Takafumi Hirata

Generalized ocean color inversion model for retrieving marine inherent optical properties

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment

A semianalytical approach to the problem of determining inherent optical properties from satellite and in situ ocean color data is presented. The model uses empirically derived spectral slopes between neighboring wavebands in combination with radiative transfer modeling to determine the spectral absorption (alpha) and backscatter (b(b)); these values are then further decomposed into absorption due to phytoplankton, detrital, and colored dissolved organic matter components. When compared with over 400 in situ data points the model makes good retrievals of the total absorption and backscatter across the entire spectrum, with regression slopes close to unity, little or no bias, high percentage of variance explained, and low rms errors.

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

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.

Global Retrieval of Diatom Abundance Based on Phytoplankton Pigments and Satellite Data

Diatoms are the major marine primary producers on the global scale and, recently, several methods have been developed to retrieve their abundance or dominance from satellite remote sensing data. In this work, we highlight the importance of the Southern Ocean (SO) in developing a global algorithm for diatom using an Abundance Based Approach (ABA). A large global in situ data set of phytoplankton pigments was compiled, particularly with more samples collected in the SO. We revised the ABA to take account of the information on the penetration depth (Zpd) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed that there is a distinct relationship between diatoms and TChla in the SO, and a new global model (ABAZpd) improved the estimation of diatoms abundance by 28% in the SO compared with the original ABA model. In addition, we developed a regional model for the SO which further improved the retrieval of diatoms by 17% compared with the global ABAZpd model. As a result, we found that diatom may be more abundant in the SO than previously thought. Linear trend analysis of diatom abundance using the regional model for the SO showed that there are statistically significant trends, both increasing and decreasing, in diatom abundance over the past eleven years in the region.

Impacts of light shading and nutrient enrichment geo-engineering approaches on the productivity of a stratified, oligotrophic ocean ecosystem

Geo-engineering proposals to mitigate global warming have focused either on methods of carbon dioxide removal, particularly nutrient fertilization of plant growth, or on cooling the Earths surface by reducing incoming solar radiation (shading). Marine phytoplankton contribute half the Earths biological carbon fixation and carbon export in the ocean is modulated by the actions of microbes and grazing communities in recycling nutrients. Both nutrients and light are essential for photosynthesis, so understanding the relative influence of both these geo-engineering approaches on ocean ecosystem production and processes is critical to the evaluation of their effectiveness. In this paper, we investigate the relationship between light and nutrient availability on productivity in a stratified, oligotrophic subtropical ocean ecosystem using a one-dimensional water column model coupled to a multi-plankton ecosystem model, with the goal of elucidating potential impacts of these geo-engineering approaches on ecosystem production. We find that solar shading approaches can redistribute productivity in the water column but do not change total production. Macronutrient enrichment is able to enhance the export of carbon, although heterotrophic recycling reduces the efficiency of carbon export substantially over time. Our results highlight the requirement for a fuller consideration of marine ecosystem interactions and feedbacks, beyond simply the stimulation of surface blooms, in the evaluation of putative geo-engineering approaches.

Relationship between the distribution function of ocean nadir radiance and inherent optical properties for oceanic waters

The distribution function of the ocean nadir radiance, defined by the upward radiance-to-irradiance ratio, is investigated as functions of the absorption coefficient and the volume scattering function to understand their relationship rather than to develop a numerical algorithm. It is shown for oceanic waters that the distribution function is directly proportional to the volume scattering function normalized by the backscattering coefficient. The relatively small spectral variation of the distribution function is explained by the small spectral variation of the normalized volume scattering function, as well as by a function that describes the contribution of the backscattering-to-absorption ratio to the distribution function. The interpretation described was verified against in situ data, highlighting factors controlling the distribution function of oceanic waters.

Comparing satellite-based phytoplankton classification methods

Satellite Phytoplankton Functional Type Algorithm Intercomparison Workshop; Sapporo, Japan, 22–23 November 2011 Satellite observations of ocean color have become synonymous with derivations of chlorophyll a concentration as a proxy for phytoplankton biomass. In addition, a number of satellite algorithms for estimating the phytoplankton community structure have been developed that provide size-structure estimates of phytoplankton and detect taxonomic groups (termed phytoplankton functional types, or PFTs). These new algorithms provide an increased level of observational detail for ecosystem and biogeochemical studies of the role of phytoplankton in marine systems.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a onedimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.