and optically complex waters characterized by very high concentrations of CDOM in the Baltic Sea. The comparison of the water-leaving radiances LWN(λ) derived from OLCI data on board Sentinel-3A and Sentinel-3B with those from AERONET-OC confirmed consistency between the products from the two satellite sensors. However, the accuracy of satellite data products exhibited dependence on the water type. A general underestimate of LWN(λ) was observed for clear waters. Conversely, overestimates were observed for data products from optically complex waters with the worst results obtained for CDOM-dominated waters. These findings suggest caution in exploiting NNv2 radiometric products, especially for highly absorbing and clear waters, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

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 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.

26 pages, 15 figures, 13 tables, 1 annex, The Ocean and Land Color Instruments (OLCI) operated onboard the Copernicus Sentinel-3 satellites are providing globally distributed Ocean Color Radiometry (OCR) data products of relevance for environmental and climate applications. This work summarizes results on the assessment of fundamental OCR data from the Operational Baseline 3 Collection OL_L2M.003.01 of OLCI-A and OLCI-B onboard Sentinel-3A and Sentinel-3B, respectively. Evaluated products are the satellite derived normalized water-leaving radiance L(λ), aerosol optical depth at 865 nm τ(865) and Ångström exponent α determined in the near-infrared spectral region. The analyses were performed relying on in situ reference data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) from sites representative of diverse water types. The comparison of OLCI-A and OLCI-B with AERONET-OC L(λ) for oligotrophic/mesotrophic waters shows cross-mission consistent spectral median percent differences (i.e., biases) varying within ±6% at the blue-green center-wavelengths. The analysis of data from regions characterized by optically complex waters, however, displays systematic negative biases for both OLCI-A and OLCI-B further increasing for waters dominated by chromophoric dissolved organic matter, thus suggesting a dependence of the atmospheric correction on water type. The direct inter-comparison of OLCI-B and OLCI-A L(λ) from the Tandem Phase characterized by Sentinel-3B and Sentinel-3A flying 30 s apart on the same orbit, shows spectral median percent differences lower than ±1% in the 412–560 nm interval, of approximately +5% at 620 and 665 nm, and −7% at 400 nm. However, outside the Tandem Phase, the inter-comparison of OLCI-B and OLCI-A data products indicates large and systematic differences explained by a notable dependence on the viewing angle. The evaluation of τ(865) and α across different geographic regions exhibits overestimated values between +48 and + 79% for the former and underestimated values between −28% and − 41% for the latter. A complementary evaluation of OCR data products from the Visible Infrared Imager Radiometer Suite on board the Suomi National Polar-orbiting Partnership (VIIRS-S), proposed as a further indirect term of reference for OLCI-A and OLCI-B data, shows large underestimates of L(λ) with respect to the in situ reference data in the various water types at 410 nm. Nevertheless, opposite to OLCI-A and OLCI-B data products, absolute differences between VIIRS-S and in situ reference data do not reveal any large or systematic dependence on water type and satellite viewing angle. Overall results suggest the need for further developing the OLCI-A and OLCI-B atmospheric correction, possibly improving the capability to identify aerosol types and to model scattering processes, This work benefitted of support from the Joint Research Centre through the COLORS project, from the European Metrology Programme for Innovation and Research (EMPIR) through the METEOC-4 project (grant 19ENV07), and from the European Commission Directorate-General for Defence Industry and Space through the Copernicus Programme. The additional support of the ‵Severo Ochoa Centre of Excellence' accreditation (CEX2019-000928-S) is also acknowledged

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.

The bulk backscattering ratio ($\tilde{b_{bp}}$) 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 heterogeneity of phytoplankton cells on $\tilde{b_{bp}}$. $\tilde{b_{bp}}$ is modeled considering viruses, heterotrophic bacteria, phytoplankton, detritus, and minerals. Three study cases are defined according to the relative abundance of these different components. Two study cases represent typical situations in open ocean, outside (No-B/No-M) and inside bloom (B/No-M). The third study case 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 $\tilde{b_{bp}}$ values are higher when heterogeneity is considered because the contribution of coated spheres to backscattering is higher than homogeneous spheres. The impact of heterogeneity is however strongly conditioned by the hyperbolic slope $\xi$ of the particle size distribution. Even if the relative concentration of phytoplankton is small (

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.

The bulk backscattering ratio ( b b p &tilde, ) 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 &tilde, b b p &tilde, 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 &tilde, 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 &xi, of the particle size distribution. Even if the relative abundance of phytoplankton is small (&lt, 1%), b b p &tilde, increases by about 58% (for &xi, = 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 &xi, = 4 ) on b b p &tilde, in the presence of suspended minerals, whose increased light scattering overwhelms that of phytoplankton.

This study presents an application of the Cytosense flow cytometer (CytoBuoy b.v., NL) for the analysis of the optical properties of phytoplankton cells. For the first time, the forward, sideward and backward cross sections (σFSC, σSSC and σsubbsubb/sub/sub) were derived for two species morphologically different (Chlamydomonas concordia and Thalassiosira pseudonana). The objective of this work is to check the validity of the estimates before any applications in the frame of marine optics studies. Thus, estimates of σFSC and σSSC are tested with radiative transfer computations as no in situ measurements are available. A synthetic database is built considering homogeneous, multi-layered spheres, aggregates and cylinders. Scanning electron micrographs were performed to investigate the cell morphology to simulate particles as close as possible to the real cells. This set of numerical results represents a valuable database for many kinds of applications dealing with marine optics. Comparisons showed that the Cytosense estimates for the cultures are consistent with values predicted by the theory. In average, more than 92% of the Cytosense estimates were encompassed by predicted values. The backscattering cross section and the backscattering efficiency were compared with in situ measurements found in the literature wherever possible. Results showed that σsubbsubb/sub/suband Qsubbsubb/sub/subestimations fall within the range of the referenced values.

Increasing our knowledge on dissolved organic carbon (DOC) spatio-temporal distribution in the coastal ocean represents a crucial challenge for better understanding the role of these ecosystems in the global oceanic carbon cycle. The assessment of DOC concentration from the absorption properties of the colored part of the dissolved organic matter (a(cdom)) was investigated from an extensive data set covering a variety of coastal environments. Our results confirmed that variation in the acdom(412) to DOC ratio (a*(cdom)(412)) can be depicted from the CDOM spectral slope in the UV domain (S275-295). They also evidenced that regional first order variation in both a*(cdom)(412) and S275-295 are highly correlated to variation in acdom(412). From these observations, generalized relationships for estimating a*(cdom)(412) from S275-295 or a(cdom)(412) were parameterized from our development sites (N = 158; English Channel, French Guiana, Hai Phong Bay) and tested against an independent data set covering others coastal regions (N = 223; French Polynesia, Rhone River estuary, Gulf of Maine, Chesapeake Bay, Southern Middle Atlantic Bight) demonstrating the possibility to derive DOC estimates from in situ CDOM optical properties with an average accuracy of similar to 16% over very contrasted coastal environments (with DOC ranging from 50 to 250 mu mol.L-1). The applicability of these generalized approaches was evaluated in the context of ocean color remote sensing observation emphasizing the limits of S275-295-based formulations and the potential for a(cdom)-based approaches to represent a compelling alternative for assessing synoptic DOC distribution. (C) 2015 Optical Society of America

Phytoplankton observation in the ocean can be a challenge in oceanography. Accurate estimations of their biomass and dynamics will help to understand ocean ecosystems and refine global climate models. This requires relevant datasets of phytoplankton at a functional level and on a daily and sub meso scale. In order to achieve this, an automated, high frequency, dedicated scanning flow cytometer (SFC, Cytobuoy, NL), 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~pocket Ferry Box during a cruise in the North Sea, 8–12 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 resolution spacial 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 analyzing chlorophyll a and the scanning flow cytometer, using the integrated red fluorescence emitted by each counted cell, showed significant correlations. The community structure observed from the automated flow cytometry was compared with the PHYSAT reflectance anomalies over a daily scale. The number of matchups observed between the SFC automated high frequency in situ sampling and the remote sensing was found to be two to three times better than when using traditional water sampling strategies. Significant differences in the phytoplankton community structure within the two days for which matchups were available, suggest that it is possible to label PHYSAT anomalies not only with dominant groups, but at the level of the community structure.

[1] 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.

International audience; Past years have seen the development of different approaches to detect phytoplankton groups from space. One of these methods, the PHYSAT one, is empirically based on reflectance anomalies. Despite observations in good agreement with in situ measurements, the underlying theoretical explanation of the method is still missing and needed by the ocean color community as it prevents improvements of the methods and characterization of uncertainties on the inversed products. In this study, radiative transfer simulations are used in addition to in situ measurements to understand the organization of the signals used in PHYSAT. Sensitivity analyses are performed to assess the impact of the variability of the following three parameters on the reflectance anomalies: specific phytoplankton absorption, colored dissolved organic matter absorption, and particles backscattering. While the later parameter explains the largest part of the anomalies variability, results show that each group is generally associated with a specific bio-optical environment which should be considered to improve methods of phytoplankton groups detection

The fine-scale study of the diffuse attenuation coefficient, K d (λ), of the spectral solar downward irradiance is only feasible by ocean color remote sensing. Several empirical and semi-analytical methods exist. However, most of these models are generally applicable for clear open ocean waters and estimate this coefficient only at 490 nm. They show limitations when applied to coastal waters. A new empirical method based on neural networks has been developed using a relationship between the remote-sensing reflectances between 412 and 670 nm and K d (λ) between 412 and 490 nm, for the SeaWiFS ocean color remote sensor. The first results concern the estimation of K d (490). The architecture of the neural network has been defined using synthetical and in situ dataset The comparison with the SeaWiFS empirical algorithms shows similar retrievals accuracies for low values of K d (490) (i.e.

The fine-scale study of the diffuse attenuation coefficient, K d (O ), of the spectral solar downward irradiance is only feasible by ocean color remote sensing. Several empirical and semi-analytical methods exist. However, most of tthese models are generally applicable for clear open ocean waters . They show limitations when applied to coastal waters. A new empirical method based on neural networks has been developed using a relationship between the remote-sensing reflectances between 412 and 670 nm and K d (490), for the SeaWiFS ocean color re mote sensor. The architecture of the neural network has been defined using synthetical and in situ dataset and the optimal design is a tow hidden layer neural network with 4 neurons of the first layer and three on the second layer. The comparis on with the SeaWiFS empirical algorithms shows similar retrievals accuracies for low values of K d (490) (i.e.

International audience; The impact of the inherent optical properties (IOP) variability on the chlorophyll, Chl, retrieval from ocean color remote sensing algorithms is analyzed from an in situ data set covering a large dynamic range. The effect of the variability of the specific phytoplankton absorption coefficient, a(phy)/Chl, specific particulate backscattering coefficient, b(bp)/Chl, and colored detrital matter absorption to non-water absorption ratio, a(cdm)/a(nw), on the performance of standard operational algorithms is examined. This study confirms that empirical algorithms are highly dependent on the specifics IOP values (especially b(bp)/Chl and a(cdm)/a(nw)): Chl is over-estimated in waters with specific IOP values higher than averaged values, and vice versa. These results clearly indicate the necessity to account for the influence of the specific IOP variability in Chl retrieval algorithms.

International audience; A methodology is developed to derive the backscattering cross section of individual particles as measured with the CytoSense (CytoBuoy b.v., NL). This in situ flow cytometer detects light scatter in forward and sideward directions and fluorescence in various spectral bands for a wide range of particles. First, the weighting functions are determined for the forward and sideward detectors to take into account their instrumental response as a function of the scattering angle. The CytoSense values are converted into forward and sideward scattering cross sections. The CytoSense estimates of uniform polystyrene microspheres from 1 to 90 μm are compared with Mie computations. The mean absolute relative differences ΔE are around 33.7% and 23.9% for forward and sideward scattering, respectively. Then, a theoretical relationship is developed to convert sideward scattering into backscattering cross section, from a synthetic database of 495,900 simulations including homogeneous and multi-layered spheres. The relationship follows a power law with a coefficient of determination of 0.95. To test the methodology, a laboratory experiment is carried out on a suspension of silica beads to compare backscattering cross section as measured by the WET Labs ECO-BB9 and derived from CytoSense. Relative differences are between 35% and 60%. They are of the same order of magnitude as the instrumental variability. Differences can be partly explained by the fact that the two instruments do not measure exactly the same parameter: the cross section of individual particles for the CytoSense and the bulk cross section for the ECO-BB9.

A methodology is presented to estimate aerosol altitude from reflectance ratio measurements in the O2 absorption A-band. Previous studies have shown the impact of the vertical distribution of scatterers on the reflectance ratio. The reflectance ratio is defined as the ratio of the reflectance in a first spectral band, strongly attenuated by O2 absorption, to the reflectance in a second spectral band, minimally attenuated. First, a sensitivity study is performed to quantify the expected accuracy for various aerosol loadings and models. An accurate, high spectral resolution, radiative transfer model that fully accounts for interactions between scattering and absorption is used in the simulations. Due to their adequate spectral characteristics, POLDER and MERIS instruments are considered for simulations. For a moderately loaded atmosphere (i.e., aerosol optical thickness of 0.3 at 760 nm), the expected error on aerosol altitude is about 0.3 km for MERIS and 0.7 km for POLDER. More accurate estimates are obtained with MERIS, since the spectral reflectance ratio is more sensitive. Second, the methodology is applied to MERIS and POLDER imagery. Estimates of aerosol altitude are compared with lidar profiles of backscattering coefficient acquired during the AOPEX-2004 experiment. Retrievals are consistent with measurements and theory. These comparisons demonstrate the potential of the differential absorption methodology for obtaining information on aerosol vertical distribution.

The particulate backscattering coefficient and the degree of polarization provide a means to study and characterize the nature of suspended marine particles. Here, we show that such information may be retrieved from remote sensing.

[1] A methodology is presented and evaluated to retrieve vertically integrated water vapor content over the ocean in any viewing geometry from POLDER data. The methodology is based on differential absorption by water vapor in the near-infrared. Over the ocean, except in sun glint conditions, surface reflectance is small, and interaction between aerosol scattering and water vapor absorption is exploited to estimate total water vapor content. A sensitivity study performed with an accurate radiative transfer code (GAME) shows that a determination of total water vapor content is theoretically possible if the optical thickness and scale height of aerosols are known. An inaccuracy of 0.1 to 0.6 g cm−2 is expected, depending on water vapor content. The aerosol optical thickness δa at 865 nm is available from POLDER standard products. The aerosol scale height Ha can be estimated from the surface pressure derived from POLDER oxygen channels at 763 and 765 nm. A retrieval scheme is devised using parameterizations calculated using GAME for water vapor and surface pressure. The inversion scheme is applied to 20 POLDER orbits with observed water vapor contents ranging from 0.2 to 6 g cm−2. Comparisons with SSM/I estimates indicate a RMS error ranging from 0.21 to 0.58 g cm−2, depending on water vapor content, with a mean RMS error of 0.44 g cm−2. This result is slightly larger than deviations obtained between POLDER and SSM/I during the POLDER standard product validation over ocean in sun glint conditions (mean RMS error of 0.42 g cm−2).

The biogeochemical characterization of marine particles suspended in sea water, is of fundamental importance in many areas of ocean science. Previous studies based on theoretical calculations and field measurements have demonstrated the importance of the use of the polarized light field in the retrieval of the suspended marine particles properties. However, because of the weakness of the water leaving polarized signal and of the limited number of appropriate spatial sensors, such measurements have never been exploited from space. Here we show that the marine polarized remote sensing reflectance, as detected from the POLarization and Directionality of the Earth's Reflectances (POLDER) sensor, can be measured from space over bright waters and in absence of aerosols. This feasibility study is carried out over two oceanic areas characterized by different nature of the bulk particulate assemblage: the Barents sea during an intense coccolithophore bloom, and the Rio de la Plata estuary waters dominated by suspended sediments. The retrieved absolute values of the degree of polarization, P, its angular pattern, and its behavior with the scattering level are consistent with theory and field measurements. Radiative transfer simulations confirm the sensitivity of the POLDER-2 P values to the nature of the particulate assemblage. These preliminary results are very promising for the assessment of the bulk particle composition from remote sensing of the polarized signal, at least over highly scattering waters.

A methodology for water vapor retrieval over ocean, using a differential absorption technique from near-IR channels, is presented. Over ocean, surface reflectance is close to zero and aerosol scattering is used to estimate water vapor contents, from an accurate radiative transfer code to account for optical thickness and scale height of aerosols. This method has been applied to POLDER data and comparisons with ECMWF (European Centre for Medium-Range Weather Forecasts) data are presented over the Straits of Gibraltar.