Abstract
Empirically-based satellite estimates of chlorophyll a [Chl] (e.g. OC3) are an important indicator of phytoplankton biomass. To correctly interpret [Chl] variability, estimates must be accurate and sources of algorithm errors known. While the underlying assumptions of band ratio algorithms such as OC3 have been tacitly hypothesized (i.e. CDOM and phytoplankton absorption covary), the influence of component absorption and scattering on the shape of the algorithm and estimated [Chl] error has yet to be explicitly revealed. We utilized the NOMAD bio-optical data set to examine variations between satellite estimated [Chl] and in situ values. We partitioned the variability into (a) signal contamination and (b) natural phytoplankton variability (variability in chlorophyll-specific phytoplankton absorption). Not surprisingly, the OC3 best-fit curve resulted from a balance between these two different sources of variation confirming the bias by detrital absorption on global scale. Unlike previous descriptions of empirical [Chl] algorithms, our study (a) quantified the mean detrital:phytoplankton absorption as ~1:1in the global NOMAD data set, and (b) removed detrital (CDOM + non-algal particle) absorption in radiative transfer models directly showing that the scale of the remaining variability in the band ratio algorithm was dominated by phytoplankton absorption cross section.
Highlights
Over the last 30 years, a major focus of the interpretation of ocean color has been estimating the surface concentration of chlorophyll a, the major light absorbing pigment in phytoplankton and proxy for phytoplankton biomass
Our approach is divided into three sections: (1) analysis of component absorption and backscattering within the NASA bio-Optical Marine Algorithm Data set (NOMAD) data set where the interrelationship between inherent optical properties (IOPs) are both confirmed and quantified, (2) development of a detrital absorption free radiative transfer model derived from NOMAD in situ data for exposing how detrital absorption influences the curvature of OC3 and for determining the range of variability leftover in the model without detrital influence, and (3) development of a Hydrolight model of reflectances based on models of aph* and bbp to isolate the influence of phytoplankton absorption and particle size on empirical algorithms
The global bio-optical data set used in this study is a subset of NOMAD that includes in situ measured above water remote sensing reflectance and a set of matching depth-weighted discrete samples (n = 771) of coincident phytoplankton absorption and detrital absorption (CDOM + non-algal particles (NAP)) plus particulate backscattering (n = 331)
Summary
Over the last 30 years, a major focus of the interpretation of ocean color has been estimating the surface concentration of chlorophyll a, the major light absorbing pigment in phytoplankton and proxy for phytoplankton biomass. The ubiquitous use of empirical satellite [Chl] estimates and their importance as a phytoplankton biomass index [1,2] despite confounding issues of photadaptation [3,4,5] dictates that the estimates must be accurate and that knowledge of the errors and biases are necessary in order to correctly interpret [Chl] variability. This is all the more important given the inclusion of empirical satellite [Chl] estimates in the NASA Earth System Data Record. The lack of covariance between bio-optical components and their common strong absorption of blue and blue-green light are confounding influences on empirical satellite [Chl] estimates [11,12,13,14,15]
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