[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.

Abstract.A new method of retrieving the parameters of a power-law particle size distribution (PSD) from ocean color remote sensing data was used to assess the global distribution and dynamics of phytoplankton functional types (PFT's). The method retrieves the power-law slope, ξ , and the abundance at a reference diameter, N 0 , based upon the shape and magnitude of the particulate backscattering coefficient spectrum. Relating the PSD to PFT's on global scales assumes that the open ocean particulate assemblage is biogenic. The retrieved PSD's can be integrated to define three size-based PFT's by the percent volume concentration contribution of three phytoplankton size classes -picoplankton (0.5-2 µm in equivalent spherical diameter), nanoplankton (2-20 µm) and microplankton (20-50 µm). Validation with in-situ HPLC diagnostic pigments resulted in better matchups for the pico-and micro-phytoplankton size classes as compared to nanoplankton. Global decadal averages derived from SeaWiFS monthly data reveal PFT and particle abundance spatial patterns that are consistent with current understanding. Oligotrophic gyres are characterized by lower particle abundance and higher contribution by picoplanktonsized particles than transitional or eutrophic regions. Seasonal succession patterns for size-based PFT's reveal good correspondence between increasing chlorophyll concentration and percent contribution by microplankton, as well as increasing particle abundance. Long-term trends in particle abundances are generally well correlated with the MEI index indicating increased oligotrophy (i.e. lower particle abunCorrespondence to: T. S. Kostadinov (tiho@eri.ucsb.edu) dance and increased contribution of picoplankton-sized particles) during the warm phase of an El Niño event. This work demonstrates the utility and future potential of assessing phytoplankton functional types using remote characterization of the particle size distribution.

Phytoplankton are composed of diverse taxonomical groups, which are manifested as distinct morphology, size, and pigment composition. These characteristics, modulated by their physiological state, impact their light absorption and scattering, allowing them to be detected with ocean color satellite radiometry. There is a growing volume of literature describing satellite algorithms to retrieve information on phytoplankton composition in the ocean. This synthesis provides a review of current methods and a simplified comparison of approaches. The aim is to provide an easily comprehensible resource for non-algorithm developers, who desire to use these products, thereby raising the level of awareness and use of these products and reducing the boundary of expert knowledge needed to make a pragmatic selection of output products with confidence. The satellite input and output products, their associated validation metrics, as well as assumptions, strengths, and limitations of the various algorithm types are described, providing a framework for algorithm organization to assist users and inspire new aspects of algorithm development capable of exploiting the higher spectral, spatial and temporal resolutions from the next generation of ocean color satellites.

Variability in the optical particle backscattering coefficient (b bp ) is investigated in oceanic waters from two sites, namely the BOUée pour l'acquiSition d'une Série Optique à Long termE site in the northwestern Mediterranean Sea and the Plumes and Blooms stations in the Santa Barbara Channel off Southern California. Data from these two sites span two orders of magnitude in b bp and likely cover typical open ocean values. A significant relationship is found between b bp at wavelengths of 442 and 555 nm and chlorophyll concentration. However the large spread in this relationship makes chlorophyll a poor predictor of b bp . The relationship between b bp and the particulate beam attenuation coefficient at 660 nm is tighter for both sites, indicating covariability of the particle size ranges that determine both coefficients. A detailed study of the seasonal changes of the b bp vs. chlorophyll relationship reveals that this bio-optical relationship might be best described as a succession of distinct regimes with rapid transitions from one to another. The backscattering ratio (b bp ; the ratio of b bp to total particulate scattering, b p ) ranges from about 0.2% to 1.5%, which is similar to previously reported values. The relationship between b bp and chlorophyll was not significant, while values of the backscattering ratio varied spectrally.

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield  ∼  0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.