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
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.
- 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).
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.