The primary ocean color product is the spectrum of remote sensing reflectance R RS that allows the quantification of in-water optically significant constituents and all ocean color applications. The determination of its uncertainties is thus key to the creation of comprehensive uncertainty budgets for all derived ocean color products. The assessment of satellite R RS uncertainties has largely relied on corresponding field measurements but this process is solid only if these field measurements are in turn fully characterized. Uncertainty budgets have therefore been defined and reported for the radiometric measurements collected in the framework of the Ocean Color component of the Aerosol Robotic Network (AERONET-OC). The contemporaneous deployment of two autonomous systems for 5.5 years on the Acqua Alta Oceanographic Tower (AAOT) located in the northern Adriatic Sea led to the collection of 4,449 pairs of coincident observations (collected with a time difference lower than 10 min) distributed over 659 days of data acquisitions that can be used to verify reported uncertainty values. The comparison of matched pairs showed a good agreement for R RS (with differences of typically 2%–3% between 412 and 560 nm), as well as for the aerosol optical thickness τ a (3%–6%). Differences between data from the two systems appear generally consistent with their stated uncertainties, indicating that they are metrologically compatible and that uncertainties reported for AERONET-OC data are usually trustworthy (with possible exceptions depending on the level of error correlation between measurements from the two systems). Using uncertainty cone diagrams, this result holds across the range of uncertainty values with few exceptions. Independent uncertainty estimates associated with non-systematic error contributions were obtained using a collocation framework allowing for error correlation between measurements from the two systems. The resulting uncertainties appeared comparable with the reported values for τ a and R RS . The related mathematical development also showed that the centered root-mean-square difference between data collected by two systems is a conservative estimate of the uncertainty associated with these data (excluding systematic contributions) if these data show a good agreement (expressed by a slope of method II regression close to 1) and if their uncertainties can be assumed similar with errors moderately correlated (typically lower than 0.5).
Among the many calcifying marine organisms, coccolithophores are the major producer of particulate inorganic carbon (PIC). Calcium carbonate plates covering coccolithophores, called coccoliths and released during blooms, are responsible for a large increase of the water reflectance. Aiming at investigating the spectral features of the remote sensing reflectance RRS(λ) of marine waters during coccolithophore blooms, this study exploits the radiometric data of Ocean Color sites of the Aerosol Robotic Network (AERONET-OC) in the Western Black Sea (Galata and Gloria/Section-7) by focusing on bloom events that occurred in 2017 and 2020. The analysis, besides showing elevated RRS(λ) in the blue-green spectral region in the presence of coccoliths, confirms a shift toward the blue of the RRS(λ) spectra as the bloom declines and coccoliths accumulate at the surface. Results also document a decreased capability of determining the bloom state in the presence of optically complex waters such as those associated with river runoff. Finally, the comparison of satellite versus AERONET-OC radiometric data for the extreme conditions created by the presence of coccolithophores, indicates agreements between RRS(λ) not significantly different from those previously determined for various satellite data products in the absence of appreciable concentrations of coccoliths.
Abstract. The extending record of ocean colour derived information, an important asset for the study of marine ecosystems and biogeochemistry, presently relies on individual satellite missions launched by several space agencies with differences in sensor design, calibration strategies and algorithms. In this study we present an extensive comparative analysis of standard products obtained from operational global ocean colour sensors (SeaWiFS, MERIS, MODIS-Aqua, MODIS-Terra), on both global and regional scales. The analysis is based on monthly mean chlorophyll-a (Chl-a) surface concentration between 2002 and 2009. Based on global statistics, the Chl-a records appear relatively consistent. The root mean square (RMS) difference Δ between (log-transformed) Chl-a from SeaWiFS and MODIS Aqua amounts to 0.137, with a bias of 0.074 (SeaWiFS Chl-a higher). The difference between these two products and MERIS Chl-a is approximately 0.15. Restricting the analysis to 2007 only, Δ between MODIS Aqua and Terra is 0.142. This global convergence is significantly modulated regionally. Statistics for biogeographic provinces representing a partition of the global ocean, show Δ values varying between 0.08 and 0.3. High latitude regions, as well as coastal and shelf provinces are generally the areas with the largest differences. Moreover, RMS differences and biases are modulated in time, with a coefficient of variation of Δ varying between 10% and 40%, with clear seasonal patterns in some provinces. The comparison of the province-averaged time series obtained from the various satellite products also shows a level of agreement that is geographically variable. Overall, the Chl-a SeaWiFS and MODIS Aqua series appear to have similar levels of variance and display high correlation coefficients, an agreement likely favoured by the common elements shared by the two missions. These results are degraded if the MERIS series is compared to either SeaWiFS or MODIS Aqua. An important outcome of the study is that the results of the inter-comparison analysis are variable with time and location, and therefore globally averaged statistics are not necessarily applicable on a seasonal or regional basis.
La teledetection optique est un outil precieux pour l'etude des ecosystemes marins. L'utilisation quantitative des series temporelles obtenues et la coherence de series issues de capteurs differents sont conditionnees par un necessaire travail de validation, des produits primaires radiometriques jusqu'aux elaborations en termes de stocks et taux biologiques. Les sorties d'un code de restitution des effets atmospheriques, utilisant les donnees SeaWiFS pour la determination des proprietes optiques de la surface marine, sont analysees avec des mesures coincidentes recueillies a un site en Adriatique Nord. Les resultats sont mis en perspective avec ceux obtenus avec un code independant et d'autres capteurs (MODIS et MERIS). L'analyse est completee par la comparaison des caracteristiques d'aerosols prevues par le code avec les mesures provenant d'un reseau d'instruments. Une application des produits satellitaux de biomasse, combines avec une distribution spectrale de l'eclairement solaire a la surface, est l'estimation de la production primaire de l'ocean global. Le code de calcul de la production primaire inclut la modelisation de la propagation spectrale de la lumiere dans la colonne d'eau et son utilisation par le phytoplancton par l'intermediaire d'une relation photosynthese-lumiere. Les parametres de celle-ci ainsi que la structure verticale de la colonne d'eau sont definis par saison et par province biogeochimique. La comparaison avec les sorties de deux autres modeles de production primaire de reference fournit une premiere indication des incertitudes liees a ce genre d'estimations: un relatif accord en bilans globaux cache de fortes disparites spatio-temporelles. Une comparaison des sorties des modeles avec des mesures caracteristiques de divers sites permet de discuter certaines des sources d'incertitude.
Abstract. The accuracy of primary satellite ocean color data products from the Moderate Resolution Imaging Spectroradiometer on-board Aqua (MODIS-A) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) is investigated in the Western Black Sea using in situ measurements from the Gloria site included in the ocean color component of the Aerosol Robotic Network (AERONET-OC). The analysis is also extended to an additional well-established AERONET-OC site in the northern Adriatic Sea characterized by optically complex coastal waters exhibiting similarities to those observed at the Gloria site. Results from the comparison of normalized water-leaving radiance LWN indicate biases of a few percent between satellite-derived and in situ data at the center wavelengths relevant for the determination of chlorophyll a concentrations (443–547 nm, or equivalent). Remarkable is the consistency between the annual cycle determined with time series of satellite-derived and in situ LWN ratios at these center wavelengths. Contrarily, the differences between in situ and satellite-derived LWN are pronounced at the blue (i.e., 412 nm) and red (i.e., 667 nm, or equivalent) center wavelengths, confirming difficulties in confidently applying satellite-derived radiometric data from these spectral regions for quantitative analysis in optically complex waters.
Atmospheric correction (AC) algorithms for ocean color (OC) data processing usually rely on ancillary data documenting the atmosphere and the sea state to help the calculation of the remote sensing reflectance $R_{\text {RS}}$ from the radiance measured by a space sensor. This study aims at assessing the impact that the uncertainties associated with these ancillary data have on the AC outputs. For this objective, a full year of global Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery is processed with the standard AC algorithm l2gen of the National Aeronautics and Space Administration with different sets of ancillary data, the reference case with National Centers for Environmental Prediction (NCEP) Reanalysis-2 meteorological data and satellite ozone products, as well as with ten ensemble members from the European Centre for Medium-Range Weather Forecast (ECMWF) CERA-20C data. The spread within the ensemble data and the differences with respect to the reference case are taken as a measure of the uncertainties associated with ancillary data. The impact on $R_{\text {RS}}$ of perturbations in ancillary variables vary in space, the variables having the largest effects being wind speed and relative humidity, and ozone at bands where ozone absorption is largest, while sea-level pressure and precipitable water have the smallest effect. Sensitivity coefficients quantifying the relationship between perturbations in ancillary variables and effects on $R_{\text {RS}}$ change with variable and wavelength. At the global scale, the variations found on $R_{\text {RS}}$ when ancillary data are perturbed are usually small but not negligible and should be considered in the ocean color (OC) data uncertainty budget.
An evaluation of the accuracy of atmospheric and marine satellite-derived products is presented and discussed for the northern Adriatic Sea coastal region using match-ups of in situ and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) data for the period September 1997-September 2001. The study, making use of a simple atmospheric correction scheme including a near-infrared (NIR) turbid-water correction, has shown mean relative percentage differences between in situ and satellite-derived aerosol optical thickness lower than 23% in the spectral range between 443 and 865 nm. By applying regional empirical bio-optical algorithms for chlorophyll a concentration (Chla), total suspended matter concentration (TSM), and diffuse attenuation coefficient at 490 nm (K/sub d/(490)), match-ups analysis has shown mean relative percentage differences of 40% for Chla, 28% for TSM, and 30% for K/sub d/(490). The analysis is supported by comparison of in situ and satellite-derived normalized water leaving radiances to highlight the importance of the NIR turbid-water correction and to discuss the intrinsic uncertainties due to the use of empirical algorithms.
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