For over 30 years, satellite ocean color imagers have contributed to our knowledge and understanding of the world’s oceans. Empirical algorithms yield global climatologies of primary production which are linked to particulate flux in the water column, thereby tracing the fate of the anthropogenically derived CO2 in the environment to its primary sink in the oceans. Some estimates suggest that twenty percent of the oceanic uptake of anthropogenic CO2 occurs in coastal and marginal seas, where traditional empirical methods are stymied by optical complexity and a lack of data. The ability of current remote sensing approaches to accurately measure bio-optical pigments and primary productivity in the coastal zone will help not only to improve carbon budgets there, but also will contribute to the parameterization of ecological models used in the investigation of estuarine eutrophication-induced hypoxia. Satellite ocean color retrieval of even the most basic bio-optical property, chlorophyll concentration, has remained elusive in LIS, which is characterized by water masses containing high chromophoric dissolved material concentrations and a bi-annual phytoplankton bloom, as well as annual eutrophication-induced hypoxia at its western end. This research uses in situ optical measurements from LIS to optimize algorithms for remote sensing of surface chlorophyll, spectral phytoplankton and dissolved absorption, and diffuse attenuation from ocean color satellite imagery.
Results from this research will be incorporated into UConn’s Long Island Sound Observatory (LISICOS ). Collaborators include: Michael Twardowski, Steve Ackleson, Hans Dam, and the LISICOS investigators. This project is part of Dirk Aurin’s dissertation.