C.5.2.7 Remote sensing (PIs: Thomas, Keafer)

Rationale: Remote sensing is an essential tool for studying HAB ecology over time and space scales not amenable to ship sampling. Satellite data allow synoptic characterizations of hydrographic and biological variability, allowing an examination of linkages between regions, providing essential model input, fields for evaluation of model output, support for field programs and direct quantification of water mass movements. Key processes controlling phytoplankton and HAB ecology and distribution are directly linked to hydrographic processes evident in NOAA AVHRR sea surface temperature (SST) imagery (e.g. Tester et al.1991, Keafer and Anderson, 1993). In the WMCC, the relatively warm Alexandrium-containing coastal plume is evident in AVHRR data (Franks and Anderson 1992a) and key wind-driven processes influencing Alexandrium distributions can be detected (Keafer and Anderson 1993). AVHRR data also indicate EMCC features (e.g. Brooks and Townsend, 1989). Furthermore, our remote sensing capabilities will be significantly enhanced during ECOHAB by data from three ocean color space missions. Color data will not provide a direct investigative tool, as Alexandrium rarely dominates the phytoplankton community and co-occurs with similarly pigmented dinoflagellates. However, in addition to improved temporal coverage, these data add multi-spectral and biological capability, allowing direct quantitative measurement of chlorophyll and turbidity and a significantly improved ability to track water masses.

Approach: Two primary satellite data sets will be employed, NOAA AVHRR data to provide SST fields, and NASA SeaWiFS data to provide surface color. SeaWiFS is scheduled to be operational when this study begins. These data will be supplemented with OCTS (color data, presently orbiting) and MODIS data (color and SST data, June 1998 launch) as available. AVHRR and SeaWiFS data are/will be received and processed to geophysical products using SeaSpace Terascan and NASA SeaDAS software. These data will be supplemented with products acquired from the NOAA Coastwatch program. Level 2 OCTS and MODIS data will be acquired from national distribution sites. Algorithm development and determination of regionally specific coefficients for color data is beyond the scope of this project. For all satellite data, community-standard algorithms and methodologies will be used to calculate geophysical fields (SST, total pigments, chl a, and diffuse attenuation coefficient (K490); e.g. Kidwell 1995, McClain et al. 1995, Aiken et al. 1995). All image data will be subset and registered to a common grid for analysis and delivery to the study team.

The focus of our satellite data analysis is to locate and track specific water masses linked to Alexandrium distributions. Efforts include a) direct comparisons of satellite measured variables with in situ biological, chemical and physical measurements, b) analysis of image time series from the study period to determine location and variability of features and/or events (e.g. frontal zones, water masses, chlorophyll, regions of differing turbidity) identified as important in Alexandrium ecology c) analysis of time series data to determine differences in seasonality and phasing between GOM regions and d) generation of spatial and temporal fields/statistics for comparison with model output. Parallel use of both SST and color imagery reduces the limitations of SST imagery alone. Color is sometimes a better tracer of upper water column circulation than temperature as visible wavelengths emanate from deeper in the water column than infrared wavelengths. Surface heating can reduce or eliminate surface thermal signatures of hydrographic processes which might remain evident as color patterns. Furthermore, image products derived from mathematical combinations of color and SST and innovative use of available multi-spectral channels might prove optimal in defining/monitoring oceanographic features important in Alexandrium ecology (e.g. turbidity of freshwater plumes).