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/•g 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. IntroductionThe influence of phytoplankton on the color of seawater has been studied for several decades. It is well understood that chlorophyll a, the primary photosynthetic pigment in phytoplankton, absorbs relatively more blue and red light than green, and the spectrum of backscattered sunlight or color of ocean water progressively shifts from deep blue to green as the concentration of phytoplankton increases [e.g.

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

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.

[1] The particle size distribution (PSD) provides important information about pelagic ocean ecosystem structure and function. Knowledge of the PSD and its changes in time can be used to assess the contributions made by phytoplankton functional groups to primary production, particle sinking, and carbon sequestration by the ocean. However, few field measurements of the PSD have been made in the pelagic ocean, and little is known about its space-time variation. Here, a novel bio-optical algorithm is introduced to retrieve the parameters of a power law particle size spectrum from satellite ocean color observations. First, the particle backscattering coefficient spectrum, b bp (l), is retrieved from monthly Sea-viewing Wide Field-of-view Sensor (SeaWiFS) normalized water-leaving radiance observations following Loisel et al. (2006). Mie modeling is then used to estimate the parameters of a power law PSD (the PSD slope and the particle differential number concentration for a given reference diameter) as a function of the particulate backscattering spectrum. Algorithm uncertainties are greater when b bp (l) slopes are low, which occurs in high-productivity areas. Satellite-based retrievals of PSD parameters are reasonably consistent with available field observations. As an example, the algorithm was applied to monthly SeaWiFS global imagery from August 2007. Global spatial distributions show subtropical oligotrophic gyres characterized by higher PSD slopes and smaller particle number concentrations, as compared with coastal and other high-productivity areas. Partitioning particle number and volume concentrations into picophytoplankton-, nanophytoplankton-, and microphytoplankton-sized classes indicates that the abundance of picoplankton-sized particles is roughly constant spatially and that they dominate the particle volume concentrations in oligotrophic regions. On the other hand, abundances of microplankton-sized particles vary over many orders of magnitude, and they contribute to volume concentration only in the highest-productivity areas. These results are consistent with current understanding of particle dynamics of pelagic ecosystems and provide new tools for biogeochemical modeling and assessment of the global ocean ecosystem.

[1] Colored dissolved organic matter (CDOM), also referred to as gelbstoff, gilvin, or yellow matter, has long been known to be an important component of the optical properties of coastal and estuarine environments. However, an understanding of the processes regulating its global distribution and variability, its relationship to the total pool of dissolved organic carbon (DOC), and its influence on light availability remain largely unexplored. Satellite imagery from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is used to characterize the global distribution of light absorption due to colored detrital and dissolved materials (CDM). The quantity CDM is considered as it is not yet possible to differentiate CDOM and detrital particulate absorption from ocean color spectra on a routine basis. Nonetheless, analysis of an extensive field data set indicates that detrital particulates make only a small contribution to CDM. A comparison of coincident field observations of CDM with SeaWiFS retrievals shows good agreement, indicating that the present procedures perform well. To first order, the basin-scale CDM distribution reflects patterns of wind-driven vertical circulation of the gyres modulated by a meridional trend of increasing CDM toward higher latitudes. The global CDM distribution appears regulated by a coupling of biological, photochemical, and physical oceanographic processes all acting on a local scale, and greater than 50% of blue light absorption is controlled by CDM. Significant differences in both CDM concentration and its contribution to blue light absorption are found spatially among the major ocean basins and temporally on variety of timescales. Significant impacts of riverine discharges can be discerned, although their effects are largely localized. Basin-scale distributions of CDM and DOC are largely unrelated, indicating that CDM is a small and highly variable fraction of the global DOC pool. This first view of the global CDM distribution opens many new doors for the quantification of global marine photoprocesses using satellite ocean color data.