An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data
An algorithm has been developed for the Great Lakes that utilizes SeaWiFS, MODIS, or MERIS satellite data to estimate concentrations of Chlorophyll (chl), dissolved organic carbon (doc), and suspended minerals (sm). The Color Producing Agent Algorithm (CPA-A) utilizes a specific, updated hydro-optical (HO) model for each lake. The HO models provide absorption functions for all three CPAs (chl, colored dissolved organic matter (cdom), and sm) as well as backscatter relationships for chl and sm, and were generated using simultaneous near surface optical data collected with in situ water chemistry measurements during research cruises in the Great lakes. A single average HO model for the Great Lakes was found to generate insufficiently accurate retrievals for Lakes Michigan, Erie, Superior and Huron. The new HO models were then evaluated with respect to EPA in situ observations, as well as compared to the NASA OC3 retrieval. The CPA-A retrievals provided more accurate chl values for Lakes Michigan, Superior, Huron, and Ontario than those from the NASA approach as well as providing concentrations of doc and sm. The CPA-A chl retrieval for Lake Erie is quite robust, producing reliable chl values within EPA concentration ranges, while the NASA chl retrieval for this case II water provided chl estimates with large uncertainty.
IAGLR 56th Annual Conference on Great Lakes Research
Shuchman, R. A.,
Sayers, M. J.,
Johengen, T. H.,
Brooks, C. N.,
An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data.
IAGLR 56th Annual Conference on Great Lakes Research.
Retrieved from: https://digitalcommons.mtu.edu/mtri_p/102