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The quantum yield of photosynthesis (mol C/mol photons) was calculated at six depths for the waters of the Marine Light-Mixed Layer (MLML) cruise of May 1991. As there were photosynthetically available radiation (PAR) but no spectral irradiance measurements for the primary production incubations, three ways are presented here for the calculation of the absorbed photons (AP) by phytoplankton for the purpose of calculating phi. The first is based on a simple, nonspectral model; the second is based on a nonlinear regression using measured PAR values with depth; and the third is derived through remote sensing measurements. We show that the results of phi calculated using the nonlinear regreesion method and those using remote sensing are in good agreement with each other, and are consistent with the reported values of other studies. In deep waters, however, the simple nonspectral model may cause quantum yield values much higher than theoretically possible.

An atmospheric-correction method which uses cloud-shaded pixels together with pixels in a neighboring region of similar optical properties is described. This cloud-shadow method uses the difference between the total radiance values observed at the sensor for these two regions, thus removing the nearly identical atmospheric radiance contributions to the two signals (e.g. path radiance and Fresnel-reflected skylight). What remains is largely due to solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by the direct solar irradiance reaching the sea surface and correction for some second-order effects provides the remote-sensing reflectance of the ocean at the location of the neighbor region, providing a known 'ground target' spectrum for use in testing the calibration of the sensor. A similar approach may be useful for land targets if horizontal homogeneity of scene reflectance exists about the shadow. Monte Carlo calculations have been used to correct for adjacency effects and to estimate the differences in the skylight reaching the shadowed and neighbor pixels.

More than 90 percent of the signal at an ocean-viewing, satellite sensor is due to the atmosphere, so a 5 percent sensor-calibration error viewing a target that contributes but 10 percent of the signal received at the sensor may result in a target-reflectance error of more than 50 percent. Since prelaunch calibration accuracies of 5 percent are typical of space-sensor requirements, recalibration of the sensor using ground-base methods is required for low-signal target. Known target reflectance or water-leaving radiance spectra and atmospheric correction parameters are required. In this article we describe an atmospheric-correction method that uses cloud shadowed pixels in combination with pixels in a neighborhood region of similar optical properties to remove atmospheric effects from ocean scenes. These neighboring pixels can then be used as known reflectance targets for validation of the sensor calibration and atmospheric correction. The method uses the difference between water-leaving radiance values for these two regions. This allows nearly identical optical contributions to the two signals (e.g., path radiance and Fresnel-reflected skylight) to be removed, leaving mostly solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by incident solar irradiance reaching the sea surface provides the remote-sensing reflectance of the ocean at the location of the neighbor region.

AVIRIS is a testbed for future spacecraft sensors (such as HIRIS and MODIS) planned for the Earth Observing System. Model-derived absorption coefficients at 415 nm, a(415), and back-scattering coefficients at 671 nm, b sub b (671) for Tampa Bay waters were used to create images from AVIRIS data of the dissolved component of a(415) due to gelbstoff, a sub g (415), and salinity. Images of a sub g (415), salinity, and b sub b (671) were used to depict the distribution of dissolved and particulate constituents, respectively, for Tampa Bay plume during late, ebb-tidal conditions. Salinity covaried with a sub g (415), which provided a means of mapping salinity from the a sub g (415) imagery. The concentration of suspended particles, as inferred from b sub g (671), was extremely variable in the shallow regions where waves and currents interacted. Pollutants covarying with fresh water or suspended sediments can be mapped from a sub g (415) and b sub b (671) images, respectively.

A reflectance model developed to estimate chlorophyll a concentrations in the presence of marine colored dissolved organic matter, pheopigments, detritus, and bacteria is presented. Nomograms and lookup tables are generated to describe the effects of different mixtures of chlorophyll a and these degradation products on the R(412):R(443) and R(443):R(565) remote-sensing reflectance or irradiance reflectance ratios. These are used to simulate the accuracy of potential ocean color satellite algorithms, assuming that atmospheric effects have been removed. For the California Current upwelling and offshore regions, with chlorophyll a not greater than 1.3 mg/cu m, the average error for chlorophyll a retrievals derived from irradiance reflectance data for degradation product-rich areas was reduced from +/-61 percent to +/-23 percent by application of an algorithm using two reflectance ratios rather than the commonly used algorithm applying a single reflectance ratio.

This paper presents an algorithm, called the two-component method, to distinguish between two aerosol types in a remote color-scanner image and to determine their relative concentrations by observing the radiance contribution from each aerosol type at the satellite. The algorithm is applied to data from a time series of CZCS orbits during which both the Saharan dust and a bluish haze due to chlorophyll presence have been observed in the coastal zone. The results are compared with in situ measurements and to values derived from CZCS imagery by single-component methods, showing reasonable agreement between in situ measurements and values estimated by the two-component method. In imagery derived using single-component methods, the aerosol and chlorophyll fields appeared confounded in imagery where several types of aerosol were present.

The present paper is concerned with studies related to the capture of aeolian mineral particles in the Sargasso Sea region in late June 1980. Attention is given to measurement techniques, aerosol sampling, particle trap sampling, investigations utilizing scanning electron microscopy, and the obtained results. Conceivable sources for nonbiogenic particles measured in the water column are related to fallout from the Mount St. Helens eruption and soil materials transported by winds from the North American or African continents. It is found that present aerosol transport models are not adequaely addressing the transport of giant particles from the Sahara to the Sargasso Sea. Data regarding the variation of Sargasso Sea aerosol mass concentrations with time are presented in a table.

An in situ instrument designed to measure the spectral attenuation coefficient of seawater and the ocean remote-sensing reflectance from 400 to 750 nm is in the test and development stage. It employs a 256 channel, charge-coupled type of linear array measuring the spectral intensities diffracted by a grating. Examples of the types of data delivered by this instrument have been simulated using a breadboard laboratory instrument and an above-water, solid-state radiometer. Algorithms developed using data from these instruments provide measures of chlorophyll a plus phaeophytin a concentrations from less than 0.1 to 77.0 mg/cu m, gelbstoff spectral absorption coefficients, and detrital spectral backscattering coefficients for waters of the west Florida shelf.

Instrument concepts which measure ocean temperature, chlorophyll, sediment and Gelbstoffe concentrations in three dimensions on a quantitative, quasi-synoptic basis were considered. Coastal zone color scanner chlorophyll imagery, laser stimulated Raman temperaure and fluorescence spectroscopy, existing airborne Lidar and laser fluorosensing instruments, and their accuracies in quantifying concentrations of chlorophyll, suspended sediments and Gelbstoffe are presented. Lidar applications to phytoplankton dynamics and photochemistry, Lidar radiative transfer and signal interpretation, and Lidar technology are discussed.