A band-ratio algorithm for retrieving open-lake chlorophyll values from satellite observations of the Great Lakes

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.

► We derive a new model for estimating Great Lakes chlorophyll from satellite data.
► The model is based on ten years of observations from all five lakes.
► Chlorophyll is related to the blue/green ratio of remote sensing reflectance.
► The model coefficients are sensor-dependent but independent of lake or year.
► We estimate the uncertainty of the chlorophyll estimates as ± 30%.