Ocean Color Chlorophyll Algorithms for SEAWIFS
TL;DR: In this article, a large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor).
Abstract: A large data set containing coincident in situ chlorophyll and remote sensing reflectance measurements was used to evaluate the accuracy, precision, and suitability of a wide variety of ocean color chlorophyll algorithms for use by SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The radiance-chlorophyll data were assembled from various sources during the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) and is composed of 919 stations encompassing chlorophyll concentrations between 0.019 and 32.79 μg L−1. Most of the observations are from Case I nonpolar waters, and ∼20 observations are from more turbid coastal waters. A variety of statistical and graphical criteria were used to evaluate the performances of 2 semianalytic and 15 empirical chlorophyll/pigment algorithms subjected to the SeaBAM data. The empirical algorithms generally performed better than the semianalytic. Cubic polynomial formulations were generally superior to other kinds of equations. Empirical algorithms with increasing complexity (number of coefficients and wavebands), were calibrated to the SeaBAM data, and evaluated to illustrate the relative merits of different formulations. The ocean chlorophyll 2 algorithm (OC2), a modified cubic polynomial (MCP) function which uses Rrs490/Rrs555, well simulates the sigmoidal pattern evident between log-transformed radiance ratios and chlorophyll, and has been chosen as the at-launch SeaWiFS operational chlorophyll a algorithm. Improved performance was obtained using the ocean chlorophyll 4 algorithm (OC4), a four-band (443, 490, 510, 555 nm), maximum band ratio formulation. This maximum band ratio (MBR) is a new approach in empirical ocean color algorithms and has the potential advantage of maintaining the highest possible satellite sensor signal: noise ratio over a 3-orders-of-magnitude range in chlorophyll concentration.
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TL;DR: For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff, based on remote-sensing reflectance models derived from the radiative transfer equation.
Abstract: For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.
1,375 citations
TL;DR: In this article, the spectral attenuation for downward irradiance Kd(X) and irradiance reflectance R(X), as well as a bio-optical model of the upper layer was developed.
Abstract: The apparent optical properties (AOPs) of oceanic case 1 waters were previously analyzed [Morel, 1988] and statistically related to the chlorophyll concentration ([Chl]) used as a global index describing the trophic conditions of water bodies. From these empirical relationships a bio-optical model of the upper layer was developed. With objectives and structure similar to those of the previous study the present reappraisal utilizes AOPs determined during recent Joint Global Ocean Flux Study cruises, namely, spectral attenuation for downward irradiance Kd(X) and irradiance reflectance R(X). This revision also benefits from improved knowledge of inherent optical properties (lOPs), namely, pure water absorption coefficients and particle scattering and absorption coefficients, and from better pigment quantification (via a systematic use of highperformance liquid chromatography). Nonlinear trends, already observed between optical properties and algal biomass, are fully confirmed, yet with numerical differences. The previous Kd(X) model, and subsequently the R(X) model, is modified to account for these new relationships. The R(X) values predicted as a function of [Chl] and the predicted ratios of reflectances at two wavelengths, which are commonly used in ocean color algorithms, compare well with field values (not used when developing the reflectance model). This good agreement means that semianalytical ocean color algorithms can be successfully applied to satellite data. Going further into purely analytical approaches, ideally based on radiative transfer computations combined with a suite of relationships between the lOPs and [Chl], remains presently problematic, especially because of the insufficient knowledge of the phase function and backscattering efficiency of oceanic particles.
1,007 citations
Cites methods from "Ocean Color Chlorophyll Algorithms ..."
...The SeaBAM data set [O’Reilly et al., 1998], containing coincident reflectance and chlorophyll measurements, can be used to test independently the present reflectance model....
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...The “Morel-3” algorithm [O’Reilly et al., 1998] (see also Appendix B) was based on the reflectances at 443 and 555 nm; this algorithm and the present algorithm (derived from the model and displayed in Figure 11b) are both operated, and the results are comparatively displayed in Figure 12b....
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...When considering the Sea-viewing Wide Field-of-view (SeaWiFS) Bio-optical Algorithm MiniWorkshop (SeaBAM) data set [O’Reilly et al., 1998] for high [Chl], the R(445)/R(555) values, admittedly very scattered [see O’Reilly et al....
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...Statistical regression analysis of the reflectance data against the chlorophyll concentration represents the so-called empirical way to derive algorithms for the ocean color interpretation [see, e.g., O’Reilly et al., 1998; Gordon and Morel, 1983, Table 2]....
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TL;DR: A procedure for optimizing SA ocean color models for global applications by tuned by simulated annealing as the global optimization protocol and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl.
Abstract: Semianalytical (SA) ocean color models have advantages over conventional band ratio algorithms in that multiple ocean properties can be retrieved simultaneously from a single water-leaving radiance spectrum. However, the complexity of SA models has stalled their development, and operational implementation as optimal SA parameter values are hard to determine because of limitations in development data sets and the lack of robust tuning procedures. We present a procedure for optimizing SA ocean color models for global applications. The SA model to be optimized retrieves simultaneous estimates for chlorophyll (Chl) concentration, the absorption coefficient for dissolved and detrital materials [a(cdm)(443)], and the particulate backscatter coefficient [b(bp)(443)] from measurements of the normalized water-leaving radiance spectrum. Parameters for the model are tuned by simulated annealing as the global optimization protocol. We first evaluate the robustness of the tuning method using synthetic data sets, and we then apply the tuning procedure to an in situ data set. With the tuned SA parameters, the accuracy of retrievals found with the globally optimized model (the Garver-Siegel-Maritorena model version 1; hereafter GSM01) is excellent and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl. The advantage of the GSM01 model is that simultaneous retrievals of a(cdm)(443) and b(bp)(443) are made that greatly extend the nature of global applications that can be explored. Current limitations and further developments of the model are discussed.
872 citations
Cites background from "Ocean Color Chlorophyll Algorithms ..."
...i , ( 1 ) where t is the sea‐air transmission factor, F0 is the extraterrestrial solar irradiance, and nw is the index of refraction of the water....
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TL;DR: The NASA Ocean Biology Processing Group's (OBPG) method for validating satellite ocean color data products using in situ measurements as ground truth is described in this article, where the results indicate that for the majority of the global ocean, SeaWiFS data approach the target uncertainties of ± 5% for clear water radiances as defined prior to launch.
766 citations
Cites methods from "Ocean Color Chlorophyll Algorithms ..."
...For example, SeaWiFS L2 processing provides a Ca warning flag that is set for either extreme reflectance ratio retrievals (O'Reilly et al., 1998) or for values falling outside a pre-defined range, indicating lower confidence in the Ca retrieval....
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...Moreover, as many Ca algorithms make use of reflectance ratios (O'Reilly et al., 1998), underlying problems with radiometry are often masked....
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...These radiance spectra are used to estimate geophysical parameters, such as the surface concentration of the phytoplankton pigment chlorophyll a, Ca, via the application of bio-optical algorithms (O'Reilly et al., 1998)....
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TL;DR: In this article, the potential of using the near-surface chlorophyll a concentration (Chla) as it can be derived from ocean color observation, to infer the column-integrated phytoplankton biomass, its vertical distribution, and ultimately the community composition.
Abstract: [1] The present study examines the potential of using the near-surface chlorophyll a concentration ([Chla]surf), as it can be derived from ocean color observation, to infer the column-integrated phytoplankton biomass, its vertical distribution, and ultimately the community composition. Within this context, a large High-Performance Liquid Chromatography (HPLC) pigment database was analyzed. It includes 2419 vertical pigment profiles, sampled in case 1 waters with various trophic states (0.03–6 mg Chla m � 3 ). The relationships between [Chla]surf and the chlorophyll a vertical distribution, as previously derived by Morel and Berthon (1989), are fully confirmed. This agreement makes it possible to go further and to examine if similar relationships between [Chla]surf and the phytoplankton assemblage composition along the vertical can be derived. Thanks to the detailed pigment composition, and use of specific pigment biomarkers, the contribution to the local chlorophyll a concentration of three phytoplankton groups can be assessed. With some cautions, these groups coincide with three size classes, i.e., microplankton, nanoplankton and picoplankton. Corroborating previous regional findings (e.g., large species dominate in eutrophic environments, whereas tiny phytoplankton prevail in oligotrophic zones), the present results lead to an empirical parameterization applicable to most oceanic waters. The predictive skill of this parameterization is satisfactorily tested on a separate data set. With such a tool, the vertical chlorophyll a profiles of each group can be inferred solely from the knowledge of [Chla]surf. By combining this tool with satellite ocean color data, it becomes possible to quantify on a global scale the phytoplankton biomass associated with each of the three algal assemblages.
724 citations
References
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01 May 1984
2,493 citations
TL;DR: In this paper, a light-dependent, depth-resolved model for carbon fixation (VGPM) was developed to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation from measurements of sea surface pigment concentrations (Csat)(Csat).
Abstract: We assembled a dataset of 14C-based productivity measurements to understand the critical variables required for accurate assessment of daily depth-integrated phytoplankton carbon fixation (PP(PPeu)u) from measurements of sea surface pigment concentrations (Csat)(Csat). From this dataset, we developed a light-dependent, depth-resolved model for carbon fixation (VGPM) that partitions environmental factors affecting primary production into those that influence the relative vertical distribution of primary production (Pz)z) and those that control the optimal assimilation efficiency of the productivity profile (P(PBopt). The VGPM accounted for 79% of the observed variability in Pz and 86% of the variability in PPeu by using measured values of PBopt. Our results indicate that the accuracy of productivity algorithms in estimating PPeu is dependent primarily upon the ability to accurately represent variability in Pbopt. We developed a temperature-dependent Pbopt model that was used in conjunction with monthly climatological images of Csat sea surface temperature, and cloud-corrected estimates of surface irradiance to calculate a global annual phytoplankton carbon fixation (PPannu) rate of 43.5 Pg C yr‒1. The geographical distribution of PPannu was distinctly different than results from previous models. Our results illustrate the importance of focusing Pbopt model development on temporal and spatial, rather than the vertical, variability.
2,471 citations
2,364 citations
TL;DR: A fluorometric method is described which provides sensitive measurements of extracted chlorophyll a free from the errors associated with conventional acidification techniques and provides adequate sensitivity for small sample sizes even in the most oligotrophic marine and freshwater environments.
Abstract: A fluorometric method is described which provides sensitive measurements of extracted chlorophyll a free from the errors associated with conventional acidification techniques. Fluorometric optical configurations were optimized to produce maximum sensitivity to Chl a while maintaining desensitized responses from both Chl b and pheopigments. Under the most extreme Chl b:Chl a ratio likely to occur in nature (1 : 1 molar), the new method results in only a 10% overestimate of the true Chl a value, while estimates from older acidification methods are 2.5-fold low. Under conditions of high pheopigment concentrations (pheo a: Chl a = 1 : 1 molar), the new method provides Chl a estimates that are equivalent to those determined from the acidification technique. The new simple method requires a single fluorescence determination and provides adequate sensitivity for small sample sizes (<200 ml) even in the most oligotrophic marine and freshwater environments.
2,343 citations
TL;DR: The R(λ) values observed for blue waters are in full agreement with computed values in which new and realistic values of the absorption coefficient for pure water are used and presented.
Abstract: Spectral measurements of downwelling and upwelling daylight were made in waters different with respect to turbidity and pigment content and from these data the spectral values of the reflectance ratio just below the sea surface, R(λ), were calculated. The experimental results are interpreted by comparison with the theoretical R(λ) values computed from the absorption and back-scattering coefficients. The importance of molecular scattering in the light back-scattering process is emphasized. The R(λ) values observed for blue waters are in full agreement with computed values in which new and realistic values of the absorption coefficient for pure water are used and presented. For the various green waters, the chlorophyll concentrations and the scattering coefficients, as measured, are used in computations which account for the observed R(λ) values. The inverse process, i.e. to infer the content of the water from R(λ) measurements at selected wavelengths, is discussed in view of remote sensing applications.
2,219 citations