Abstract
The U.S. Environmental Protection Agency's Great Lakes National Program Office (GLNPO) has collected water quality data from the five Great Lakes annually since 1993. We used the GLNPO observations made since 2002 along with coincident measurements made by the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and the Moderate-resolution Imaging Spectroradiometer (MODIS) to develop a new band-ratio algorithm for estimating chlorophyll concentrations in the Great Lakes from satellite observations. The new algorithm is based on a third-order polynomial model using the same maximum band ratios employed in the standard NASA algorithms (OC4 for SeaWiFS and OC3M for MODIS). The sensor-specific coefficients for the new algorithm were obtained by fitting the relationship to several hundred matched field and satellite observations. Although there are some seasonal variations in some lakes, the relationship between the observed chlorophyll values and those modeled using the new coefficients is fairly stable from lake to lake and across years. The accuracy of the satellite chlorophyll estimates derived from the new algorithm was improved substantially relative both to the standard NASA retrievals and to previously published algorithms tuned to individual lakes. Monte-Carlo fits to randomly selected subsets of the observations allowed us to estimate the uncertainty associated with the retrievals purely as a function of the satellite data. Our results provide, for the first time, a single simple band ratio method for retrieving chlorophyll concentrations in the offshore “open” waters of the Great Lakes from satellite observations.
Highlights
The problem of estimating chlorophyll concentration in the surface waters of the Great 3 Lakes from satellite observations is one that has challenged researchers for years
Histograms of the subsets of chlorophyll values that were matched with the 315 Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) observations (Fig. 2) are very similar to overall distribution indicat316 ing that the matching process resulted in samples representative of the overall population 317 of observations
Re323 calling that the coefficients determined for the Great Lakes Fit (GLF) models (Table 2) were constrained to result in a slope of one and intercept of zero, the values for dr, %USE, and mean absolute error (MAE) were 0.780, 0.976, 0.142 for MODIS and 0.758, 0.956, and 0.158 for SeaWiFS, respectively
Summary
The problem of estimating chlorophyll concentration in the surface waters of the Great 3 Lakes from satellite observations is one that has challenged researchers for years. The influence of optically active non-algal substances, such as non-algal particulates (NAP, primarily suspended mineral particles), or colored dissolved organic material (CDOM), that would interfere with the chlorophyll retrievals based on band ratio methods can be calculated by using models that include the optical effects of these compo nents explicitly These calculations require knowledge of the spectrally resolved scattering and absorption properties of each optically active component (Preiur and Sathyendranath, 1981). The standard NASA retrieval algorithms are based on the work of O’Reilly et al (1998) who conducted an extensive study comparing a large and diverse set of oceanic field mea surements of chlorophyll concentrations with predictions made from a number of different retrieval algorithms They found that, in general, the multi-component (or semi-analytical) methods did not perform as well as did band ratio methods.
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