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River-to-lake transitional areas are biogeochemically active ecosystems that can alter the amount and composition of dissolved organic matter (DOM) as it moves through the aquatic continuum. However, few studies have directly measured carbon processing and assessed the carbon budget of freshwater rivermouths. We compiled measurements of dissolved organic carbon (DOC) and DOM in several water column (light and dark) and sediment incubation experiments conducted in the mouth of the Fox river (Fox rivermouth) upstream from Green Bay, Lake Michigan. Despite variation in the direction of DOC fluxes from sediments, we found that the Fox rivermouth was a net sink of DOC where water column DOC mineralization outweighed the release of DOC from sediments at the rivermouth scale. Although we found DOM composition also changed during our experiments, alterations in DOM optical properties were largely independent of the direction of sediment DOC fluxes. We found a consistent decrease in humic-like and fulvic-like terrestrial DOM and a consistent increase in the overall microbial composition of rivermouth DOM during our incubations. Moreover, greater ambient total dissolved phosphorus concentrations were positively associated with the consumption of terrestrial humic-like, microbial protein-like, and more recently derived DOM but had no effect on bulk DOC in the water column. Unexplained variation indicates that other environmental controls and water column processes affect the processing of DOM in this rivermouth. Nonetheless, the Fox rivermouth appears capable of substantial DOM transformation with implications for the composition of DOM entering Lake Michigan.

Satellite ocean color missions require accurate system vicarious calibrations (SVC) to retrieve the relatively small remote-sensing reflectance ( $R_{\mathrm {rs}}$ , sr−1) from the at-sensor radiance. However, the current atmospheric correction and SVC procedures do not include calibration of the “long” near infrared band (NIRL—869 nm for MODIS), partially because earlier studies, based primarily on simulations, indicate that accuracy in the retrieved $R_{\mathrm {rs}}$ is insensitive to moderate changes in the NIRL vicarious gain ( $g$ ). However, the sensitivity of ocean color data products to $g$ (NIRL) has not been thoroughly examined. Here, we first derive 10 SVC “gain configurations” (vicarious gains for all visible and NIR bands) for MODIS/Aqua using current operational NASA protocols, each time assuming a different $g$ (869). From these, we derive a suite of ~1.4E6 unique gain configurations with $g$ (869) ranging from 0.85 to 1.2. All MODIS/A data for 25 locations within each of five ocean gyres were then processed using each of these gain configurations. Resultant time series show substantial variability in dominant $R_{\mathrm {rs}}$ (547) patterns in response to changes in $g$ (869) (and associated gain configurations). Overall, mean $R_{\mathrm {rs}}$ (547) values generally decrease with increasing $g$ (869), while the standard deviations around those means show gyre-specific minima for $0.97 (869) $g$ (869) using such time series, finding $g$ (869) = 1.025 most closely comports with expectations. This approach is broadly applicable to other ocean color sensors, and highlights the importance of rigorous cross-sensor calibration of the NIRL bands, with implications on consistency of merged-sensor data sets.

A recently developed algorithm to estimate surface ocean chlorophyll a concentrations (Chl in milligrams per cubic meter), namely, the ocean color index (OCI) algorithm, has been adopted by the U.S. National Aeronautics and Space Administration to apply to all satellite ocean color sensors to produce global Chl maps. The algorithm is a hybrid between a band‐difference color index algorithm for low‐Chl waters and the traditional band‐ratio algorithms (OCx) for higher‐Chl waters. In this study, the OCI algorithm is revisited for its algorithm coefficients and for its algorithm transition between color index and OCx using a merged data set of high‐performance liquid chromatography and fluorometric Chl. Results suggest that the new OCI algorithm (OCI2) leads to lower Chl estimates than the original OCI (OCI1) for Chl less than 0.05 milligrams per cubic meter, but smoother algorithm transition for Chl between 0.25 and 0.40 milligrams per cubic meter. Evaluation using in situ data suggests that similar to OCI1, OCI2 has significantly improved image quality and cross‐sensor consistency between SeaWiFS (Sea-viewing Wide Field-of-view Sensor), MODISA (Moderate Resolution Imaging Spectroradiometer on Aqua), and VIIRS (Visible Infrared Imaging Radiometer Suite) over the OCx algorithms for oligotrophic oceans. Mean cross‐sensor difference in monthly Chl data products over global oligotrophic oceans reduced from approximately 10 percent for OCx to 1-2 percent for OCI2. More importantly, data statistics suggest that the current straylight masking scheme used to generate global Chl maps can be relaxed from 7 by 5 to 3 by 3 pixels without losing data quality in either Chl or spectral remote sensing reflectance (R (sub rs) by lambda (sensor wavelength), per steradian (sr (sup −1)) for not just oligotrophic oceans but also more productive waters. Such a relaxed masking scheme yields an average relative increase of 39 percent in data quantity for global oceans, thus making it possible to reduce data product uncertainties and fill data gaps.

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in...

Retrievals of skin Sea-Surface Temperature (SSTskin) from the measurements of the Visible Infrared Imaging Radiometer Suite on the Suomi-National Polar-orbiting Partnership satellite are presented and discussed. The algorithms used to derive the SSTskin from the radiometric measurements are given in detail. A number of approaches to assess the accuracy and stability of the Visible Infrared Imaging Radiometer Suite (VIIRS) SSTskin retrievals are reported, and factors including latitude and season, and physical processes in the atmosphere and at the surface are discussed. We conclude that the Suomi National Polar-orbiting Partnership (S-NPP) VIIRS is capable of matching and improving upon the accuracies of SSTskin from the MODISs on Terra and Aqua, and that the VIIRS SSTskin fields have the potential to contribute to the extension of the satellite-derived Climate Data Records of SST into the future.

In North America, native unionid mussels are imperiled due to factors such as habitat degradation, pollution, and invasive species. One of the most substantial threats is that posed by dreissenid mussels, which are invasive mussels that attach to hard substrates including unionid shells and can restrict movement and feeding of unionids. This dreissenid mussel biofouling of unionids varies spatially in large ecosystems, such as the Great Lakes, with some areas having low enough biofouling to form effective refugia where unionid mussels might persist. Here, we measured biofouling on mussels suspended in cages over the growing season (generally first week in June to last week of August) over 3 years in nearshore areas in Lake Erie (2014-2016), Lake Michigan (Grand Traverse Bay, 2015 and Green Bay, 2016), and Lake Huron (2015). Biofouling varied substantially by years within Lake Erie, with increasingly higher biofouling rates each year. Although dreissenid mussels are present throughout these lakes, we observed very low biofouling in Grand Traverse Bay (Lake Michigan) and Saginaw Bay (Lake Huron), with no dreissenid mussels in 8 of 9 sites across these two bays. Sampling in the rivermouth of the Fox River (Wisconsin) and the Maumee River (Ohio) both showed very high biofouling in areas adjacent to the outlet of these tributaries into Green Bay and Maumee Bay (Lake Erie), respectively. These watersheds are dominated by agriculture, and we would expect high growth of primary producers (i.e., mussel food) and primary consumers (unionids and zebra mussels) in these areas compared to the other sampled bays or the open waters of the Great Lakes.

Algorithm Theoretical Basis Documents (ATBDs) are documents which accompany Earth observation data products generated from algorithms. While ATBDs are essential to scientific reproducibility, these key documents are not standardized and are often difficult to find. In this paper, we present the prototype Algorithm Publication Tool (APT), a cloud-based ATBD authoring and editing tool for NASA's Earth science data systems. A standardized ATBD information model is also described as well as lessons learned from developing the prototype tool.

Understanding the quantity and form of nutrient loads to large lakes is necessary to understand controls over primary production, phytoplankton community composition and the production of phytotoxins. Nutrient loading estimates to large lakes are primarily made at stream gages that are deliberately placed outside the direct influence of lake processes, but these estimates cannot take into account processes that occur in the biologically active river-to-lake transition zone. These transition zones (rivermouths) sometimes alter nutrient concentrations and ratios substantially, but few studies have directly measured processing rates of nutrients within rivermouths. From April through September 2016, we conducted 23 water column incubation experiments to measure nutrient loss rates in four rivermouths. First order loss rates (K) for inorganic nitrogen (N) and phosphorus (P) indicated greater loss in light than in dark treatments, suggesting primary production increases N and P removal. Variability in K was high across both time and space, and the measured environmental parameters did not appear to be strongly associated with this variation in K for most N and P forms. If the measured K values and water residence times are accurate, then between 0 and 99% of the inorganic P and nitrates entering the rivermouth would be lost (i.e., converted to organic or particulate P). In late summer, Fox River discharge is low and residence times are usually long, which allow for much higher proportional nutrient removal in the water column. Water column processing appears to be capable of transforming large quantities of dissolved N and P to particulate forms and thus altering its transport and presumably its bioavailability.

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Fatty acid and stable isotope signatures allow researchers, managers, and policy makers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were (a) to evaluate variance structures for fatty acids and stable isotopes (i.e., δ¹³C and δ¹⁵N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegills across spatial scales (10s–100s of km) in large rivers of the Upper Mississippi River Basin, USA, that were sampled annually for 2 years and (b) to evaluate the implications of this variance on the design and interpretation of trophic studies. The greatest variance for both stable isotopes was present at the largest spatial scale for all taxa (except seston δ¹⁵N), indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local‐scale alterations. Conversely, the greatest variance for fatty acids was present at the smallest spatial scale (i.e., among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable for use in assessing ecological questions at larger spatial scales.

Generation of consistent multi-sensor datasets is critical to the assessment of long-term global changes using satellite-borne instruments. Recent research suggests, however, that a fundamental assumption in satellite ocean color data processing concerning the calibration of the long near infrared band (i.e., 865 nm for MODIS) may introduce sensor-specific biases in space and/or time, which may also contribute to cross-sensor inconsistency in the derived reflectance data products. As such, it is necessary to assess the calibration of this band across sensors – performed here for MODIS/Aqua and VIIRS/SNPP using ‘simultaneous same view’ matchups (SSV; similar to simultaneous nadir overpass, but allowing for non-nadir measurements). Towards that end, we assess geometric, temporal, and spatial homogeneity metrics to identify SSVs, and develop a band-shifting approach applicable within standard satellite data processing routines to resolve expected spectral differences in the radiometry. We find top-of-atmosphere (TOA) radiance data from VIIRS/SNPP long near infrared band to be approximately 3% higher than the corresponding MODIS/A data. With the expectation that cross-calibrating the NIRL should improve cross-sensor continuity of downstream geophysical products (e.g., chlorophyll-a), we reprocessed VIIRS data using updated calibration coefficients. While we noticed many minor improvements in cross-sensor continuity in such data products, large-scale geographic and temporal biases between these two datasets still remain. These discontinuities may be the result of disparate errors in polarization correction or atmospheric correction, both of which are modulated by radiant path geometry.

Large lakes provide a variety of ecological services to surrounding cities and communities. Many of these services are supported by ecological processes that are threatened by the increasing prevalence of cyanobacterial blooms which occur as aquatic ecosystems experience cultural eutrophication. Over the past 10 yr, Lake Erie experienced cyanobacterial blooms of increasing severity and frequency, which have resulted in impaired drinking water for the surrounding communities. Cyanobacterial blooms may impact ecological processes that support other services, but many of these impacts have not been documented. Secondary production (production of primary consumers) is an important process that supports economically important higher trophic levels. Cyanobacterial blooms may influence secondary production because cyanobacteria are a poor-quality food resource and cyanotoxins may be harmful to consumers. Over 3 yr at 34 sites across the western basin of Lake Erie, we measured three indices of secondary production that focus on the dominant bivalve taxa: (1) growth of a native unionid mussel, (2) the size of young-of-year dreissenid mussels, and (3) the mass of colonizing animals on a Hester-Dendy sampler. Associations between these indices and cyanobacterial data were estimated to assess whether cyanobacteria are associated with variation in secondary production in the western basin of Lake Erie. The results suggest cyanobacterial abundance alone is only weakly associated with secondary production, but that cyanotoxins have a larger effect on secondary production. Given recurring late-summer cyanobacterial blooms, this impact on secondary production has the potential to undermine Lake Erie's ability to sustain important ecosystem services.

The Operational Land Imager (OLI) onboard Landsat-8 is generating high-quality aquatic science products, the most critical of which is the remote sensing reflectance (Rrs), defined as the ratio of water-leaving radiance to the total downwelling irradiance just above water. The quality of the Rrs products has not, however, been extensively assessed. This manuscript provides a comprehensive evaluation of Level-1B, i.e., top of atmosphere reflectance, and Rrs products available from OLI imagery under near-ideal atmospheric conditions in moderately turbid waters. The procedure includes a) evaluations of the Rrs products at sites included in the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), b) intercomparisons and cross-calibrations against other ocean color products, and c) optimizations of vicarious calibration gains across the entire OLI observing swath. Results indicate that the near-infrared and shortwave infrared (NIR-SWIR) band combinations yield the most robust and stable Rrs retrievals in moderately turbid waters. Intercomparisons against products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODISA) indicate slight across-track non-uniformities (

The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nLw(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nLw(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nLw(λ) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nLw(λ) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nLw(λ) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.

Recent work indicates that the establishment of bigheaded carps (Hypophthalmichthys spp.) in the United States has led to a reduction in condition of native planktivores and may detrimentally affect other trophic levels by altering the base of aquatic food webs. We used fatty acids to evaluate potential effects of bigheaded carps on taxa from multiple trophic levels in the Upper Mississippi, Illinois, and St. Croix rivers. Seston fatty acid concentrations were highest in the Illinois River lotic sites and connected backwaters and were positively associated with omega-3 highly unsaturated fatty acids, indicating that these locations had abundant, high-quality basal food resources despite hosting the greatest bigheaded carp densities. Fatty acid profiles of threeridge freshwater mussels tracked the fatty acid values in the seston and were not influenced by bigheaded carp abundances. Hydropsychid caddisflies and bluegill did not differ significantly in total fatty acids or percent lipid among spatial locations, indicating that omnivorous species may be relatively unaffected by bigheaded carps. Gizzard shad, however, exhibited the lowest fatty acid concentrations in the locations with the highest relative bigheaded carp densities, and multivariate models identified bigheaded carp densities as the predictive factor that explained the greatest amount of variability. Zooplankton abundance has been greatly reduced after bigheaded carps' establishment in the Illinois River, which may explain the disconnect between the gizzard shad fatty acids and the plentiful, high-quality phytoplankton in that river. Our data provide additional evidence that bigheaded carps are negatively affecting native planktivores such as gizzard shad.

article Concentrations of the phytoplankton pigment chlorophyll-a (Ca) provide indicators of nutrient over- enrichment that has negatively affected Chesapeake Bay, U.S.A. Ca time-series from the National Aeronautics andSpaceAdministration(NASA)Sea-viewingWideField-of-viewSensor(SeaWiFS)andModerateResolution Imaging Spectroradiometer aboard the Aqua spacecraft (MODIS-Aqua) provide observations on temporal and spatial scales that far exceed current field and aircraft sampling strategies. These sensors provide consistent, frequent, and high density data to potentially complement ongoing Bay monitoring activities. We used the in situ Water Quality Monitoring Data set of the Chesapeake Bay Program to evaluate decade-long time-series of SeaWiFS and MODIS-Aqua Ca retrievals in the Bay. The accuracy of the retrievals generally degraded with increasing latitude as the optical complexity increases northward. Ca derived using empirical ("band ratio") algorithms overestimated in situ measurements by 10-50 and 40-100% for SeaWiFS and MODIS-Aqua, respectively, but with limited variability. Ca derived using spectral-matching algorithms showed less bias for both sensors, but with significant variability and sensitivity to radiometric errors. Regionally-tuned empirical algorithms performed best throughout the Bay, offering a combination of reasonable accuracyand high spatial coverage. The radiometric spectral resolution used as input tothe algorithms strongly influenced the quality of Ca retrievals from both sensors. These results establish a baseline quantification of algorithm and sensor performance in a variable and stressed ecosystem against which novel approaches might be compared.

Monitoring of mercury in fish typically involves removal of individuals from the sampled population and subsequent analysis of fillets. This study assessed whether the analysis of fins, structures routinely clipped to mark released fish in population studies, could provide a nonlethal approach for estimating mercury concentrations in axial muscle (fillets). We analyzed fillets and selected fins from 401 northern pike (Esox lucius) and 79 walleye (Sander vitreus) from 21 lakes in Minnesota and Wisconsin, 19 Arctic grayling (Thymallus arcticus) from Toolik Lake, Alaska, and 14 winter flounder (Pseudopleuronectes americanus) from Long Island Sound, New York. On average, 83% of mercury in fins was methylmercury, and concentrations in the proximal portion were about half-those in the distal portion in pelvic fins. Mean concentrations of mercury in fins, averaged by species and fin type, ranged from 2.7 to 8.9% of those in fillets. Coefficients of determination (r2) for linear regressions of mercury concentrati...

The validation of satellite ocean color data products is a critical component in establishing their measurement uncertainties, assessing their scientific utility, and identifying conditions for which their reliability is suspect. Such efforts require a considerable amount of high quality in situ data, preferably consistently processed and spanning the satellite mission lifetime. This paper outlines the NASA Ocean Biology Processing Group's (OBPG) method for validating satellite data products using in situ measurements as ground truth. Currently, the OBPG uses the described method for validating several historical and operational ocean color missions. By way of a case study, results for the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) are shown. These results indicate that for the majority of the global ocean, SeaWiFS data approach the target uncertainties of ± 5% for clear water radiances as defined prior to launch. Our results add confidence in the use of these data for global climate studies, where a consistent, high quality data set covering a multi-year time span is essential.

Global satellite ocean color instruments provide the scientific community a high-resolution means of studying the marine biosphere. Satellite data product validation and algorithm development activities both require the substantial accumulation of high-quality in-situ observations. The NASA Ocean Biology Processing Group maintains a local repository of in-situ marine bio-optical data, the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), to facilitate their ocean color satellite validation analyses. Data were acquired from SeaBASS and used to compile a large set of coincident radiometric observations and phytoplankton pigment concentrations for use in bio-optical algorithm development. This new data set, the NASA bio-Optical Marine Algorithm Data set (NOMAD), includes over 3400 stations of spectral water-leaving radiances, surface irradiances, and diffuse downwelling attenuation coefficients, encompassing chlorophyll a concentrations ranging from 0.012 to 72.12 mg m− 3. Metadata, such as the date, time, and location of data collection, and ancillary data, including sea surface temperatures and water depths, accompany each record. This paper describes the assembly and evaluation of NOMAD, and further illustrates the broad geophysical range of stations incorporated into NOMAD.

Mercury (Hg) in water, sediment, soils, seston, and biota were quantified for three streams in the Grand Portage National Monument (GRPO) in far northeastern Minnesota to assess ecosystem contamination and the potential for harmful exposure of piscivorous fish, wildlife, and humans to methylmercury (MeHg). Concentrations of total Hg in water, sediment, and soil were typical of those in forest ecosystems within the region, whereas MeHg concentrations and percent MeHg in these ecosystem components were markedly higher than values reported elsewhere in the western Great Lakes Region. Soils and sediment were Hg-enriched, containing approximately 4-fold more total Hg per unit of organic matter. We hypothesized that localized Hg enrichment was due in part to anthropogenic pollution associated with historic fur-trading activity. Bottom-up forcing of bioaccumulation was evidenced by MeHg concentrations in larval dragonflies, which were near the maxima for dragonflies sampled concurrently from five other national park units in the region. Despite its semi-remote location, GRPO is a Hg-sensitive landscape in which MeHg is produced and bioaccumulated in aquatic food webs to concentrations that pose ecological risks to MeHg-sensitive piscivores, including predatory fish, belted kingfisher, and mink.

The on-orbit calibration program for ocean color sensors involves both methodologies of tracking the instrument radiometric response over time through solar and lunar observations and the vicarious calibration, or tuning, of the instrument calibration against in situ data sources. This chapter discusses calibration strategies that have been developed for heritage instruments (SeaWiFS, Terra MODIS, Aqua MODIS, MERIS) and are being applied to a new instrument (SNPP VIIRS).

International audience; Photosynthetic production of organic matter by microscopic oceanic phytoplankton fuels ocean ecosystems and contributes roughly half of the Earth's net primary production. For 13 years, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission provided the first consistent, synoptic observations of global ocean ecosystems. Changes in the surface chlorophyll concentration, the primary biological property retrieved from SeaWiFS, have traditionally been used as a metric for phytoplankton abundance and its distribution largely reflects patterns in vertical nutrient transport. On regional to global scales, chlorophyll concentrations covary with sea surface temperature (SST) because SST changes reflect light and nutrient conditions. However, the ocean may be too complex to be well characterized using a single index such as the chlorophyll concentration. A semi-analytical bio-optical algorithm is used to help interpret regional to global SeaWiFS chlorophyll observations from using three independent, well-validated ocean color data products; the chlorophyll a concentration, absorption by CDM and particulate backscattering. First, we show that observed long-term, global-scale trends in standard chlorophyll retrievals are likely compromised by coincident changes in CDM. Second, we partition the chlorophyll signal into a component due to phytoplankton biomass changes and a component caused by physiological adjustments in intracellular chlorophyll concentrations to changes in mixed layer light levels. We show that biomass changes dominate chlorophyll signals for the high latitude seas and where persistent vertical upwelling is known to occur, while physiological processes dominate chlorophyll variability over much of the tropical and subtropical oceans. The SeaWiFS data set demonstrates complexity in the interpretation of changes in regional to global phytoplankton distributions and illustrates limitations for the assessment of phytoplankton dynamics using chlorophyll retrievals alone. (C) 2013 Elsevier Inc. All rights reserved.

Ocean color climate data records (CDRs) require water-leaving radiances with 5% absolute and 1% relative accuracies as input. Because of the amplification of any sensor calibration errors by the atmospheric correction, the 1% relative accuracy requirement translates into a 0.1% long-term radiometric stability requirement for top-of-the-atmosphere (TOA) radiances. The rigorous prelaunch and on-orbit calibration program developed and implemented for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) by the NASA Ocean Biology Processing Group (OBPG) has led to the incorporation of significant changes into the on-orbit calibration methodology over the 13-year lifetime of the instrument. Evolving instrument performance and ongoing algorithm refinement have resulted in updates to approaches for the lunar, solar, and vicarious calibration of SeaWiFS. The uncertainties in the calibrated TOA radiances are addressed in terms of accuracy (biases in the measurements), precision (scatter in the measurements), and stability (repeatability of the measurements). The biases are 2%–3% from lunar calibration and 1%–2% from vicarious calibration. The precision is 0.16% from solar signal-to-noise ratios, 0.13% from lunar residuals, and 0.10% from vicarious gains. The long-term stability of the TOA radiances, derived from the lunar time series, is 0.13%. The stability of the vicariously calibrated TOA radiances, incorporating the uncertainties of the in situ measurements and the atmospheric correction, is 0.30%. This stability of the radiometric calibration of SeaWiFS over its 13-year on-orbit lifetime has allowed the OBPG to produce CDRs from the ocean color data set.

The NASA VIIRS Ocean Science Team (VOST) has the task of evaluating Suomi NPP VIIRS ocean color data for the continuity of the NASA ocean color climate data records. The generation of science quality ocean color data products requires an instrument calibration that is stable over time. Since the VIIRS NIR Degradation Anomaly directly impacts the bands used for atmospheric correction of the ocean color data (Bands M6 and M7), the VOST has adapted the VIIRS on-orbit calibration approach to meet the ocean science requirements. The solar diffuser calibration time series and the solar diffuser stability monitor time series have been used to derive changes in the instrument response and diffuser reflectance over time for bands M1-M11.

The uncertainties associated with MERIS remote sensing reflectance (RRS) data derived from the SeaWiFS Data Analysis System (SeaDAS) are assessed with field observations. In agreement with the strategy applied for other sensors, a vicarious calibration is conducted using in situ data from the Marine Optical BuoY offshore Hawaii, and leads to vicarious adjustment factors departing from 1 by 0.2% to 1.6%. The three field data sets used for validation have been collected at fixed stations in the northern Adriatic Sea and the Baltic Sea, and in a variety of European waters in the Baltic, Black, Mediterranean and North Seas. Excluding Baltic waters, the mean absolute relative difference psi is between 10% and 14% for the spectral interval 490-560 nm, 16-18% at 443 nm, and 24-26% at 413 nm. In the Baltic Sea, the psi values are much higher for the blue bands characterized by low RRS amplitudes, but similar or lower at 560 and 665 nm. For the three validation sets, the root-mean-square differences decrease from approximately 0.0013 sr^-1 at 413 nm to 0.0002 sr^-1 at 665 nm, and are found similar or lower than those obtained for SeaWiFS or MODIS-Aqua. As derived from SeaDAS, the RRS records associated with these three missions thus provide a multi-mission data stream of consistent accuracy., JRC.H.3-Global environment monitoring

The atmospheric correction algorithm employed by the NASA Ocean Biology Processing Group requires an assumption of negligible water-leaving reflectance in the near-infrared region of the spectrum. For waters where this assumption is not valid, an optical model is used to estimate near-infrared water-leaving reflectance. We describe this optical model as implemented for the sixth reprocessing of the SeaWiFS mission-long time-series (September 2009). Application of the optical model resulted in significant reductions in the number of negative water-leaving reflectance retrievals in turbid and optically complex waters, and improved agreement with in situ chlorophyll-a observations. The incidence of negative water-leaving reflectance retrievals at 412 nm was reduced by 40%, while negative reflectance at 490 nm was nearly eliminated.

Monitoring of mercury in fish typically involves removal of individuals from the sampled population and subsequent analysis of fillets. This study assessed whether the analysis of fins, structures routinely clipped to mark released fish in population studies, could provide a nonlethal approach for estimating mercury concentrations in axial muscle (fillets). We analyzed fillets and selected fins from 401 northern pike (Esox lucius) and 79 walleye (Sander vitreus) from 21 lakes in Minnesota and Wisconsin, 19 Arctic grayling (Thymallus arcticus) from Toolik Lake, Alaska, and 14 winter flounder (Pseudopleuronectes americanus) from Long Island Sound, New York. On average, 83% of mercury in fins was methylmercury, and concentrations in the proximal portion were about half-those in the distal portion in pelvic fins. Mean concentrations of mercury in fins, averaged by species and fin type, ranged from 2.7 to 8.9% of those in fillets. Coefficients of determination (r2) for linear regressions of mercury concentrations in fillets against those in fins of individual fish ranged from 0.04 to 0.96 among species and water bodies (median r2 = 0.52). The concentration in fin clips was a better predictor of mercury in fillets for individual Arctic grayling (r2 = 0.65, n = 12 and r2 = 0.84, n = 8) and winter flounder (r2 = 0.94, n = 14) than for individual northern pike (median r2 = 0.56) or walleye (median r2 = 0.22) from a given lake. In northern pike in the 400-500 mm total-length interval, the mean concentrations of total mercury in caudal fins and fillets, averaged by lake (n = 12), were strongly correlated (r2 = 0.95). The analysis of composited samples of fin clips from fish within a restricted length interval could, therefore, be a useful screening tool for assessing the relative mercury contamination of fish among different water bodies.

Spaceborne ocean color sensors require vicarious calibration to sea-truth data to achieve accurate water-leaving radiance retrievals. The assumed requirements of an in situ data set necessary to achieve accurate vicarious calibration were set forth in a series of papers and reports developed nearly a decade ago, which were embodied in the development and site location of the Marine Optical BuoY (MOBY). Since that time, NASA has successfully used data collected by MOBY as the sole source of sea-truth data for vicarious calibration of the Sea-viewing Wide field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer instruments. In this paper, we make use of the 10-year, global time series of SeaWiFS measurements to test the sensitivity of vicarious calibration to the assumptions inherent in the in situ requirements (e.g., very low chlorophyll waters, hyperspectral measurements). Our study utilized field measurements from a variety of sources with sufficient diversity in data collection methods and geophysical variability to challenge those in situ restrictions. We found that some requirements could be relaxed without compromising the ability to vicariously calibrate to the level required for accurate water-leaving radiance retrievals from satellite-based sensors. (C) 2008 Optical Society of America.

The NASA Ocean Biology Processing Group's Calibration and Validation Team has analyzed the mission-long Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) on-orbit gain and detector calibration time series to verify that lunar calibrations, obtained at nonstandard gains and radiance ranges, are valid for Earth data collected at standard gains and typical ocean, cloud, and land radiances. For gain calibrations, a constant voltage injected into the postdetector electronics allows gain ratios to be computed for all four detectors in each band. The on-orbit lunar gain ratio time series show small drifts for the near infrared bands. These drifts are propagated into the ocean color data through the atmospheric correction parameter epsilon, which uses the 765/865 nm band ratio. An anomaly analysis of global mean normalized water-leaving radiances at 510 nm shows a small decrease over the mission, while an analysis of epsilon shows a corresponding increase. The drifts in the lunar time series for the 765 and 865 nm bands were corrected. An analysis of the revised water-leaving radiances at 510 nm shows the drift has been eliminated, while an analysis of epsilon shows a reduced drift. For detector calibrations, solar diffuser observations made by the individual detectors in each band allows the response of the detectors to be monitored separately. The mission-long time series of detector calibration data show that the variations in the response of the individual detectors are less than 0.5% over the mission for all bands except the 865 nm band, where the variations are less than 1%.

The NASA Ocean Biology Processing Group's Calibration and Validation (Cal/Val) Team has used SeaWiFS onorbit lunar and gain calibration data, in conjunction with mission-long trends of global ocean color data products, to diagnose and correct recently emergent residual drifts in the radiometric response of the instrument. An anomaly analysis of the time series of global mean normalized water-leaving radiances, the atmospheric correction parameter ∈ , and chlorophyll show significant departures from the mission-long trends beginning in January 2006. The lunar time series trends for the near infrared (NIR) bands (765 nm and 865 nm) show significant periodic departures from mission-long trends beginning at the same time. ∈ is dependent on the ratio of these two bands; trends in this parameter would propagate through the atmospheric correction algorithm to the retrieved water-leaving radiances. An analysis of fit residuals from the lunar time series shows that the focal plane temperature dependencies of the radiometric response of the detectors for these two bands have changed over the 9+ year mission. The Cal/Val Team has used these residuals to compute a revised set of temperature corrections for data collected starting 1 January 2006. The lunar calibration data and a mission-long ocean color test data set have been reprocessed with the revised temperature corrections. The reprocessed data show that the trends in the NIR bands have been minimized and that the departures of the water-leaving radiances, ∈ , and chlorophyll from the mission-long trends have been greatly reduced. The anomaly analysis of the water-leaving radiances in the 510 nm band still shows a residual drift of -2.9% over the mission. The anomaly analysis of the ∈ time series shows a residual drift of +2.8% over the mission. A corresponding drift is not observed in the lunar calibration time series for the NIR bands. The lunar calibration data are obtained at a different set of instrument gains than are the ocean data. An analysis of the mission-long time series of on-orbit gain calibration data shows that the gain ratios for the NIR bands change -0.76% (765 nm) and +0.56% (865 nm) over the mission, corresponding to a -1.3% drift in the band ratio. The lunar calibration time series for the NIR bands have been corrected for this gain drift, and the change in radiometric response over time has been recomputed for each band. The mission-long ocean color test data set has been reprocessed with these revised corrections for the NIR bands. The anomaly analysis of the reprocessed water-leaving radiances at 510 nm shows the drift to have been essentially eliminated, while the anomaly analysis of epsilon shows a reduced drift of +2.0%. These analyses show the sensitivity of ocean color data to small drifts in instrument calibration and demonstrate the use of time series of global mean geophysical parameters to monitor the long-term stability of the instrument calibration on orbit. The two updates to SeaWiFS radiometric calibration have been incorporated into the recent reprocessing of the SeaWiFS mission-long ocean data set.

Ocean color satellites provide a mechanism for studying the marine biosphere on temporal and spatial scalesotherwise unattainable via conventional in situ sampling methods. These satellites measure visible and infraredradiances, which are used to estimate additional geophysical data products, such as the concentration of thephytoplankton pigment chlorophyll a, C a , via the application of secondary bio-optical algorithms. The op-erational C a algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate ResolutionImaging Spectroradiometer (MODIS), for example, perform well in the global open ocean, but often degradein more optically complex coastal environments where global parameterizations are less applicable. Organiza-tions such as the Chesapeake Bay Program, which have interest in using SeaWiFS and MODIS data productsto facilitate regional monitoring activities, must rely on locally parameterized algorithms to achieve requisiteaccuracies. To facilitate algorithm selection, the NASA Ocean Biology Processing Group recently developed theinfrastructure to spatially and temporally evaluate a long-term regional time-series of satellite observations usingin situ measurements as ground-truth. Here, we present this approach using a case study in the Chesapeake Bay,where a series of C

Requirements on accuracy of the atmospheric correction of satellite ocean color data are rather high, and so far attempts to solve this problem as needed have not been quite successful, especially at high latitudes and in coastal waters. New approach to the atmospheric correction problem consists in simultaneous retrieval of the unknown aerosol and ocean reflectances ρα(λi) and ρw(λi) from the top-of-the-atmosphere reflectance ρt(λi) with use of all spectral channels of a satellite sensor in infrared and visible ranges. The approach is based on parameterization of the spectral behavior of ρα(λi) and ρw(λi) with help of several basic functions. In this way the problem reduces to determination of several weight coefficients at these basic functions. This allows us to cut drastically the size and number of required lookup tables. The inversion problem is solved by a least square method with inequality constraints. It is shown that the new algorithm results in better agreement with in situ measured ρw(λi), compared with the standard SeaWiFS algorithm, in Case 2 waters.© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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.

The NASA Ocean Biology Processing Group (OBPG) developed two independent calibrations of the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate resolution reflective solar bands using solar diffuser measurements and lunar observations, and implemented a combined solar- and lunar-based calibration to track temporal changes in radiometric response of the instrument. Differences between the solar and lunar data sets have been used to identify issues and verify improvements in each. Linearization of the counts-to-radiance conversion yields a more consistent calibration at low radiance levels. Correction of a recently identified error in the VIIRS solar unit vector coordinate frame has been incorporated into the solar data and diffuser screen transmission functions. Temporal trends in the solar diffuser stability monitor data have been evaluated and addressed. Fits to the solar calibration time series show mean residuals per band of 0.067%-0.17%. Periodic residuals in the VIIRS lunar data are confirmed to arise from a wavelength-dependent libration effect for the sub-spacecraft point in the output of the U.S. Geological Survey Robotic Lunar Observatory photometric model of the Moon. Temporal variations in the relative spectral responses for each band have been assessed, and significant impact on band M1 (412 nm) lunar data has been identified and rectified. Fits to the lunar calibration time series, incorporating sub-spacecraft point libration corrections, show mean residuals per band of 0.069%-0.20%. Lunar calibrations have been used to adjust the solar-derived radiometric corrections for bands M1, M3, and M4. After all corrections, the relative differences in the solar and lunar calibrations for bands M1-M7 are 0.093%-0.22%. The OBPG has achieved a radiometric stability for the VIIRS on-orbit calibration that is commensurate with those achieved for SeaWiFS and Aqua MODIS, supporting the incorporation of VIIRS data into the long-term NASA ocean color data record.

The NASA Ocean Biology Processing Group's Calibration and Validation Team has used monthly lunar calibrations of SeaWiFS to establish and maintain the on-orbit radiometric stability of instrument at the 0.1% level over its 9-year mission. The Cal/Val Team has compared the SeaWiFS lunar observations with the USGS ROLO photometric model of the Moon to verify the long-term stability of the SeaWiFS radiometric calibration. This stability has allowed the Team to apply a system-level vicarious calibration of the sensor/atmospheric calibration algorithm that is independent of time, yielding a single gain per band. SeaWiFS bands 1-6 (412-670 nm) are calibrated against water-leaving radiances measured by the Marine Optical Buoy (MOBY) that have been propagated to the top of the atmosphere. Band 7 (765 nm) is calibrated relative to band 8 (865 nm) so that the atmospheric correction algorithm selects maritime aerosol models over open ocean scenes. The long-term radiometric stability of SeaWiFS allows the Cal/Val Team to directly compare the mean residuals of the lunar observations from the ROLO model with the vicarious gains. A linear fit of the vicarious gains vs - (mean ROLO residual) for bands 1-6 gives a slope of 1.084 with a correlation of 0.980. The predicted mean ROLO residual for band 7, computed from the observed mean residual for band 8 and the vicarious gain for band 7, agrees with the observed mean residual for band 7 to within 0.5%. The radiometric stability of SeaWiFS allows the comparison of the prelaunch calibration of SeaWiFS, the calibration of MOBY, and the calibration of the USGS ROLO model. Such a comparison is of interest to other Earth-observing instruments which use the Moon as a calibration reference, such as MODIS, VIIRS, and ABI.