An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data Robert A. Shuchman a, ⁎, George Leshkevich b,1 , Michael J. Sayers a,2 , Thomas H. Johengen c,3 , Colin N. Brooks a,4 , Dmitry Pozdnyakov d,5 a Michigan Tech Research Institute (MTRI), Michigan Technological University, 3600 Green Ct., Ste 100, Ann Arbor, MI 48105, USA b National Oceanic and Atmospheric Administration (NOAA)/Great Lakes Environmental Research Laboratory (GLERL), 4840 S. State Rd, Ann Arbor, MI 48108, USA c Cooperative Institute for Limnology and Ecosystems Research (CILER), University of Michigan, 4840 S. State Rd, Ann Arbor, MI 48108, USA d Nansen International Environmental and Remote Sensing Centre (NIERSC), 7, 14th Line, office 49, Business Centre “Preobrazhensky”, Vasilievsky Island, 199034 St. Petersburg, Russia abstract article info Article history: Received 26 January 2012 Accepted 28 April 2013 Available online 4 August 2013 Communicated by Barry Lesht Keywords: Chlorophyll Remote sensing Great Lakes MODIS, MERIS SeaWiFS Water color An algorithm that utilizes individual lake hydro-optical (HO) models has been developed for the Great Lakes that uses SeaWiFS, MODIS, or MERIS satellite data to estimate concentrations of chlorophyll, dissolved organic carbon, and suspended minerals. The Color Producing Agent Algorithm (CPA-A) uses a specific HO model for each lake. The HO models provide absorption functions for the Color Producing Agents (CPAs) (chlorophyll (chl), colored dissolved organic matter (as dissolved organic carbon, doc), and suspended minerals (sm)) as well as backscatter for the chlorophyll, and suspended mineral parameters. These models were generated using simultaneous opti- cal data collected with in situ measurements of CPAs collected during research cruises in the Great Lakes using regression analysis as well as using specific absorption and backscatter coefficients at specific chl, doc, and sm concentrations. A single average HO model for the Great Lakes was found to generate insufficiently accurate con- centrations for Lakes Michigan, Erie, Superior and Huron. These new individual lake retrievals were evaluated with respect to EPA in situ field observations, as well as compared to the widely used OC3 MODIS retrieval. The new algorithm retrievals provided slightly more accurate chl values for Lakes Michigan, Superior, Huron, and Ontario than those obtained using the OC3 approach as well as providing additional concentration informa- tion on doc and sm. The CPA-A chl retrieval for Lake Erie is quite robust, producing reliable chl values in the re- ported EPA concentration ranges. Atmospheric correction approaches were also evaluated in this study. © 2013 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved. Introduction Satellite remote sensing of the Great Lakes has become increasingly important over the past two decades. The Great Lakes account for ap- proximately 20% of the Earth's surface fresh water and supplies drinking water for forty million United States and Canadian people (Van der Leeden et al., 1991). Lakes Michigan and Huron in particular have un- dergone major changes in lower food web production as witnessed by decreases in average chlorophyll, primary productivity, Diporeia, and fish populations (Fahnenstiel et al., 2010a,b; Nalepa et al., 2009). Lake Erie and to a lesser extent Lake Ontario continue to exhibit multiple Harmful Algal Blooms (HABs) each summer (Boyer, 2008; Rinta-Kanto et al., 2005). Remote sensing observations from satellites allow for the synoptic long term monitoring of all the Laurentian Great Lakes to doc- ument changes in water quality parameters and primary productivity as a result of the climate, anthropogenic, and invasive species forcing functions. Only visible radiation penetrates into a water column to any great ex- tent (Jerlov, 1976). As light travels through the water column it interacts with both molecules and particles that comprise the chlorophyll (chl), colored dissolved organic matter (cdom) and inorganic suspended minerals (sm) resulting in alterations of the upwelling radiative flux (Pozdnyakov and Grassel, 2003). Thus the backscattered flux emerging from beneath the water surface contains information about the optical properties of the water column which when observed over time provides insight into the dynamic processes of the Great Lakes (Shuchman et al., 2006). For the open ocean case, the satellite retrieval of the chlorophyll and other related water quality parameters is straight forward. For example the OC3, OC4 and other algorithms currently used by NASA for the open ocean (Ackleson, 2001; O'Reilly et al., 1998, 2000a) are empirical, visible (blue/green) band ratio techniques. These algorithms are effective due Journal of Great Lakes Research Supplement 39 (2013) 14–33 ⁎ Corresponding author. Tel.: +1 734 913 6860. E-mail addresses: shuchman@mtu.edu (R.A. Shuchman), george.leshkevich@noaa.gov (G. Leshkevich), mjsayers@mtu.edu (M.J. Sayers), tom.johengen@noaa.gov (T.H. Johengen), colin.brooks@mtu.edu (C.N. Brooks), dmitry.pozdnyakov@niersc.spb.ru (D. Pozdnyakov). 1 Tel.: +1 734 741 2265; fax: +1 734 741 2055. 2 Tel.: +1 734 913 6852. 3 Tel.: +1 734 741 2203; fax: +1 734 741 2055. 4 Tel.: +1 734 913 6858; fax: +1 734 913 6880. 5 Tel.: +7 812 324 51 03; fax: +7 812 324 51 02. 0380-1330/$ – see front matter © 2013 International Association for Great Lakes Research. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jglr.2013.06.017 Contents lists available at ScienceDirect Journal of Great Lakes Research journal homepage: www.elsevier.com/locate/jglr