45. An Assessment of Ocean Color Contribution to Satellite Radiance:
Implication for Ocean Color Assimilation
Author：
W. Li1, Y. Fan1, B. Yan2, J. J. Stamnes3, and K. Stamnes1
Affiliation： Stevens Institute of Technology
Ocean Color (OC) is the water hue due to the presence of tiny plants containing
chlorophyll pigments, sediments containing inorganic particulate matter (IPM), and
colored dissolved organic material (CDOM). The upwelling OC radiance due to
scattering from chlorophyll-containing particles and IPM will contribute to satellite
radiance observations at visible (both over open ocean and coastal areas) and
Near-InfraRed (NIR) (primarily over coastal areas) wavelengths. How much of the
observed satellite radiance comes from the ocean? Can ocean color (OC) signals be
assumed to be constant when satellite ocean color observation data are assimilated
into numerical weather prediction systems? In this presentation, the contribution of
the OC radiance to satellite observations is assessed using a coupled
atmosphere-ocean radiative transfer model (Stamnes et al., presentation at this
workshop). Results from a sensitivity study will be reported that quantify how the
satellite radiance varies with the amount of chlorophyll, IPM, and CDOM in the
water. To understand the significance of using realistic ocean color data in
assimilation of satellite OC radiances, the difference between the satellite-observed
radiance and the model-computed radiance using retrieved atmosphere-ocean
parameters is also analyzed. These retrieved parameters are obtained from an
inversion scheme that employs the coupled atmosphere-ocean radiative transfer
model to simulate satellite-measured radiances. MERIS (the Medium Resolution
Imaging Spectrometer on Envisat) images over the Santa Barbara Channel (SBC)
and the North Sea will be used in study.
In contrast to traditional decoupled OC retrieval algorithms that rely on atmospheric
corrections, the coupled atmosphere-ocean forward/inverse radiative transfer
approach provides a direct link between the OC products and the satellite radiances,
thereby making OC data assimilation possible. We can apply this coupled forward
radiative transfer model in conjunction with standard nonlinear optimal estimation
for simultaneous retrieval of aerosol and marine parameters (Li et al., Int. J. Rem.
Sens., 29, 5689-5698, 2008) as well as for system error analysis (to quantify the
difference between satellite-observed and model-simulated radiances based on the
retrieval parameters). This forward/inverse modeling approach has been successfully
applied to different satellite sensor data, including SeaWiFS, MODIS, and MERIS
data. Further, we will show how this approach could also be applied to existing
ocean color products derived from decoupled OC retrieval algorithms.