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Passive ocean-color data at 32 wavelengths in the visible domain and laser-induced fluorescence line heights of chlorophyll and phycoerythrin, measured simultaneously from an aircraft in the New York Bight area, are used to examine the problem of developing algorithms for pigment retrieval from ocean-color data that would be capable of distinguishing between chlorophyll and phycoerythrin. Using factor analysis, it is shown that it is indeed possible to develop such algorithms. Furthermore, the wavelengths used in the algorithms can be reduced from 32 to 6 (similar to the SeaWiFS channels) without much loss in information. These multiwavelength algorithms yield significantly higher correlation coefficients for chlorophyll compared with the conventional blue-green ratio used for retrieval of this pigment. The Coastal Zone Color Scanner wavelengths appear to be inadequate for quantitative retrieval of the phycoerythrin signal.

Remote sensing of ocean color, applied to the estimation of chlorophyll biomass, is discussed for the case where the vertical distribution of phytoplankton pigments is nonuniform. Using a spectral model of reflectance, the consequences of vertical structure are evaluated by sensitivity analysis on a generalized pigment profile. It is shown that the assumption of a vertically homogeneous chlorophyll distribution can lead to significant errors (relative error exceeding 100%) in the estimation from satellite data of photic depth and total pigment content in the photic zone. The errors are shown to be functions of the parameters of the pigment profile. It is further shown that, if the shape of the pigment profile is known from independent data, the entire pigment profile may be recovered from the satellite data by making slight changes in the existing algorithms for chlorophyll retrieval.

Satellites provide the only avenue by which marine primary production can be studied at ocean-basin scales. With maps of chlorophyll distribution derived from remotely sensed data on ocean color as input, deduction of a suitable algorithm for primary production is a problem in applied plant physiology. An algorithm is proposed that combines a spectral and angular model of submarine light with a model of the spectral response of algal photosynthesis. To apply the algorithm at large horizontal scale, a dynamic biogeography is needed for the physiological rate parameters and the biological structure of the water column. Fieldwork to obtain this type of data should be undertaken so that the use of satellite data in modern biological oceanography may be optimized.