Ocean Color Radiometry Research Articles

Determining the Spectral Requirements for Cyanobacteria Detection for the CyanoSat Hyperspectral Imager with Machine Learning.

This study determines an optimal spectral configuration for the CyanoSat imager for the discrimination and retrieval of cyanobacterial pigments using a simulated dataset with machine learning (ML). A minimum viable spectral configuration with as few as three spectral bands enabled the determination of cyanobacterial pigments phycocyanin (PC) and chlorophyll-a (Chl-a) but may not be suitable for determining cyanobacteria composition. A spectral configuration with about nine ideally positioned spectral bands enabled estimation of the cyanobacteria-to-algae ratio (CAR) and pigment concentrations with almost the same accuracy as using all 300 spectral channels. A narrower spectral band full-width half-maximum (FWHM) did not provide improved performance compared to the nominal 12 nm configuration. In conclusion, continuous sampling of the visible spectrum is not a requirement for cyanobacterial detection, provided that a multi-spectral configuration with ideally positioned, narrow bands is used. The spectral configurations identified here could be used to guide the selection of bands for future ocean and water color radiometry sensors.

Uncertainty of atmospheric scattering functions relevant for Satellite Ocean Colour Radiometry in European Seas

ABSTRACT Uncertainty assessment of Ocean Colour Radiometry (OCR) usually relies on the comparison between satellite marine reflectance and concurrent in situ radiometric measurements. However, when dealing with the standard atmospheric correction (AC), uncertainty of marine reflectance originates fundamentally from two sources: (i) uncertainty of the Level-1 calibration at top of the atmosphere, and (ii) uncertainty of the atmospheric scattering functions computed by the AC (atmospheric path reflectance and transmittance). The aim of this alternative work is thus to assess the uncertainty of these scattering functions, thanks to inherent optical properties of aerosols extracted from the AErosol Robotic NETwork (AERONET) and ingested in a radiative transfer code. The study is conducted for the MEdium Resolution Imaging Spectrometer (MERIS), over three AERONET sites selected in European seas (Aqua Alta Oceanographic Tower, AAOT; Gustav Dalen Tower, GDT; Lampedusa) and Lanai in the Pacific Ocean as a reference. We develop an uncertainty budget based on the statistical analysis of the errors between MERIS and AERONET-derived data. At 443 nm, uncertainty of MERIS atmospheric path reflectance due to random effects is estimated around 2%, while that of total atmospheric transmittance is between 0.6% and 1%. Propagation of these uncertainties to OCR is achieved following metrological principles and varies between match-ups and sites due to the distinctive contribution of the marine signal to the total radiometry: uncertainty of MERIS marine reflectance at 443 nm is 10.8% (±1.1%) at Lanai, 18.3% (±4.6%) at Lampedusa, 29.4% (±12.2%) at AAOT and up to 68.7% (±127.4%) at GDT (i.e. with a significant intra-site variability). The methodology is a first step aimed at deriving a pixel-by-pixel uncertainty budget of OCR, instead of providing overall estimates as generally done in the OC community. Limitations due to uncertainties in the AERONET data are also discussed, with a tentative quantification.

A new method to estimate the dissolved organic carbon concentration from remote sensing in the global open ocean

The Dissolved Organic Carbon (DOC) represents the largest organic carbon reservoir in the ocean. Therefore, describing its spatio-temporal distribution is crucial for better understanding the global carbon cycle. Recent studies have demonstrated the possibility to determine DOC in coastal waters from ocean color radiometry (OCR) based on its strong correlation with the absorption coefficient of Colored Dissolved Organic Matter (acdom(λ)). However, in the open ocean, the CDOM to DOC relationship is highly variable as they present different sources, sinks, and kinetics. Here we present a new approach to estimating DOC over the open ocean based on an Artificial Neural Network (ANN) algorithm. This model accounts for i) Optical Water Classes (OWC) ii) sea surface temperature (SST), mixed layer depth (MLD), acdom(443), and chlorophyll-a (Chl-a) concentration, and iii) different time lags depending on the input parameter. The satellite DOC estimated with this model is in good agreement with in situ measurements (MAPD = 7.04%), while the spatial patterns follow former observations and model outputs. A sensitivity analysis has shown that the main descriptors to assess satellite DOC at a given time for oligotrophic and mesotrophic open ocean waters are SST one week before, and acdom(443) two weeks before; with Chl-a one week before as an additional input parameter for more productive waters. This study allows for the first time the assessment of the contribution of the particulate organic carbon (POC) to the total organic carbon (TOC) over the global ocean. The POC/TOC ratio value varies between 1.31% and 9.07%, with a mean value of about 4.57 ± 1.87%.

Diel changes of the optical backscattering coefficient of oceanic particulate matter determined from diel changes in apparent optical properties: a case study in the Mediterranean Sea (BOUSSOLE site).

Using in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter (bbp) at an oceanic site, we show that diel cycles of bbp 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 bbp 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 bbp from measured reflectance data. The uncertainty in deriving bbp 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 bbp diel changes. While the results are encouraging, they also emphasize the inherent limitation of current inversion algorithms in deriving diel changes of bbp, which essentially stems from the empirical parameterizations that such algorithms include.

Assessment of OLCI-A and OLCI-B radiometric data products across European seas

The Ocean and Land Color Instruments (OLCI) operated onboard the Copernicus Sentinel-3 satellites are providing globally distributed Ocean Color Radiometry (OCR) data products of relevance for environmental and climate applications. This work summarizes results on the assessment of fundamental OCR data from the Operational Baseline 3 Collection OL_L2M.003.01 of OLCI-A and OLCI-B onboard Sentinel-3A and Sentinel-3B, respectively. Evaluated products are the satellite derived normalized water-leaving radiance LWN(λ), aerosol optical depth at 865 nm τa(865) and Ångström exponent α determined in the near-infrared spectral region. The analyses were performed relying on in situ reference data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) from sites representative of diverse water types. The comparison of OLCI-A and OLCI-B with AERONET-OC LWN(λ) for oligotrophic/mesotrophic waters shows cross-mission consistent spectral median percent differences (i.e., biases) varying within ±6% at the blue-green center-wavelengths. The analysis of data from regions characterized by optically complex waters, however, displays systematic negative biases for both OLCI-A and OLCI-B further increasing for waters dominated by chromophoric dissolved organic matter, thus suggesting a dependence of the atmospheric correction on water type. The direct inter-comparison of OLCI-B and OLCI-A LWN(λ) from the Tandem Phase characterized by Sentinel-3B and Sentinel-3A flying 30 s apart on the same orbit, shows spectral median percent differences lower than ±1% in the 412–560 nm interval, of approximately +5% at 620 and 665 nm, and −7% at 400 nm. However, outside the Tandem Phase, the inter-comparison of OLCI-B and OLCI-A data products indicates large and systematic differences explained by a notable dependence on the viewing angle. The evaluation of τa(865) and α across different geographic regions exhibits overestimated values between +48 and + 79% for the former and underestimated values between −28% and − 41% for the latter. A complementary evaluation of OCR data products from the Visible Infrared Imager Radiometer Suite on board the Suomi National Polar-orbiting Partnership (VIIRS-S), proposed as a further indirect term of reference for OLCI-A and OLCI-B data, shows large underestimates of LWN(λ) with respect to the in situ reference data in the various water types at 410 nm. Nevertheless, opposite to OLCI-A and OLCI-B data products, absolute differences between VIIRS-S and in situ reference data do not reveal any large or systematic dependence on water type and satellite viewing angle. Overall results suggest the need for further developing the OLCI-A and OLCI-B atmospheric correction, possibly improving the capability to identify aerosol types and to model scattering processes.

Comparison of Above-Water Seabird and TriOS Radiometers along an Atlantic Meridional Transect

The Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) project has carried out a range of activities to evaluate and improve the state-of-the-art in ocean color radiometry. This paper described the results from a ship-based intercomparison conducted on the Atlantic Meridional Transect 27 from 23rd September to 5th November 2017. Two different radiometric systems, TriOS-Radiation Measurement Sensor with Enhanced Spectral resolution (RAMSES) and Seabird-Hyperspectral Surface Acquisition System (HyperSAS), were compared and operated side-by-side over a wide range of Atlantic provinces and environmental conditions. Both systems were calibrated for traceability to SI (Système international) units at the same optical laboratory under uniform conditions before and after the field campaign. The in situ results and their accompanying uncertainties were evaluated using the same data handling protocols. The field data revealed variability in the responsivity between TRiOS and Seabird sensors, which is dependent on the ambient environmental and illumination conditions. The straylight effects for individual sensors were mostly within ±3%. A near infra-red (NIR) similarity correction changed the water-leaving reflectance (ρw) and water-leaving radiance (Lw) spectra significantly, bringing also a convergence in outliers. For improving the estimates of in situ uncertainty, it is recommended that additional characterization of radiometers and environmental ancillary measurements are undertaken. In general, the comparison of radiometric systems showed agreement within the evaluated uncertainty limits. Consistency of in situ results with the available Sentinel-3A Ocean and Land Color Instrument (OLCI) data in the range from (400…560) nm was also satisfactory (−8% < Mean Percentage Difference (MPD) < 15%) and showed good agreement in terms of the shape of the spectra and absolute values.

ROSACE: A Proposed European Design for the Copernicus Ocean Colour System Vicarious Calibration Infrastructure

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.

Fiducial Reference Measurements for Satellite Ocean Colour (FRM4SOC)

Earth observation data can help us understand and address some of the grand challenges and threats facing us today as a species and as a planet, for example climate change and its impacts and sustainable use of the Earth’s resources. However, in order to have confidence in earth observation data, measurements made at the surface of the Earth, with the intention of providing verification or validation of satellite-mounted sensor measurements, should be trustworthy and at least of the same high quality as those taken with the satellite sensors themselves. Metrology tells us that in order to be trustworthy, measurements should include an unbroken chain of SI-traceable calibrations and comparisons and full uncertainty budgets for each of the in situ sensors. Until now, this has not been the case for most satellite validation measurements. Therefore, within this context, the European Space Agency (ESA) funded a series of Fiducial Reference Measurements (FRM) projects targeting the validation of satellite data products of the atmosphere, land, and ocean, and setting the framework, standards, and protocols for future satellite validation efforts. The FRM4SOC project was structured to provide this support for evaluating and improving the state of the art in ocean colour radiometry (OCR) and satellite ocean colour validation through a series of comparisons under the auspices of the Committee on Earth Observation Satellites (CEOS). This followed the recommendations from the International Ocean Colour Coordinating Group’s white paper and supports the CEOS ocean colour virtual constellation. The main objective was to establish and maintain SI traceable ground-based FRM for satellite ocean colour and thus make a fundamental contribution to the European system for monitoring the Earth (Copernicus). This paper outlines the FRM4SOC project structure, objectives and methodology and highlights the main results and achievements of the project: (1) An international SI-traceable comparison of irradiance and radiance sources used for OCR calibration that set measurement, calibration and uncertainty estimation protocols and indicated good agreement between the participating calibration laboratories from around the world; (2) An international SI-traceable laboratory and outdoor comparison of radiometers used for satellite ocean colour validation that set OCR calibration and comparison protocols; (3) A major review and update to the protocols for taking irradiance and radiance field measurements for satellite ocean colour validation, with particular focus on aspects of data acquisition and processing that must be considered in the estimation of measurement uncertainty and guidelines for good practice; (4) A technical comparison of the main radiometers used globally for satellite ocean colour validation bringing radiometer manufacturers together around the same table for the first time to discuss instrument characterisation and its documentation, as needed for measurement uncertainty estimation; (5) Two major international side-by-side field intercomparisons of multiple ocean colour radiometers, one on the Atlantic Meridional Transect (AMT) oceanographic cruise, and the other on the Acqua Alta oceanographic tower in the Gulf of Venice; (6) Impact and promotion of FRM within the ocean colour community, including a scientific road map for the FRM-based future of satellite ocean colour validation and vicarious calibration (based on the findings of the FRM4SOC project, the consensus from two major international FRM4SOC workshops and previous literature, including the IOCCG white paper on in situ ocean colour radiometry).

Monte Carlo–Based Quantification of Uncertainties in Determining Ocean Remote Sensing Reflectance from Underwater Fixed-Depth Radiometry Measurements

AbstractA 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 = 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.

Using overlapping VIIRS scenes to observe short term variations in particulate matter in the coastal environment

In coastal areas, the concentrations and the optical properties of the water components have a large spatial and temporal variability, due to river discharges and meteo-marine conditions, such as wind, wave and current, and their interaction with shallow water bathymetry. This large temporal variability cannot be captured using the standard Ocean Colour Radiometry (OCR) polar orbiting satellites, the latter providing almost one image per day. On the contrary, the use of OCR geostationary sensors, like the Geostationary Ocean Colour Imager (GOCI), centred above the Korean Peninsula, enable to capture the short-term variability of the optical properties. To compensate the lack of a geostationary sensor similar to GOCI over other coastal environments, like the North Adriatic Sea (NAS), the multiple observations provided during the same day by the Visible Infrared Imaging Radiometer Suite (VIIRS) mounted on the SUOMI NPP satellite, can be exploited. Indeed, due to its large swath of 3060 km, the VIIRS orbits can overlap over the NAS during the same day within 1 h and 42 min, an important feature that can be useful in capturing the short term variability of the optical properties.A large number of VIIRS overlaps in the NAS are characterized by high sensor zenith angle (SZA) of the observation, resulting in a large portion of images masked by the high satellite zenith flag. In order to make available those observations and, in general, to reduce the dependence of the VIIRS observations from the SZA, an adjustment based on a multi linear regression scheme, which exploits radiometric in situ observations, was here applied.This study aims to prove the suitability of the adjusted overlapping VIIRS in capturing the short time scale dynamics of particulate backscattering, and this was demonstrated by the analysis of a case study for the 21st and 22nd of March 2013. In order to evaluate the advantages in using multiple observations during the same day, also the ~24 h dynamics was analysed, comparing the overlapping VIIRS results with the ones obtained from the daily product.

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

ProVal: A New Autonomous Profiling Float for High Quality Radiometric Measurements

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, 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 sampled 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 45% 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 less than 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 & 3B) 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.

Seasonal Impact of Adjacency Effects on Ocean Color Radiometry at the AAOT Validation Site

The seasonal impact of adjacency effects (AE) on satellite ocean color data at visible and near-infrared (NIR) wavelengths by the Sea-Viewing Wide Field-of-View Sensor, the Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODISA), the Medium Resolution Imaging Spectrometer, the Ocean and Land Color Instrument, the Operational Land Imager (OLI), and the MultiSpectral Imagery (MSI) was theoretically evaluated at a validation site in the northern Adriatic Sea. The analysis made use of comprehensive simulations accounting for multiple scattering, sea surface roughness, sensor viewing geometry, actual coastline, typical and extreme atmospheric conditions, and the seasonal variability of solar illumination and, land and water optical properties. Results, obtained by relying on the normalization of the radiometric sensitivity of each sensor to the same input radiance, show that the spectral and seasonal impacts of AE considerably vary among sensors. AE significantly exceed the radiometric sensitivity of MSI at its sole blue band in winter, whereas they significantly outdo the noise threshold of OLI and MODISA high-resolution data exclusively in the NIR in summer. Conversely, for all other sensors and for MODISA low-resolution data, AE are particularly significant at NIR bands between March and October and at the blue-green bands in winter.

Water Optics and Water Colour Remote Sensing

The editorial paper aims to highlight the main topics investigated in the Special Issue (SI) “Water Optics and Water Colour Remote Sensing”. The outcomes of the 21 papers published in the SI are presented, along with a bibliometric analysis in the same field, namely, water optics and water colour remote sensing. This editorial summarises how the research articles of the SI approach the study of bio-optical properties of aquatic systems, the development of remote sensing algorithms, and the application of time-series satellite data for assessing long-term and temporal-spatial dynamics in inland, coastal, and oceanic waters. The SI shows the progress with a focus on: (1) bio-optical properties (three papers); (2) atmospheric correction and data uncertainties (five papers); (3) remote sensing estimation of chlorophyll-a (Chl-a) (eight papers); (4) remote sensing estimation of suspended matter and chromophoric dissolved organic matter (CDOM) (four papers); and (5) water quality and water ecology remote sensing (four papers). Overall, the SI presents a variety of applications at the global scale (with case studies in Europe, Asia, South and North America, and the Antarctic), achieved with different remote sensing instruments, such as hyperspectral field and airborne sensors, ocean colour radiometry, geostationary platforms, and the multispectral Landsat and Sentinel-2 satellites. The bibliometric analysis, carried out to include research articles published from 1900 to 2016, indicates that “chlorophyll-a”, “ocean colour”, “phytoplankton”, “SeaWiFS” (Sea-Viewing Wide Field-of-View Sensor), and “chromophoric dissolved organic matter” were the five most frequently used keywords in the field. The SI contents, along with the bibliometric analysis, clearly suggest that remote sensing of Chl-a is one of the topmost investigated subjects in the field.

Ocean-colour products for climate-change studies: What are their ideal characteristics?

Ocean-colour radiometry is recognised as an Essential Climate Variable (ECV) according to the Global Climate Observing System (GCOS), because of its capability to observe significant properties of the marine ecosystem at synoptic to global scales. Yet the value of ocean colour for climate-change studies depends to a large extent not only on the decidedly important quality of the data per se, but also on the qualities of the algorithms used to convert the multi-spectral radiance values detected by the ocean-colour satellite into relevant ecological, bio-optical and biogeochemical variables or properties of the ocean. The algorithms selected from the pool of available algorithms have to be fit for purpose: detection of marine ecosystem responses to climate change. Marine ecosystems might respond in a variety of ways to changing climate, including perturbations to regional distributions in the quantity and in the type of phytoplankton present, their locations and in their seasonal dynamics. The ideal algorithms would be capable of distinguishing between abundance and type, and would not mistake one for the other. They would be robust to changes in climate, and would not rely on assumptions that might be valid only under current climatic conditions. Based on such considerations, we identify a series of ideal qualitative traits that algorithms for climate-change studies would possess. Necessarily, such traits would have to complement the quantitative requirements for precision, accuracy and stability in the data over long time scales. We examine the extent to which available algorithms meet the criteria, according to the work carried out in the Ocean Colour Climate Change Initiative, and where improvements are still needed.

Retrieval of Colored Detrital Matter (CDM) light absorption coefficients in the Mediterranean Sea using field and satellite ocean color radiometry: Evaluation of bio-optical inversion models

Abstract 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 a cdm (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 a cdm (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.

Assessing satellite sea surface salinity from ocean color radiometric measurements for coastal hydrodynamic model data assimilation

Improving forecasts of salinity from coastal hydrodynamic models would further our predictive capacity of physical, chemical, and biological processes in the coastal ocean. However, salinity is difficult to estimate in coastal and estuarine waters at the temporal and spatial resolution required. Retrieving sea surface salinity (SSS) using satellite ocean color radiometry may provide estimates with reasonable accuracy and resolution for coastal waters that could be assimilated into hydrodynamic models to improve SSS forecasts. We evaluated the applicability of satellite SSS retrievals from two algorithms for potential assimilation into National Oceanic and Atmospheric Administration’s Chesapeake Bay Operational Forecast System (CBOFS) hydrodynamic model. Of the two satellite algorithms, a generalized additive model (GAM) outperformed that of an artificial neural network (ANN), with mean bias and root-mean-square error (RMSE) of 1.27 and 3.71 for the GAM and 3.44 and 5.01 for the ANN. However, the RMSE for the SSS predicted by CBOFS (2.47) was lower than that of both satellite algorithms. Given the better precision of the CBOFS model, assimilation of satellite ocean color SSS retrievals will not improve CBOFS forecasts of SSS in Chesapeake Bay. The bias in the GAM SSS retrievals suggests that adding a variable related to precipitation may improve its performance.

New Technology and Teamwork to Tackle Ocean Color Radiometry

International Ocean Colour Science Meeting; San Francisco, California, 15–18 June 2015

Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS

The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat­8 satellite. OLI includes a suite of relatively narrow spectral bands at 30 m spatial resolution in the visible to shortwave infrared, which makes it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of spaceborne multispectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote sensing reflectance (Rrs; sr−1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents, such as the concentration of the phytoplankton pigment chlorophyll a.

Ocean-color radiometry across the Southern Atlantic and Southeastern Pacific: Accuracy and remote sensing implications

Ocean color radiometry (OCR) provides valuable data for biogeochemical oceanography. In situ OCR measurements are used in the development and validation of bio-optical models and vicarious calibration of satellite ocean-color sensors. It is thus crucial to obtain accurate in situ OCR measurements, which is a challenge, especially in regions subjected to adverse environmental conditions and where waters are optically complex. In the present work, the accuracy of in situ OCR is analyzed with data acquired in a wide range of bio-geographic provinces across the Southern Atlantic and Southeastern Pacific during the R/V Melville MV1102 cruise. Varied techniques employed to measure above-water remote sensing reflectance (Rrs) are inter-compared. Measured Rrs is also compared with modeled Rrs in a closure experiment. The impact of Rrs uncertainties on the retrieval of chlorophyll a concentration (Chla) and inherent optical properties (IOPs) is evaluated using operational bio-optical algorithms. The relative percent difference (RPD) between Rrs measured by the various techniques ranged from 12 to 26% for the ocean-color bands (412–555nm), and 3–12% for the ratios (412–510/555). A merged Rrs obtained by averaging the different types of measurements, INS, is recommended to reduce uncertainties. The coefficient of variation of INS and reflectance ratios was 11–13% and 3–5%, respectively. The RPD between INS and modeled Rrs and the corresponding ratios ranged from 18 to 34% and from 13 to 17%, respectively. Complete closure could not be obtained due to both measurement and modeling uncertainties. The impact of INS uncertainties on retrieved Chla and IOPs was generally smaller than the intrinsic errors of the inversion schemes. The results suggest that even though more accurate ocean-color radiometry is desirable, improving retrieval algorithms is essential to properly describing and furthering our understanding of bio-optical variability in the world's oceans.