Ocean Color Observations Research Articles

A Multidisciplinary Remote Sensing Ocean Color Sensor: Analysis of User Needs and Recommendations for Future Developments

Advancing remote sensing into the future to serve the expanding needs of the scientific community requires enhancing current capabilities of space-borne sensors and sustaining ocean color observations for diverse applications. In this study, an extensive set of experimental and space-borne measurements is analyzed for describing the operating characteristics of a global multidisciplinary ocean color sensor. Essential requirements for a successful mission include sensor characterization, high signal-to-noise ratio (SNR) and dynamic range, sensor stability, minimal polarization sensitivity, on-orbit calibration, vicarious calibration, atmospheric and in-water algorithms, product validation, and widely distributed regional and global products. To achieve high-quality products, an in-depth analysis of some key design aspects is provided which include spectral band sets, radiance levels, SNR, and dynamic range. These are essential characteristics of satellite sensors for measuring atmospheric signal in both ocean color and aerosol bands without saturation yet allowing high sensitivity measurements of water-leaving radiances and enabling ocean color measurements in aerosol and sun-glint contaminated regions of the ocean. Provisions to meet other requirements for improving retrievals of chlorophyll and phycocyanin fluorescence, partitioning algal and nonalgal color signals, and for implementing new approaches in atmospheric correction are further discussed. With these new capabilities and key design features, it will become feasible to resolve ocean color signals under most environmental circumstances and answer science questions related to changing conditions in the coastal and marine ecosystems and biogeochemical cycles due to climate change.

Satellite-measured interannual variability of turbid river plumes off central-southern Chile: Spatial patterns and the influence of climate variability

Ocean color imagery from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the Aqua platform is used to characterize the interannual variability of turbid river plumes off central-southern Chile. Emphasis is placed on the influence of climate fluctuations, namely El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the Antarctic Oscillation (AAO). Additional satellite data on wind, boat-based hydrographic profiles, and regional climate indices are used to identify the influence of climate variability on the generation of anomalous turbid river plumes. The evolution of salinity at a coastal station on the 90m isobath between the Itata and Biobío Rivers shows a freshwater surface layer with salinity <32.5 and 5–10m thick during major plume events in 2002, 2005 and 2006. Surface salinity minima are correlated with peaks in turbidy from the normalized water leaving radiance at 555nm (nLw(555)), both representing turbid river plumes. EOF analysis reveals that major turbid plume events occurred primarily during warm phases of the ENSO and PDO, and negative phases of the AAO, when storm tracks are further north. Anomalously large turbid plumes extend long distances offshore (∼70–80km), and individual plumes coalesce into a continuous plume along the coast that covers the entire continental shelf. Season-specific correlation analyses reveal an increased influence of the AAO on river plumes south of Punta Lavapié in spring-summer (negative correlation). North of this major cape, ENSO and PDO indices have a dominant influence on plumes with positive correlations with the nLw(555) signal in winter (and negative in summer). We discuss the biogeochemical implications of plume events and the importance of long-term and high-resolution ocean color observations for studying the temporal evolution of river plumes.

Interannual variability of the Mediterranean trophic regimes from ocean color satellites

Abstract. D'Ortenzio and Ribera d'Alcalà (2009, DR09 hereafter) divided the Mediterranean Sea into “bioregions” based on the climatological seasonality (phenology) of phytoplankton. Here we investigate the interannual variability of this bioregionalization. Using 16 years of available ocean color observations (i.e., SeaWiFS and MODIS), we analyzed the spatial distribution of the DR09 trophic regimes on an annual basis. Additionally, we identified new trophic regimes, exhibiting seasonal cycles of phytoplankton biomass different from the DR09 climatological description and named “Anomalous”. Overall, the classification of the Mediterranean phytoplankton phenology proposed by DR09 (i.e., “No Bloom”, “Intermittently”, “Bloom” and “Coastal”), is confirmed to be representative of most of the Mediterranean phytoplankton phenologies. The mean spatial distribution of these trophic regimes (i.e., bioregions) over the 16 years studied is also similar to the one proposed by DR09, although some annual variations were observed at regional scale. Discrepancies with the DR09 study were related to interannual variability in the sub-basin forcing: winter deep convection events, frontal instabilities, inflow of Atlantic or Black Sea Waters and river run-off. The large assortment of phytoplankton phenologies identified in the Mediterranean Sea is thus verified at the interannual scale, further supporting the “sentinel” role of this basin for detecting the impact of climate changes on the pelagic environment.

Development of Structural Thermal Model of MicroDragon Satellite for Vietnam National Satellite Center

MicroDragon (MDG) is the first 50-kg satellite developed by researchers of Vietnam National Satellite Center (VNSC) in collaboration with Okuyama laboratory to develop the structure. The satellite shall be launched by H2A rocket in beginning of 2018. The main mission of this satellite is the observation of ocean color to assess coastal water quality and locate living resources. The system will provide data which will be used and analyzed by researchers and scientists in fishery and oceanography. Finally, the information will be distributed and exploited by fishermen and environmental managers. In this article, the structural thermal model (STM) of MDG is presented from the point of view the natural frequency analysis by finite element method (FEM) and the results of vibration test. The FEM model is carried out by Nei-works Nastran embedded in Solidworks software. The validity of the FEM analysis results is assured by comparing to the results of vibration test.

Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations.

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites and in situ physical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA's operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed—signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN's generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series.

Estimating the Bulk Refractive Index and Related Particulate Properties of Natural Waters From Remote-Sensing Data

A proof-of-concept method is developed to estimate bulk refractive index ( ${{{\eta }}_{{\bm {bp}}}}$ ) of particles for deriving information on their composition and optical properties of natural waters using satellite ocean color data. It estimates ${{{\eta }}_{{\bm {bp}}}}$ as a function of the backscattering ratio ( ${{\bm {B}}_{\bm {p}}}$ ), hyperbolic slope of the particle size distribution ( ${{\xi }}$ derived from the beam attenuation slope ${{\beta }}$ ), and apparent density of particles ( ${{{\rho }}_{\bm {a}}}$ ) as described in our previous inversion model. For deriving these parameters from remote-sensing data, large in situ measurement data of the remote-sensing reflectance ( ${{\bm {R}}_{{\bm {rs}}}}$ ), particulate scattering ( ${{\bm {b}}_{\bm {p}}}$ ), backscattering ( ${{\bm {b}}_{{\bm {bp}}}}$ ) beam attenuation ( ${{\bm {c}}_{\bm {p}}}$ ), and seawater constituents’ concentrations are used to establish the required relationships and derive the model parameters (i.e., ${{{\eta }}_{{\bm {bp}}}} \leftarrow {{\bm {B}}_{\bm {p}}}$ , ${{\xi }}$ , ${{{\rho }}_{\bm {a}}}$ ; ${{\bm {B}}_{\bm {p}}} \leftarrow {{\bm {R}}_{{\bm {rs}}}}$ ; ${{\xi }} \leftarrow {{\beta }} \leftarrow {{\bm {c}}_{\bm {p}}} \leftarrow {\bf Turbidity}$ ; ${\bf Turbidity} \leftarrow {{\bm {R}}_{{\bm {rs}}}}$ ; and ${{{\rho }}_{\bm {a}}} \leftarrow {{\bm {c}}_{\bm {p}}}$ ). When validated with those derived from in situ data spanning the large dynamic range in water optical properties and relevant water constituents impacting the remote-sensing signal, the derived model parameters and bulk refractive index had errors of a few percent which falls well within the benchmark for a validated uncertainty of ${\rm \pm }{\bf 35}\% $ endorsed for the remote-sensing retrieval of chlorophyll- $a$ in oceanic waters. The model was applied to regional and global images of satellite ocean color observations provided by the MODIS-Aqua sensor. Global images of seasonal climatology over a decade of MODIS-Aqua ocean color observations provided interesting insights into the seasonal variability of ${{{\eta }}_{{\bm {bp}}}}$ in coastal and open ocean waters. To further investigate the bulk particulate assemblages in some regional waters, several MODIS-Aqua imageries from different regional waters dominated by sediment-laden river plumes and phytoplankton blooms were analyzed. Satellite retrievals of the ${{{\eta }}_{{\bm {bp}}}}$ varied from 1.035 to 1.05 for clear oceanic waters, 1.045–1.07 for phytoplankton-dominated waters (higher water content), 1.05–1.15 for floating algal blooms and Cocolithophore blooms, 1.07–1.10 for coastal waters dominated by detrital particles, and 1.10–1.28 for river plume and sediment-laden coastal waters (lower water content). These results were consistent with those expected for the waters examined, being in excellent agreement with the previous reports and estimates based on the laboratory/ in situ measurements and modeling studies. Given the fact that there is currently no satellite-based method to differentiate between bulk particulate compositions, the new method provides a valuable tool for estimating ${{{\eta }}_{{\bm {bp}}}}$ values as a proxy for the apparent density and composition of particles and such information when derived from satellite ocean color data provides new tools for improving our current understanding of particle dynamics of pelagic ecosystems, advancing biogeochemical modeling, assessing the global ocean ecosystem, and elucidating the coastal processes.

Shelf break exchange events near the De Soto Canyon

Observations of currents, temperature, sea-surface height, sea-surface temperature and ocean color, derived from moorings, surface and deep drifters, hydrographic surveys, and satellites, are used to characterize shelf-slope exchange events near the apex of the De Soto Canyon in the northeast Gulf of Mexico. During the winter of 2012–2013, shelf-break time series showed a number of events where cold shelf water extruded over the slope. These events were largely consistent with slope eddies of both signs influencing shelf break currents. Larger-scale circulations, derived from the Loop Current and a separating Loop Current eddy, strongly influenced circulation over the De Soto slope during summer 2012, with flow patterns consistent with potential vorticity conservation over shoaling topography. Statistical investigation into shelf-slope exchange using large numbers of surface drifters indicated that export from the shelf is larger than vice-versa, and is more uniformly distributed along the shelf break. Import onto the shelf appears to favor a region just east of the Mississippi Delta, which is also consistent with the observed onshore transport of surface oil from the Deepwater Horizon disaster.

Autonomous profiling float observations of the high-biomass plume downstream of the Kerguelen Plateau in the Southern Ocean

Abstract. Natural iron fertilisation from Southern Ocean islands results in high primary production and phytoplankton biomass accumulations readily visible in satellite ocean colour observations. These images reveal great spatial complexity with highly varying concentrations of chlorophyll, presumably reflecting both variations in iron supply and conditions favouring phytoplankton accumulation. To examine the second aspect, in particular the influences of variations in temperature and mixed layer depth, we deployed four autonomous profiling floats in the Antarctic Circumpolar Current near the Kerguelen Plateau in the Indian sector of the Southern Ocean. Each "bio-profiler" measured more than 250 profiles of temperature (T), salinity (S), dissolved oxygen, chlorophyll a (Chl a) fluorescence, and particulate backscattering (bbp) in the top 300 m of the water column, sampling up to 5 profiles per day along meandering trajectories extending up to 1000 km. Comparison of surface Chl a estimates (analogous to values from satellite images) with total water column inventories revealed largely linear relationships, suggesting that these images provide credible information on total and not just surface biomass spatial distributions. However, they also showed that physical mixed layer depths are often not a reliable guide to biomass distributions. Regions of very high Chl a accumulation (1.5–10 μg L−1) were associated predominantly with a narrow T–S class of surface waters. In contrast, waters with only moderate Chl a enrichments (0.5–1.5 μg L−1) displayed no clear correlation with specific water properties, including no dependence on mixed layer depth or the intensity of stratification. Geostrophic trajectory analysis suggests that both these observations can be explained if the main determinant of biomass in a given water parcel is the time since leaving the Kerguelen Plateau. One float became trapped in a cyclonic eddy, allowing temporal evaluation of the water column in early autumn. During this period, decreasing surface Chl a inventories corresponded with decreases in oxygen inventories on sub-mixed-layer density surfaces, consistent with significant export of organic matter (~35%) and its respiration and storage as dissolved inorganic carbon in the ocean interior. These results are encouraging for the expanded use of autonomous observing platforms to study biogeochemical, carbon cycle, and ecological problems, although the complex blend of Lagrangian and Eulerian sampling achieved by the floats suggests that arrays rather than single floats will often be required, and that frequent profiling offers important benefits in terms of resolving the role of mesoscale structures on biomass accumulation.

Phytoplankton phenology indices in coral reef ecosystems: Application to ocean-color observations in the Red Sea

Phytoplankton, at the base of the marine food web, represent a fundamental food source in coral reef ecosystems. The timing (phenology) and magnitude of the phytoplankton biomass are major determinants of trophic interactions. The Red Sea is one of the warmest and most saline basins in the world, characterized by an arid tropical climate regulated by the monsoon. These extreme conditions are particularly challenging for marine life. Phytoplankton phenological indices provide objective and quantitative metrics to characterize phytoplankton seasonality. The indices i.e. timings of initiation, peak, termination and duration are estimated here using 15years (1997–2012) of remote sensing ocean-color data from the European Space Agency (ESA) Climate Change Initiative project (OC-CCI) in the entire Red Sea basin. The OC-CCI product, comprising merged and bias-corrected observations from three independent ocean-color sensors (SeaWiFS, MODIS and MERIS), and processed using the POLYMER algorithm (MERIS period), shows a significant increase in chlorophyll data coverage, especially in the southern Red Sea during the months of summer NW monsoon. In open and reef-bound coastal waters, the performance of OC-CCI chlorophyll data is shown to be comparable with the performance of other standard chlorophyll products for the global oceans. These features have permitted us to investigate phytoplankton phenology in the entire Red Sea basin, and during both winter SE monsoon and summer NW monsoon periods. The phenological indices are estimated in the four open water provinces of the basin, and further examined at six coral reef complexes of particular socio-economic importance in the Red Sea, including Siyal Islands, Sharm El Sheikh, Al Wajh bank, Thuwal reefs, Al Lith reefs and Farasan Islands. Most of the open and deeper waters of the basin show an apparent higher chlorophyll concentration and longer duration of phytoplankton growth during the winter period (relative to the summer phytoplankton growth period). In contrast, most of the reef-bound coastal waters display equal or higher peak chlorophyll concentrations and equal or longer duration of phytoplankton growth during the summer period (relative to the winter phytoplankton growth period). The ecological and biological significance of the phytoplankton seasonal characteristics are discussed in context of ecosystem state assessment, and particularly to support further understanding of the structure and functioning of coral reef ecosystems in the Red Sea.

Analysis of riverine suspended particulate matter fluxes (Gulf of Lion, Mediterranean Sea) using a synergy of ocean color observations with a 3‐D hydrodynamic sediment transport model

AbstractThe export of riverine suspended particulate matter (SPM) in the coastal ocean has major implications for the biogeochemical cycles. In the Mediterranean Sea (France), the Rhone River inputs of SPM into the Gulf of Lion (GoL) are highly variable in time, which severely impedes the assessment of SPM fluxes. The objectives of this study are (i) to investigate the prediction of the land‐to‐ocean flux of SPM using the complementarity (i.e., synergy) between a hydrodynamic sediment transport model and satellite observations, and (ii) to analyze the spatial distribution of the SPM export. An original approach that combines the MARS‐3D model with satellite ocean color data is proposed. Satellite‐derived SPM and light penetration depth are used to initialize MARS‐3D and to validate its predictions. A sensitivity analysis is performed to quantify the impact of riverine SPM size composition and settling rate on the horizontal export of SPM. The best agreement between the model and the satellite in terms of SPM spatial distribution and export is obtained for two conditions: (i) when the relative proportion of “heavy and fast” settling particles significantly increases relative to the “light and slow” ones, and (ii) when the settling rate of heavy and light SPM increases by fivefold. The synergy between MARS‐3D and the satellite data improved the SPM flux predictions by 48% near the Rhone River mouth. Our results corroborate the importance of implementing satellite observations within initialization procedures of ocean models since data assimilation techniques may fail for river floods showing strong seasonal variability.

Satellite observations of the small-scale cyclonic eddies in the western South China Sea

Abstract. High-resolution ocean color observations offer an opportunity to investigate the oceanic small-scale processes. In this study, the Medium Resolution Imaging Spectrometer (MERIS) daily 300 m data were used to study small-scale processes in the western South China Sea. It is indicated that the cyclonic eddies with horizontal scales of 10 km are frequently observed during the upwelling season of each year over the 2004–2009 period. These small-scale eddies were generated in the vicinity of the southern front of the cold tongue, and then propagated eastward with a speed of approximately 12 cm s−1. This propagation speed was consistent with the velocity of the western boundary current. As a result, the small-scale eddies kept the high levels of phytoplankton rotating away from the coastal areas, resulting in the accumulation of phytoplankton in the interior of the eddies. The generation of the small-scale eddies may be associated with strengthening of the relative movement between the rotation speed of the anticyclonic mesoscale eddies and the offshore transport. With the increases of the normalized rotation speed of the anticyclonic mesoscale eddies relative to the offshore transport, the offshore current became a meander under the impacts of the anticyclonic mesoscale eddies. The meandered cold tongue and instability front may stimulate the generation of the small-scale eddies. Unidirectional uniform wind along the cold tongue may also contribute to the formation of the small-scale eddies.

Southern Ocean wind‐driven entrainment enhances satellite chlorophyll‐a through the summer

AbstractDespite being the largest High Nitrate Low Chlorophyll (HNLC) region, the Southern Ocean sustains phytoplankton blooms through the summer, when presumably there is sufficient light, but nutrients in the euphotic zone have been depleted. Physical processes that can potentially supply nutrients from subsurface waters to the euphotic zone, and promote phytoplankton growth in the summer, have not been fully explored at the large scale. By means of a correlation analysis, this study combines high‐resolution satellite observations of ocean color, winds and sea surface temperature, surface heat fluxes from reanalysis and Argo mixed‐layer depth (MLD) estimates to explore the role of the atmospheric forcing (i.e., winds and surface heat fluxes) on upper ocean processes that may help sustain high satellite chlorophyll‐a (Chl‐a) through the summer. Two physical processes that can supply nutrients to the euphotic zone are: MLD deepening, caused by wind‐mixing and/or surface cooling, and Ekman pumping driven by the wind stress curl. We find that high winds correlate with high Chl‐a over broad open ocean areas, suggesting that transient MLD deepening through wind‐mixing (i.e., wind‐driven entrainment) helps sustain high Chl‐a. Wind‐driven entrainment plays a dominant role on time scales associated with atmospheric synoptic storms (i.e., &lt;10 days) and has a larger influence on surface Chl‐a than storm scale local Ekman pumping. Based on our analysis of statistically significant correlation patterns, we identify regions in the Southern Ocean where wind‐induced entrainment may play a role in sustaining summer phytoplankton blooms.

A model for estimating size-fractioned phytoplankton absorption coefficients in coastal and oceanic waters from satellite data

One of the central goals of using satellite ocean color remote sensing is to detect and identify different phytoplankton groups (size classes) and describe their variability continuously and synoptically for various applications including marine ecosystem dynamics, carbon and biogeochemical cycles, and related fields in oceanography. Taking the advantage of phytoplankton communities having distinct optical properties, this study presents a new model to explicitly detect and differentiate between three phytoplankton size-classes namely, picophytoplankton, nanophytoplankton, and microphytoplankton, based on distinct differences in the optical signatures of these phytoplankton groups in a wide variety of coastal and oceanic waters. The model is based on the assumption that there is a significant relationship between chlorophyll-a concentration, and total as well as the size-fractioned absorption coefficients of phytoplankton. The new model is validated using three different in-situ datasets collected from a wide variety of locations in the global and regional oceans (including turbid coastal and eutrophic waters) and its results are further compared with those of the existing two- and three-component models. The new model performs better than other models in terms of yielding more accurate estimates of the total and size-dependent phytoplankton absorption coefficients across the entire visible wavelengths. Since satellite observation of ‘ocean color’ as detected by a remote sensor provides an estimate of the chlorophyll-a concentration, commonly used as an index of phytoplankton biomass, the new model is also applied to regional and global images of seasonal climatology over a decade of satellite ocean color observations provided by the MODIS-Aqua sensor. When applied to the MODIS-Aqua images of the Arabian Sea dominated by spatially intense algal blooms, the present model is generally excellent at predicting and describing the spatial distribution of these phytoplankton groups within cyclonic eddies and adjacent regions in the Arabian Sea. Conversely, size-fractioned phytoplankton absorption coefficients derived from global images of seasonal climatology are found to vary depending on the season and ocean basin. These global images imply that when phytoplankton abundance increases, larger size-classes are added incrementally to a background of smaller cells. Further examination of these data showed that picophytoplankton population is generally low, although dominating a major part of the surface ocean during summer and winter. Nanophytoplankton and microphytoplankton populations are high in surface waters of the North and South Atlantic, North and South Pacific Oceans, Arabian Sea, and equatorial region, showing an increasing trend in summer and a decreasing trend in winter in each hemisphere. These results suggest that the new model is an important tool which will inspire further research to investigate different phytoplankton size classes and their variability on regional and global scales.

On the temporal consistency of chlorophyll products derived from three ocean-colour sensors

Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.

On-orbit radiometric characterization of OLI (Landsat-8) for applications in aquatic remote sensing

Landsat-8 carries two separate sensors, namely the Operational Land Imager (OLI) and the Thermal Infrared Radiometer Suite (TIRS), that image the earth surface throughout the visible and thermal portions of the spectrum. Compared to Landsat heritage sensors, the OLI has enhanced features, which include its 12-bit radiometric resolution and the addition of a band centered at 443nm. The dramatically improved data quality/quantity expands existing applications of Landsat imagery in aquatic sciences from the retrieval of bio-geochemical properties, such as near-surface concentrations of chlorophyll-a (CHL) and total suspended solids (TSS), to benthic mapping. This study offers analysis of OLI's absolute radiometric performance over bodies of water using benchmark observations, namely the top-of-atmosphere (TOA) ocean color observations and marine in situ radiometric measurements. Sensor-to-sensor comparisons are performed to derive gain factors (g1) from near-concurrent observations in TOA radiance and reflectance domains. The gains in the radiance domain were further validated/adjusted by determining a second set of gains (g2) via analysis of OLI-derived water-leaving radiance, i.e., Lw(λ), against in situ measurements made either at the Ocean Color AErosol RObotic NETwork (AERONET-OC) sites or during field campaigns. The analyses yield the OLI calibration uncertainties that need to be accounted for when studying aquatic environments. It was found that, for the visible and near-infrared channels, the OLI radiometric responses, on average, are well in agreement (<2% discrepancies) with the TOA radiances estimated by ocean color satellites or those predicted by models based on measurements of aquatic and atmospheric properties. However, the TOA radiance at the new 443-nm band is found to be, on average, 3.4% larger than the reference observations. The inter-sensor comparisons in the reflectance domain, however, indicated slightly different results with the OLI responses being low in the blue bands. To enhance the retrieval accuracy of aquatic-science products from OLI datasets, sets of temporally averaged gains (radiance and reflectance) are derived and recommended for use prior to the retrieval of in-water products.

Diel variability of the beam attenuation and backscattering coefficients in the northwestern Mediterranean Sea (BOUSSOLE site)

AbstractThe diel variability of the particulate beam attenuation coefficient, cp, and of the particulate backscattering coefficient, bbp, were investigated during five seasonal cycles at an oceanic site in the northwestern Mediterranean Sea, covering contrasting physical and trophic situations. We observed a diel cycle in cp and bbp, related to changes in phytoplankton properties (i.e., size and refractive index) induced by the accumulation of carbon within phytoplankton cells associated with photosynthetic processes, during the winter mixing of the water column, the development of the spring phytoplankton bloom, its decline, and during the summer oligotrophy. The relative amplitude of the cp diel variability was much larger during the spring bloom (20–50%) than during other seasons (10–20%), whereas that of bbp is steadily around 20% and does not show significant seasonal variability. The minimal cp and bbp occurred at sunrise and are synchronized, whereas maximum bbp values are often reached 3–6 h before those for cp (except during bloom conditions), which occur near sunset. These different amplitudes and timing are tentatively explained using Mie computations, which allow discerning the respective roles of changes in the particle size distribution and refractive index. The differences observed here in the diel cycles of cp and bbp show that they cannot be used interchangeably to determine the daily increase of the particle pool. This result has implications on the feasibility to determine net community production from the bbp diel changes, when only bbp is measured in situ or available from ocean color observations.

Impact of missing data on the estimation of ecological indicators from satellite ocean-colour time-series

Ocean-colour remote sensing provides high-resolution and global-coverage of chlorophyll concentration, which can be used to estimate ecological indicators and to study inter-annual and long-term trends in the state of the marine ecosystem. To date, the record of ocean-colour observations is a rich one, including data from a number of sensors spanning more than three decades. The ESA Ocean-Colour Climate Change Initiative has advanced seamless merging of ocean-colour observations from missions during the period 1990s to 2010s. However, comparison of these more recent observations with records from 1970s to 1980s remains a complex undertaking, particularly for absolute values of chlorophyll concentration, primarily due to differences in the sensors. A further impediment to the analysis of the past records is the non-uniform distribution of gaps in the observations, in both time and space dimensions, when data from two or more sensors are compared. Here, we use the CZCS gap distribution from the Coastal Zone Color Scanner (CZCS, 1978–1986) as a mask to evaluate the impact that missing data may have on the estimation of six ecological indicators, when using the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data set. Specifically, we evaluate the precision and accuracy of indicators by computing the root-mean-square-error (RMSE) and the bias arising purely from missing data. We develop an original resampling method allowing comparison of indicator estimates between SeaWiFS reference time-series and SeaWiFS time-series with CZCS-like gaps. We reduce some of the sampling gaps by applying a linear interpolation procedure, and compute multi-year averages of the indicators for every one-by-one degree pixel where sufficient data are available. Indicators from SeaWiFS reference and SeaWiFS with CZCS-like gaps are compared. Lowest uncertainty arising from missing data is observed in the indicators of annual mean and median chlorophyll concentration (global mean RMSE of 8% and |bias| ≤1%), whilst higher uncertainty is recorded for the peak chlorophyll values and the duration of the phytoplankton growing period (global mean RMSE of 33 and 47% respectively and |bias| ≤20%). Timing of initiation of the increasing phase of chlorophyll concentration in the seasonal cycle and timing of peak chlorophyll are subject to a global mean RMSE of nearly two months and a bias of two weeks or less. The present quantitative evaluation of uncertainty due to missing data demonstrates that, when pooled to create a nine-year climatology at 8-day temporal resolution, the coverage of CZCS is adequate for many climate-related studies on the marine ecosystem. Phytoplankton annual mean biomass can be estimated with low error in approximately 95% of the global oceans (i.e. regions where the indicators can be estimated with RMSE values of less than 30% and bias within ±10%), and the phenological patterns can be estimated with low error in approximately 25% of the global oceans.

Assessment of the colored dissolved organic matter in coastal waters from ocean color remote sensing.

Knowledge on absorption by colored dissolved organic matter, a(cdom), spatio-temporal variability in coastal areas is of fundamental importance in many field of researches related to biogeochemical cycles studies, coastal areas management, as well as land and water interactions in the coastal domain. A new method, based on the theoretical link between the vertical attenuation coefficient, K(d), and the absorption coefficient, has been developed to assess a(cdom). This method, confirmed from radiative transfer simulations and in situ measurements, and tested on an independent in situ data set (N = 126), allows a(cdom) to be assessed with a Mean Relative Absolute Difference, MRAD, of 33% over two order of magnitude (from 0.01 to 1.16 m(-1)). In the frame of ocean color observation, K(d) is not directly measured but estimated from the remote sensing reflectance, R(rs). Based on 109 satellite (SeaWiFS) and in situ coincident (i.e. match-up) data points a(cdom) is retrieved with a MRAD value of 37%. This simple model generally presents slightly better performances than recently developed empirical or semi-analytical algorithms.

Multivariate Analysis of the Senegalo-Mauritanian Area by Merging Satellite Remote Sensing Ocean Color and SST Observations

The Senegalo-Mauritanian upwelling is a very productive upwelling occurring along the West coast of Africa. The seasonal and inter-annual variability of the upwelling region between 9° and 22°N and 14° and 25°W was studied by merging monthly ocean color data and sea surface temperature provided by satellite sensors during twelve years from 1998 up to 2010. We combined these two parameters to obtain a unique index describing the spatio-temporal variability of the upwelling. We used a classification methodology consisting in a neural network topological map and a hierarchical ascendant classification. Six classes can explain most of the variability of this region, one of them (class 6) being dedicated to the coastal upwelling water, another being the signature of the Gulf of Guinea dome water (class 2), a third one to case 2 water (class 5). The classes can be considered as multi-factorial statistical indices allowing us to characterize the different water types of this region and to investigate their variability. It is shown that the upwelling extent is maximum in February-March, minimum in August-September. Its variability is linked to that of the wind and to the ITCZ position. The Gulf of Guinea waters moves northward in June and relaxes to their southward position in December. During the twelve years of observation, we were not able to evidence climatic trends of the SST and Chl-a concentration. The methodology we have developed can be used in a large variety of problems implying multi sensor measurements.

Satellite observations of chlorophyll, phytoplankton biomass, and Ekman pumping in nonlinear mesoscale eddies

Nonlinear mesoscale eddies can influence biogeochemical cycles in the upper ocean through vertical and horizontal advection of nutrients and marine organisms. The relative importance of these two processes depends on the polarity of an eddy (cyclones versus anticyclones) and the initial biological conditions of the fluid trapped in the core of the eddy at the time of formation. Eddies originating in the eastern South Indian Ocean are unique in that anticyclones, typically associated with downwelling, contain elevated levels of chlorophyll‐a, enhanced primary production and phytoplankton communities generally associated with nutrient‐replete environments. From analysis of 9 years of concurrent satellite measurements of sea surface height, chlorophyll, phytoplankton carbon, and surface stress, we present observations that suggest eddy‐induced Ekman upwelling as a mechanism that is at least partly responsible for sustaining positive phytoplankton anomalies in anticyclones of the South Indian Ocean. The biological response to this eddy‐induced Ekman upwelling is evident only during the Austral winter. During the Austral summer, the biological response to eddy‐induced Ekman pumping occurs deep in the euphotic zone, beyond the reach of satellite observations of ocean color.