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Ocean Color Chlorophyll Algorithms for SEAWIFS

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TLDR
In this article, a large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor).
Abstract
A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, 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 during the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is composed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 μg L−1. Most of the observations are from Case I nonpolar waters, and ∼20 observations are from more turbid coastal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlorophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic polynomial formulations were generally superior to other kinds of equations. Empirical algorithms with increasing complexity (number of coefficients and wavebands), were calibrated to the SeaBAM data, and evaluated to illustrate the relative merits of different formulations. The ocean chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) function which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and has been chosen as the at-launch SeaWiFS operational chlorophyll a algorithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ratio formulation. This maximum band ratio (MBR) is a new approach in empirical ocean color algorithms and has the potential advantage of maintaining the highest possible satellite sensor signal: noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.

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Bio-Optical Inversion in Highly Turbid and Cyanobacteria-Dominated Waters

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Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain

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Fishery forecast using OCM chlorophyll concentration and AVHRR SST: validation results off Gujarat coast, India

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An optimized Chlorophyll a switching algorithm for MERIS and OLCI in phytoplankton-dominated waters

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References
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Journal ArticleDOI

Photosynthetic rates derived from satellite‐based chlorophyll concentration

TL;DR: In this paper, a light-dependent, depth-resolved model for carbon fixation (VGPM) was developed to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation from measurements of sea surface pigment concentrations (Csat)(Csat).
Journal ArticleDOI

Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments

TL;DR: A fluorometric method is described which provides sensitive measurements of extracted chlorophyll a free from the errors associated with conventional acidification techniques and provides adequate sensitivity for small sample sizes even in the most oligotrophic marine and freshwater environments.
Journal ArticleDOI

Analysis of variations in ocean color1

TL;DR: The R(λ) values observed for blue waters are in full agreement with computed values in which new and realistic values of the absorption coefficient for pure water are used and presented.
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