An empirical algorithm for light absorption by ocean water based on color Public Deposited

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  • 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 absorption algorithms.
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  • 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.
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  • 103
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  • C12
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  • 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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  • description.provenance : Submitted by Deborah Campbell ( on 2012-07-09T18:01:38ZNo. of bitstreams: 1DavisCOCEOASEmpiricalAlgorithmLight.pdf: 864671 bytes, checksum: b8cacef855780dca7cf1dff282175074 (MD5)
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