Abstract Photosynthetic available radiation (PAR) is the light usable by photosynthetic organisms. Photosynthetic available radiation measurements at depth are required to quantify the light availability for primary production. Direct PAR measurements may be measured with full‐spectrum quantum sensors for the range 400 to 700 nm. When spectrally resolved light is measured, as for the downwelling irradiance spectrum , PAR may be computed by numerically integrating within those limits. As radiation varies across a spectral continuum, needs to be resolved at a sufficiently large number of bands, to provide an unbiased PAR estimate. When is available at a small number of spectral bands, as for multispectral sensors, it is still possible to numerically integrate , but the estimation will contain errors. Here, we propose a method that delivers unbiased PAR estimates, based on two‐layer neural networks, formulable in a small number of matrix equations, and thus exportable to any software platform. The method was calibrated with a dataset of hyperspectral acquired by new types of BioGeoChemical (BGC)‐Argo floats deployed in a variety of open ocean locations, representative of a wide range of bio‐optical properties. This procedure was repeated for several band configurations, including those existing on multispectral radiometers presently the standard for the BGC‐Argo fleet. Validation results against independent data were highly satisfactory, displaying minimal uncertainties across a wide PAR range, with the performance varying as a function of each sensor configuration, overall supporting the operational implementation in the Argo program. Model codes are findable at https://github.com/jaipipor/PAR_BGC_Argo .

<div><p>In the first part of this paper series (Sun et al., 2023), we developed an ecological model that partitions the total chlorophyll-a concentration (Chl-a) into three phytoplankton size classes (PSCs), pico-, nano-, and microplankton. The parameters of this model are controlled by sea surface temperature (SST), intended to capture shifts in phytoplankton size structure independently of variations in total Chl-a. In this second part of the series, we present an Ocean Colour Modelling Framework (OCMF), building on the classical Case-1 assumption, that explicitly incorporates our ecological model. The OCMF assumes the presence of the three PSCs and the existence of an independent background of non-algal particles. The framework assumes each phytoplankton group resides in a distinct optical environment, assigning chlorophyll-specific inherent optical properties to each group, both directly (phytoplankton) and indirectly (non-algal particulate and dissolved substances). The OCMF is parameterised, validated, and assessed using a large global dataset of inherent and apparent optical properties. We use the OCMF to explore the influence of variations in temperature and Chl-a on phytoplankton size structure and its resulting effects on ocean colour. We also discuss applications of the OCMF, such as its potential for inverse modelling and phytoplankton climate trend detection, which will be explored further in subsequent papers.</p></div>

Phytoplankton chlorophyll Sun‐induced fluorescence is observable in the upwelling light field of the ocean. This allows its observation by radiometers in situ or on satellite sensors. Since it is influenced by both biomass and physiology it can potentially provide information about both. Since fluorescence yield is complementary to photosynthesis and heat in photosystem II, its observation throughout the day provides information on the response of phytoplankton to diel light cycles. Here we use a time series collected in the northwestern Mediterranean Sea (BOUSSOLE site) to extract photophysiological parameters of phytoplankton using the Sun‐induced fluorescence and as well as with an active chlorophyll fluorometer. The daily resolved patterns are consistent with photoacclimation and photoadaptation processes and reflect seasonal variations of the mixed‐layer average irradiance. We also show that fluorescence yields derived from satellite measurements (MODIS) at the same location are not correlated to these patterns, confirming the limited influence of photoacclimation and photoadaptation on the satellite‐derived chlorophyll fluorescence yield near solar noon.

Abstract System vicarious calibration (SVC) enhances the accuracy of satellite ocean color radiometric data products by removing the bias due to the intrinsic inaccuracies affecting both the responsivity of the space sensor and the correction for the atmospheric and sea surface contributions to the measured signal. Various SVC procedures have been implemented and applied for regional studies, specific mission goals, and the most challenging quantification of global long-term climate-driven changes that require accurate and consistent data products across multiple missions. This paper summarizes the outcome of a workshop organized by the ocean color SVC task force of the International Ocean Color Coordinating Group (IOCCG) to review requirements for SVC supporting ocean color missions for climate and global long-term operational applications. The work emphasizes the essential need for long-term sustained SVC infrastructures and associated services, summarizes the primary requirements for establishing a comprehensive ocean color SVC framework, and provides directions for new investigations to tackle arising needs on SVC advancements and methods. Significance Statement System vicarious calibration is the process applied to satellite ocean color missions to achieve the required accuracy over time for data products targeting climate and global long-term operational applications. This process requires access to dedicated long-term marine infrastructures and services to sustain the creation of consistent multimission time series. Aiming at unifying system vicarious calibration across missions managed by independent space agencies, this work streamlines the requirements for establishing the necessary infrastructures and services, standardizing the methods, and providing guidance to new advancements as well as maintaining current capabilities to enable steady linkage to historical satellite ocean color missions.

Abstract. Total alkalinity (AT) and dissolved inorganic carbon (CT) in the oceans are important properties with respect to understanding the ocean carbon cycle and its link to global change (ocean carbon sinks and sources, ocean acidification) and ultimately finding carbon-based solutions or mitigation procedures (marine carbon removal). We present a database of more than 44 400 AT and CT observations along with basic ancillary data (spatiotemporal location, depth, temperature and salinity) from various ocean regions obtained, mainly in the framework of French projects, since 1993. This includes both surface and water column data acquired in the open ocean, coastal zones and in the Mediterranean Sea and either from time series or dedicated one-off cruises. Most AT and CT data in this synthesis were measured from discrete samples using the same closed-cell potentiometric titration calibrated with Certified Reference Material, with an overall accuracy of ±4 µmol kg−1 for both AT and CT. The data are provided in two separate datasets – for the Global Ocean and the Mediterranean Sea (https://doi.org/10.17882/95414, Metzl et al., 2023), respectively – that offer a direct use for regional or global purposes, e.g., AT–salinity relationships, long-term CT estimates, and constraint and validation of diagnostic CT and AT reconstructed fields or ocean carbon and coupled climate–carbon models simulations as well as data derived from Biogeochemical-Argo (BGC-Argo) floats. When associated with other properties, these data can also be used to calculate pH, the fugacity of CO2 (fCO2) and other carbon system properties to derive ocean acidification rates or air–sea CO2 fluxes.

Deep Chlorophyll Maxima (DCMs) are ubiquitous in low-latitude oceans, and of recognized biogeochemical and ecological importance. DCMs have been observed in the Southern Ocean, initially from ships and recently from profiling robotic floats, but with less understanding of their onset, duration, underlying drivers, or whether they are associated with enhanced biomass features. We report the characteristics of a DCM and a Deep Biomass Maximum (DBM) in the Inter-Polar-Frontal-Zone (IPFZ) south of Australia derived from CTD profiles, shipboard-incubated samples, a towbody, and a BGC-ARGO float. The DCM and DBM were ∼20 m thick and co-located with the nutricline, in the vicinity of a subsurface ammonium maximum characteristic of the IPFZ, but ∼100 m shallower than the ferricline. Towbody transects demonstrated that the co-located DCM/DBM was broadly present across the IPFZ. Large healthy diatoms, with low iron requirements, resided within the DCM/DBM, and fixed up to 20 mmol C m⁻² d⁻¹. The BGC-ARGO float revealed that DCM/DBM persisted for >3 months. We propose a dual environmental mechanism to drive DCM/DBM formation and persistence within the IPFZ: sustained supply of both recycled iron within the subsurface ammonium maxima, and upward silicate transport from depth. DCM/DBM cell-specific growth rates were considerably slower than those in the overlying mixed layer, implying that phytoplankton losses such as herbivory are also reduced, possibly because of heavily silicified diatom frustules. The light-limited seasonal termination of the observed DCM/DBM did not result in a "diatom dump", rather ongoing diatom downward export occurred throughout its multi-month persistence.

Since 2004, the Service facility SNAPO-CO2 (Service National d’Analyse des Paramètres Océaniques du CO2) housed by the LOCEAN laboratory (Paris, France) has been in charge for the analysis of Total Alkalinity (AT) and Total dissolved inorganic carbon (CT) of seawater samples on a series of cruises or ships of opportunity conducted in different regions in the frame of French projects. More than 44000 observations are synthetized in this work. Sampling was performed either from CTD-Rosette casts (Niskin bottles) or collected from the ship’s seawater supply (intake at about 5m depth). After completion of each cruise, discrete samples were returned back at LOCEAN laboratory and stored in a dark room at 4 °C before analysis generally within 2-3 months after sampling (sometimes within a week). AT and CT were analyzed simultaneously by potentiometric titration using a closed cell (Edmond, 1970). Certified Reference Materials (CRMs) provided by Pr. A. Dickson (Scripps Institution of Oceanography, San Diego, USA) were used to calibrate the measurements. The same instrumentation was used for underway measurements during OISO cruises (https://doi.org/10.18142/228) and OISO AT-CT data for 1998-2018 in the South Indian Ocean added in this synthesis. The synthesis is organized in two files (one for Global ocean and the Coastal Zones, one for the Mediterranean Sea) with the same format: Cruise name, Ship name, day, month, year, hour, minute, second, latitude, longitude, depth, AT (µmol/kg), Flag-AT, CT (µmol/kg), Flag-CT, Temperature (°C), Flag-Temp, Salinity (PSU), Flag-Salinity, nsample/cruise, nsample on file, sampling method.

Chromophoric dissolved organic matter (CDOM) significantly contributes to the non-water absorption budget in the Mediterranean Sea. The absorption coefficient of CDOM, aCDOM(λ), is measurable in situ and can be retrieved remotely, although ocean-colour algorithms do not distinguish it from the absorption of detritus. These observations can be used as indicators for the concentration of other relevant biogeochemical variables in the ocean, e.g. dissolved organic carbon. However, our ability to model the biogeochemical processes that determine CDOM concentrations is still limited. Here we propose a novel parameterization of the CDOM cycle that accounts for the interplay between the light- and nutrient-dependent dynamics of local CDOM production and degradation, as well as its vertical transport. The parameterization is included in a one-dimensional (1D) configuration of the Biogeochemical Flux Model (BFM), which is here coupled to the General Ocean Turbulence Model (GOTM) through the Framework for Aquatic Biogeochemical Models (FABM). Here the BFM is augmented with a bio-optical component that resolves spectrally the underwater light transmission. We run this new GOTM-(FABM)-BFM configuration to simulate the seasonal aCDOM(λ) cycle at the deep-water site of the Bouée pour l'acquisition de Séries Optiques à Long Terme (BOUSSOLE) project in the northwestern Mediterranean Sea. Our results show that accounting for both nutrient and light dependence of CDOM production improves the simulation of the seasonal and vertical dynamics of aCDOM(λ), including a subsurface maximum that forms in spring and progressively intensifies in summer. Furthermore, the model consistently reproduces the higher-than-average concentrations of CDOM per unit chlorophyll concentration observed at BOUSSOLE. The configuration, outputs, and sensitivity analyses from this 1D model application will be instrumental for future applications of BFM to the entire Mediterranean Sea in a three-dimensional configuration.

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.org/10.1594/PANGAEA.941318 (Valente et al., 2022).

Abstract Vicarious calibration coefficients ( k v ) of Second-generation GLobal Imager (SGLI) for ocean color processing were derived using in-situ radiometric buoy measurements from the Marine Optical BuoY (MOBY) and the BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE). Two aerosol-model look up tables (LUTs) used in the GCOM-C aerosol retrieval algorithm (LUT-A) and in the previous version of ocean color atmospheric correction algorithm (LUT-B) were tested in the procedures to calculate k v and retrieve remote sensing reflectance ( R rs ) and aerosol optical thickness (AOT). Bias of the processed R rs compared to AERONET-OC R rs was reduced by applying the determined k v (i.e., corrected SGLI radiance = original SGLI radiance/ k v ). LUT-A yielded smaller AOT bias compared to AERONET-OC AOT; on the other hand, LUT-B gave smaller R rs noise due to gentle slope of the aerosol reflectance even though it caused AOT overestimation. When k v was derived by adjusting to the AOT measurements, k v was about 1.1 by LUT-A and 1.2 by LUT-B in the near-infrared (NIR) channel. However, the k v in the NIR channel was close to 1.0 when AOT and land surface reflectance measurements of Radiometric Calibration Network (RadCalNet) were used. The LUT-A with k v from MOBY and BOUSSOLE are currently adopted for the SGLI standard ocean color processing. Improvement is needed, however, to design an optimal LUT suitable for both aerosol and ocean color purposes.

We estimated pelagic primary production (PP) in the coastal (<200 m depth) Mediterranean Sea from satellite-borne data, its contribution to basin-scale carbon fixation, its variability, and long-term trends during the period 2002–2016. Annual coastal PP was estimated at 0.041 Gt C, which approximately represents 12 % of total carbon fixation in the Mediterranean Sea. About 51 % of this production occurs in the eastern basin, whereas the western and Adriatic shelves contribute with ∼25 % each of total coastal production. Strong regional variability is revealed in coastal PP, from high-production areas (>300 g C m−2) associated with major river discharges to less productive provinces (<50 g C m−2) located in the southeastern Mediterranean. PP variability in the Mediterranean Sea is dominated by interannual variations, but a notable basin-scale decline (17 %) has been observed since 2012 concurring with a period of increasing sea surface temperatures in the Mediterranean Sea and positive North Atlantic Oscillation and Mediterranean Oscillation climate indices. Long-term trends in PP reveal slight declines in most coastal areas (−0.05 to −0.1 g C m−2 per decade) except in the Adriatic where PP increases at +0.1 g C m−2 per decade. Regionalization of coastal waters based on PP seasonal patterns reveals the importance of river effluents in determining PP in coastal waters that can regionally increase up to 5-fold. Our study provides insight into the contribution of coastal waters to basin-scale carbon balances in the Mediterranean Sea while highlighting the importance of the different temporal and spatial scales of variability.

We estimated pelagic primary production (PP) in the coastal (< 200 m depth) Mediterranean Sea from satellite-borne data, its contribution to basin-scale carbon fixation, its variability and long-term trends during the period 2002–2016. Annual coastal PP was estimated at 0.041 Gt C, which approximately represents 12 % of total carbon fixation in the Mediterranean Sea. About 50 % of this production occurs in the eastern basin, whereas the western and Adriatic shelves contribute with 25 % each of total coastal production. Strong regional variability is revealed, from high-production areas (> 300 g C m−2) associated with major river discharges, to less productive provinces (< 50 g C m−2) located in the southeastern Mediterranean. PP variability in the Mediterranean Sea is dominated by interannual variations but overall trend during the study period shows notable decrease (17 %) since 2012 concurring with a period of increasing sea surface temperatures in the Mediterranean Sea and positive North Atlantic Oscillation and the Mediterranean Oscillation climate indices. PP declines in most coastal areas (−0.05 to −0.1 g C m−2 per decade) except in the Adriatic where PP increases at +0.1 g C m−2 per decade. Regionalization of coastal waters based on PP seasonal patterns reveals the importance of river effluents in determining PP in coastal waters that can regionally increase in up to five-fold. Our study provides insight on the contribution of coastal waters to basin scale carbon balances in the Mediterranean Sea while highlighting the importance of the different temporal and spatial scales of variability.

Using in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter (b bp) at an oceanic site, we show that diel cycles of b bp are large enough to generate measurable diel variability of the ocean reflectance. This means that biogeochemical quantities such as net phytoplankton primary production, which are derivable from the diel b bp signal, can be potentially derived also from the diel variability of ocean color radiometry (OCR). This is a promising avenue for basin-scale quantification of such quantities, because OCR is now performed from geostationary platforms that enable quantification of diel changes in the ocean reflectance over large ocean expanses. To assess the feasibility of this inversion, we applied three numerical inversion algorithms to derive b bp from measured reflectance data. The uncertainty in deriving b bp transfers to the retrieval of its diel cycle, making the performance of the inversion better in the green part of the spectrum (555 nm), with correlation coefficients >0.75 and a variability of 40% between the observed and derived b bp diel. While the results are encouraging, they also emphasize the inherent limitation of current inversion algorithms in deriving diel changes of b bp , which essentially stems from the empirical parameterizations that many such algorithms include.

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.

Marine particles of different nature are found throughout the global ocean. The term “marine particles” describes detritus aggregates and fecal pellets as well as bacterioplankton, phytoplankton, zooplankton and nekton. Here, we present a global particle size distribution dataset obtained with several Underwater Vision Profiler 5 (UVP5) camera systems. Overall, within the 64 µm to about 50 mm size range covered by the UVP5, detrital particles are the most abundant component of all marine particles; thus, measurements of the particle size distribution with the UVP5 can yield important information on detrital particle dynamics. During deployment, which is possible down to 6000 m depth, the UVP5 images a volume of about 1 L at a frequency of 6 to 20 Hz. Each image is segmented in real time, and size measurements of particles are automatically stored. All UVP5 units used to generate the dataset presented here were inter-calibrated using a UVP5 high-definition unit as reference. Our consistent particle size distribution dataset contains 8805 vertical profiles collected between 19 June 2008 and 23 November 2020. All major ocean basins, as well as the Mediterranean Sea and the Baltic Sea, were sampled. A total of 19 % of all profiles had a maximum sampling depth shallower than 200 dbar, 38 % sampled at least the upper 1000 dbar depth range and 11 % went down to at least 3000 dbar depth. First analysis of the particle size distribution dataset shows that particle abundance is found to be high at high latitudes and in coastal areas where surface productivity or continental inputs are elevated. The lowest values are found in the deep ocean and in the oceanic gyres. Our dataset should be valuable for more in-depth studies that focus on the analysis of regional, temporal and global patterns of particle size distribution and flux as well as for the development and adjustment of regional and global biogeochemical models. The marine particle size distribution dataset (Kiko et al., 2021) is available at https://doi.org/10.1594/PANGAEA.924375.

The Mediterranean Sea comprises just 0.8 % of the global oceanic surface, yet considering its size, it is regarded as a disproportionately large sink for anthropogenic carbon due to its physical and biogeochemical characteristics. An underwater glider mission was carried out in March–April 2016 close to the BOUSSOLE and DyFAMed time series moorings in the northwestern Mediterranean Sea. The glider deployment served as a test of a prototype ion-sensitive field-effect transistor pH sensor. Dissolved oxygen (O2) concentrations and optical backscatter were also observed by the glider and increased between 19 March and 1 April, along with pH. These changes indicated the start of a phytoplankton spring bloom, following a period of intense mixing. Concurrent measurements of CO2 fugacity and O2 concentrations at the BOUSSOLE mooring buoy showed fluctuations, in qualitative agreement with the pattern of glider measurements. Mean net community production rates (N) were estimated from glider and buoy measurements of dissolved O2 and inorganic carbon (DIC) concentrations, based on their mass budgets. Glider and buoy DIC concentrations were derived from a salinity-based total alkalinity parameterisation, glider pH and buoy CO2 fugacity. The spatial coverage of glider data allowed the calculation of advective O2 and DIC fluxes. Mean N estimates for the euphotic zone between 10 March and 3 April were (-17±36) for glider O2, (44±94) for glider DIC, (17±37) for buoy O2 and (49±86) mmolm-2d-1 for buoy DIC, all indicating net metabolic balance over these 25 d. However, these 25 d were actually split into a period of net DIC increase and O2 decrease between 10 and 19 March and a period of net DIC decrease and O2 increase between 19 March and 3 April. The latter period is interpreted as the onset of the spring bloom. The regression coefficients between O2 and DIC-based N estimates were 0.25 ± 0.08 for the glider data and 0.54 ± 0.06 for the buoy, significantly lower than the canonical metabolic quotient of 1.45±0.15. This study shows the added value of co-locating a profiling glider with moored time series buoys, but also demonstrates the difficulty in estimating N, and the limitations in achievable precision.

The EPIC/DSCOVR observations of the Earth's surface lit by the Sun made from the first Lagrange point several times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) at the ice-free ocean surface. The PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known), the irradiance reflected to space (estimated from the EPIC Level 1b radiance data), taking account of atmospheric transmission and surface albedo (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, which dismisses the need for often-arbitrary assumptions about cloudiness distribution within a pixel and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness changes during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NCEP Reanalysis 2 data, aerosol optical thickness and Angström coefficient from MERRA-2 data, and ozone amount from EPIC Level 2 data. Areas contaminated by Sun glint are excluded using a threshold on Sun glint reflectance calculated using wind data. Ice masking is based on NSIDC near-real-time ice fraction data. The product is evaluated against in situ measurements at various locations and compared with estimates from sensors in polar and geostationary orbits (MODIS, AHI). Unlike with MODIS, the EPIC PAR product does not exhibit gaps at low and middle latitudes. Accuracy is satisfactory for long-term studies of aquatic photosynthesis, especially given the much larger uncertainties on the fraction of PAR absorbed by live algae and the quantum yield of carbon fixation. The EPIC daily mean PAR product is generated operationally on a Plate Carrée (equal-angle) grid with 18.4 km resolution at the equator and on an 18.4 km equal-area grid, i.e., it is fully compatible with the NASA Greenbelt OBPG ocean-color products. Data are available since the beginning of the DSCOVR mission (i.e., June 2015) from the NASA Langley ASDC website.

We used above-and below-water radiometry measurements collected during a research voyage in the eastern Indian Ocean to assess uncertainties in deriving the remote sensing reflectance, R rs , from unattended above-water radiometric data collection with the In-Situ Marine Optics Pty. Ltd. (IMO) Dynamic Above-water Radiance (L) and Irradiance (E) Collector (DALEC). To achieve this, the R rs values derived from using the latest version of this hyperspectral radiometer were compared to values obtained from two in-water profiling radiometer systems of rather general use in the ocean optics research community, i.e., the Biospherical Instruments Inc. Compact Optical Profiling System (C-OPS) and the Seabird HyperPro II. Our results show that unattended, carefully quality-controlled, DALEC measurements provide R rs for wavelengths < 600 nm that match those derived from the in-water systems with no bias and a dispersion of about 8%, provided that the appropriate technique is used to quantify the contribution of sky light reflection to the measured signal. The dispersion is larger (25-50%) for red bands, which is expected for clear oligotrophic waters as encountered during the voyage, where ∼2 10 −5 < R rs < ∼2 10 −4 sr −1. For comparison, the two in-water systems provided R rs in agreement within 4% for wavelengths < 600 nm.

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.

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 µ m 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 .

The MALINA oceanographic campaign was conducted during summer 2009 to investigate the carbon stocks and the processes controlling the carbon fluxes in the Mackenzie River estuary and the Beaufort Sea. Dur- ing the campaign, an extensive suite of physical, chemical and biological variables was measured across seven shelf–basin transects (south-north) to capture the meridional gradient between the estuary and the open ocean.Key variables such as temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll-a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured onboard the Canadian research icebreaker CCGS Amundsen and from a barge in shallow coastal areas or for sampling within broken ice fields. Here, we present the results of a joint effort to tidy and standardize the collected data sets that will facilitate their reuse in further studies of the changing Arctic Ocean.

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.

A multiplatform assessment of the Ocean–Atmosphere Spectral Irradiance Model (OASIM) radiative model focussed on the Mediterranean Sea for the period 2004–2017 is presented. The BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE) mooring and biogeochemical Argo (BGC-Argo) float optical sensor observations are combined with model outputs to analyse the spatial and temporal variabilities in the downward planar irradiance at the ocean–atmosphere interface. The correlations between the data and model are always higher than 0.6. With the exception of downward photosynthetic active radiation and the 670 nm channel, correlation values are always higher than 0.8 and, when removing the inter-daily variability, they are higher than 0.9. At the scale of the BOUSSOLE sampling (15 min temporal resolution), the root mean square difference oscillates at approximately 30 %–40 % of the averaged model output and is reduced to approximately 10 % when the variability between days is filtered out. Both BOUSSOLE and BGC-Argo indicate that bias is up to 20 % for the irradiance at 380 and 412 nm and for wavelengths above 670 nm, whereas it decreases to less than 5 % at the other wavelengths. Analysis of atmospheric input data indicates that the model skill is strongly affected by cloud dynamics. High skills are observed during summer when the cloud cover is low.

Understanding long‐term variations of ocean ecosystems requires untangling the time scales involved in their natural fluctuations. We applied a temporal decomposition procedure to two decades of satellite ocean color observations to characterize the time variability of surface chlorophyll‐a (SChl) in the Mediterranean Sea. In order to assess the reliability of the satellite data at capturing intraseasonal, seasonal, and interannual variability, we first show that satellite SChl data compare well with field data of chlorophyll‐a fluorescence from the long‐term BOUSSOLE time series, at all three time scales. The decomposition procedure is then applied to satellite SChl and to mixing‐layer depth (MxLD) data from an ocean reanalysis, both at the scale of the entire Mediterranean Sea. Our results reveal similar amplitude for the seasonal and intraseasonal SChl variations in the northwestern bloom region, together explaining about 90% of the SChl variance. Coherent seasonal SChl variations occur at the scale of the bloom region (~400 km) and are tightly connected with seasonal MxLD changes. Intraseasonal SChl fluctuations occur at smaller spatial scales (~100 km), suggesting they would be generated by storms although they weakly correlate to variations of the MxLD reanalysis. Over the oligotrophic part of the Mediterranean Sea, about 80% of the variability in both SChl and MxLD are explained by basin‐scale (~1,000 km) seasonal variations. Intraseasonal variability occurs at much smaller spatial scales, typical of mesoscale activity (~30 km). These results support the hypothesis that seasonal SChl variations are driven by changes in MxLD, while mesoscale activity and storms drive the intraseasonal SChl fluctuations.

Isoprene produced by marine phytoplankton acts as a precursor of secondary organic aerosol and thereby affects cloud formation and brightness over the remote oceans. Yet the marine isoprene emission is poorly constrained, with discrepancies among estimates that reach 2 orders of magnitude. Here we present ISOREMS, the first satellite-only based algorithm for the retrieval of isoprene concentration in the Southern Ocean. Sea surface concentrations from six cruises were matched with remotely sensed variables from MODIS Aqua, and isoprene was best predicted by multiple linear regression with chlorophyll a and sea surface temperature. Climatological (2002-2018) isoprene distributions computed with ISOREMS revealed high concentrations in coastal and near-island waters, and within the 40-50°S latitudinal band. Isoprene seasonality paralleled phytoplankton productivity, with annual maxima in summer. The annual Southern Ocean emission of isoprene was estimated at 63 Gg C yr<SUP>-1</SUP>. The algorithm can provide spatially and temporally realistic inputs to atmospheric and climate models.

A 21 year (1998–2018) continuous monthly data set of the global distribution of light (photosyntheti-cally available radiation, PAR, or irradiance) reaching the seabed is presented. This product uses ocean color andbathymetric data to estimate benthic irradiance, offering critical improvements on a previous data set. The timeseries is 4 times longer (21 versus 5 years), the spatial resolution is better (pixel size of 4.6 versus 9.3 km at theEquator), and the bathymetric resolution is also better (pixel size of 0.46 versus 3.7 km at the Equator). The paperdescribes the theoretical and methodological bases and data processing. This new product is used to estimate thesurface area of the seafloor where (1) light does not limit the distribution of photosynthetic benthic organismsand (2) net community production is positive. The complete data set is provided as 14 netCDF files available onPANGAEA (Gentili and Gattuso, 2020a, https://doi.org/10.1594/PANGAEA.910898). The R packageCoastal-Light, available on GitHub (https://github.com/jpgattuso/CoastalLight.git, last access: 29 July 2020), allows us(1) to download geographical and optical data from PANGAEA and (2) to calculate the surface area that receivesmore than a given threshold of irradiance in three regions (nonpolar, Arctic, and Antarctic). Such surface areascan also be calculated for any subregion after downloading data from a remotely and freely accessible server

The European Copernicus programme ensures long-term delivery of high-quality, global satellite ocean colour radiometry (OCR) observations from its Sentinel-3 (S3) satellite series carrying the ocean and land colour instrument (OLCI). In particular, the S3/OLCI provides marine water leaving reflectance and derived products to the Copernicus marine environment monitoring service, CMEMS, for which data quality is of paramount importance. This is why OCR system vicarious calibration (OC-SVC), which allows uncertainties of these products to stay within required specifications, is crucial. The European organisation for the exploitation of meteorological satellites (EUMETSAT) operates the S3/OLCI marine ground segment, and envisions having an SVC infrastructure deployed and operated for the long-term. This paper describes a design for such an SVC infrastructure, named radiometry for ocean colour satellites calibration and community engagement (ROSACE), which has been submitted to Copernicus by a consortium made of three European research institutions, a National Metrology Institute, and two small-to medium-sized enterprises (SMEs). ROSACE proposes a 2-site infrastructure deployed in the Eastern and Western Mediterranean Seas, capable of delivering up to about 80 high quality matchups per year for OC-SVC of the S3/OLCI missions.

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.

A new framework that enables evaluation of the in situ ocean color radiometry measurement uncertainty is presented. The study was conducted on the multispectral data from a permanent mooring deployed in clear open ocean water. The uncertainty is evaluated for each component of the measurement equation and data processing step that leads to deriving the remote sensing reflectance. The Monte Carlo method was selected to handle the data complexity such as correlation and nonlinearity in an efficient manner. The results are presented for a prescreened dataset that is suitable for system vicarious calibration applications. The framework provides uncertainty value per measurement taking into consideration environmental conditions present during acquisition. A summary value is calculated from the statistics of the individual uncertainties per each spectral channel. This summary value is below 4% (k 5 1) for the blue and green spectral range. For the red spectral channels, the summary uncertainty value increases to approximately 5%. The presented method helps to understand the significance of various uncertainty components and to provide a way of identifying major contributors. This can be used for efficient system performance improvement in the future.

A global compilation of in situ data is useful 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 (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT and GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenization, 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) was propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188 (Valente et al., 2019).

A wavelet analysis has been applied, for the first time, to 3-year high-frequency field observations of bio-optical properties (i.e. chlorophyll-fluorescence, beam attenuation and backscattering coefficients) in the northwestern Mediterranean Sea (BOUSSOLE site), in order to identify their dominant temporal patterns and evolution. A cross-wavelet and coherence analysis has also been applied to paired bio-optical coefficients time-series at the BOUSSOLE site, which allows identifying the temporal relationship between the cycles of the bio-optical properties. Annual, six-and four-month, intra-seasonal (i.e., mid-and short-terms) cycles are identified from the time-series analysis. The periodicities of chlorophyll-fluorescence, beam attenuation and particulate back-scattering coefficients correlate well at different temporal scales and specific seasons. At annual, six-and four-month scales, different bio-optical properties follow rather similar patterns, likely driven by physical forcing. Intra-seasonal variability consists in both mid-and short-term variations. The former dominates during the winter and are related to episodic bloom events, while the latter variations (i.e., diel) prevail during summer, in a stratified water column.

Two 3-year time series of hourly measurements of the fugacity of CO₂ (<em>f</em> CO₂) 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 <em>f</em> 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.

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.

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.

We introduce a new method to determine the anisotropy of reflectance of sea ice and snow at spatial scales from 1 m2 to 80 m2 using a multispectral circular fish-eye radiance camera (CE600). The CE600 allows measuring radiance simultaneously in all directions of a hemisphere at a 1° angular resolution. The spectral characteristics of the reflectance and its dependency on illumination conditions obtained from the camera are compared to those obtained with a hyperspectral field spectroradiometer manufactured by Analytical Spectral Device, Inc. (ASD). Results confirm the potential of the CE600, with the suggested measurement setup and data processing, to measure commensurable sea ice and snow hemispherical-directional reflectance factor, HDRF, values. Compared to the ASD, the reflectance anisotropy measured with the CE600 provides much higher resolution in terms of directional reflectance (N = 16,020). The hyperangular resolution allows detecting features that were overlooked using the ASD due to its limited number of measurement angles (N = 25). This data set of HDRF further documents variations in the anisotropy of the reflectance of snow and ice with the geometry of observation and illumination conditions and its spectral and spatial scale dependency. Finally, in order to reproduce the hyperangular CE600 reflectance measurements over the entire 400–900 nm spectral range, a regression-based method is proposed to combine the ASD and CE600 measurements. Results confirm that both instruments may be used in synergy to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set.

An efficient system to produce in situ high quality radiometric measurements is compulsory to rigorously perform the vicarious calibration of satellite sensors dedicated to Ocean Color Radiometry (OCR) and to validate their derived products. This requirement is especially needed during the early stages of an OCR satellite activity or for remote areas poorly covered by oceanographic cruises with possible bio-optical anomalies. Taking advantage of Argo's profiling float technology, we present a new autonomous profiling float dedicated to in situ radiometric measurements. The float is based on the Provor CTS5 (manufacturer NKE) with an added novel two protruding arm design allowing for sensor redundancies, shading mitigation and near-surface data. Equipped with two identical radiometers on each arm that measure downward irradiance and upwelling radiance at seven wavelengths, the ProVal float generates both redundant radiometric profiles as well as an estimate of Remote Sensing Reflectance. Results from 449 profiles obtained in the NW Mediterranean Sea and in the Indian sector of the Southern Ocean are presented to illustrate the ProVal float technical maturity. Analysis of the behavior of the profiling float, including tilting and ascent speeds is presented. The vertical stability of the ProVal exhibits 85% of surface data of the Mediterranean Sea with a tilt smaller than 10 degrees. This percentage is 40% in the Southern Ocean due to rougher seas. Redundant sensors provide a characterization of the relative drift between sensors over the deployment which is found to be <0.15% per month over a year. Post-cruise calibration of a recovered float revealed no significant drift. As an example of the utility of ProVal floats, a match-up of Remote Sensing Reflectance measured with the European Space Agency Ocean and Land Color Imager (OLCI onboard Sentinel-3A) is shown. It follows that profiling floats, such as ProVal, could provide a significant contribution to an upcoming global System Vicarious Calibration of space-based radiometers.

In-situ high quality measurements of radiometric quantities are mandatory to enable a "system vicarious calibration" (SVC) of satellite sensors dedicated to Ocean Color Radiometry (OCR) as well as to validate their derived products. High density of acquisition is particularly critical during the early stages of an OCR satellite activity. The ProVal float measures downward irradiance and upwelling radiance at seven wavelengths on two arms that allow radiometer redundancy and shading mitigation. We analyzed more than 500 profiles sampled in the Southern Ocean and Mediterranean Sea to date. We find that 45% and 85% of data in the surface layer exhibit tilts lower than 10°in the Southern Ocean and Mediterranean Sea respectively. Floats deployed in the Mediterranean Sea were recovered allowing post-deployment calibrations of radiometers that confirmed the low sensor drift. In addition, platform shading, estimated from the difference between the two radiometers, shows good agreement with Monte-Carlo simulations. Finally, comparisons of Remote Sensing Reflectance with the OLCI sensor (Sentinel-3A) show results in agreement with other sources of in-situ data but with extended coverage capabilities.

Development of autonomous profiling floats, allowing for long-term continuous measurement of bio-optical variables, promises to significantly increase our knowledge of the variability of the particulate optical backscattering coefficient b(bp) in marine environments. However, because autonomous floats are designed for unattended data collection and only rarely are recovered for analysis of the condition of the sensors in situ, the quality-control analysis of float data streams is of paramount importance in both a particular dataset and the larger understanding of the response of sensors over the lifetime of the floats. Anomalous data from a backscattering sensor (MCOMS) mounted on autonomous profiling floats are reported here. The observed sensor behavior, which presents itself as significant differences in the values observed at the parking depth between profiles, caused by a steady increase in the signal during the profiling time, is neither common to all sensors nor can it be a function of changes in the particle population. A simple quality-control procedure that is able to detect this spurious sensor response is proposed. Further characterization of this effect will require laboratory experimentation under controlled conditions of temperature and pressure.

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

Satellite ocean color observations revealed that unusually deep convection events in 2005, 2006, 2010, and 2013 led to an increased phytoplankton biomass during the spring bloom over a large area of the northwestern Mediterranean Sea (NWM). Here we investigate the effects of these events on the seasonal phytoplankton community structure, we quantify their influence on primary production, and we discuss the potential biogeochemical impact. For this purpose, we compiled in situ phytoplankton pigment data from five ship surveys performed in the NWM and from monthly cruises at a fixed station in the Ligurian Sea. We derived primary production rates from a light photosynthesis model applied to these in situ data. Our results confirm that the maximum phytoplankton biomass during the spring bloom is larger in years associated with intense deep convection events (151%). During these enhanced spring blooms, the contribution of diatoms to total phytoplankton biomass increased (133%), as well as the primary production rate (1115%). The occurrence of a highly productive bloom is also related to an increase in the phytoplankton bloom area (1155%) and in the relative contribution of diatoms to primary production (163%). Therefore, assuming that deep convection in the NWM could be significantly weakened by future climate changes, substantial decreases in the spring production of organic carbon and of its export to deep waters can be expected.

Shifts in global climate resonate in plankton dynamics, biogeochemical cycles, and marine food webs. We studied these linkages in the North Atlantic subpolar gyre (NASG), which hosts extensive phytoplankton blooms. We show that phytoplankton abundance increased since the 1960s in parallel to a deepening of the mixed layer and a strengthening of winds and heat losses from the ocean, as driven by the low frequency of the North Atlantic Oscillation (NAO). In parallel to these bottom-up processes, the top-down control of phytoplankton by copepods decreased over the same time period in the western NASG, following sea surface temperature changes typical of the Atlantic Multi-decadal Oscillation (AMO). While previous studies have hypothesized that climate-driven warming would facilitate seasonal stratification of surface waters and long-term phytoplankton increase in subpolar regions, here we show that deeper mixed layers in the NASG can be warmer and host a higher phytoplankton biomass. These results emphasize that different modes of climate variability regulate bottom-up (NAO control) and top-down (AMO control) forcing on phytoplankton at decadal timescales. As a consequence, different relationships between phytoplankton, zooplankton, and their physical environment appear subject to the disparate temporal scale of the observations (seasonal, interannual, or decadal). The prediction of phytoplankton response to climate change should be built upon what is learnt from observations at the longest timescales.

Abstract. 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).

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.

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.

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.

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.

A 6 yr time series of high frequency inherent optical property (IOP) measurements in the Mediterranean was used to derive information on the diel and seasonal variability of particulate production. Empirical relationships between particulate attenuation (c(p)), particulate backscattering (b(bp)), and particulate organic carbon allowed calculation of estimates of net community production (NCP), daytime NCP (NCPd), and gross community production (GCP) from the diel variations in either IOP. Similar seasonal variations and good correlation (r = 5 0.83, p < 0.001) between daily means of c(p) and b(bp) were observed, yet differences in the timing and amplitude of their diel cycles led to significant differences in their derived production metrics. Best agreement was obtained during bloom proliferation (44.1-66.7% shared variance) when all three production estimates were highest, while worst was during bloom decline. Best overall correlation was found for NCPd. Accordingly, only c(p)-derived estimates reproduced predicted seasonal variations in community production and seasonality of ``traditional'' chlorophyll-based primary production models. Analysis of the diel cycles of ``real-time'' net community production (NCPh), determined from the first-derivative of either c(p) or b(bp), revealed ca. fourfold to eightfold lower daytime NCPh, twofold to fivefold lower daily maximum NCPh, and twice as much intraseasonal variability relative to the mean amplitude of diel variations for b(bp). Although the timing of maximum of c(p)-derived NCPh was consistently prior to solar noon, significant seasonal differences in the timing of maximum b(bp)-derived NCPh was observed. Particulate backscattering may be used to infer biogeochemical properties, while greater understanding of the diel cycles of b(bp) is needed before b(bp) can be used to investigate daily community production.

Andre Morel (1933-2012) was a prominent pioneer of modern optical oceanography, enabling significant advances in this field. Through his forward thinking and research over more than 40 years, he made key contributions that this field needed to grow and to reach its current status. This article first summarizes his career and then successively covers different aspects of optical oceanography where he made significant contributions, from fundamental work on optical properties of water and particles to global oceanographic applications using satellite ocean color observations. At the end, we share our views on Andre's legacy to our research field and scientific community.

André Morel (1933-2012) was a prominent pioneer of modern optical oceanography, enabling significant advances in this field. Through his forward thinking and research over more than 40 years, he made key contributions that this field needed to grow and to reach its current status. This article first summarizes his career and then successively covers different aspects of optical oceanography where he made significant contributions, from fundamental work on optical properties of water and particles to global oceanographic applications using satellite ocean color observations. At the end, we share our views on André's legacy to our research field and scientific community. Expected final online publication date for the Annual Review of Marine Science Volume 6 is January 03, 2014. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

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.

The 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.

Models based on the multivariate partial least squares (PLS) regression technique are developed for the retrieval of phytoplankton size structure from measured light absorption spectra (BOUSSOLE site, northwestern Mediterranean Sea). PLS-models trained with data from the Mediterranean Sea showed good accuracy in retrieving, over the nine-year BOUSSOLE time series, the concentrations of total chlorophyll a [Tchl a], of the sum of seven diagnostic pigments and of pigments associated with micro, nano, and picophytoplankton size classes separately. PLS-models trained using either total particle or phytoplankton absorption spectra performed similarly, and both reproduced seasonal variations of biomass and size classes derived by high performance liquid chromatography. Satisfactory retrievals were also obtained using PLS-models trained with a data set including various locations of the world's oceans, with however a lower accuracy. These results open the way to an application of this method to absorption spectra derived from hyperspectral and field satellite radiance measurements. (C) 2013 Optical Society of America

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. Satellite time series have been providing remote observations of the sea surface for several decades. Due to satellite lifetime, usually between 5 and 10 years, these 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 in order 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 duration of this future time series necessary to actually enhance the trend detection performed with the joint SeaWiFS-MERIS analysis.

[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

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.

Miniaturized radiance cameras measuring underwater multispectral radiances in all directions at highradiometric accuracy (CE600) are presented. The camera design is described, as well as the main steps of its optical and radiometric characterization and calibration. The results show the excellent optical quality of the specifically designed fish-eye objective. They also show the low noise and excellent linearity of the complementary metal oxide semiconductor (CMOS) detector array that is used. Initial results obtained in various oceanic environments demonstrate the potential of this instrument to provide new measurements of the underwater radiance distribution from the sea surface to dimly lit layers at depth. Excellent agreement is obtained between nadir radiances measured with the camera and commercial radiometers. Comparison of the upwelling radiance distributions measured with the CE600 and those obtained with another radiance camera also shows a very close agreement. The CE600 measurements allow all apparent optical properties (AOPs) to be determined from integration of the radiance distributions and inherent optical properties (IOPs) to be determined from inversion of the AOPs. This possibility represents a significant advance for marine optics by tying all optical properties to the radiometric standard and avoiding the deployment of complex instrument packages to collect AOPs and IOPs simultaneously (except when it comes to partitioning IOPs into their component parts).

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 amplitude of the trend to be detected, the length of the available datasets, and the noise properties. Although the auto-correlation 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 auto-correlation level typically leads to an over-detection of significant trends. Satellite time series have been providing remote observations of the sea surface for several decades. Due to satellite lifetime, usually between 5 and 10 years, these 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 datasets, which affect the trend detection. We propose here a generic framework to address the detectability of a linear trend and its significance from multi-sensor datasets.

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

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.1x)

As one of the major oceanic sinks of anthropogenic CO₂, the Southern Ocean plays a critical role in the climate system. However, due to the scarcity of observations, little is known about physical and biological processes that control air-sea CO₂ fluxes and how these processes might respond to climate change. It is well established that primary production is one of the major drivers of air-sea CO₂ fluxes, consuming surface Dissolved Inorganic Carbon (DIC) during Summer. Southern Ocean primary production is though constrained by several limiting factors such as iron and light availability, which are both sensitive to mixed layer depth. Mixed layer depth is known to be affected by current changes in wind stress or freshwater fluxes over the Southern Ocean. But we still don't know how primary production may respond to anomalous mixed layer depth neither how physical processes may balance this response to set the seasonal cycle of air-sea CO₂ fluxes. In this study, we investigate the impact of anomalous mixed layer depth on surface DIC in the Atlantic and Indian sectors of the Subantarctic zone of the Southern Ocean (60W-60E, 38S-55S) with a combination of in situ data, satellite data and model experiment. We use both a regional eddy permitting ocean biogeochemical model simulation based on NEMO-PISCES and data-based reconstruction of biogeochemical fields based on CARIOCA buoys and SeaWiFS data. A decomposition of the physical and biological processes driving the seasonal variability of surface DIC is performed with both the model data and observations. A good agreement is found between the model and the data for the amplitude of biological and air-sea flux contributions. The model data are further used to investigate the impact of winter and summer anomalies in mixed layer depth on surface DIC over the period 1990-2004. The relative changes of each physical and biological process contribution are quantified and discussed.

We estimate in situ biological carbon production rates from high frequency measurements along the trajectories of 6 CARIOCA drifters in the Atlantic and Indian sector of the Southern Ocean during 2006-2009 spring-summer periods. Net Community production (NCP) integrated over the mixed layer is derived from the daily change of the dissolved inorganic carbon (DIC) combined with mixed layer depths estimated from Argo profiles. Daily values of NCP range from 30 to 140 mmol C m^-2 d^-1. A satellite based ocean color model is used to compute depth integrated marine net primary production (NPP) for the same periods along the trajectories of the buoys. As already mentioned by other authors, the SEAWIFS chlorophyll are underestimated by a factor ≈ 2-3 in the Southern Ocean. Taking this into account, the export ratio NCP/NPP is included between 0.2 and 0.9 and decreases with increasing sea surface temperature. Monthly satellite based NPP are computed over the 38°S-55°S, 60°W-60°E area of the Southern Ocean. A seasonal budget of DIC and pCO₂ in the mixed layer is assessed. We quantitatively separate all the physical and biological processes that control their monthly changes. A good agreement is found with pCO₂ climatology of Takahashi (2009). On an annual timescale, mean NCP is ≈ 4-5 times greater than mean CO₂ invasion, being respectively equal to -4.9 and 1.1 mol C m^-2 yr^-1. Attention is drawn on key parameters that control the seasonal distribution of surface pCO₂ and air-sea CO₂ uptake that will have to be carefully monitored or modeled under changing environmental conditions.

Large-scale climate patterns influenced temperature and weather patterns around the globe in 2011. In particular, a moderate-to-strong La Nina at the beginning of the year dissipated during boreal spring but reemerged during fall. The phenomenon contributed to historical droughts in East Africa, the southern United States, and northern Mexico, as well the wettest two-year period (2010-11) on record for Australia, particularly remarkable as this follows a decade-long dry period. Precipitation patterns in South America were also influenced by La Nina. Heavy rain in Rio de Janeiro in January triggered the country's worst floods and landslides in Brazil's history. The 2011 combined average temperature across global land and ocean surfaces was the coolest since 2008, but was also among the 15 warmest years on record and above the 1981-2010 average. The global sea surface temperature cooled by 0.1 degrees C from 2010 to 2011, associated with cooling influences of La Nina. Global integrals of upper ocean heat content for 2011 were higher than for all prior years, demonstrating the Earth's dominant role of the oceans in the Earth's energy budget. In the upper atmosphere, tropical stratospheric temperatures were anomalously warm, while polar temperatures were anomalously cold. This led to large springtime stratospheric ozone reductions in polar latitudes in both hemispheres. Ozone concentrations in the Arctic stratosphere during March were the lowest for that period since satellite records began in 1979. An extensive, deep, and persistent ozone hole over the Antarctic in September indicates that the recovery to pre-1980 conditions is proceeding very slowly. Atmospheric carbon dioxide concentrations increased by 2.10 ppm in 2011, and exceeded 390 ppm for the first time since instrumental records began. Other greenhouse gases also continued to rise in concentration and the combined effect now represents a 30% increase in radiative forcing over a 1990 baseline. Most ozone depleting substances continued to fall. The global net ocean carbon dioxide uptake for the 2010 transition period from El Nino to La Nina, the most recent period for which analyzed data are available, was estimated to be 1.30 Pg C yr(-1), almost 12% below the 29-year long-term average. Relative to the long-term trend, global sea level dropped noticeably in mid-2010 and reached a local minimum in 2011. The drop has been linked to the La Nina conditions that prevailed throughout much of 2010-11. Global sea level increased sharply during the second half of 2011. Global tropical cyclone activity during 2011 was well-below average, with a total of 74 storms compared with the 1981-2010 average of 89. Similar to 2010, the North Atlantic was the only basin that experienced above-normal activity. For the first year since the widespread introduction of the Dvorak intensity-estimation method in the 1980s, only three tropical cyclones reached Category 5 intensity level-all in the Northwest Pacific basin. The Arctic continued to warm at about twice the rate compared with lower latitudes. Below-normal summer snowfall, a decreasing trend in surface albedo, and above-average surface and upper air temperatures resulted in a continued pattern of extreme surface melting, and net snow and ice loss on the Greenland ice sheet. Warmer-than-normal temperatures over the Eurasian Arctic in spring resulted in a new record-low June snow cover extent and spring snow cover duration in this region. In the Canadian Arctic, the mass loss from glaciers and ice caps was the greatest since GRACE measurements began in 2002, continuing a negative trend that began in 1987. New record high temperatures occurred at 20 m below the land surface at all permafrost observatories on the North Slope of Alaska, where measurements began in the late 1970s. Arctic sea ice extent in September 2011 was the second-lowest on record, while the extent of old ice (four and five years) reached a new record minimum that was just 19% of normal. On the opposite pole, austral winter and spring temperatures were more than 3 degrees C above normal over much of the Antarctic continent. However, winter temperatures were below normal in the northern Antarctic Peninsula, which continued the downward trend there during the last 15 years. In summer, an all-time record high temperature of -12.3 degrees C was set at the South Pole station on 25 December, exceeding the previous record by more than a full degree. Antarctic sea ice extent anomalies increased steadily through much of the year, from briefly setting a record low in April, to well above average in December. The latter trend reflects the dispersive effects of low pressure on sea ice and the generally cool conditions around the Antarctic perimeter.

As the proxy for Chlorophyll a (Chl a) concentration, thousands of fluorescence profiles were measured by instrumented elephant seals in the Kerguelen region (Southern Ocean). For accurate retrieval of Chl a concentrations acquired by in vivo fluorometer, a two-step procedure is applied: 1) A predeployment intercalibration with accurate determination by high performance liquid chromatography (HPLC) analysis, which not only calibrates fluorescence in appropriate Chl a concentration units, but also strongly reduces variability between fluorometers, and 2) a profile-by-profile quenching correction analysis, which effectively eliminates the fluorescence quenching issue at surface around noon, and results in consistent profiles between day and night. The quenching correction is conducted through an extrapolation of the deep fluorescence value toward surface. As proved by a validation procedure in the Western Mediterranean Sea, the correction method is practical and relatively reliable when there is no credible reference, especially for deep mixed waters, as in the Southern Ocean. Even in the shallow mixed waters, the method is also effective in reducing the influence of quenching.

OBJECTIVE: To assess, in obese type 2 diabetics (T2D), the impact of a home-based effort training program and the barriers to physical activity (PA) practice. METHOD: Twenty-three obese T2D patients (52.7 ± 8.2 years, BMI = 38.5 ± 7.6 kg/m(2)) were randomized to either a control group (CG), or an intervention group (IG) performing home-based cyclergometer training during 3 months, 30 min/day, with a monthly-supervised session. The initial and final measurements included: maximal graded effort test on cyclergometer, 6-minute walk test (6MWT) and 200-meter fast walk test (200mFWT), quadriceps maximal isometric strength, blood tests and quality of life assessment (SF- 36). A long-term assessment of the amount of physical activity (PA) and the barriers to PA practice was conducted using a questionnaire by phone call. RESULTS: Patients in the CG significantly improved the maximal power developed at the peak of the cyclergometer effort test (P < 0.05) as well as the quadriceps strength (P < 0.01). There were no significant changes in the other physical and biological parameters, neither in quality of life. At a mean distance of 17 ± 6.4 months, the PA score remained low in the two groups. The main barriers to PA practice identified in both groups were the perception of a low exercise capacity and a poor tolerance to effort, lack of motivation, and the existence of pain associated to PA. CONCLUSION: This home-based intervention had a positive impact on biometrics and physical ability in the short term in obese T2D patients, but limited effects in the long term. The questionnaires completed at a distance suggest considering educational strategies to increase the motivation and compliance of these patients.

Recent studies using models have reported opposite trends in the past decadal evolution of phytoplankton in the subpolar North Atlantic. In another hand, while long time series of phytoplankton observations are available in this region, they never have been investigated in parallel to physical forcing to understand their variability. Here, we investigated the multi decadal variability of phytoplankton and its underlying mechanisms since the 1960s, thanks to fifty years of in situ observations combined with satellite missions, reanalysed and model products. We show that a phytoplankton increase paralleled a deepening of the mixed layer depth (MLD) since the 1960s. This MLD deepening was related to a strengthening of the winds and net heat loss of the ocean after the mid-1980s following the low frequency signal of the North Atlantic Oscillation. Moreover, the decadal increase of sea surface temperature reported in this region was not associated with the expected scenario of shallower MLD. Our results run counter to the paradigm about how global warming could impact on MLD and phytoplankton abundance.

We investigated the phenology of oceanic phytoplankton at large scales over two 5-year time periods: 1979-1983 and 1998-2002. Two ocean-color satellite data archives (Coastal Zone Color Scanner (CZCS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS)) were used to investigate changes in seasonal patterns of concentration- normalized chlorophyll. The geographic coverage was constrained by the CZCS data distribution. It was best for the Northern Hemisphere and also encompassed large areas of the Indian, South Pacific, and Equatorial Atlantic regions. For each 2° pixel, monthly climatologies were developed for satellite-derived chlorophyll, and the resulting seasonal cycles were statistically grouped using cluster analysis. Five distinct groups of mean seasonal cycles were identified for each half-decade period. Four types were common to both time periods and correspond to previously identified phytoplankton regimes: Bloom, Tropical, Subtropical North, and Subtropical South. Two other mean seasonal cycles, one in each of the two compared 5-year periods, were related to transitional or intermediate states (Transitional Tropical and Transitional Bloom). Five mean seasonal cycles (Bloom, Tropical, Subtropical North, and Subtropical South, Transitional Bloom) were further confirmed when the whole SeaWiFS data set (1998-2010) was analyzed. For ~35% of the pixels analyzed, characteristic seasonal cycles of the 1979-1983 years differed little from those of the 1998-2002 period. For ~65% of the pixels, however, phytoplankton seasonality patterns changed markedly, especially in the Northern Hemisphere. Subtropical regions of the North Pacific and Atlantic experienced a widespread expansion of the Transitional Bloom regime, which appeared further enhanced in the climatology based on the full SeaWiFS record (1998-2010), and, as showed by a more detailed analysis, is associated to La Niña years. This spatial pattern of Transitional Bloom regime reflects a general smoothing of seasonality at macroscale, coming into an apparent greater temporal synchrony of the Northern Hemisphere. The Transitional Bloom regime is also the result of a higher variability, both in space and time. The observed change in phytoplankton dynamics may be related not only to biological interactions but also to large-scale changes in the coupled atmosphere-ocean system. Some connections are indeed found with climate indices. Changes were observed among years belonging to opposite phases of ENSO, though discernible from the change among the two periods and within the SeaWiFS era (1998-2010). These linkages are considered preliminary at present and are worthy of further investigation.

The spring, bloom is a renowned feature of many seasonal seas in the global ocean. Perhaps most famous of all is the spring bloom that occurs at middle and high latitudes of the North Atlantic. Since the 1950's the Sverdurp's theory prevails to explain the spring bloom initiation in the North Atlantic subpolar region. Photosynthesis is light limited during winter, so the bloom occurs in spring when the mixed layer shoals sufficiently to allow phytoplankton to remain within the sunlit region and enable net growth. Therefore an increase of stratification, due to global warming for instance, would lead to a strengthened bloom through phytoplankton spending more time in the euphotic zone. In this context, a stepwise increase in biomass has been reported in the mid-1980s correlated with the sea surface temperature (SST), an indicator of stratification, and the Atlantic Multidecadal Oscillation in the North Sea and Northeastern Atlantic. Chlorophyll-a (Chl), a measure of phytoplankton biomass, derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) from 1997-2002 was combined with in situ measurements of the Phytoplankton Color Index (PCI) collected by the Continuous Plankton Recorder survey since 1946. Recently, an increase of Chl has also been observed in satellite ocean color observations of the northeastern Atlantic (30°-50°N and 40°-0°W), from the 1980s to the 2000s (Coastal Zone Color Scanner ― CZCS, and SeaWiFS missions respectively) in parallel to an increase of SST. However, this increase of SST appeared to be related with a deepening of the Mixed Layer Depth (MLD) in this region rather than an increase of stratification. This result gives substance to the "dilution-recoupling hypothesis". The Dilution-Recoupling hypothesis suggests, under climate warming conditions, that weaken of winter mixing may lead to decreased net phytoplankton growth rates and vernal biomass (i.e., an opposite conclusion from one based on the Sverdrup's theory). However, because these contradictory results are restricted to PCI and SST data in an remote northeastern region in one case and to a discontinue radiometric time series of 10 years of data over a 20 year time period in the other case, it is of primordial importance to go further in the assessment of the Chl, and related physical parameters, decadal variability over a longer time period in the north Atlantic. The objective of the present study is to provide new elements to understand the response of phytoplankton to climate multi decadal changes through its physical forcing to better understand and forecast phytoplankton evolution in future. Here, we present the multi decadal variability of Chl in the North Atlantic (40°-60°N; 40°-0°W) in parallel to different physical forcing as the wind, SST and mixed layer depth. We combined extended in situ time series with modern high coverage satellite observations. The PCI, an index of Chl since 1946, is combined with a global merged satellite product of Chl (GlobColour, ESA) since 1997. MLD is derived from in situ vertical temperature profiles since 1941. The wind stress data (one important dynamical driver of MLD) and SST are issued from an extensive collection of surface marine data since 1960 (ICOADS). These in situ observations are respectively combined with ERS1-2/QuikSCAT and AVHRR satellite data since 1991 and 1981. The overlap between the various kinds of observations shows a good agreement for the different data sets. Since 1950-1960, while SST oscillates following the Atlantic Multidecadal Oscillation, the other parameters rather show a trend to increase. Beginning of the 1980s, there is a shift toward deeper MLD which is likely related to stronger wind stress. It is followed by a shift toward stronger Chl values. These patterns are emphasised in the north over 50°-60°N compared to 40°-50°N. The Chl increase in parallel to the MLD deepening might support the Dilution-Recoupling hypothesis rather than the Critical Depth hypothesis.

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 nanoeucaryote 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.

Eight autonomous profiling floats equipped with miniaturized radiometers and fluorimeters have collected data in Pacific, Atlantic, and Mediterranean offshore zones. They measured in particular 0-400 m vertical profiles of the downward irradiance at three wavelengths (412, 490, and 555 nm) and of the chlorophyll a fluorescence. Such autonomous sensors collect radiometric data regardless of sky conditions and collect essentially uncalibrated fluorescence data. Usual processing and calibration techniques are no longer usable in such remote conditions and have to be adapted. The proposition here is an interwoven processing by which missing parts of irradiance profiles (due to intermittent cloud occurrence) are interpolated by accounting for possible changes in optical properties (detected by the fluorescence signal) and by which the attenuation coefficient for downward irradiance, used as proxy for [Chl a] (the chlorophyll a concentration), allows the fluorescence signal to be calibrated in absolute units (mg m −3). This method is successfully applied to about 600 irradiance and fluorescence profiles. Validation of the results in terms of [Chl a] is made by matchup with satellite (MODIS-A) chlorophyll (24.3% RMSE, N = 358). Validation of the method is obtained by applying it on similar field data acquired from ships, which, in addition to irradiance and fluorescence profiles, include the [Chl a] HPLC determination, used for final verification.

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.

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°N to 50°N and longitudes from 60°W to 0°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°W), because of a delayed deepening of the mixed layer at the end of summer (mixed-layer depths - 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 North Western Atlantic (northwest of 38°N-40°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 growth of the phytoplankton population.

The changes in shape, amplitude, and timing in the diel variability of the particulate beam attenuation coefficient (c(p)) were investigated at 4 and 9 m during two seasonal cycles at an oceanic site in the northwestern Mediterranean Sea under contrasting physical and trophic situations. We observed a diel cycle in c(p) during the winter mixing of the water column, the development of the spring phytoplankton bloom, its collapse, and during the summer oligotrophy. The relative amplitude of the c(p) diel cycle was about 10-20% during winter mixing and summer oligotrophy and at least twice as large during the spring bloom. Diel c(p) minima generally occurred around sunrise and maxima a few hours before sunset. The specific particle rate of variation (r) was consistent over the diel cycle, with positive and negative values during daytime and nighttime, respectively. A striking feature of the r diel cycle was a morning maximum, i.e., before solar noon, which was successfully reproduced by a new model of particle assemblage growth rate based on three parameters: maximum growth rate, growth efficiency, and saturation irradiance. Each model parameter undergoes a diel cycle and shows a seasonal variation. A c(p)-based estimation of the particle net community production is computed from the measurements and model outputs. Results compare favorably with modeled primary production on the basis of continuous measurements of surface chlorophyll using fluorescence.

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ ¹⁴C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.

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.

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.

Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of ∼ 1000 <SUP>14</SUP>C measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PP, specifically yielding too few low PP (< 0.2 g C m <SUP>- 2 </SUP> d <SUP>- 1 </SUP>) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomass-normalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140°W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill.

A new concept of oceanographic data buoy is described, which couples a taut mooring and a ``transparent-to-swell'' superstructure, and is specifically designed for the collection of radiometric quantities in offshore environments. The design of the thin superstructure addresses two major requirements: stabilizing the instruments in the water column and avoiding shading them. The development of the buoy is described, starting with the theoretical assessment and then describing the various stages of development leading to the latest version of the mooring and buoy. Its performance at sea is also analyzed. This new platform has been deployed in the deep waters (>2400 m) of the northwestern Mediterranean Sea for about 4 yr (since September 2003) and provides a quasi-continuous record of optical properties at this site. The data are used for bio-optics research and for calibration and validation operations of several European and U. S. ocean color satellite missions. The plan is to continue the deployment to build a decadal time series of optical properties. The instrument suite that is installed on this buoy is also briefly described, and sample results are shown to demonstrate the ability of this new system to collect the data at the desired frequency and quality.

The match-up of satellite-derived reflectances with in situ observations is crucial to evaluate their quality and temporal stability. To contribute to this effort, a project has been set up to collect a data set of in situ radiometric and bio-optical quantities, in support to satellite ocean color calibration and validation. The project has been named ''BOUSSOLE'', and one of its key elements is a deep-sea optics mooring collecting data on a near-continuous basis since September 2003. This buoy is deployed in the deep clear waters of the northwestern Mediterranean Sea, and is visited on a monthly basis for servicing and acquisition of complementary data. The characteristics of the work area establish the site as a satisfactory location for validating satellite ocean color observations. A description of the data processing protocols is provided, followed by an analysis of the uncertainty of the buoy radiometry measurements. The results of a match-up analysis of the marine reflectances, diffuse attenuation coefficients, and chlorophyll concentrations for three major missions, i.e., MERIS, SeaWiFS, and MODIS-A, are then analyzed. They show poor performances for the bluest band (412 nm) of the three sensors, and performances within requirements at 443 and 490 nm for SeaWiFS and MODIS-A. These results suggest that a vicarious calibration should be introduced for the MERIS sensor. This analysis also demonstrates that a major effort is still required to improve atmospheric correction procedures whatever the mission.

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.

The radiance viewed from the ocean depends on the illumination and viewing geometry along with the water properties, and this variation is called the bidirectional effect. This bidirectional effect depends on the inherent optical properties of the water, including the volume scattering function, and is important when comparing data from different satellite sensors. The current model of <i>f/Q</i>, which contains the bidirectional effect, by Morel et al. (2002) depends on modeled, not measured, water parameters, thus must be carefully validated. In this paper we combined upwelling radiance distribution data from several cruises, in varied water types and with a wide range of solar zenith angles. We compared modeled and measured <i>L</i>_view/<i>L</i>_nadir and found that the average difference between the model and data was less than 0.01, while the RMS difference between the model and data was on the order of 0.02–0.03. This is well within the statistical noise of the data, which was on the order of 0.04–0.05, due to environmental noise sources such as wave focusing.

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 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]) which were determined in two environments, the Pacific and Mediterranean waters. These oceanic zones apparently form two extremes of the bio-optical variability range. 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 and lower than the average, in the Mediterranean Sea and Pacific Ocean, respectively. The divergences between the two water bodies, detected 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. Their prediction based on the sole [Chl] index is problematic; although it is probably possible on a regional scale, an ubiquitous relationship does not seem to exist for the global scale.

The radiance viewed from the ocean depends on the illumination and viewing geometry along with the water properties and this variation is called the bidirectional effect, or BRDF of the water. This BRDF depends on the inherent optical properties of the water, including the volume scattering function, and is important when comparing data from different satellite sensors. The current model by Morel et al. (2002) depends on modeled water parameters, thus must be carefully validated. In this paper we combined upwelling radiance distribution data from several cruises, in varied water types and with a wide range of solar zenith angles. We found that the average error of the model, when compared to the data was less than 1%, while the RMS difference between the model and data was on the order of 0.02–0.03. This is well within the statistical noise of the data, which was on the order of 0.04–0.05, due to environmental noise sources such as wave focusing.

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.

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.

An algorithm is presented, which is designed to identify blue-absorbing aerosols from near infrared and visible remote-sensing observations, as they are in particular collected by satellite ocean color sensors. The technique basically consists in determining an error budget at one wavelength around 5 10 nm, based on a first-guess estimation of the atmospheric path reflectance as if the atmosphere was of a maritime type, and on a reasonable hypothesis about the marine signal at this wavelength. The budget also includes the typical calibration uncertainty and the natural variability in the ocean optical properties. Identification of blue-absorbing aerosols is then achieved when the error budget demonstrates a significant over-correction of the atmospheic signal when using non-absorbing maritime aerosols. Implementation of the algorithm is presented, and its application to real observations by the MERIS and SeaWiFS ocean color sensors is discussed. The results demonstrate the skill of the algorithm in various regions of the ocean where absorbing aerosols are present, and for two different sensors. A validation of the results is also performed against in situ data from the AERONET, and further illustrates the skill of the algorithm and its general applicability. (c) 2005 Elsevier Inc. All rights reserved.

A new 0.5°resolution Mediterranean climatology of the mixed layer depth based on individual profiles of temperature and salinity has been constructed. The criterion selected is a threshold value of temperature from a near-surface value at 10 m depth, mainly derived by a method applied on the global (de Boyer Montégut et al., 2004 dBM04). With respect to dBM04, the main differences reside in the absence of spatial interpolation of the final fields and in the improved spatial resolution. These changes to the method are necessary to reproduce the Mediterranean mixed layer's behavior. In the derived climatological maps, the most relevant features of the basin surface circulation are reproduced, as well as the areas prone of the deep water formation are clearly identified. Finally, the role of density in the definition of the mixed layer's differing behaviors between the oriental and the occidental regions of the basin is presented.

[ 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.

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.

The bidirectionality of the upward radiance field in oceanic case 1 waters has been reinvestigated by incorporation of revised parameterizations of inherent optical properties as a function of the chlorophyll concentration (Chl), considering Raman scattering and making the particle phase function shape ((beta) over tilde (p)) continuously varying along with the Chl. Internal consistency is thus reached, as the decrease in backscattering probability (for increasing Chl) translates into a correlative change in (beta) over tilde (p). The single particle phase function (previously used) precluded a realistic assessment of bidirectionality for waters with Chl > 1 mg m(-3). This limitation is now removed. For low Chl, Raman emissions significantly affect the radiance field. For moderate Chl (0.1-1 mg m(-3)), new and previous bidirectional parameters remain close. The ocean reflectance anisotropy has implications in ocean color remote-sensing problems, in derivation of coherent water-leaving radiances, in associated calibration-validation activities, and in the merging of data obtained under various geometrical configurations. (C) 2002 Optical Society of America.

The Mediterranean Basin, subject both to climate changes and to increasing anthropogenic inputs, is an appropriate test site for observing the evolution of algal biomass and primary production on a long-term basis. With this aim, it is first necessary to study the consistency of the various sets of satellite data as provided by the space agencies, and to compare them to in situ available data. Pixel-by-pixel comparisons of the Level 3 chlorophyll products derived from the ocean color and temperature scanner (OCTS; Version 4, August 1999), polarization and directionality of earth reflectances (POLDER; reprocessing no. 2, July 2000), and the sea-viewing wide field-of-view sensor (SeaWiFS; reprocessing no. 3, May 2000) reveal a reasonably good agreement. Discrepancies, however, appear particularly in oligotrophic areas: weekly (or 10-day) means for OCTS and POLDER (which were operating simultaneously) differ in these areas by 30-70% on average, and OCTS and SeaWiFS weekly means, at 1-year distance, reveal differences by up to a factor of 2. Comparisons with measurements at sea, performed during various cruises, show that all these sensors tend to overestimate chlorophyll concentrations in oligotrophic waters. A ``regional algorithm'' is proposed to reduce this bias. The impact of using the various datasets for chlorophyll concentration, and for seawater temperature (Reynolds sea surface temperature [SST] analyses, Levitus climatological profiles) for primary production computations is shown. Because they are simultaneous to ocean color data, Reynolds analyses appear to be the most appropriate inputs to such computations. They have, however, to be combined with climatological vertical profiles of seawater temperature, so as to provide representative values for the productive layer. (C) 2002 Elsevier Science Inc. All rights reserved.

In situ optical measurements provide evidence that oligotrophic waters of the Mediterranean Sea have a greener color than would result from their phytoplankton content alone. This anomaly, detectable in low chlorophyll waters, remains unnoticed in the chlorophyll-rich waters of the nearby waters of the Moroccan upwelling zone. It is due to enhanced absorption in the blue and enhanced backscattering in the green parts of the visible spectrum likely resulting from the presence of submicron Saharan dust in suspension within the upper layer. This result implies that regional estimations of carbon fixation from ocean color images might be significantly overestimated, not only in the Mediterranean Sea, but also in other oligotrophic areas of the Northern hemisphere, subjected to desert dust deposition.

[1] Results of a single-blind round-robin comparison of satellite primary productivity algorithms are presented. The goal of the round-robin exercise was to determine the accuracy of the algorithms in predicting depth-integrated primary production from information amenable to remote sensing. Twelve algorithms, developed by 10 teams, were evaluated by comparing their ability to estimate depth-integrated daily production (IP, mg C m(-2)) at 89 stations in geographically diverse provinces. Algorithms were furnished information about the surface chlorophyll concentration, temperature, photosynthetic available radiation, latitude, longitude, and day of the year. Algorithm results were then compared with IP estimates derived from C-14 uptake measurements at the same stations. Estimates from the best-performing algorithms were generally within a factor of 2 of the C-14-derived estimates. Many algorithms had systematic biases that can possibly be eliminated by reparameterizing underlying relationships. The performance of the algorithms and degree of correlation with each other were independent of the algorithms' complexity.

A multiple scattering algorithm for atmospheric correction of satellite ocean colour observations is described. This algorithm, precisely designed for the MERIS instrument, globally assesses the combined contributions of aerosols and molecules to the multiple scattering regime. The approach was introduced in a previous work, where it was shown that, for a given aerosol, multiple scattering effects can be assessed through the relationship between the aerosol optical thickness and the relative increase in the path radiance that results from the progressive introduction of this aerosol within an aerosol-free atmosphere. Based on considerations about the accuracy to which the water-leaving radiances should be retrieved, the need to account for multiple scattering is argued. The principle of the algorithm is then presented, and tests and sensitivity studies (especially as regards aerosol type and vertical distribution) are performed to assess its performance in terms of errors on the retrieved water-leaving reflectances and pigment concentrations. The algorithm is able to perform the correction for atmospheres carrying several aerosol types, including absorbing ones, through their identification in the near-infrared, and through the detection of their absorption by means of appropriate assumptions on the marine signals at 510 and 705 nm.

Single and multiple scattering by molecules or by atmospheric aerosols only (homogeneous scattering), and heterogeneous scattering by aerosols and molecules, are recorded in Monte Carlo simulations. It is shown that heterogeneous scattering (1) always contributes significantly to the path reflectance (rho(path)), (2) is realized at the expense of homogeneous scattering, (3) decreases when aerosols are absorbing, and (4) introduces deviations in the spectral dependencies of reflectances compared with the Rayleigh exponent and the aerosol angstrom exponent. The ratio of rho(path) to the Rayleigh reflectance for an aerosol-free atmosphere is linearly related to the aerosol optical thickness. This result provides a basis for a new scheme for atmospheric correction of remotely sensed ocean color observations. (C) 1998 Optical Society of America.

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.

Use of ocean color satellite data in global biogeochemical studies requires models to predict primary production from the satellite-derived chlorophyll fields. In this paper, measured biooptical and photo-physiological data are used in place of standard (constant) parameters to adjust a previously published primary production model. In the JGOFS-France program, systematic studies were carried out at three locations in the tropical northeast Atlantic, selected to represent typical EUtrophic, MEsotrophic and oLIgotrophic regimes (EUMELI cruises). During cruise no. 4, these studies included the spectral measurements of the photosynthetically available radiation at sea level and within the water column, the determination of the algal absorption spectra and the determination of the physiological parameters derivable from P versus E experiments (photosynthesis-irradiance responses). The model predictions are compared with in situ determinations made by the C-14 technique (JGOFS core parameter). At the three sites, the physical structure (mixed layer and euphotic depths), the algal abundance and community structure, as well as their bio-optical and physiological properties, are very different, so that the predictive performance of the model was tested in trophic conditions that span most of those expected in the global open ocean. The model, when adjusted by entering the actual physiological parameters (chlorophyll-specific absorption of algae, maximum quantum yield, and light saturated carbon fixation rate), provides satisfying results compared to those observed in situ. The relative roles of the physiological parameters are analyzed and sensitivity studies are performed. For global applications, and in the absence of specific information when all seasons and provinces of the world ocean are considered, it will remain necessary for a while to rely on generic models and a selected standard set of physiological properties. The sensitivity studies here presented help in this choice, and a modified set of parameters is proposed and tested. With this set, reconstructed production profiles are close to those determined in the field, and the integrated values are retrieved with no bias and a reduced scatter (18% at one SD) for 17 stations (cruises 3 and 4) and daily production ranging from 0.3 to 2.3 gC m(-2). Copyright (C) 1996 Elsevier Science Ltd

A fast method has been proposed [Antoine and Morel, this issue] to compute the oceanic primary production from the upper ocean chlorophyll-like pigment concentration, as it can be routinely detected by a spaceborne ocean color sensor. This method is applied here to the monthly global maps of the photosynthetic pigments that were derived from the coastal zone color scanner (CZCS) data archive [Feldman et at., 1989]. The photosynthetically active radiation (PAR) field is computed from the astronomical constant and by using an atmospheric model, thereafter combined with averaged cloud information, derived from the International Satellite Cloud Climatology Project (ISCCP). The aim is to assess the seasonal evolution, as well as the spatial distribution of the photosynthetic carbon fixation within the world ocean and for a `'climatological year'', to the extent that both the chlorophyll information and the cloud coverage statistics actually are averages obtained over several years. The computed global annual production actually ranges between 36.5 and 45.6 Gt C yr(-1) according to the assumption which is made (0.8 or 1) about the ratio of active-to-total pigments (recall that chlorophyll and pheopigments are not radiometrically resolved by CZCS). The relative contributions to the global productivity of the various oceans and zonal belts are examined. By considering the hypotheses needed in such computations, the nature of the data used as inputs, and the results of the sensitivity studies, the global numbers have to be cautiously considered. Improving the reliability of the primary production estimates implies (1) new global data sets allowing a higher temporal resolution and a better coverage, (2) progress in the knowledge of physiological responses of phytoplankton and therefore refinements of the time and space dependent parameterizations of these responses.

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.

Solar radiation absorption and local heating within the upper layers of the open ocean are strongly in by the abundance of phytoplankton as depicted by the chlorophyll concentration. According to whether this concentration is high or low, the heat deposition occurs within a layer that may vary in thickness from less than 10 m to more than 100 m. A simple parameterization, accounting for this dependence, is developed. It allows the vertical profiles of heating rate to be predicted from the phytoplanktonic pigment concentration, as it can (and will) be remotely detected from space, by using ocean color sensors. This computationally efficient parameterization has been validated in reference to the results of a full spectral model. In the simplified computation, the solar spectrum is partitioned into two domains, below and above the wavelength 0.75 mum. For the infrared waveband, not influenced by biological materials, the irradiance profile is described by a single exponential function. For the ultraviolet and visible (<0.75 mum) band, a bimodal exponential form is adopted. The weights associated with each of these exponential functions, as well as their specific attenuation lengths, are dependent upon pigment concentration. These dependences are explicated through polynomial formulas. The remotely sensed pigment values can thus be readily introduced in numerical models of the mixed layer and of regional upper ocean dynamics or general circulation.