Frédéric Mélin

AERONET-OC: a Network for the Validation of Ocean Color Primary Products

Abstract The ocean color component of the Aerosol Robotic Network (AERONET-OC) has been implemented to support long-term satellite ocean color investigations through cross-site consistent and accurate measurements collected by autonomous radiometer systems deployed on offshore fixed platforms. The AERONET-OC data products are the normalized water-leaving radiances determined at various center wavelengths in the visible and near-infrared spectral regions. These data complement atmospheric AERONET aerosol products, such as optical thickness, size distribution, single scattering albedo, and phase function. This work describes in detail this new AERONET component and its specific elements including measurement method, instrument calibration, processing scheme, quality assurance, uncertainties, data archive, and products accessibility. Additionally, the atmospheric and bio-optical features of the sites currently included in AERONET-OC are briefly summarized. After illustrating the application of AERONET-OC dat...

Generalized ocean color inversion model for retrieving marine inherent optical properties

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.

An autonomous above-water system for the validation of ocean color radiance data

An operational system for autonomous above-water radiance measurements, called the SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM), was deployed at the Acqua Alta Oceanographic Tower in the northern Adriatic Sea and used for the validation of remote sensing radiometric products in coastal waters. The SeaPRISM data were compared with simultaneous data collected from an independent in-water system for a wide variety of sun elevations along with different atmospheric, seawater, and sea state conditions. The average absolute differences between the above- and in-water determinations of water-leaving radiances (computed linearly) were less than 4.5% in the 412-555-nm spectral interval. A similar comparison for normalized water-leaving radiances showed average absolute differences less than 5.1%. The comparison between normalized water-leaving radiances computed from remote sensing and SeaPRISM matchup data, showed absolute spectral average (linear) differences of 17.0%, 22.1%, and 20.8% for SeaWiFS, MODIS, and MERIS, respectively. The results, in keeping with those produced by independent in-water systems, suggest the feasibility of operational coastal networks of autonomous above-water radiometers deployed on fixed platforms (towers, lighthouses, navigation aids, etc.) to support ocean color validation activities.

A network for standardized ocean color validation measurements

The Aerosol Robotic Network (AERONET), originally developed to evaluate aerosol optical properties and validate satellite retrievals of those properties at various scales with measurements from worldwidedistributed autonomous Sun photometers [Holben et al., 1998],since January 2006 has been extended to support marine remote sensing and monitoring applications. This new network component, called AERONETOcean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea—the ‘water-leaving radiance’—with modified Sun photometers installed on offshore platforms such as lighthouses, oceanographic towers, and derricks. AERONET-OC is proving to be instrumental in supporting satellite ocean color validation activities through standardized measurements performed at different sites with identical measuring systems and protocols, calibrated using a single reference source and method, and processed with the same code. Recent investigations [Zibordi et al., 2006] suggest that in order to generate accurate climate data records from remote sensing data, time series of in situ measurements from a cadre of AERONET-OC sites could play a major role in the assessment and merging of radiometric products from different ocean color missions.

Use of the novelty detection technique to identify the range of applicability of empirical ocean color algorithms

Novelty detection is used to identify the range of applicability of empirical ocean color algorithms. This method is based on the assumption that the level of accuracy of the algorithm output depends on the representativeness of inputs in the training dataset. The effectiveness of the novelty detection method is assessed using two datasets: one representative of the northern Adriatic Sea coastal waters and the other representative of open sea waters. The two datasets are independently used to develop neural network algorithms for the retrieval of chlorophyll-a concentration (Chl-a). The range of applicability of the individual algorithms is presented using remote sensing data derived from the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) for three selected regions: the central Mediterranean Sea, the North Sea, and the Baltic Sea. An extension of the novelty detection technique is also proposed to blend the individual algorithms and to avoid discontinuities in the resulting Chl-a maps.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

Abstract 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.

Assessment of SeaWiFS atmospheric and marine products for the northern Adriatic Sea

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.

Optically based technique for producing merged spectra of water-leaving radiances from ocean color remote sensing

An optically based technique is presented that produces merged spectra of normalized water-leaving radiances L(WN) by combining spectral data provided by independent satellite ocean color missions. The assessment of the merging technique is based on a four-year field data series collected by an autonomous above-water radiometer located on the Acqua Alta Oceanographic Tower in the Adriatic Sea. The uncertainties associated with the merged L(WN) obtained from the Sea-viewing Wide Field-of-view Sensor and the Moderate Resolution Imaging Spectroradiometer are consistent with the validation statistics of the individual sensor products. The merging including the third mission Medium Resolution Imaging Spectrometer is also addressed for a reduced ensemble of matchups.

A time-series of above-water radiometric measurements for coastal water monitoring and remote sensing product validation

A three-year time-series of radiometric data collected with an autonomous above-water system at the Acqua Alta Oceanographic Tower in the northern Adriatic Sea has shown its applicability for monitoring the trophic state of marine waters and its suitability for the validation of remote sensing products in coastal areas. Specifically, the radiometric data have been used to produce surface chlorophyll a concentration (Chla) by applying a regional algorithm proposed for the northern Adriatic Sea coastal waters. A comparison based on 41 match-ups between these Chla and reference values from high-performance liquid chromatography, has shown an average absolute difference of 32%. The comparison of Chla derived from remote sensing SeaWiFS and in situ above-water radiances has shown an average absolute difference of 21% for 183 match-ups, when the same regional algorithm is applied to both types of radiometric data.

Vicarious calibration of satellite ocean color sensors at two coastal sites

Regionally specific vicarious calibration coefficients for ocean color sensors have been computed for the visible bands using the normalized water leaving radiance L(wn) collected at sites in the northern Adriatic Sea and Baltic Proper. These coefficients are consistent with those found in oligotrophic waters for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) . The extension of the vicarious calibration process to the near-infrared is investigated by taking advantage of the field data of aerosol optical thickness coincident with L(wn). Results further confirm the importance of accurately modeling and identifying the aerosol components in atmospheric correction schemes.