OCEAN COLOR CHLOROPHYLL ALGORITHMS FOR SEAWIFS

A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, pr ecision, and suitability of a wide variety of ocean color chlorophyll algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The radiance-chlorophyll data were assembled from various sources dur ing the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is co mposed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 mu g L-1. Most of the observations are from Case I no npolar waters, and similar to 20 observations are from more turbid coa stal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlor ophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic pol ynomial formulations were generally superior to other kinds of equatio ns. Empirical algorithms with increasing complexity (number of coeffic ients and wavebands), were calibrated to the SeaBAM data, and evaluate d to illustrate the relative merits of different formulations. The oce an chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) fu nction which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and h as been chosen as the at-launch SeaWiFS operational chlorophyll a algo rithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ra tio formulation. This maximum band ratio (MBR) is a new approach in em pirical ocean color algorithms and has the potential advantage of main taining the highest possible satellite sensor signal:noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.