Verification and Application of a Bio-optical Algorithm for Lake Michigan Using SeaWiFS: a 7-year Inter-annual Analysis |
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| Affiliation: | 1. Departments of Medicine and Pathology, Johns Hopkins Hospital, Baltimore, MD;2. Minneapolis Heart Institute Foundation, Minneapolis, MN;3. Cardiovascular Division, Washington University at St Louis School of Medicine, St Louis, MO;4. Department of Medicine, New York University, New York City, NY;5. Summa Health, Akron, OH;6. University of Minnesota, Minneapolis, MN;1. Centro de Vigilancia Sanitaria Veterinaria (VISAVET), Universidad Complutense, 28040 Madrid, Spain;2. Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense, 28040 Madrid, Spain;3. Groupe de Recherche sur les Maladies Infectieuses du Porc, Faculté de Médecine, Vétérinaire, Université de Montréal, 3200 Sicotte, St.-Hyacinthe, Québec, J2S 2M2, Canada;1. State Oceanic Administration Key Laboratory for Ecological Environment in Coastal Areas, National Marine Environmental Monitoring Center, Dalian 116023, China;2. Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116011, China;3. School of Chemistry Engineering & Light Industry, Dalian Polytechnic University, Dalian 116034, China |
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| Abstract: | In this paper we utilize 7 years of SeaWiFS satellite data to obtain seasonal and interannual time histories of the major water color-producing agents (CPAs), phytoplankton chlorophyll (chl), dissolved organic carbon (doc), and suspended minerals (sm) for Lake Michigan. We first present validation of the Great Lakes specific algorithm followed by correlations of the CPAs with coincident environmental observations. Special attention is paid to the satellite observations of the extensive episodic event of sediment resuspension and calcium carbonate precipitation out of the water. We then compare the obtained time history of the CPA's spatial and temporal distributions throughout the lake to environmental observations such as air and water temperature, wind speed and direction, significant wave height, atmospheric precipitation, river runoff, and cloud and lake ice cover. Variability of the onset, duration, and spatial extent of both episodic events and seasonal phenomena are documented from the SeaWiFS time series data, and high correlations with relevant environmental driving factors are established. The relationships between the CPAs retrieved from satellite data and environmental observations are then used to speculate on the future of Lake Michigan under a set of climate change scenarios. |
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