Antonio Mannino

Dynamic range and sensitivity requirements of satellite ocean color sensors: learning from the past

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(typical)) and maximum (L(max)) at-sensor radiances from the visible to the shortwave IR were determined. The L(typical) values at an SZA of 45° were used as constraints to calculate SNRs of 10 multiband sensors at the same L(typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(typical). The tabulated L(typical), L(max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

The United States' next generation of atmospheric composition and coastal ecosystem measurements : NASA's Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission

The Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission was recommended by the National Research Councils (NRCs) Earth Science Decadal Survey to measure tropospheric trace gases and aerosols and coastal ocean phytoplankton, water quality, and biogeochemistry from geostationary orbit, providing continuous observations within the field of view. To fulfill the mandate and address the challenge put forth by the NRC, two GEO-CAPE Science Working Groups (SWGs), representing the atmospheric composition and ocean color disciplines, have developed realistic science objectives using input drawn from several community workshops. The GEO-CAPE mission will take advantage of this revolutionary advance in temporal frequency for both of these disciplines. Multiple observations per day are required to explore the physical, chemical, and dynamical processes that determine tropospheric composition and air quality over spatial scales ranging from urban to continental, and over temporal scales ranging from diu...

Remote sensing of the absorption coefficients and chlorophyll a concentration in the United States southern Middle Atlantic Bight from SeaWiFS and MODIS‐Aqua

[1] At present, satellite remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of satellite sensors in oceanic waters. In this study, field measurements collected on a series of cruises within United States southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of satellite ocean color products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectrometer (MODIS-Aqua) in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in satellite retrievals of absorption coefficients of phytoplankton (aph), colored dissolved organic matter (CDOM) (ag), nonpigmented particles (ad), nonpigmented particles plus CDOM (adg), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing reflectance (Rrs) ratios. The validation match-ups showed that the mean absolute percent differences were typically <35%, although higher errors were found for ad retrievals. Seasonal and spatial variability of satellite-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35–70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30–45% for phytoplankton and 0–20% for nonpigmented particles. The overestimation of [Chl_a] from the operational satellite algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.

Dissolved organic carbon fluxes in the Middle Atlantic Bight: An integrated approach based on satellite data and ocean model products

Continental margins play an important role in global carbon cycle, accounting for 15-21% of the global marine primary production. Since carbon fluxes across continental margins from land to the open ocean are not well constrained, we undertook a study to develop satellite algorithms to retrieve dissolved organic carbon (DOC) and combined these satellite data with physical circulation model products to quantify the shelf boundary fluxes of DOC for the U.S. Middle Atlantic Bight (MAB). Satellite DOC was computed through seasonal relationships of DOC with colored dissolved organic matter absorption coefficients, which were derived from an extensive set of in situ measurements. The multiyear time series of satellite-derived DOC stocks (4.9 Teragrams C; Tg) shows that freshwater discharge influences the magnitude and seasonal variability of DOC on the continental shelf. For the 2010-2012 period studied, the average total estuarine export of DOC into the MAB shelf is 0.77 Tg C yr-1 (year). The integrated DOC tracer fluxes across the shelf boundaries are 12.1 Tg C yr-1 entering the MAB from the southwest alongshore boundary, 18.5 Tg C yr-1 entering the MAB from the northeast alongshore boundary, and 29.0 Tg C yr-1 flowing out of the MAB across the entire length of the 100 m isobath. The magnitude of the cross-shelf DOC flux is quite variable in time (monthly) and space (north to south). The highly dynamic exchange of water along the shelf boundaries regulates the DOC budget of the MAB at subseasonal time scales.

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

Abstract The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

Carbon Budget of Tidal Wetlands, Estuaries, and Shelf Waters of Eastern North America

Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here, we construct such a budget for Eastern North America using historical data, empirical models, remote-sensing algorithms, and process-based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they respectively make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.

Cloud motion in the GOCI/COMS ocean colour data

ABSTRACT The Geostationary Ocean Colour Imager (GOCI) instrument, on Korea’s Communications, Oceans, and Meteorological Satellite (COMS), can produce a spectral artefact arising from the motion of clouds – the cloud is spatially shifted and the amount of shift varies by spectral band. The length of time it takes to acquire all eight GOCI bands for a given slot (portion of a scene) is sufficient to require that cloud motion be taken into account to fully mask or correct the effects of clouds in all bands. Inter-band correlations can be used to measure the amount of cloud shift, which can then be used to adjust the cloud mask so that the union of all shifted masks can act as a mask for all bands. This approach reduces the amount of masking required versus a simple expansion of the mask in all directions away from clouds. Cloud motion can also affect regions with unidentified clouds – thin or fractional clouds that evade the cloud identification process – yielding degraded quality in retrieved ocean colour parameters. Areas with moving and unidentified clouds require more elaborate masking algorithms to remove these degraded retrievals. Correction for the effects of moving fractional clouds may also be possible. The cloud shift information can be used to determine cloud motion and thus wind at the cloud levels on sub-minute timescales. The beneficial and negative effects of moving clouds should be considered for any ocean colour instrument design and associated data processing plans.

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), Scdm (units: nm-1), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving Scdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of Scdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

Bio-physical Interactions in Ocean Margin Ecosystems (BIOME): understanding coastal dynamics in the Southern Mid-Atlantic Bight

Coastal regions within the Mid-Atlantic Bight (MAB) are significantly influenced by regional freshwater fluxes emanating from several large bay systems, most notably the Hudson-Raritan river systems, the Delaware and Chesapeake Bays. The outflows from these bays have high sediment loads and high levels of nutrients, particulate and dissolved organic matter (POM and DOM) associated with them which strongly influence the adjacent coastal margin ecosystems. Our research and observational effort includes the development and deployment of an observing system aimed at characterizing and monitoring the influence of the Chesapeake Bay on the adjacent coastal ocean margin ecosystem. A primary focus of this effort is to develop and apply state-of-the-art technologies and methodologies to support research, observation, monitoring, and management applications in the coastal ocean. We have developed a program that addresses coastal spatial and temporal scales. Our observing system consists of four components including 1) High Frequency (HF) Radar: 3 long-range HF Radar systems for mapping coastal ocean surface currents along Delmarva and 2 standard-range systems for the Chesapeake Bay mouth region, 2) a Coastal Ocean Bio-optical buoY (COBY), which will be deployed southeast of the Maryland-Virginia border at about 40m water depth, and will be instrumented with an above-water spectroradiometer (19 channel UV-VIS-NIR, 10nm BW, sea- and sky-viewing radiometers plus solar reference) on a robotic arm to measure water-leaving radiances, meteorological package, in-water mooring instruments with ADCP, CTD, nitrate sensor, ac-9, ac-s, and fluorometers for chlorophyll, colored dissolved organic matter (CDOM) and phycoerythrin detection; 3) seasonal cruises in the Mid-Atlantic Bight collecting optical, biological, and chemical data; and 4) the Ocean-Atmosphere Sensor Integration System (OASIS), which is comprised of a fleet (6-12) of solar-powered surface autonomous vehicles deployed offshore to measure surface ocean currents, meteorological measurements, surface ocean salinity and temperature, air-sea CO2 fluxes, water-leaving radiances, chlorophyll and CDOM fluorescence, HAB detection, etc. The HF radars, COBY and OASIS are being deployed this summer, with plans for a fully deployed observing system by the end of 2005 or early 2006.

The adsorption of dissolved organic carbon onto glass fiber filters and its effect on the measurement of particulate organic carbon: A laboratory and modeling exercise

Particulate organic carbon (POC) represents a small portion of total carbon in the ocean. However, it plays a large role in the turnover of organic matter through the biological pump and other processes. Early on since the development of the POC measurement technique in the 1960s, it was known that dissolved organic carbon (DOC) adsorbs and is retained both on and in the filter. That retained DOC is measured as if it was part of the particulate fraction, an artifact that can cause significant overestimates of POC concentration. We set out to address the long-standing question of whether the magnitude of the DOC adsorption is affected by the quantity and quality of the dissolved organic matter in the sample. However, our results precluded an unequivocal answer to that question; nevertheless, the experimental data generated did allow us to develop and test predictive models that relate the mass of carbon adsorbed to the volume of sample filtered. The results indicate that the uptake of DOC can be predicted using an exponential model and that a saturation point is approached when approximately a half-liter of water is filtered. This model can be a valuable tool for correcting existing POC data sets that did not account for DOC adsorption. Nonetheless, this approach should not be regarded as a substitute for collecting in situ filter blanks in parallel with POC samples to prop-erly correct for this artifact.