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Evaluation of forward reflectance models and empirical algorithms for chlorophyll concentration of stratified waters.
Appl Opt ; 59(30): 9340-9352, 2020 Oct 20.
Article em En | MEDLINE | ID: mdl-33104650
ABSTRACT
For waters with stratified chlorophyll concentration (Chl), numerical simulations were carried out to gain insight into the forward models of subsurface reflectance and empirical algorithms for Chl from the ocean color. It is found that the Gordon and Clark (1980) forward model for reflectance using an equivalent homogeneous water with a weighted average Chl (⟨Chl⟩) as the input works well, but depending on the contribution of gelbstoff, the difference in reflectance between stratified and the equivalent homogeneous water can be more than 10%. Further, the attenuation of upward light is better approximated as ∼1.5times that of the diffuse attenuation coefficient of downwelling irradiance. On the other hand, although the forward model for reflectance developed in Zaneveld et al. [Opt. Express13, 9052 (2005)] using equivalent homogeneous water with a weighted average of the backscattering to absorption ratio as the input also works well, this model cannot be used to obtain equivalent ⟨Chl⟩ for reflectance. Further, for empirical Chl algorithms designed for "Case 1" waters, it has been discovered that, for surface Chl in a range of ∼0.06-22.0mg/m3, the predictability of surface Chl is basically the same as that of ⟨Chl⟩ from the blue-green band ratio or the band difference of reflectance. Because ⟨Chl⟩ is wavelength and weighting-formula dependent, and it is required to have profiles of both Chl and the optical properties, these results emphasize that for empirical Chl algorithms, it is easier, less ambiguous, and certainly more straightforward and simple to use surface Chl for algorithm development and then its evaluation, rather than to use ⟨Chl⟩, regardless of whether or not the water is stratified.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article