NOAA CoastWatch East Coast Node
Data Types Info Data Types: SST         - AVHRR                 - GOES                 - Geo-Polar Blended                 - PODAAC MUR Chl-a       - MODIS                 - OLCI (HiRes)                 - VIIRS Clarity     - K490 (MODIS)                 - K490 (MODIS HiRes)                 - K490 (OLCI HiRes)                 - K490 (VIIRS)                 - Rrs667 (MODIS)                 - Rrs672 (VIIRS)                 - TSM (MODIS HiRes)                 - TSM (OLCI HiRes)                 - TSM (VIIRS HiRes) True Color (VIIRS)
Data Access Info HTTP Rolling Archive FTP Time Series Archive
Region Info Regions: U.S. East Coast North East Coast Gulf of Maine Massachusetts & RI Bays Mid-Atlantic Coast NY-NJ Bight & Long Island Sound Chesapeake & Delaware Bays South East Coast Carolina Coast Florida - Georgia Coast
CoastWatch Utilities Time Series Tool ERDDAP MGET Experimental Algal Bloom Monitor

 

VIIRS Chlorophyll-a

Chlorophyll from satellite is an estimation of the concentration of the phytoplankton pigment, chlorophyll-a, in the ocean surface and is used as a proxy for the amount of phytoplankton in the surface water. This measurement has many applications in marine ecology, from ecosystem modeling, to fisheries management, and monitoring of water quality, to name only a few applications.

NOAA CoastWatch produces ocean color products, including chlorophyll, from the Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the polar-orbiting Suomi-NPP and NOAA-20 satellites (Wang et al., 2017).

Atmospheric correction uses the near-infrared (NIR) approach of Jiang and Wang (2014), which is an iterative NIR approach combining the NIR approachs of Bailey et al. (2010), MUMM (or Ruddick et al. (2000)), and Wang et al. (2012), referred to as the BMW atmospheric correction (see Jiang and Wang, 2014, for detailed references). While short-wave infrared (SWIR) approaches, like that used for NOAA's MODIS ocean color products, generate more accurate results for coastal waters than NIR approaches, the improved BMW approach of Jiang and Wang (2014) was found to offer the most accurate results compared to other NIR approaches.

Chlorophyll is generated using the blue-green reflectance ratio empirical approach of O'Reilly et al. (1998), adjusting the algorithm for the VIIRS spectral bands. Specifically, the algorithm is a 3-band algorithm (OC3V, Ocean Chlorophyll 3-band algorithm for VIIRS) whose inputs are the water-leaving radiance at wavelengths of 443, 486, and 551 nm.

Data validation compared Suomi-NPP VIIRS chlorophyll values to in situ measurements from the NASA SeaBASS database, including both open ocean and coastal data (Wang et al., 2017). Results showed that VIIRS-derived chlorophyll data compared quite well with the in situ measurements with mean and median ratios of 1.299 and 1.142 respectively and standard deviation of 0.624 for a matchup time difference within 3-hours. Thus, errors in VIIRS-derived chlorophyll data are all within 30%. However, it should be particularly noted that for coastal water (e.g. CDOM-dominated water), satellite chlorophyll still has significant issues. For example, Le et al. (2013) point out a high chlorophyll bias in coastal water.


Data Access
  • See the Data Access page for data offerings by satellite, data-type, or region.
  • Or use Direct Download to retrieve files by time-interval and region (via http).

References:
Wang, M., Liu, X., Jiang, L., and Son, S.H. 2017. VIIRS Ocean Color Algorithm Theoretical Basis Document (ATBD), Version 1, NOAA NESDIS Center for Satellite Applications and Research.

Jiang, L. and Wang, M. 2014. Improved near-infrared ocean reflectance correction algorithm for satellite ocean color data processing, Optics Express, 22, 21657–21678.

O'Reilly, J. E., Maritorena, S., Mitchell, B. G., Siegel, D. A., Carder, K. L., Garver, S. A., Kahru, M., and McClain, C. R. 1998. Ocean color chlorophyll algorithms for SeaWiFS, Journal of Geophysical Research, 103, 24937–24953.

Le, C., Hu, C., Cannizzaro, J., English, D., Muller-Karger, F., and Lee, Z. 2013. Evaluation of chlorophyll-a remote sensing algorithms for an optically complex estuary, Remote Sensing of Environment, 129, 75–89.


 
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