Posters

Poster Session 2, Tuesday,  October  4, 10:40–12:40

Poster 98

Global satellite water classification data products over oceanic, coastal, and inland waters

Satellites have generated extensive data of remote sensing reflectance spectra ( R rs ( λ )) covering diverse water classes or types across global waters. Spectral classification of satellite R rs ( λ ) data allows for distinguishing and grouping of waters of characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite ( VIIRS) . We developed and implemented a hyperspectral scheme that accounts for the R rs ( λ ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation results suggest that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of various applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data product is a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, and daily global water class data are being routinely produced.

Jianwei Wei, NOAA/STAR; Global Science & Technology Inc., [email protected]

Menghua Wang, NOAA/STAR, [email protected] 

Karlis Mikelsons, NOAA/STAR; GST INC, [email protected] 

Lide Jiang, NOAA/STAR; Cooperative Institute for Research in the Atmosphere, Colorado State University, CO, USA, [email protected]

Xiaoming Liu, NOAA/STAR; Cooperative Institute for Research in the Atmosphere, Colorado State University, CO, USA, [email protected] 

Susanne Kratzer, DEEP, Stockholm University, Stockholm, Sweden, [email protected] 

Zhongping Lee, University of Massachusetts Boston, Boston, MA, USA, [email protected] 

Tim Moore, Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL, USA, [email protected] 

Heidi Sosik, Woods Hole Oceanographic Institution, Woods Hole, MA, USA, [email protected] 

Dimitry Van der Zande, Operational Directorate Natural Environment, Royal Belgian Institute of Natural Sciences, Brussels, Belgium, [email protected]