Richard W. Gould

Spectral dependence of the scattering coefficient in case 1 and case 2 waters

An approximate linear relationship between the scattering coefficient and the wavelength of light in the visible is found in case 1 and case 2 waters. From this relationship, we estimate scattering at an unknown wavelength from scattering at a single measured wavelength. This approximation is based on measurements in a 1.5-m-thick surface layer collected with an AC9 instrument at 63 stations in the Arabian Sea, northern Gulf of Mexico, and coastal North Carolina. The light-scattering coefficient at 412 nm ranged from 0.2 to 15.1 m(-1) in these waters, and the absorption coefficient at 412 nm ranged from 0.2 to 4.0 m(-1). A separate data set for 100 stations from Oceanside, California, and Chesapeake Bay, Virginia, was used to validate the relationship. Although the Oceanside waters were considerably different from the developmental data set (based on absorption-to-scattering ratios and single-scattering albedos), the average error between modeled and measured scattering values was 6.0% for the entire test data set over all wavelengths (without regard to sign). The slope of the spectral scattering relationship decreases progressively from high-scattering, turbid waters dominated by suspended sediments to lower-scattering, clear waters dominated by phytoplankton.

Optical scattering and backscattering by organic and inorganic particulates in U.S. coastal waters

We present the results of a study of optical scattering and backscattering of particulates for three coastal sites that represent a wide range of optical properties that are found in U.S. near-shore waters. The 6000 scattering and backscattering spectra collected for this study can be well approximated by a power-law function of wavelength. The power-law exponent for particulate scattering changes dramatically from site to site (and within each site) compared with particulate backscattering where all the spectra, except possibly the very clearest waters, cluster around a single wavelength power-law exponent of -0.94. The particulate backscattering-to-scattering ratio (the backscattering ratio) displays a wide range in wavelength dependence. This result is not consistent with scattering models that describe the bulk composition of water as a uniform mix of homogeneous spherical particles with a Junge-like power-law distribution over all particle sizes. Simultaneous particulate organic matter (POM) and particulate inorganic matter (PIM) measurements are available for some of our optical measurements, and site-averaged POM and PIM mass-specific cross sections for scattering and backscattering can be derived. Cross sections for organic and inorganic material differ at each site, and the relative contribution of organic and inorganic material to scattering and backscattering depends differently at each site on the relative amount of material that is present.

Distribution and composition of biogenic particulate matter in a Gulf Stream warm-core ring

Abstract We have characterized the biogenic particle field in Gulf Stream warm-core ring 82-B in June of 1982. Our observations include chlorophyll α and phaeopigments, ATP, particulate organic carbon and nitrogen, biogenic silica, total particle volume and size distribution, bacterial abundance and picoplankton biomass, and the abundances of diatoms, dinoflagellates and coccolithophorids in the upper 700 m along two transects of the ring. A distinct maximum in phytoplankton biomass occurred within the thermocline (20 to 40 m) at the rings center of rotation. This maximum had not been present in late April, and apparently developed within 3 to 4 weeks after the ring stratified in mid May. It exhibited a high degree of axial symmetry about the center of the ring, with biomass decreasing outward from ring center. A second biomass maximum associated with shelf surface water was being entrained into the anticyclonic flow field of the ring 60 to 70 km from its center. Maximum chlorophyll α and ATP concentrations observed in the two biomass maxima were similar, but the ring-center maximum was 2 to 10 times richer in particulate carbon, biogenic silica, particles > 5 μm in diameter, dinoflagellates, diatoms and estimated organic detritus, while the entrained shelf water had 2 to 5 times greater abundances of unicellular monads. Heterotrophic bacterial abundance and biomass, and the abundance of cocoid cyanobacteria were maximal in the region of highest rotational velocity 40 to 50 km from ring center. In this region the abundances of bacteria and cyanobacteria were 2 to 5 times as great as at the center of the ring. Two possible mechanisms can explain the development of an axially symmetrical maximum in biogenic particulate matter in the center of a warm-core ring: concentration by the flow field and in situ growth. Our data on the distribution and composition of biogenic material in ring 82-B indicate a greater likehood that this particular ring-center maximum developed in situ .

Comparisons of optical properties of the coastal ocean derived from satellite ocean color and in situ measurements

Satellite-derived optical properties are compared to in situ mooring and ship-based measurements at a coastal site. Comparisons include remote sensing reflectance (R(rs)), chlorophyll concentration (Chl) using two different Chl algorithms, and spectral absorption [a(pg)(lambda)] and backscattering coefficients [b(b)(555)] using three different bio-optical algorithms. For mooring/shipboard comparisons, we observed mean relative errors of 70.5%/-3.8% (SeaWiFS OC4v4), -21.4%/-49.3% (SeaWiFS Stumpf), 109.5%/13.4% (MODIS OC3m) and 0.5%/-48.9% (MODIS Stumpf) for Chl. For satellite-derived and mooring comparisons of a(pg)(412), we found mean relative errors of -69.4% (-67.1%), -52.6% (- 48.9%), and -62.7% (-65.4%) for the Arnone, GSM, and QAA algorithms for SeaWiFS (MODIS), respectively. Mean relative errors of 21.3%, 19.9%, and 16.5% were found between SeaWiFS-derived (Arnone, GSM, and QAA algorithms, respectively) and moored b(b)(555) measurements. Discrepancies in Rrs at blue wavelengths are attributed to the satellite atmospheric correction and sea surface variations of the moored radiometers. High spatial and temporal variability of bio-optical properties coupled with differences in measurement techniques (pixel versus point) contribute to inconsistencies between remotely sensed and in situ biooptical properties.

Barriers to adopting satellite remote sensing for water quality management

Sustainable practices require a long-term commitment to creating solutions to environmental, social, and economic issues. The most direct way to ensure that management practices achieve sustainability is to monitor the environment. Remote sensing technology has the potential to accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long time periods, and is now proving useful in coastal waters, estuaries, lakes, and reservoirs, which are relevant to water quality managers. Comprehensive water quality climate data records have the potential to provide rapid water quality assessments, thus providing new and enhanced decision analysis methodologies and improved temporal/spatial diagnostics. To best realize the full application potential of these emerging technologies an open and effective dialogue is needed between scientists, policy makers, environmental managers, and stakeholders at the federal, state, and local levels. Results from an internal US Environmental Protection Agency qualitative survey were used to determine perceptions regarding the use of satellite remote sensing for monitoring water quality. The goal of the survey was to begin understanding why management decisions do not typically rely on satellite-derived water quality products.

Estimating the beam attenuation coefficient in coastal waters from AVHRR imagery

This paper presents an algorithm to estimate particle beam attenuation at 660 nm (cp660) in coastal areas using the red and near-infrared channels of the NOAA AVHRR satellite sensor. In situ reflectance spectra and cp660 measurements were collected at 23 stations in Case I and II waters during an April 1993 cruise in the northern Gulf of Mexico. The reflectance spectra were weighted by the spectral response of the AVHRR sensor and integrated over the channel 1 waveband to estimate the atmospherically corrected signal recorded by the satellite. An empirical relationship between integrated reflectance and cp660 values was derived with a linear correlation coefficient of 0.88. Because the AVHRR sensor requires a strong channel 1 signal, the algorithm is applicable in highly turbid areas (cp660 > 1.5 m−1) where scattering from suspended sediment strongly controls the shape and magnitude of the red (550–650 nm) reflectance spectrum. The algorithm was tested on a data set collected 2 years later in different coastal waters in the northern Gulf of Mexico and satellite estimates of cp660 averaged within 37% of measured values. Application of the algorithm provides daily images of nearshore regions at 1 km resolution for evaluating processes affecting ocean color distribution patterns (tides, winds, currents, river discharge). Further validation and refinement of the algorithm are in progress to permit quantitative application in other coastal areas. Published by Elsevier Science Ltd

Assessing the Application of Cloud–Shadow Atmospheric Correction Algorithm on HICO

Several ocean color earth observation satellite sensors are presently collecting daily imagery, including the Hyperspectral Imager for the Coastal Ocean (HICO). HICO has been operating aboard the International Space Station since its installation on September 24, 2009. It provides high spatial resolution hyperspectral imagery optimized for the coastal ocean. Atmospheric correction, however, still remains a challenge for this sensor, particularly in optically complex coastal waters. In this paper, we assess the application of the cloud-shadow atmospheric correction approach on HICO data and validate the results with the in situ data. We also use multiple sets of cloud, shadow, and sunlit pixels to correct a single image multiple times and intercompare the results to assess variability in the retrieved reflectance spectra. Retrieved chlorophyll values from this intercomparison are similar and also agree well with the in situ chlorophyll measurements.

Extending Coastal Zone Color Scanner estimates of the diffuse attenuation coefficient into Case II waters

An iterative technique has been developed to improve coastal zone color scanner (CZCS) estimates of upwelled subsurface water radiances (Lu) in Case II waters. Regional relationships between the diffuse attenuation coefficient measured at 490 nm (K490) and Lu measured at 443, 520, and 550 nm were developed using data collected in the northern Gulf of Mexico in April 1993. These relationships are used to iteratively adjust the aerosol contribution to the total radiance measured at the sensor. The open-ocean assumption that there is no water-leaving radiance at 670 nm is not valid in coastal areas with a high sediment load. If the sediment signal is not considered the aerosol contribution is overestimated during the atmospheric correction of the CZCS data. Subsequently, the calculations of Lu are underestimated, even to the point of negative radiances calculated in extremely turbid areas. Because the Lu are used in the geophysical algorithms to estimate K490 and pigment concentration, these derived products are overestimated in Case II waters if the 670 nm radiance is not partitioned into aerosol and sediment components.

Optical Algorithm for Cloud Shadow Detection Over Water

The application of ocean color product retrieval algorithms for pixels containing cloud shadows leads to erroneous results. Thus, shadows are an important scene type that should be identified and excluded from the set of clear-sky pixels. In this paper, we present an optical cloud shadow-detection technique called the Cloud Shadow Detection Index (CSDI). This approach is for homogeneous water bodies such as deep waters where shadow detection is very challenging due to the relatively small differences in the brightness values of the shadows and neighboring sunlit or some other regions. The CSDI technique is developed based on the small differences between the total radiances reaching the sensor from the shadowed and neighboring sunlit regions of similar optical properties by amplifying the differences through integrating the spectra of the two regions. The Integrated Value (IV) is then normalized by the mean of the IVs within a spatial adaptive sliding box where atmospheric and marine optical properties are assumed homogeneous. Assuming that the true color and the IV images represent accurate shadow locations, the results were visually compared. The CSDI images agree reasonably well with the corresponding true color and the IV images over open ocean. Also, the shape of the cloud shadow particularly for the isolated cloud closely follows that of the cloud, as expected, reconfirming the potential of the CSDI technique.

Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery

We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite ocean color imagery are related to a variety of factors, including errors associated with sensor calibration, atmospheric correction, and the bio-optical inversion algorithms. In many cases, selection of an inappropriate or erroneous aerosol model during atmospheric correction can dominate the errors in the satellite estimation of the normalized water-leaving radiances (nLw), especially over turbid, coastal waters. These errors affect the downstream bio-optical properties. Here, we focus on the impact of aerosol model selection on the nLw radiance estimates by comparing Aerosol Robotic Network-Ocean Color (AERONET-OC) measurements of nLw and aerosol optical depth (AOD) to satellite-derived values from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We also apply noise to the satellite top-of-atmosphere (TOA) radiance values in the two near-infrared (NIR) wavelengths used for atmospheric correction, to assess the effect on aerosol model selection and nLw retrievals. In general, for the data sets examined, we found that as little as 1% uncertainty (noise) in the NIR TOA radiances can lead to the selection of a different pair of bounding aerosol models, thus changing nLw retrievals. We also