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Several trigger mechanisms have been proposed for the onset of the phytoplankton spring bloom. Among these is that phytoplankton cells begin to bloom when they experience higher average light levels in shallower mixed layers, a result of the surface net heat fluxes becoming positive and wind strength decreasing. We study the impact of these two forcings in the northwestern Mediterranean Sea. We take advantage of hourly measurements of oceanic and atmospheric parameters collected at two neighbouring moorings during the months of March and April in the years 2016 to 2019, combined with glider data in 2016. We identify the onset of the surface phytoplankton growth as concomitant with the start of significant biological activity detected by a sudden decrease in dissolved inorganic carbon derived from measurements in the upper 10 m of the water column. A rapid reduction in wind stress following high-wind events is observed at the same time. A resulting shallow mixing layer favours carbon uptake by phytoplankton lasting a few days. Simultaneously, the air–sea net heat flux switches from negative to positive, linked to changes in the latent air–sea heat flux, which is proportional to the wind speed. This results in an increased thermal stratification of the ocean's surface layers. In 2016, glider data show that the mixing layer is significantly shallower than the mixed layer at the onset of the surface phytoplankton bloom. We conclude that decreases in the mixing- and mixed-layer depths lead to the onset of the phytoplankton growth due to the relaxation of wind speed following storms. We estimate net daily community production in the mixing layer over periods of 3 d between 2016 and 2019 as between 38 and 191 mmol C m−2. These results have important implications, as biological processes play a major role in the seasonal evolution of surface pCO2 and thereby the rate of reduction in atmospheric CO2 by exchange at the air–sea interface.

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.

Utility of data from autonomous profiling floats for the validation of satellite ocean colour products from current satellite ocean colour sensors was assessed using radiometric and chlorophyll a fluorescence data from bio-geochemical profiling floats (BGC-Argo) deployed in the subtropical gyre of the Indian Ocean. One of the floats was equipped with downward irradiance and upwelling radiance sensors, allowing the remote sensing reflectance, R-rs, to be determined. Comparisons between satellite and in situ R-rs, indicated good agreement for the shorter wavelengths, but weak relationships for both satellites for the 555 nm channel, and showed that radiometers deployed on multipurpose, off-the-shelf BGC-Argo floats can provide validation-quality measurements. About 300 chlorophyll a concentration match-ups were achieved within 18 months, which increased the number of validation data points available for the Indian Ocean as a whole by a factor of similar to 4 from the previous historical record. Generally, the satellite data agreed with the float-derived chlorophyll concentration within the uncertainty of +/- 35%, for the band-difference (OCI) and band-ratio (OC3) algorithms, but not for a semi analytical ocean colour model (GSM) that exhibited significantly higher chlorophyll values (> 100% mean difference). Our results indicate that autonomous float-based measurements provide substantial potential for improving regional validation of satellite ocean colour products in remote areas.

International audience; Investigating the variability of phytoplankton phenology plays a key role in regions characterized by cyclonic circulation regimes or convective events, like the north-western Mediterranean Sea (NWM). The main goal of this study is to assess the potential of the robust satellite techniques (RST) in identifying anomalous phytoplankton blooms in the NWM by using 9 years (2008–2017) of multi-sensor chlorophyll-a (chl-a) products from the CMEMS and OC-CCI datasets. Further application of the RST approach on a corresponding time-series of in situ chl-a measurements acquired at the BOUSSOLE site allows evaluation ofthe accuracy of the satellite-based change detection indices and selecting the best indicator. The OC-CCI derived chl-a anomaly index shows the best performances when compared to in situ data (R2 and RMSE of 0.75 and 0.48, respectively). Thus, it has been used to characterize an anomalous chl-a bloom that occurred in March 2012 at regional scale. Results show positive chl-a anomalies between the BOUSSOLE site and the Center of Convection Zone (CCZ) as a possible consequence of an intense convection episode that occurred in February 2012.

International audience; Comprehensively sampling the ocean in situ remains a challenge, even in the current era of rapid technological development. In less than a decade, the deployment of thousands of autonomous profiling floats increased the number of ocean temperature profiles by an order of magnitude compared to ship-based sampling in the past. But expendable floats cannot sample all the physical and biogeochemical regimes in the global ocean. A promising avenue that could guide in situ sampling is to partition oceans based on selected properties in order to identify "homogeneous" areas. This approach greatly reduces the number of measurements needed to represent the state of the ocean. However, homogeneous areas can be partitioned in many ways: depending on whether a single or several properties are considered; and on whether the definition of boundaries is left to expert knowledge or derived from objective analysis techniques. Here, we use a clustering method to map and partition many surface variables, and we further examine how this partitioning is affected by various ways of averaging or normalizing the input data. We performed this study using 15 different surface fields of physical and biological properties derived from satellite remote sensing observations and from global model outputs at a monthly resolution. The area of study is the Indian Ocean-one of the least-sampled oceans-which is the focus of a global research effort under the auspices of the second International Indian Ocean Expedition (IIOE-2). We show a strong effect of the average absolute values of the data, which can be removed to better examine the phenology of the properties. However, normalization is not mandatory; the technique selected should depend on the scientific questions at hand. Our clusters did generally did not match closely the regions identified by Longhurst in his seminal work on ocean provinces.

Studying the biogeochemistry of the Southern Ocean using remote sensing relies on accurate interpretation of ocean colour through bio-optical and biogeochemical relationships between quantities and properties of interest. During the Antarctic Circumnavigation Expedition of the 2016/2017 Austral Summer, we collected a spatially comprehensive dataset of phytoplankton pigment concentrations, particulate absorption and particle size distribution and compared simple bio-optical and particle property relationships as a function of chlorophyll a. Similar to previous studies we find that the chlorophyll-specific phytoplankton absorption coefficient is significantly lower than in other oceans at comparable chlorophyll concentrations. This appears to be driven in part by lower concentrations of accessory pigments per unit chlorophyll a as well as increased pigment packaging due to relatively larger sized phytoplankton at low chlorophyll a than is typically observed in other oceans. We find that the contribution of microphytoplankton (>20 µm size) to chlorophyll a estimates of phytoplankton biomass is significantly higher than expected for the given chlorophyll a concentration, especially in higher latitudes south of the Southern Antarctic Circumpolar Current Front. Phytoplankton pigments are more packaged in larger cells, which resulted in a flattening of phytoplankton spectra as measured in these samples when compared to other ocean regions with similar chlorophyll a concentration. Additionally, we find that at high latitude locations in the Southern Ocean, pheopigment concentrations can exceed mono-vinyl chlorophyll a concentrations. Finally, we observed very different relationships between particle volume and chlorophyll a concentrations in high and low latitude Southern Ocean waters, driven by differences in phytoplankton community composition and acclimation to environmental conditions and varying contribution of non-algal particles to the particulate matter. Our data confirm that, as previously suggested, the relationships between bio-optical properties and chlorophyll a in the Southern Ocean are different to other oceans. In addition, distinct bio-optical properties were evident between high and low latitude regions of the Southern Ocean basin. Here we provide a region-specific set of power law functions describing the phytoplankton absorption spectrum as a function of chlorophyll a.

Small spectral differences from the mean remote sensing reflectance (Rrs) of the ocean - anomalies - can provide unique environmental information from ocean color satellite data. First, we describe the average relationship between three input spectral bands and an output band by developing a look-up table (WT) based on the fully normalized Rrs from the MODIS AQUA sensor. By dividing the Rrs measured at the output wavelength by the prediction from the LUT, we obtain several anomalies depending on the combination of input and output bands. None of these anomalies are correlated with chlorophyll concentration on the global scale. Some anomalies are strongly correlated with previously described data products (e.g., CDOM index, backscattering coefficients from semi-analytical inversion models), but others are not correlated with any product currently distributed by NASA. In the latter case, new information about oceanic optical properties is extracted from the ocean color spectra, which allows identification of water masses that was otherwise impossible with standard ocean color products. It was not possible, in some cases, to identify the optical source of this information, which may be spatially and temporally variable. We also show that by removing the main source of variability, the anomalies show interesting potential to identify subtle shifts in sensor response in satellite time series. (C) 2016 Elsevier Inc. All rights reserved.

In this study, we report on the performance of satellite-based photosynthetically available radiation (PAR) algorithms used in published oceanic primary production models. The performance of these algorithms was evaluated using buoy observations under clear and cloudy skies, and for the particular case of low sun angles typically encountered at high latitudes or at moderate latitudes in winter. The PAR models consisted of (i) the standard one from the NASA-Ocean Biology Processing Group (OBPG), (ii) the Gregg and Carder (GC) semi-analytical clear-sky model, and (iii) look-up-tables based on the Santa Barbara DISORT atmospheric radiative transfer (SBDART) model. Various combinations of atmospheric inputs, empirical cloud corrections, and semi-analytical irradiance models yielded a total of 13 (11 + 2 developed in this study) different PAR products, which were compared with in situ measurements collected at high frequency (15 min) at a buoy site in the Mediterranean Sea (the ``BOUee pour l'acquiSition d'une Serie Optique a Long termE,'' or, ``BOUSSOLE'' site). An objective ranking method applied to the algorithm results indicated that seven PAR products out of 13 were well in agreement with the in situ measurements. Specifically, the OBPG method showed the best overall performance with a root mean square difference (RMSD) (bias) of 19.7% (6.6%) and 10% (6.3%) followed by the look-up-table method with a RMSD (bias) of 25.5% (6.8%) and 9.6% (2.6%) at daily and monthly scales, respectively. Among the four methods based on clear-sky PAR empirically corrected for cloud cover, the Dobson and Smith method consistently underestimated daily PAR while the Budyko formulation overestimated daily PAR. Empirically cloud-corrected methods using cloud fraction (CF) performed better under quasi-clear skies (CF < 0.3) with an RMSD(bias) of 9.7%-14.8%(3.6%-11.3%) than under partially clear to cloudy skies (0.3 < CF < 0.7) with 16.1%-21.2% (-2.2%-8.8%). Under complete overcast conditions (CF > 0.7), however, all methods showed larger RMSD differences (biases) ranging between 32% and 80.6% (-54.5%-8.7%). Finally, three methods tested for low sun elevations revealed systematic overestimation, and one method showed a systematic underestimation of daily PAR, with relative RMSDs as large as 50% under all sky conditions. Under partially clear to overcast conditions all the methods underestimated PAR. Model uncertainties predominantly depend on which cloud products were used. (C) 2018 Optical Society of America

International audience; Two 3-year time series of hourly measurements of the fugacity of CO2 (f CO 2) in the upper 10 m of the surface layer of the northwestern Mediterranean Sea have been recorded by CARIOCA sensors almost two decades apart, in 1995-1997 and 2013-2015. By combining them with the alkalinity derived from measured temperature and salinity, we calculate changes in pH and dissolved inorganic carbon (DIC). DIC increased in surface seawater by ∼ 25 µmol kg−1 and f CO2 by 40 µatm, whereas seawater pH decreased by ∼ 0.04 (0.0022 yr−1). The DIC increase is about 15 % larger than expected from the equilibrium with atmospheric CO2 . This could result from natural variability, e.g. the increase between the two periods in the frequency and intensity of winter convection events. Likewise, it could be the signature of the contribution of the Atlantic Ocean as a source of anthropogenic carbon to the Mediterranean Sea through the Strait of Gibraltar. We then estimate that the part of DIC accumulated over the last 18 years represents ∼ 30 % of the total inventory of anthropogenic carbon in the Mediterranean Sea.

We analyze a two-year time-series of chromophoric dissolved organic matter (CDOM) light absorption measurements in the upper 400 m of the water column at the BOUSSOLE site in the NW Mediterranean Sea. The seasonal dynamics of the CDOM light absorption coefficients at 440 nm (a(cdom)(440)) is essentially characterized by (i) subsurface maxima forming in spring and progressively reinforcing throughout summer, (ii) impoverishment in the surface layer throughout summer and (iii) vertical homogeneity in winter. Seasonal variations of the spectral dependence of CDOM absorption, as described by the exponential slope value (S-cdom), are characterized by highest values in summer and autumn at the surface and low values at the depths of a(cdom)(440) subsurface maxima or just below them. Variations of a(cdom)(440) are likely controlled by microbial digestion of phytoplankton cells, which leads to CDOM production, and by photochemical destruction (photobleaching), which leads to CDOM degradation. Photobleaching is also the main driver of S-cdom variations. Consistently with previous observations, a(cdom)(440) for a given chlorophyll a concentration is higher than expected from Case I waters bio-optical models. The total non-water light absorption budget shows that surface waters at the BOUSSOLE site are largely dominated by CDOM during all seasons but the algal bloom in March and April. These results improve the knowledge of CDOM absorption dynamics in the Mediterranean Sea, which is scarcely documented. In addition, they open the way to improved algorithms for the retrieval of CDOM absorption from field or satellite radiometric measurements. (C) 2014 Elsevier Ltd. All rights reserved.

[1] In recent decades, it has been found useful to partition the pelagic environment using the concept of biogeochemical provinces, or BGCPs, within each of which it is assumed that environmental conditions are distinguishable and unique at global scale. The boundaries between provinces respond to features of physical oceanography and, ideally, should follow seasonal and interannual changes in ocean dynamics. But this ideal has not been fulfilled except for small regions of the oceans. Moreover, BGCPs have been used only as static entities having boundaries that were originally established to compute global primary production. In the present study, a new statistical methodology based on non-parametric procedures is implemented to capture the environmental characteristics within 56 BGCPs. Four main environmental parameters (bathymetry, chlorophyll a concentration, surface temperature, and salinity) are used to infer the spatial distribution of each BGCP over 1997–2007. The resulting dynamic partition allows us to integrate changes in the distribution of BGCPs at seasonal and interannual timescales, and so introduces the possibility of detecting spatial shifts in environmental conditions.

[1] The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data sets, and the noise properties. Although the noise autocorrelation observed in geophysical time series does not bias the trend estimate, it affects the estimation of its uncertainty and consequently the ability to detect, or not, a significant trend. Ignoring the noise autocorrelation level typically leads to an overdetection of significant trends. Due to satellite lifetime, usually between 5 and 10 years, sea surface time series do not cover the same period and are acquired by different sensors with different characteristics. These differences lead to unknown level shifts (biases) between the data sets, which affect the trend detection. In this work, we develop a generic framework to detect and evaluate linear trends and level shifts in multisensor time series of satellite chlorophyll-a concentrations, as provided by the Medium Resolution Imaging Spectrometer instrument (MERIS) and sea-viewing wide field-of-view sensor (SeaWiFS) ocean-color missions. We also discuss the optimization of the observation networks, in terms of needed time overlap between successive time series to reduce the uncertainty on the detection of long-term trends. For the incoming Sentinel 3-Ocean and Land Color Instrument (3-OLCI) mission that should be launched at the end of 2014, we propose a global map of the number of months of observations to enhance the trend detection performed with the joint SeaWiFS-MERIS analysis.

Quantifying Colored Detrital Matter (CDM) from satellite observations can improve our knowledge of carbon dynamics in coastal areas and the open oceans. Several bio-optical inversion models have been developed for this purpose. However, care must be taken when they are applied to waters where optical properties significantly differ from model assumptions, which is the case in the Mediterranean Sea. Algorithm testing and validation are thus required before routine use. Here, in situ radiometric measurements collected in the NW Mediterranean Sea (BOUSSOLE site) are used to evaluate three bio-optical inversion models that retrieve the CDM light absorption coefficients at 443 nm (a(cdm)(443)). Although all methods reproduced the CDM seasonal cycles at the surface, comparisons of predicted and in situ acdm(443) coefficients showed that the Quasi-Analytical Algorithm version 6 (QAAv6) and a locally-adapted version of the Garver-Siegel-Maritorena model (GSM-Med) were the two best algorithms. Applying these two models to SeaWiFS remote sensing reflectances, collected between 2003 and 2010, reproduced with good accuracy the acdm(443) coefficients retrieved from field radiometric measurements at the BOUSSOLE site, with seasonal patterns consistent with previous observations. Finally, bio-optical relationships derived from satellite-retrieved a(cdm)(443) and chlorophyll values confirmed the higher-than-average CDM contribution for a given chlorophyll concentration in the Mediterranean Sea as compared to many oceanic regions. (C) 2016 Elsevier Inc. All rights reserved.

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).

Variability in the optical particle backscattering coefficient (b(bp)) is investigated in oceanic waters from two sites, namely the BOUee pour l'acquiSition d'une Serie Optique a Long termE site in the northwestern Mediterranean Sea and the Plumes and Blooms stations in the Santa Barbara Channel off Southern California. Data from these two sites span two orders of magnitude in b(bp) and likely cover typical open ocean values. A significant relationship is found between b(bp) at wavelengths of 442 and 555 nm and chlorophyll concentration. However the large spread in this relationship makes chlorophyll a poor predictor of b(bp). The relationship between b(bp) and the particulate beam attenuation coefficient at 660 nm is tighter for both sites, indicating covariability of the particle size ranges that determine both coefficients. A detailed study of the seasonal changes of the b(bp) vs. chlorophyll relationship reveals that this bio-optical relationship might be best described as a succession of distinct regimes with rapid transitions from one to another. The backscattering ratio ((b) over tilde (bp); the ratio of b(bp) to total particulate scattering, b(p)) ranges from about 0.2% to 1.5%, which is similar to previously reported values. The relationship between (b) over tilde (bp) and chlorophyll was not significant, while values of the backscattering ratio varied spectrally.

International audience; Currently, observations from low-Earth orbit (LEO) ocean color sensors represent one of the most used tools to study surface optical and biogeochemical properties of the ocean. LEO observations are available at daily temporal resolution, and are often combined into weekly, monthly, seasonal, and annual averages in order to obtain sufficient spatial coverage. Indeed, daily satellite maps of the main oceanic variables (e.g., surface phytoplankton chlorophyll-a) generally have many data gaps, mainly due to clouds, which can be filled using either Optimal Interpolation or the Empirical Orthogonal Functions approach. Such interpolations, however, may introduce large uncertainties in the final product. Here, our goal is to quantify the potential benefits of having high-temporal resolution observations from a geostationary (GEO) ocean color sensor to reduce interpolation errors in the reconstructed hourly and daily chlorophyll-a products. To this aim, we used modeled chlorophyll-a fields from the Copernicus Marine Environment Monitoring Service's (CMEMS) Baltic Monitoring and Forecasting Centre (BAL MFC) and satellite cloud observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor (on board the geostationary satellite METEOSAT). The sampling of a GEO was thus simulated by combining the hourly chlorophyll fields and clouds masks, then hourly and daily chlorophyll-a products were generated after interpolation from neighboring valid data using the Multi-Channel Singular Spectral Analysis (M-SSA). Two cases are discussed: (i) A reconstruction based on the typical sampling of a LEO and, (ii) a simulation of a GEO sampling with hourly observations. The results show that the root mean square and interpolation bias errors are significantly reduced using hourly observations.

The optical properties of Case 1 waters have been empirically related to the chlorophyll concentration, [Chl], historically used as an index of the trophic state and of the abundance of the biological materials. The well-known natural variability around the mean statistical relationships is here examined by comparing the apparent optical properties (spectral downward irradiance attenuation and reflectance) as a function of [Chl] in two Case 1 environments, the Pacific and Mediterranean waters. These oceanic zones apparently represent two extremes of the possible bio-optical variability range around the mean. The systematic deviations, in both directions with respect to the average laws, mainly result from the differing contents in non-algal detrital materials and dissolved colored substance for a given [Chl] level. These contents are higher than the average in the Mediterranean Sea, and lower in the Pacific Ocean, respectively. These divergences between the two water bodies, detectable in the visible spectral domain, are considerably accentuated in the UV domain. The bio-optical properties in this spectral domain (310–400 nm) are systematically explored. They are more varying for a given [Chl] than those in the visible domain. Their prediction based on the sole [Chl] index is thus problematic, although it is probably possible on a regional scale if reliable field data are available. It does not seem, however, that ubiquitous relationships exist for this spectral domain for all Case 1 waters at global scale.

International audience; On a mean annual basis, the Southern Ocean is a sink for atmospheric CO2. However the seasonality of the air–sea CO2 flux in this region is poorly documented. We investigate processes regulating air–sea CO2 flux in a large area of the Southern Ocean (38°S–55°S, 60°W–60°E) that represents nearly one third of the subantarctic zone. A seasonal budget of CO2 partial pressure, pCO2 and of dissolved inorganic carbon, DIC in the mixed layer is assessed by quantifying the impacts of biology, physics and thermodynamical effect on seawater pCO2. A focus is made on the quantification at a monthly scale of the biological consumption as it is the dominant process removing carbon from surface waters. In situ biological carbon production rates are estimated from high frequency estimates of DIC along the trajectories of CARIOCA drifters in the Atlantic and Indian sector of the Southern Ocean during four spring–summer seasons over the 2006–2009 period. Net community production (NCP) integrated over the mixed layer is derived from the daily change of DIC, and mixed layer depth estimated from Argo profiles. Eleven values of NCP are estimated and range from 30 to 130 mmol C m− 2 d− 1. They are used as a constraint for validating satellite net primary production (NPP). A satellite data-based global model is used to compute depth integrated net primary production, NPP, for the same periods along the trajectories of the buoys. Realistic NCP/NPP ratios are obtained under the condition that the SeaWiFS chlorophyll are corrected by a factor of ≈ 2–3, which is an underestimation previously reported for the Southern Ocean. Monthly satellite based NPP are computed over the 38°S–55°S, 60°W–60°E area. pCO2 derived from these NPP combined with an export ratio, and taking into account the impact of physics and thermodynamics is in good agreement with the pCO2 seasonal climatology of Takahashi (2009). On an annual timescale, mean NCP values, 4.4 to 4.9 mol C m− 2 yr− 1 are ≈ 4–5 times greater than air–sea CO2 invasion, 1.0 mol C m− 2 yr− 1. Our study based on in situ and satellite observations provides a quantitative estimate of both seasonal and mean annual uptake of CO2 in the subantarctic zone of the Southern Ocean. These results bring important constraints for ocean circulation and biogeochemical models investigating future changes in the Southern Ocean CO2 fluxes.

International audience; System Vicarious Calibration (SVC) ensures a relative radiometric calibration to satellite ocean color sensors that minimizes uncertainties in the water-leaving radiance L w derived from the top of atmosphere radiance L T. This is achieved through the application of gain-factors, g-factors, to pre-launch absolute radiometric calibration coefficients of the satellite sensor corrected for temporal changes in radiometric sensitivity. The g-factors are determined by the ratio of simulated to measured spectral L T values where the former are computed using: i. highly accurate in situ L w reference measurements; and ii. the same atmospheric models and algorithms applied for the atmospheric correction of satellite data. By analyzing basic relations between relative uncertainties of L w and L T , and g-factors consistently determined for the same satellite mission using different in situ data sources, this work suggests that the creation of ocean color Climate Data Records (CDRs) should ideally rely on: i. one main long-term in situ calibration system (site and radiometry) established and sustained with the objective to maximize accuracy and precision over time of g-factors and thus minimize possible biases among satellite data products from different missions; and additionally ii. unique (i.e., standardized) atmospheric model and algorithms for atmospheric correction to maximize cross-mission consistency of data products at locations different from that supporting SVC. Finally, accounting for results from the study and elements already provided in literature, requirements and recommendations for SVC sites and field radiometric measurements are streamlined.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll‐a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed‐layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite‐derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low‐productivity seasons as well as in sea ice‐covered/deep‐water regions. Depth‐resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption‐based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll‐a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic‐relevant parameters., Key Points The models reproduced primary productivity better using in situ chlorophyll‐a than satellite valuesThe models performed well in low‐productivity seasons and in sea ice‐covered/deep‐water regionsNet primary productivity models need to be carefully tuned for the Arctic Ocean

A data set of radiometric measurements collected in the Beaufort Sea (Canadian Arctic) in August 2009 (Malina project) is analyzed in order to describe apparent optical properties (AOPs) in this sea, which has been subject to dramatic environmental changes for several decades. The two properties derived from the measurements are the spectral diffuse attenuation coefficient for downward irradiance, Kd, and the spectral remote sensing reflectance, Rrs. The former controls light propagation in the upper water column. The latter determines how light is backscattered out of the water and becomes eventually observable from a satellite ocean color sensor. The data set includes offshore clear waters of the Beaufort Basin as well as highly turbid waters of the Mackenzie River plumes. In the clear waters, we show Kd values that are much larger in the ultraviolet and blue parts of the spectrum than what could be anticipated considering the chlorophyll concentration. A larger contribution of absorption by colored dissolved organic matter (CDOM) is responsible for these high Kd values, as compared to other oligotrophic areas. In turbid waters, attenuation reaches extremely high values, driven by high loads of particulate materials and also by a large CDOM content. In these two extreme types of waters, current satellite chlorophyll algorithms fail. This questions the role of ocean color remote sensing in the Arctic when Rrs from only the blue and green bands are used. Therefore, other parts of the spectrum (e.g., the red) should be explored if one aims at quantifying interannual changes in chlorophyll in the Arctic from space. The very peculiar AOPs in the Beaufort Sea also advocate for developing specific light propagation models when attempting to predict light availability for photosynthesis at depth.

In situ observation of the marine environment has traditionally relied on ship-based platforms. The obvious consequence is that physical and biogeochemical properties have been dramatically undersampled, especially in the remote Southern Ocean (SO). The difficulty in obtaining in situ data represents the major limitations to our understanding, and interpretation of the coupling between physical forcing and the biogeochemical response. Southern elephant seals (Mirounga leonina) equipped with a new generation of oceanographic sensors can measure ocean structure in regions and seasons rarely observed with traditional oceanographic platforms. Over the last few years, seals have allowed for a considerable increase in temperature and salinity profiles from the SO, but we were still lacking information on the spatiotemporal variation of phytoplankton concentration. This information is critical to assess how the biological productivity of the SO, with direct consequences on the amount of CO2 "fixed'' by the biological pump, will respond to global warming. In this research programme, we use an innovative sampling fluorescence approach to quantify phytoplankton concentration at sea. For the first time, a low energy consumption fluorometer was added to Argos CTD-SRDL tags, and these novel instruments were deployed on 27 southern elephant seals between 25 December 2007 and the 4 February 2011. As many as 3388 fluorescence profiles associated with temperature and salinity measurements were thereby collected from a vast sector of the Southern Indian Ocean. This paper addresses the calibration issue of the fluorometer before being deployed on elephant seals and presents the first results obtained for the Indian sector of the Southern Ocean. This in situ system is implemented in synergy with satellite ocean colour radiometry. Satellite-derived data is limited to the surface layer and is restricted over the SO by extensive cloud cover. However, with the addition of these new tags, we are able to assess the 3-dimension distribution of phytoplankton concentration by foraging southern elephant seals. This approach reveals that for the Indian sector of the SO, the surface chlorophyll a (chl a) concentrations provided by MODIS were underestimated by a factor 2 compared to chl a concentrations estimated from HPLC corrected in situ fluorescence measurements. The scientific outcomes of this programme include an improved understanding of both the present state and variability in ocean biology, and the accompanying biogeochemistry, as well as the delivery of real-time and open-access data to scientists (doi:10.7491/MEMO.1).

International audience; Photosynthetic production of organic matter by microscopic oceanic phytoplankton fuels ocean ecosystems and contributes roughly half of the Earth's net primary production. For 13 years, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission provided the first consistent, synoptic observations of global ocean ecosystems. Changes in the surface chlorophyll concentration, the primary biological property retrieved from SeaWiFS, have traditionally been used as a metric for phytoplankton abundance and its distribution largely reflects patterns in vertical nutrient transport. On regional to global scales, chlorophyll concentrations covary with sea surface temperature (SST) because SST changes reflect light and nutrient conditions. However, the ocean may be too complex to be well characterized using a single index such as the chlorophyll concentration. A semi-analytical bio-optical algorithm is used to help interpret regional to global SeaWiFS chlorophyll observations from using three independent, well-validated ocean color data products; the chlorophyll a concentration, absorption by CDM and particulate backscattering. First, we show that observed long-term, global-scale trends in standard chlorophyll retrievals are likely compromised by coincident changes in CDM. Second, we partition the chlorophyll signal into a component due to phytoplankton biomass changes and a component caused by physiological adjustments in intracellular chlorophyll concentrations to changes in mixed layer light levels. We show that biomass changes dominate chlorophyll signals for the high latitude seas and where persistent vertical upwelling is known to occur, while physiological processes dominate chlorophyll variability over much of the tropical and subtropical oceans. The SeaWiFS data set demonstrates complexity in the interpretation of changes in regional to global phytoplankton distributions and illustrates limitations for the assessment of phytoplankton dynamics using chlorophyll retrievals alone. (C) 2013 Elsevier Inc. All rights reserved.

Mixed-layer CO2 fluxes in the 1980s (1979–1983) and the 2000s (1998–2001) are assessed in the Mediterranean Sea. The analysis uses an array of one-dimensional physical–biological–chemical coupled models covering all areas where depth is greater than 300 m. These models are driven by surface heat fluxes and wind stress, and surface chlorophyll concentrations. This approach provides estimations of basin-scale oceanic CO2 levels over two time periods separated by a 14-year gap and allows characterizing differences between these two periods. The results indicate that the Mediterranean Sea was more biologically productive (by about 16 gC m−2 y−1) during the 2000s, with an increase of carbon export to deep layers by about 7 gC m−2 y−1 as compared to the 1980s. The consecutive modification of CO2 fluxes toward deep layers did not, however, strongly modify the oceanic CO2 levels, which differ by only ∼5–10 μatm between the two periods. The reason is the increase of atmospheric CO2 levels by 30 μatm between the two periods, which led to an increase of the CO2 flux from the atmosphere to the ocean. The Mediterranean Sea was a CO2 source to the atmosphere in the 1980s (about 1.5×1012 molC y−1). It is close to equilibrium with the atmosphere in the 2000s (slight sink of about −0.2×1012 molC y−1).

Phytoplankton are unicellular algae that use radiant energy to build organic molecules from dissolved CO. In their perspective, Morel and Antoine comment on how accurately the net primary productivity (NPP) of phytoplankton in the world ocean can now be estimated. New satellite sensors give accurate measurements of the phytoplankton biomass distribution, but the rate of production is less well known. A better estimate of NPP will require better knowledge of algal physiology and ecology.

[1] El Nino events are known to strongly affect biological production and ecosystem structure in the tropical Pacific. Understanding and predicting biological processes in this area are hampered because the existing in situ observing system focuses primarily on physical measurements and does not observe key biological parameters; the only high spatial and temporal resolution biology-related observations are from the global array of ocean color satellites which provide an estimate of surface chlorophyll concentrations only. Since the 1990s, an apparent shift of the El Nino maximum sea-surface temperature (SST) warm anomaly from the eastern to the central equatorial Pacific has frequently been observed. Satellite observations show significant changes in chlorophyll-a (Chl-a), new production (NP) and total primary production (PP) in the equatorial Pacific associated with these new central Pacific (CP) El Nino events (also called El Nino Modoki) relative to eastern Pacific El Ninos. During CP-El Ninos, NP, Chl-a and PP in the central basin are depressed relative to EP-El Ninos and lower values of Chl-a and PP coincide spatially with higher SST in the central Pacific. While surface Chl-a, and integrated NP and PP over the entire equatorial band, decrease during both CP and EP-El Ninos, the magnitude of this decrease seems to depend more on the intensity than type of event. The changing spatial patterns have significant implications for equatorial biological dynamics if, as has been suggested, CP-El Ninos increase in frequency in the future. Citation: Turk, D., C. S. Meinen, D. Antoine, M. J. McPhaden, and M. R. Lewis (2011), Implications of changing El Nino patterns for biological dynamicsinthe equatorial PacificOcean, Geophys. Res. Lett., 38, L23603, doi:10.1029/2011GL049674.

Phytoplankton chlorophyll-a (Chl) seasonal cycles of the North Atlantic are described using satellite ocean color observations covering the 1980s and the 2000s. The study region is where warmer SST and higher Chl in the 2000s as compared to the 1980s have been reported. It covers latitudes from 30 degrees N-50 degrees N and longitudes from 60 degrees W-0 degrees W, where two phytoplankton blooms take place: a spring bloom that follows stratification of upper layers, and a fall bloom due to nutrient entrainment through deepening of the mixed layer. In the 1980s, spring and fall blooms were of similar amplitude over the entire study region. In the 2000s, the fall bloom was weaker in the eastern Atlantic (east of 40 degrees W), because of a delayed deepening of the mixed layer at the end of summer (mixed layer depth (MLD) determined from in situ data). Conversely, the spring bloom of the eastern Atlantic was stronger in the 2000s than it was in the 1980s, because of a deeper MLD and stronger winds in winter. In the Northwestern Atlantic (northwest of 38 degrees N-40 degrees W), little differences are observed for spring and fall blooms, and for the wintertime MLD. Our results show that the links between upper layer stratification, SST changes, and biological responses are more complex than the simple paradigm that sequentially relates higher stratification with warmer SST and an enhanced (weakened) growth of the phytoplankton population in the subpolar (subtropical) region.

The El Niño Southern Oscillation (ENSO) drives important changes in the marine productivity of the Equatorial Pacific, in particular during major El Niño/La Niña transitions. Changes in environmental conditions associated with these climatic events also likely impact phytoplankton composition. In this work, the distribution of four major phytoplankton groups (nanoeucaryotes, Prochlorococcus, Synechococcus, and diatoms) was examined between 1996 and 2007 by applying the PHYSAT algorithm to the ocean color data archive from the Ocean Color and Temperature Sensor (OCTS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Coincident with the decrease in chlorophyll concentrations, a large-scale shift in the phytoplankton composition of the Equatorial Pacific, that was characterized by a decrease in Synechococcus and an increase in nanoeucaryotes dominance, was observed during the early stages of both the strong El Niño of 1997 and the moderate El Niño of 2006. A significant increase in diatoms dominance was observed in the Equatorial Pacific during the 1998 La Niña and was associated with elevated marine productivity. An analysis of the environmental variables using a coupled physical-biogeochemical model (NEMO-PISCES) suggests that the Synechococcus dominance decrease during the two El Niño events was associated with an abrupt decline in nutrient availability (−0.9 to −2.5 μM NO3 month−1). Alternatively, increased nutrient availability (3 μM NO3 month−1) during the 1998 La Niña resulted in Equatorial Pacific dominance diatom increase. Despite these phytoplankton community shifts, the mean composition is restored after a few months, which suggests resilience in community structure. Such rapid changes to the composition of phytoplankton groups should be considered in future modeling approaches to represent variability of the marine productivity in the Equatorial Pacific and to quantify its potential implications on food-web and on global carbon cycle.

Untangling the Web Chlorophyll-containing phytoplankton is at the core of the marine food web. Martinez et al. (p. 1253 ) combined satellite data about upper ocean chlorophyll and sea surface temperatures to demonstrate a clear connection between phytoplankton and sea surface temperatures on a multidecadal time scale. Basin-scale ocean dynamic processes such as the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation connect the physical, climate-related variability to changes in phytoplankton distribution and amount. Thus, improving the reliability of forecasts of large-scale ocean dynamics may help to improve predictions of changes in ocean community ecology.

International audience; A methodology is proposed to infer the altitude of aerosol plumes over the ocean from reflectance ratio measurements in the O2 absorption A-band (759 to 770 nm). The reflectance ratio is defined as the ratio of the reflectance in a first spectral band, strongly attenuated by O2 absorption, and the reflectance in a second spectral band, minimally attenuated. For a given surface reflectance, simple relations are established between the reflectance ratio and the altitude of an aerosol layer, as a function of atmospheric conditions and the geometry of observation. The expected accuracy for various aerosol loadings and models is first quantified using an accurate, high spectral resolution, radiative transfer model that fully accounts for interactions between scattering and absorption. The method is developed for POLDER and MERIS, satellite sensors with adequate spectral characteristics. The simulations show that the method is only accurate over dark surfaces when aerosol optical thickness at 765 nm is relatively large (> 0.3). In this case, the expected accuracy is on the order of ± 0.5 km or ± 0.2 km for POLDER or MERIS respectively. More accurate estimates are obtained with MERIS, since in this case the spectral reflectance ratio is more sensitive to aerosol altitude. However, a precise spectral calibration is needed for MERIS. The methodology is applied to MERIS and POLDER imagery acquired over marine surfaces. The estimated aerosol altitude is compared with in situ lidar profiles of backscattering coefficient measured during the AOPEX-2004 experiment for MERIS, or obtained with the space-borne lidar CALIOP for POLDER. The retrieved altitudes agree with lidar measurements in a manner consistent with theory. These comparisons demonstrate the potential of the differential absorption methodology for obtaining information on aerosol altitude over dark surfaces

International audience; A field characterization of the amplitude and periods of the underwater light field fluctuations is presented on the basis of field measurements of the downward and upward irradiances at a deep-sea mooring in the Mediterranean Sea (BOUSSOLE site). The optical time series at this site includes multispectral irradiance measurements at two depths and irradiance profiles taken from free-fall radiometers. It is already several years long and is paralleled by a time series of wind and waves. When pooled together, both data sets provide an opportunity to complement previous field experiments dedicated to the understanding of underwater light fluctuations, which were mostly carried out in coastal waters and essentially for the downward irradiance, by exploring more systematically the electromagnetic spectrum and the range of environmental parameters. In addition, the characteristics of the upward flux are also investigated. The behavior of the amplitude and period of the E-d fluctuations are coherent with previous findings, although a more global picture is provided. The conditions for maximum fluctuations under clear skies are for wave heights of similar to 0.5 m or wind speeds between similar to 1 and 5 m s(-1). Fluctuations are reduced under clear skies for wave heights >similar to 1.5 m or for wind speeds >7 m s(-1). The dominant periods of the fluctuations in the upward flux are changing in parallel to those in the downward flux. The amplitude of the fluctuations in the upward flux is, however, evolving in the opposite direction as compared to the downward flux, e.g., decreasing when the water becomes clearer.

The air–sea CO 2 flux, the carbon export to the deep layers, and more generally the carbon budgets are presently poorly characterized in the Mediterranean Sea. An approach to the simulation of these fluxes at regional scale is proposed, based on an array of unconnected one-dimensional (1D) physical–biological–chemical coupled models. The rationale is to massively assimilate satellite information, on one hand to derive accurate surface heat fluxes, and, on the other hand, to implicitly account for the horizontal processes not explicitly represented in the 1D scheme. This method is applied here to simulate the upper ocean physical and biogeochemical dynamics of the entire Mediterranean Sea over the years 1998–2004, and at a 0.5° spatial resolution. The mixed-layer annual cycles are validated against the values determined from a database of in situ temperature profiles, demonstrating the validity of the approach in various physical regimes. A validation of the simulated annual cycles of the total inorganic carbon (TCO 2 ) and of the carbon dioxide partial pressure ( p CO 2 ) is presented at a measurement site in the northwestern Mediterranean where both properties were determined in 1998–1999 and in 2003–2004. An additional validation of the p CO 2 fields is presented using along-track data collected during the “Productivite des Systemes Oceaniques Pelagiques” (PROSOPE) cruise. The basin-scale air–sea carbon budget derived from the model outputs shows that the Mediterranean Sea, over the study period, is close to equilibrium with the atmosphere, with a slight sink for the atmospheric CO 2 . This is in agreement with the results previously obtained via indirect methods and is supported here by a series of sensitivity studies. A detailed analysis of the p CO 2 and TCO 2 seasonal distributions in the Mediterranean Sea is provided for the first time. It shows that the biological processes play a major role in shaping the p CO 2 seasonal evolution in the eastern and western basins.

Spaceborne ocean color sensors require vicarious calibration to sea-truth data to achieve accurate water-leaving radiance retrievals. The assumed requirements of an in situ data set necessary to achieve accurate vicarious calibration were set forth in a series of papers and reports developed nearly a decade ago, which were embodied in the development and site location of the Marine Optical BuoY (MOBY). Since that time, NASA has successfully used data collected by MOBY as the sole source of sea-truth data for vicarious calibration of the Sea-viewing Wide field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer instruments. In this paper, we make use of the 10-year, global time series of SeaWiFS measurements to test the sensitivity of vicarious calibration to the assumptions inherent in the in situ requirements (e.g., very low chlorophyll waters, hyperspectral measurements). Our study utilized field measurements from a variety of sources with sufficient diversity in data collection methods and geophysical variability to challenge those in situ restrictions. We found that some requirements could be relaxed without compromising the ability to vicariously calibrate to the level required for accurate water-leaving radiance retrievals from satellite-based sensors. (C) 2008 Optical Society of America.

International audience; The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

International audience; [ 1] A comprehensive revision of the Coastal Zone Color Scanner ( CZCS) data-processing algorithms has been undertaken to generate a revised level 2 data set from the near-8-year archive ( 1979-1986) collected during this ``proof-of-concept'' mission. The final goal of this work is to establish a baseline for a global, multiyear, multisensor ocean color record, to be built from observations of past ( i.e., CZCS), present, and future missions. To produce an internally consistent time series, the same revised algorithms also have been applied to the first 5 years of the Sea-viewing Wide Field-of-view Sensor ( SeaWiFS) ocean color observations ( 1998-2002). Such a database is necessary in order to determine whether or not the ocean biogeochemistry has evolved in the past years and, if so, to be able to detect near future trends. Algorithmic and calibration aspects, along with validation results presented in this paper, are tailored toward the identification of long-term trends, which mandated this reprocessing effort. The analysis of decadal changes from the CZCS to the SeaWiFS era shows an overall increase of the world ocean average chlorophyll concentration by about 22%, mainly due to large increases in the intertropical areas, where the seasonal cycles also substantially changed over the past 2 decades. Increases in higher latitudes, where seasonal cycles did not change, contribute to a lesser extent to the general trend. In contrast, oligotrophic gyres display declining concentrations.

[1] Because the Mediterranean has been subject for several decades to increasing anthropogenic influences, monitoring algal biomass and primary production on a long-term basis is required to detect possible modifications in the biogeochemical equilibrium of the basin. This work was initiated thanks to a 4-year-long time series of SeaWiFS observations. Seasonal variations of algal biomass (estimated using a previously developed regional algorithm) and primary production were analyzed for the various regions, and compared with those estimated using the CZCS sensor (1978–1986). Also, interannual variations could be assessed for the first time. The seasonal cycles of algal biomass generally reveal a maximum in winter or spring, and a minimum in summer. Some conspicuous differences with CZCS observations (e.g., in the Northwest Basin, reduction of the deep convection zone, earlier start of the spring bloom, quasi-absence of the vernal bloom) likely result from environmental changes. Interannual variations in algal biomass are noticeable all over the basin, including in the very oligotrophic waters of the Eastern Basin. The seasonal evolution of primary production is predominantly influenced by that of algal biomass in the Western Basin (with, in particular, a spring maximum). In the Eastern Basin, the seasonal courses of PAR and biomass tend to compensate each other, and primary production varies weakly along the year. The annual values computed over the 1998–2001 period for the Western Basin (163 ± 7 gC m−2 yr−1) and the Eastern Basin (121 ± 5 gC m−2 yr−1) are lower (by 17 and 12%, respectively) than those previously derived (using the same light-photosynthesis model) from CZCS data.

International audience; A global equation, designed to estimate the column-integrated oceanic primary production realized by a given phytoplankton biomass under various environmental conditions, is used to develop a practical method to assess the primary production (P) from the chlorophyll concentration as provided by satellite imagery. This basic equation combines three terms, namely the photosynthetically available radiation impinging at the sea, surface, PAR(0+), the column-integrated chlorophyll content, < Chl >(tot), and the cross section for photosynthesis per unit of chlorophyll, Psi*. Global monitoring of incident irradiance and near-surface algal biomass is now achievable from space, and thus the next step toward a monitoring of oceanic primary production would be to dispose in parallel of a `'climatological field'' of the Psi* quantity. Actually, Psi* depends on the two other terms of the equation (PAR(0+) and < Chl >(tot)), and in addition, on temperature (also detectable from satellite). Therefore such a `'climatological field'' is variable and complex and it can be conveniently replaced by lookup tables allowing easy interpolation. The entries are date, latitude, cloudiness, temperature, and remotely sensed chlorophyll concentration. This upper layer concentration is extended downward owing to previous results of a statistical analysis of the chlorophyll vertical distribution; accordingly, two parallel tables, corresponding to well-mixed or stratified upper layers with uniform or non uniform chlorophyll vertical profiles, respectively, are constructed. These tables are produced by systematically using a previously published spectral light-photosynthesis model. For such extensive computations, the model necessarily relies on, and is operated with, a standard set of ecological and physiological parameters. Therefore sensitivity analyses have been carried out in view of assessing the impact on Psi*, and on the resulting production of deviations in these parameters or parameterizations, vis-a-vis the standard values or formulations which were adopted when building the tables. The effects of the biomass vertical structure, of possible light and temperature adaptation, and of the presence of degraded pigments are among the sensitivity studies which have been performed. The method as proposed can accomodate any improvement and complexity in parameterization to the extent that additional computation time is faced only when generating the lookup tables, not when using them in conjunction with satellite data.

About 300 coastal zone color scanner (CZCS) scenes, gathered over the eastern Mediterranean basin mostly during the years 1979-1981, have been processed from level 1 by using improved pixel-by-pixel procedures for the atmospheric correction and pigment retrieval. The seasonal evolution of the upper ocean pigment concentration is described and analyzed within the whole basin and its subbasins. From the chlorophyll concentration in the top layer, and by using statistical relationships, the depth-integrated pigment content is estimated and used in conjunction with a light-photosynthesis model to estimate the carbon fixation. The model relies on a set of physiological parameters, selected after the validation of the light-photosynthesis model and not on locally measured parameters. Additional information needed in the modeling are the photosynthetically available radiation (computed from astronomic and atmospheric parameters, combined with a cloud climatology), sea temperature and mixed-layer depth (taken from Levitus (1982)). Actually, the model is used to generate look-up tables in such a way that all possible situations (concerning available radiation, chlorophyll concentration, and temperature) are covered. The appropriate situation associated with any pixel is selected from these tables to generate primary production maps. Despite a relatively good spatial coverage, studying the interannual variability of the pigment distribution and primary production appeared to be impossible. Therefore 12 `'climatological'' monthly chlorophyll maps have been produced by merging the data corresponding to several years. The carbon fixation rates in each of the subbasins have been computed on a monthly basis, and annual mean values derived thereafter. The primary production values are compared with sparse field determinations. They are also compared with those previously derived for the Western basin, also by using CZCS data (Morel and Andre, 1991). When put together, these companion works provide a kind of record of the trophic status of the entire Mediterranean Sea in the early 1980s. Ocean color sensors to be launched next, like SeaWIFS, will allow the seasonal and interannual variabilities in the late 1990s to be addressed.

One of the major features of the coastal zone is that part of its sea floor receives a significant amount of sunlight and can therefore sustain benthic primary production by seagrasses, macroalgae, microphytobenthos and corals. However, the contribution of benthic communities to the primary production of the global coastal ocean is not known, partly because the surface area where benthic primary production can proceed is poorly quantified. Here, we use a new analysis of satellite (SeaWiFS) data collected between 1998 and 2003 to estimate, for the first time at a nearly global scale, the irradiance reaching the bottom of the coastal ocean. The following cumulative functions provide the percentage of the surface (S) of the coastal zone receiving an irradiance greater than Ez (in mol photons m-2 d-1): SNon-polar = 29.61-17.92 log10(Ez)+0.72 log10 2(Ez)+0.901og10 3(Ez) SArctic = 15.99-13.56 log 10(Ez)+1.49 log10 2(E z)+0.701og10 3(Ez) Data on the constraint of light availability on the major benthic primary producers and net community production are reviewed. Some photosynthetic organisms can grow deeper than the nominal bottom limit of the coastal ocean (200m). The minimum irradiance required varies from 0.4 to 5.1 mol photons m-2 d -1 depending on the group considered. The daily compensation irradiance of benthic communities ranges from 0.24 to 4.4 mol photons m -2d-1. Data on benthic irradiance and light requirements are combined to estimate the surface area of the coastal ocean where (1) light does not limit the distribution of primary producers and (2) net community production (NCP, the balance between gross primary production and community respiration) is positive. Positive benthic NCP can occur over 33% of the global shelf area. The limitations of this approach, related to the spatial resolution of the satellite data, the parameterization used to convert reflectance data to irradiance, the lack of global information on the benthic nepheloid layer, and the relatively limited biological information available, are discussed.