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.

[1] Data assimilation experiments with the coupled physical, bio-optical model of Monterey Bay are presented. The objective of this study is to investigate whether the assimilation of satellite-derived bio-optical properties can improve the model predictions (phytoplankton population, chlorophyll) in a coastal ocean on time scales of 1-5 days. The Monterey Bay model consists of a physical model based on the Navy Coastal Ocean Model and a biochemical model which includes three nutrients, two phytoplankton groups (diatoms and small phytoplankton), two groups of zooplankton grazers, and two detrital pools. The Navy Coupled Ocean Data Assimilation system is used for the assimilation of physical observations. For the assimilation of bio-optical observations, we used reduced-order Kalman filter with a stationary forecast error covariance. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions estimated from a monthlong model run. With the assimilation of satellite-derived bio-optical properties (chlorophyll a or absorption due to phytoplankton), the model was able to reproduce intensity and tendencies in subsurface chlorophyll distributions observed at water sample locations in the Monterey Bay, CA. Data assimilation also improved agreement between the observed and model-predicted ratios between diatoms and small phytoplankton populations. Model runs with or without assimilation of satellite-derived bio-optical observations show underestimated values of nitrate as compared to the water sample observations. We found that an instantaneous update of nitrate based on statistical relations between temperature and nitrate corrected the model underestimation of the nitrate fields during the multivariate update.

The U.S. Food and Drug Administration recently published a Vibrio parahaemolyticus risk assessment for consumption of raw oysters that predicts V. parahaemolyticus densities at harvest based on water temperature. We retrospectively compared archived remotely sensed measurements (sea surface temperature, chlorophyll, and turbidity) with previously published data from an environmental study of V. parahaemolyticus in Alabama oysters to assess the utility of the former data for predicting V. parahaemolyticus densities in oysters. Remotely sensed sea surface temperature correlated well with previous in situ measurements (R(2) = 0.86) of bottom water temperature, supporting the notion that remotely sensed sea surface temperature data are a sufficiently accurate substitute for direct measurement. Turbidity and chlorophyll levels were not determined in the previous study, but in comparison with the V. parahaemolyticus data, remotely sensed values for these parameters may explain some of the variation in V. parahaemolyticus levels. More accurate determination of these effects and the temporal and spatial variability of these parameters may further improve the accuracy of prediction models. To illustrate the utility of remotely sensed data as a basis for risk management, predictions based on the U.S. Food and Drug Administration V. parahaemolyticus risk assessment model were integrated with remotely sensed sea surface temperature data to display graphically variations in V. parahaemolyticus density in oysters associated with spatial variations in water temperature. We believe images such as these could be posted in near real time, and that the availability of such information in a user-friendly format could be the basis for timely and informed risk management decisions.

Abstract. The regional and monthly intensity of photosynthetically available radiation (PAR) (350-700 nm) just below the sea surface (EdnA}0 for the Arabian Sea is determined from solar irradiance models and 7 years of satellite data (1979)(1980)(1981)(1982)(1983)(1984)(1985). Model results of high spatial resolution (18 km) PAR distribution computed from actual monthly measurements (aerosols, cloud cover, and ozone) displayed small-scale patchiness that is not observed in PAR climatology models. Two elevated PAR periods are observed each year, as opposed to a single elevated period per year observed in the North Atlantic during the summer. When the biannual cycle for each of the 7 years is compared with the 7-year average, interannual changes in intensity and time are observed. Additionally, the PAR cycle is found to vary regionally within the Arabian Sea. The bimodal PAR distribution shows elevated peaks in May and October and minima in December (corresponding to the winter equinox) and July. The second minima occurs at the onset of the southwest monsoon, apparently in response to increased cloud cover and aerosols associated with the monsoon. This summer minima varied latitudinally. It originates in the southern regions (0ø-10 ø latitude) in April and migrates north as the influence of the southwest monsoon moves northward, reaching the northern Oman coast (20 ø latitude) in August. Additionally, the summer minima is less pronounced as the southwest monsoon moves northward. Maximum PAR intensity is observed in early spring (preceding the minima), originating in the southern Arabian Sea and extending northward into the central Arabian Sea. The timing of the northward movement of this spring maximum is slightly different each year. The net yearly PAR intensity for each of the 7 years appears to remain approximately the same, despite the interannual variability in the cycle and regional variability. The timing and location of PAR cycles are important since they must be coupled with nutrient availability to understand biological cycles. We determined that for the Arabian Sea, PAR cycles determined by climatology may be inadequate to define the submarine light field and that high-resolution PAR cycles are needed to resolve realistic bio-optical and nutrient cycles.

Abstract:The Ocean Color Monitor (OCM) provides radiance measurements in eight visible and near-infrared bands, similar to the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) but with higher spatial resolution. For small-to moderate-sized coastal lakes and estuaries, where the 1 × 1 km spatial resolution of SeaWiFS is inadequate, the OCM provides a good alternative because of its higher spatial resolution (240 × 360 m) and an exact repeat coverage of every two days. This paper describes a detailed step-by-step atmospheric correction procedure for OCM data applicable to coastal Case 2 waters. This development was necessary as accurate results could not be obtained for our Case 2 water study area in coastal Louisiana with OCM data by using existing atmospheric correction software packages. In addition, since OCM-retrieved radiances were abnormally low in the blue wavelength region, a vicarious calibration procedure was developed. The results of our combined vicarious calibration and atmospheric correction procedure for OCM data were compared with the results from the SeaWiFS Data Analysis System (SeaDAS) software package outputs for SeaWiFS and OCM data. For Case 1 waters, our results matched closely with SeaDAS results. For Case 2 waters, our results demonstrated closure with in situ radiometric measurements, while SeaDAS produced negative normalized water leaving radiance ( n L w ) and remote sensing reflectance (R rs ). In summary, our procedure OPEN ACCESSRemote Sens. 2012, 4 1717 resulted in valid n L w and R rs values for Case 2 waters using OCM data, providing a reliable method for retrieving useful n L w and R rs values which can be used to develop ocean color algorithms for in-water substances (e.g., pigments, suspended sediments, chromophoric dissolved organic matter, etc.) at relatively high spatial resolution in regions where other software packages and sensors such as SeaWiFS and Moderate Resolution Imaging Spectrometer (MODIS) have proven unsuccessful. The method described here can be applied to other sensors such as OCM-2 or other Case 2 water areas.