- Empirical algorithms for the total absorption coefficient and absorption
coefficient by pigments for surface waters at 440 nm were developed by applying a quadratic formula that combines two spectral ratios of remote-sensing reflectance. For
total absorption coefficients ranging from 0.02 to 2.0 m⁻¹, a goodness of fit was achieved
between the measured and modeled data with a root-mean-squared difference between the
measured and modeled values for log10 scale(RMSDₗₒ𝓰₁₀) of 0.062 (15.3% for linear
scale, number of samples N = 63), while RMSDₗₒ𝓰₁₀ is 0.111 ( 29.1% for linear scale,
N = 126) for pigment absorption (ranging from 0.01 to 1.0 m⁻¹). As alternatives to
pigment concentration algorithms, the absorption algorithms developed can be applied to
the coastal zone color scanner and sea-viewing wide-field-of-view sensor data to derive
inherent optical properties of the ocean. For the same data sets, we also directly related
the chlorophyll a concentrations to the spectral ratios and obtained an RMSDₗₒ𝓰₁₀ value
of 0.218 (65.2% for linear scale, N = 120) for concentrations ranging from 0.06 to 50.0
mg m⁻³. These results indicate that it is more accurate to estimate the absorption
coefficients than the pigment concentrations from remotely sensed data. This is likely due
to the fact that for the broad range of waters studied the pigment-specific absorption
coefficient at 440nm ranged from 0.02 to 0.2 m² (mg chl)⁻¹. As an indirect test of the
algorithms developed, the chlorophyll a concentration algorithm is applied to an
independent global dataset and an RMSDₗₒ𝓰₁₀ of 0.191( 55.2% for linear scale, N = 919)
is obtained. There is no independent global absorption data set available as yet to test the
- Lee, Z. P., K. L. Carder, R. G. Steward, T. G. Peacock, C. O. Davis, and J. S. Patch (1998), An empirical algorithm for light absorption by ocean water based on color, Journal of Geophysical Research, 103(C12), 27,967–27,978, doi:10.1029/98JC01946.
- The published article can be found at AGU - American Geophysical Union.
|Funding Statement (additional comments about funding)
- Financial support was provided by ONRthrough grant N00014-96-I-5013 and by NASA through grants NAS5-31716, UPN463-11-09-04, and NAGW465.
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