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VIIRS-derived chlorophyll-a using the ocean color index method



Details

  • Journal Title:
    Remote Sensing of Environment
  • Personal Author:
  • NOAA Program & Office:
    NOAA General Documents
  • Description:
    An implementation approach using the ocean color index (OCI)-based chlorophyll-a (Chl-a) algorithm for the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) has been developed. The OCI Chl-a algorithm for satellite-derived Chl-a data was originally developed by Hu, Lee, and Franz (2012) (J. Geophys. Res., 117, C01011, doi: 01010.01029/02011JC007395) for the Moderate Resolution Imaging Spectroradiometer (MODIS). It uses two Chl-a algorithms, i.e., the color index (CI)-based (reflectance difference-based) algorithm for oligotrophic waters and the usual ocean chlorophyll-type (OCx)-based (reflectance ratio-based) algorithm (e.g., OC3M for MODIS and OC3V for VIIRS), and merges the two algorithms for different Chl-a range applications (named OCI algorithm). In this study, we use the in situ Marine Optical Buoy (MOBY) optics data to demonstrate conclusively that using the CI-based Chl-a algorithm can significantly improve VIIRS Chl-a data over oligotrophic waters with much reduced data noise from instrument calibration and the imperfect atmospheric correction. Using the VIIRS-measured global Chl-a data derived from the Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system, we have developed the CI-based algorithm specifically for VIIRS, and further improved the two Chl-a algorithms merging method using the blue-green reflectance ratio values. Extensive evaluation results show that the new OCI Chl-a algorithm for VIIRS can produce consistent Chl-a data compared with those from the OC3V algorithm. In particular, the data transition between the CI-based and OC3V-based Chl-a algorithm is quite smooth, and there are no obvious discontinuities in VIIRS-derived Chl-a data. The new OCI-based Chl-a algorithm has been implemented in MSL12 for routine production of VIIRS global Chl-a data.
  • Keywords:
  • Source:
    Remote Sensing of Environment, 182, 141-149
  • DOI:
  • ISSN:
    0034-4257
  • Format:
    PDF
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article
  • Rights Information:
    Accepted Manuscript
  • Compliance:
    Library
  • Main Document Checksum:
    urn:sha256:d67655e6aceaa4d6fe85db78f1155fe175a48088a10e068217084768a6893167
  • Download URL:
  • File Type:
    Filetype[PDF - 1.18 MB ]
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