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Standard ocean color data products from the Medium Resolution Imaging Spectrometer (MERIS) are compared with equivalent regional products in European seas exhibiting different bio-optical properties: the northern Adriatic Sea, the Baltic Sea and the Western Black Sea (ADRS, BLTS and BLKS, respectively). Investigated quantities are: 1) the algal-2 pigment index, alg2; 2) the composite absorption coefficient of yellow substance and non-pigmented particles at 442 nm, adg; and 3) the concentration of the total suspended matter, TSM. Regional data products are created using ocean color inversion schemes based on MultiLayer Perceptron (MLP) neural nets trained with field measurements from the Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs. MLP input is the remote sensing reflectance RRS at MERIS center-wavelengths specifically selected for different water types in view of minimizing the perturbing effects of inaccurate atmospheric correction on the retrieval of regional data products. A new method is also proposed to define the applicability of regional MLPs to input RRS. Results indicate that MERIS alg2 values tend to overestimate the equivalent quantity computed with MLP regional algorithms. The agreement between MERIS and regional TSM data products is significantly better than that reported for alg2 and adg, especially for BLKS. Findings highlight the relevance of using regional inversion schemes to evaluate standard products over extended oceanographic regions as a complement to the analysis of match-ups between marine products measured in situ and derived from space-born data.

Multilayer perceptron (MLP) neural networks for regional satellite ocean color applications have been developed and assessed using in situ data from various European seas. Considered MLP products are chlorophyll a concentration ( Chl–a ), absorption by yellow substance at 412 nm ( a ys (412)) and concentration of total suspended matter (TSM), all determined from spectral remote sensing reflectance R RS . Investigated oceanographic regions comprise the Eastern Mediterranean Sea, the northern Adriatic Sea, the Western Black Sea and the Baltic Sea. The in situ measurements applied in the study were produced within the framework of the Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical Mapping of Marine Properties (BiOMaP) programs contributing to a unique dataset that represents different water types including chlorophyll a , yellow substance and sediment dominated waters. Performance analysis of the proposed regional MLPs indicates that Chl–a can be quantified with the highest accuracy in the Eastern Mediterranean Sea (with absolute percent difference of 14% with respect to in situ measurements). In the case of a ys (412), the most accurate determination is observed for the Baltic Sea waters (13%). Instead, TSM retrieval is the most accurate in the Black Sea (14%). The study demonstrated the limited generalization capability of regional algorithms. Within this context, saturation of MLP output occurring with input data not statistically represented in the training set has been investigated through cross-basin product analysis in view of proposing a practical solution to the problem.

The assessment of uncertainties and biases affecting remote sensing products is a pre-condition for an effective exploitation of these data in climate studies. Within such a context, this work presents and discusses the intra-annual variations of biases in primary satellite ocean color products (i.e., normalized water-leaving radiance and aerosol optical thickness) at a coastal site in the northern Adriatic Sea for the period 2002–2010. The analysis is performed using in situ data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) and satellite data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS-A and MODIS-T) onboard the Aqua and Terra platforms. Results indicate biases in the normalized water leaving radiance significantly increasing with the sun zenith angle and, to a lesser extent, also affected by variations in chlorophyll concentration and aerosol optical thickness.

Abundance and carbon biomass of different phytoplankton groups obtained by microscopy were compared with taxonomy derived from pigment measurements and CHEMTAX analysis of samples collected in June 2006 in the NW Black Sea. The diatom Chaetoceros curvisetus was dominant in terms of carbon biomass based on cell volume at inshore stations, while the coccolithophore Emiliania huxleyi was prevalent at offshore. Emiliania huxleyi reached bloom abundance of 3.3 × 106 cells L− 1. The chlorophyll a (chl a) concentration within phytoplankton groups as allocated by CHEMTAX was in agreement with microscopy derived carbon biomasses of the taxonomic groups diatoms, dinoflagellates and cryptophytes only. Carbon biomass of less abundant phytoplankton taxa (cyanophytes, euglenophytes and chlorophytes) did not correlate with group-specific chl a. It was not possible to detect E. huxleyi bloom by CHEMTAX analysis probably due to much higher biomass of other species containing 19’-hexanoyloxyfucoxanthin. Nutrient concentrations were generally high in the waters where diatom and dinoflagellates dominated the community but low in the area of E. huxleyi bloom. A good correlation between total carbon biomass of phytoplankton and chl a was found and the estimated C:chl a ratio of phytoplankton varied between 36 and 256 (in average 124 ± 50).

Advanced remote sensing techniques and regional algorithms are combined to produce and analyze a 12-year multi-sensor time series of bio-optical properties for the Adriatic Sea. First, a multi-sensor series of normalized water-leaving radiance LWN is created with an optically-based merging technique applied to SeaWiFS and MODIS data, then distributions of inherent optical properties (IOPs) are obtained with a semi-analytical bio-optical model. Additionally, Chla is computed by two regional empirical algorithms associated with two classes of optical properties representative of open ocean waters and Adriatic coastal regions (Classes 1 and 2, respectively). The domain of applicability of each algorithm is dynamically determined on the basis of the LWN input spectrum by a novelty detection approach. The various satellite products are validated using a comprehensive bio-optical time series collected in the northern Adriatic. At the basin level, the frequency of occurrence of Classes 1 and 2 are 61% and 10%, respectively, with Class 2 waters particularly located in the northern part and characterized by higher levels of Chla and IOPs. The annual cycle of Chla over the 12-year period exhibits significant variations in amplitude and phase; moreover, the annual cycle shows a reduced amplitude during a period centered on 2004 for a time interval that varies with the region. In the northern Adriatic, the overall level of Chla appears lower between 2003 and 2008 compared to the beginning of the series.

The development and assessment of satellite ocean color products require quality assured in situ data representative of the variety of bio-optical regimes encountered in the different seas. The measurement program named Bio-Optical mapping of Marine Properties (BiOMaP) fulfills this requirement by using identical instruments and applying cross-site consistent methods for the characterization of seawater inherent and apparent optical properties in the various European seas. This work introduces the BiOMaP radiometric data and describes their application to the validation of primary ocean color products. Within this framework, the radiometric data are discussed through the spectral shape and amplitude of normalized water-leaving radiances ( L WN ). Specifically, the spectral shape is expressed through the Principal Component Analysis of L WN (λ)/ L WN (555) while the amplitude is represented by L WN (555). The resulting distribution of BiOMaP data in a three dimensional feature space demonstrates a continuity of cases across the investigated marine regions confirming a wide representativity of bio-optical regimes. The application of BiOMaP data to the validation of remote sensing reflectance from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), indicates improved performance of the SeaWiFS Data Analysis System (SeaDAS, version 6.1) atmospheric correction. In particular, the comparison of satellite and in situ matchups in the blue spectral region shows biases of a few percent with respect to the much larger reported in studies relying on earlier SeaDAS versions. Matchup analyses, restricted to the Eastern Mediterranean, Black and Baltic Seas, indicate marked regional differences likely explained by the diversity of water and aerosol types.

article i nfo The study presents and discusses the application of in situ data from the ocean color component of the Aerosol Robotic Network (AERONET-OC) to assess primary remote sensing products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the AQUA platform and from the Sea-viewing Wide- Field-of-view Sensor (SeaWiFS) on the OrbView-2 spacecraft. Three AERONET-OC European coastal sites exhibiting different atmospheric and marine optical properties were considered for the study: the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea representing Case-1 and Case-2 moderately sediment dominated waters; and, the Gustaf Dalen Lighthouse Tower (GDLT) in the northern Baltic Proper and the Helsinki Lighthouse Tower (HLT) in the Gulf of Finland, both characterized by Case-2 waters dominated by colored dissolved organic matter (CDOM). The analysis of MODIS derived normalized water- leaving radiance at 551 nm, LWN(551), has shown relatively good results for all sites with uncertainties of the order of 10% and biases ranging from − 1t o−4%. Larger uncertainty and bias have been observed at 443 nm for the AAOT (i.e., 18 and −7%, respectively). At the same center wavelength, results for GDLT and HLT have exhibited much larger uncertainties (i.e., 56 and 67%, respectively) and biases (i.e., 18 and 25%, respectively), which undermine the possibility of presently using remote sensing LWN data at the blue center wavelengths for bio-optical investigations in the Baltic Sea. An evaluation of satellite derived aerosol optical thickness, τa, has shown uncertainties and biases of the order of tens of percent increasing with wavelength at all sites. Specifically, MODIS derived τa at 869 nm has shown an overestimate of 71% at the AAOT, 101% at GDLT and 91% at HLT, respectively. This result highlights the effects of a limited number of aerosol models for the atmospheric correction process, and might also indicate the need of applying a vicarious calibration factor to the remote sensing data at the 869 nm center wavelength to remove the effects of uncertainties in the atmospheric optical model and the space sensor radiometric calibration. Similar results have been obtained from the analysis of SeaWiFS data. Finally, in view of illustrating the possibility of increasing the accuracy of satellite regional radiometric products, AERONET-OC data have been applied to reduce systematic errors in MODIS and Medium Resolution Imaging Spectrometer (MERIS) LWN data likely due to the atmospheric correction process. Results relying on MODIS match-ups for the Baltic Sites (i.e., GDLT and HLT) and MERIS matchups for the AAOT, have indicated a substantial reduction of both uncertainty and bias in the blue and red center wavelengths.

A comprehensive set of bio-optical measurements collected at the Acqua Alta Oceanographic Tower site in the northern Adriatic Sea is used to assess satellite derived optical properties and concentrations of optically significant constituents. These include normalized water leaving radiance spectra LWN, absorption spectra due to phytoplankton, non-pigmented particles and chromophoric dissolved organic matter, back-scattering spectra, concentrations of chlorophyll a, Chla, and total suspended matter, TSM, and diffuse attenuation coefficients, Kd, obtained with a diverse set of algorithms. A total of 81 and 21 match-ups are found for SeaWiFS and MODIS LWN, respectively. For both sensor products, the match-ups show mean absolute percentage differences of approximately 30% at 412 nm, 20% at 443 nm, and 14% from 490 to 555 nm. Some dependence of these differences has been found with respect to the aerosol optical thickness and the single scattering albedo associated with the in-water constituents. However, the performance of the atmospheric correction scheme appears relatively robust with respect to angular and environmental conditions. The different Chla products generally show quite large uncertainties whereas a TSM product shows encouraging results. Three algorithms produce Kd (490) with a RMS uncertainty of 0.13 for log-transformed data. The comparison between in situ data and satellite derived absorption values yields varying levels of uncertainties for the three bio-optical algorithms considered here and for the different wavelengths. Preliminary improvements could be reached by reducing biases affecting the total absorption coefficient at various wavelengths. Another general result is that the bio-optical models are able to represent a larger part of the observed variability for phytoplankton absorption than for the absorption by dissolved and non-pigmented particulate matter. The assumed spectral shape of the latter absorption term appears logically as a strong determinant of the partition of the total absorption. The three sets of satellite derived back-scattering spectra compare favorably with in situ optical measurements, with mean RMS differences between 0.12 and 0.18. Importantly, the uncertainties obtained here for satellite match-ups of absorption coefficients are comparable to published estimates of the inherent uncertainties associated with the bio-optical algorithms.

The knowledge of the absorption and scattering characteristics of the ocean supports diverse applications for studying biological and physical processes of marine ecosystems. The determination of the related inherent optical properties from remote sensing is addressed for a site located in the northern Adriatic Sea using coincident SeaWiFS images and field measurements. The proposed methodology first combines regional algorithms to determine the spectra of irradiance reflectance and diffuse attenuation coefficient from the normalized water leaving radiance by accounting for the bidirectional structure of the light field. These spectra are then used as inputs to an inverse model that yields the absorption, scattering, and backscattering coefficients of seawater (considered without the contribution of pure water). The uncertainties associated with the different steps in the sequence of calculations are quantified and discussed. Specifically, the analysis of 48 match-ups comparing in situ irradiance reflectance with that derived from remote sensing water leaving radiance shows mean absolute differences below 20% between 490 and 555 nm and approximately 30% at 443 and 670 nm. Lower discrepancies are obtained if more stringent criteria for the selection of match-ups are implemented (12–15% and 20–22%, respectively). The results obtained with 42 match-ups show a reasonable agreement for the absorption coefficient from 412 to 490 nm (approximately 35%), the scattering coefficient from 443 to 555 nm (approximately 30%), and the attenuation coefficient in the spectral range 412–555 nm (approximately 30%). Based on 17 match-ups, the comparison for the backscattering coefficient gives mean absolute differences in the range of 31–53%. The comparison between field and derived scattering properties suggests that the particulate scattering phase function inherent to the inverse model is not appropriate for the site considered. Finally, in the framework of the selected inversion scheme, uncertainties associated with the satellite derived irradiance reflectance in the blue and the determination of K d at 490 nm through an empirical band ratio algorithm appear as the elements where improvements would be particularly needed to derive high quality spectra of inherent optical properties.