Phytoplankton are key components of ocean ecosystems that play a critical role in regulating Earth's climate. However, how climate‐driven changes in light availability in the ocean will affect marine phytoplankton remains poorly understood. Here, we assess the impact of climate‐induced shifts in the spectral quality of the underwater light field on the relative fitness of phytoplankton with distinct pigment traits using a global ecosystem model. We focus on Synechococcus pigment types, comparing light color specialists with a chromatic acclimator capable of adjusting its pigment composition. Under a high‐emission scenario, the model simulation projected an increase in the average blue‐to‐green ratio across 76% of the ocean area by the end of the 21st century, while 24% of the simulated ocean showed a shift toward greener wavelengths. Regions characterized by larger seasonal variability in blue‐to‐green ratio values appeared to be reduced due to climate‐driven spectral changes. We find that reduced variability in the ocean light field makes the chromatic acclimators' plasticity less advantageous, and this pigment type was most negatively affected. These findings highlight the potential of Synechococcus pigment types as functional bioindicators of ecosystem change and underscore the importance of incorporating functional diversity in global models to better predict phytoplankton responses to changing ocean conditions.

<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 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 .

Marine photoautotrophs have evolved to exploit the ocean’s variable light conditions, with chromatic acclimators being able to adjust their pigment content to better match the ambient light color. The impact of chromatic acclimation on phytoplankton distribution and competition is not well understood despite its global importance. This study explores chromatic acclimation’s role in shaping the biogeography of Synechococcus , a widespread cyanobacterium. We integrated three pigment types into a global ecosystem model: a green-light specialist, a blue-light specialist, and a chromatic acclimator. Laboratory studies defined each type’s specific absorption properties. Our results indicate that chromatic acclimation offers an evolutionary advantage by enabling Synechococcus to adapt to varying light environments. This ability to mimic blue- and green-light specialists and enhance absorption at intermediate states, particularly in areas with high seasonal light variations, increases Synechococcus distribution and biomass. Thus, chromatic acclimation affects ecosystem functioning and biogeochemical processes in the ocean.

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.

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.

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.

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.

Influence of the phytoplankton community composition on the in situ fluorescence signal: Implication for an improved estimation of the chlorophyll-a concentration from BiogeoChemical-Argo profiling floats.

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.

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).

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.

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.

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.

We present the results from Verification of Reference Irradiance and Radiance Sources Laboratory Calibration Experiment Campaign. Ten international laboratories took part in the measurements. The spectral irradiance comparison included the measurements of the 1000 W tungsten halogen filament lamps in the spectral range of 350 nm–900 nm in the pilot laboratory. The radiance comparison took a form of round robin where each participant in turn received two transfer radiometers and did the radiance calibration in their own laboratory. The transfer radiometers have seven spectral bands covering the wavelength range from 400 nm–700 nm. The irradiance comparison results showed an agreement between all lamps within ±1.5%. The radiance comparison results presented higher than expected discrepancies at the level of ±4%. Additional investigation to determine the causes for these discrepancies identified them as a combination of the size-of-source effect and instrument effective field of view that affected some of the results.

Particulate optical backscattering (b bp) is a crucial parameter for the study of ocean biology and oceanic carbon estimations. In this work, b bp retrieval, by the quasi-analytical algorithm (QAA), is assessed using a large in situ database of matched b bp and remote-sensing reflectance (R rs). The QAA is also applied to satellite R rs (ESA OC-CCI project) as well, after their validation against in situ R rs. Additionally, the effect of Raman Scattering on QAA retrievals is studied. Results show negligible biases above random noise when QAA-derived b bp is compared to in situ b bp. In addition, R rs from the CCI archive shows good agreement with in situ data. The QAA's functional form of spectral backscattering slope, as derived from in situ radiometry, is validated. Finally, we show the importance of correcting for Raman Scattering over clear waters prior to semi-analytical retrieval. Overall, this work demonstrates the high efficiency of QAA in the b bp detection in case of both in situ and ocean color data, but it also highlights the necessity to increase the number of observations that are severely under-sampled in respect to others environmental parameters.

A field intercomparison was conducted at the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea, from 9 to 19 July 2018 to assess differences in the accuracy of in- and above-water radiometer measurements used for the validation of ocean colour products. Ten measurement systems were compared. Prior to the intercomparison, the absolute radiometric calibration of all sensors was carried out using the same standards and methods at the same reference laboratory. Measurements were performed under clear sky conditions, relatively low sun zenith angles, moderately low sea state and on the same deployment platform and frame (except in-water systems). The weighted average of five above-water measurements was used as baseline reference for comparisons. For downwelling irradiance ( E d ), there was generally good agreement between sensors with differences of <6% for most of the sensors over the spectral range 400 nm–665 nm. One sensor exhibited a systematic bias, of up to 11%, due to poor cosine response. For sky radiance ( L s k y ) the spectrally averaged difference between optical systems was <2.5% with a root mean square error (RMS) <0.01 mWm−2 nm−1 sr−1. For total above-water upwelling radiance ( L t ), the difference was <3.5% with an RMS <0.009 mWm−2 nm−1 sr−1. For remote-sensing reflectance ( R r s ), the differences between above-water TriOS RAMSES were <3.5% and <2.5% at 443 and 560 nm, respectively, and were <7.5% for some systems at 665 nm. Seabird-Hyperspectral Surface Acquisition System (HyperSAS) sensors were on average within 3.5% at 443 nm, 1% at 560 nm, and 3% at 665 nm. The differences between the weighted mean of the above-water and in-water systems was <15.8% across visible bands. A sensitivity analysis showed that E d accounted for the largest fraction of the variance in R r s , which suggests that minimizing the errors arising from this measurement is the most important variable in reducing the inter-group differences in R r s . The differences may also be due, in part, to using five of the above-water systems as a reference. To avoid this, in situ normalized water-leaving radiance ( L w n ) was therefore compared to AERONET-OC SeaPRiSM L w n as an alternative reference measurement. For the TriOS-RAMSES and Seabird-HyperSAS sensors the differences were similar across the visible spectra with 4.7% and 4.9%, respectively. The difference between SeaPRiSM L w n and two in-water systems at blue, green and red bands was 11.8%. This was partly due to temporal and spatial differences in sampling between the in-water and above-water systems and possibly due to uncertainties in instrument self-shading for one of the in-water measurements.

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 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.

Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of "regression method" (i.e., either type-I or type-II) to derive bio-optical relationships, both from theoretical perspectives and by using specific examples. We have applied usual regression methods to an in situ data set of particulate organic carbon (POC), total chlorophyll-a (TChla), optical particulate backscattering coefficient (b bp), and 19 years of monthly TChla and b bp ocean colour data. Results of the regression analysis have been used to calculate phytoplankton carbon biomass (C phyto) and POC from: i) BGC-Argo float observations; ii) oceanographic cruises, and iii) satellite data. These applications enable highlighting the differences in C phyto and POC estimates relative to the choice of the method. An analysis of the statistical properties of the dataset and a detailed description of the hypothesis of the work drive the selection of the linear regression method.

Fixed point observatories in the northwestern Mediterranean Sea have a major contribution in monitoring physical and biogeochemical variables in the region. The capability of recording long-term, high quality time-series, using smart sensors, upgrades scientific knowledge regarding sea processes sensitive to climate change. Existing open sea multi-parametric moorings are located in the key areas where dynamic processes (e.g. convection, ventilation) and bio-regions (from high bloom to intermittent regimes) drive biogeochemical content that are essential to the carbon pump and the marine ecosystem (nutrients, oxygen, pH, pCO2). For the last 5 years, new biogeochemical sensors (O2, pCO2 and pH) have been integrated in the open sea fixed moorings (ERIC EMSO and others), on gliders and Argo floats (MOOSE network) in this region to deliver integrated data relevant for marine environmental studies and monitoring services. We will present here the last biogeochemical O2, pCO2 and pH time series that could be used to derive the net air-sea CO2 flux and to estimate the acidification trend in the northwestern Mediterranean Sea, a crucial region for ventilation and anthropogenic CO2 invasion.

Sentinel-2 and Landsat data products when combined open opportunities for capturing the dynamics of nearshore coastal and inland waters at rates that have never been possible before. Recognizing the differences in their spectral and spatial sampling, to generate a seamless data record for global water quality monitoring, it is critical to quantify how well the derived data products agree under various atmospheric and aquatic conditions. This study provides an extensive quantitative assessment of how Landsat-8 and Sentinel-2A/B equivalent data products compare and discusses implications on differences in downstream products generated via the SeaWiFS Data Analysis System (SeaDAS). These products include the top-of-atmosphere (TOA) reflectance (ρ t), the remote-sensing reflectance (R rs), as well as biogeochemical properties, such as the total suspended solids (TSS). The analyses are conducted a) for Landsat-8 and Sentinel-2A/B near-simultaneous nadir overpasses (n-SNO) and b) over several highly turbid/eutrophic inland/nearshore waters. Following the implementation of vicarious gains for Sentinel-2A, the n-SNO analyses indicated that Landsat-8 and Sentinel-2A agree within ± 1% in ρ t and ± 5% in R rs products across the visible and near-infrared (NIR) bands. Similar evaluations with preliminary vicarious gains for Sentinel-2B showed ± 2% in ρ t and ± 7% in R rs products. Considering Landsat-8-derived R rs products as a reference, we found < 5% difference in Sentinel-2A and-2B R rs products. Analyses of combined TSS and R rs time-series products over several aquatic systems further corroborated these results and demonstrated the remarkable value of combined products. Occasional negative retrievals of R rs products over hypereutrophic and highly turbid waters suggest the need for improvements in the atmospheric correction procedure to empower science/application community to fully explore Landsat-Sentinel-2 products. With very similar absolute radiometric observations and products, the science community should consider developments of suitable biogeochemical algorithms to maximize the utility of merged Landsat-Sentinel-2 products.

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.

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

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.

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.

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.

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.

An array of Bio-Argo floats equipped with radiometric sensors has been recently deployed in various open ocean areas representative of the diversity of trophic and bio-optical conditions prevailing in the so-called case 1 waters. Around solar noon and almost every day, each float acquires 0-250-m vertical profiles of photosynthetically available radiation and downward irradiance at three wavelengths (380, 412, and 490 nm). Up until now, more than 6500 profiles for each radiometric channel have been acquired. As these radiometric data are collected out of an operator's control and regardless of meteorological conditions, specific and automatic data processing protocols have to be developed. This paper presents a data quality-control procedure aimed at verifying profile shapes and providing near-real-time data distribution. This procedure is specifically developed to 1) identify main issues of measurements (i.e., dark signal, atmospheric clouds, spikes, and wavefocusing occurrences) and 2) validate the final data with a hierarchy of tests to ensure a scientific utilization. The procedure, adapted to each of the four radiometric channels, is designed to flag each profile in a way compliant with the data management procedure used by the Argo program. Main perturbations in the light field are identified by the new protocols with good performances over the whole dataset. This highlights its potential applicability at the global scale. Finally, the comparison with modeled surface irradiances allows for assessing the accuracy of quality-controlled measured irradiance values and identifying any possible evolution over the float lifetime due to biofouling and instrumental drift.

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.

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.

Strong tidal currents, shallow water and numerous freshwater inputs characterize the coastal waters of the eastern English Channel. These case 2 waters were investigated through an intensive sampling effort in 2000 aiming to study the distribution and variability of the Chromophoric Dissolved Organic Matter (CDOM), Non-Algal Particles (NAP) and phytoplankton absorption at the mesoscale. Four cruises were carried out in February, March, May and July and more than 80 stations each cruise were sampled for hydrographical, chemical and bio-optical analyses. Results showed two distinct situations, the winter period characterized by the strong dominance of CDOM absorption over the particulate matter, and the spring-summer period when phytoplankton and CDOM represented the same contribution. Meteorology was the main factor driving the bio-optical properties of the water column in winter whereas in spring-summer the biological activity seemed to be the more active driving force. The algal community composition in term of dominant cell size and, therefore pigment packaging, is the main factor driving the phytoplankton specific absorption in the water column. Photoprotective pigments did not significantly influence algal absorption, due to turbid and highly mixed water masses. This feature also explained the bio-optical homogeneity found along the water column. On the mesoscale, distinct bio-optical provinces were defined in relation with the observed bio-hydrographical variability.