New satellite observations from MODIS-Aqua provide an unprecedented opportunity to observe ocean surface properties in an integrated fashion. By assimilating satellite data products into a global coupled three-dimensional model of physical, biogeochemical, and radiative processes, we can potentially extend these remote observations to understand the underlying fundamental processes governing the distributions of biogeochemically important variables observed from space.
We propose to enhance an ocean biogeochemical assimilation system using data products from MODIS-Aqua and other satellites and a coupled general circulation, biogeochemical, and radiative model of the global oceans. The model uses an ocean general circulation model for physical forcing, multiple phytoplankton and nutrient components for local source terms, and a complete cloud and atmospheric optically forced radiative transfer model to provide irradiance for growth. Recent results using two different assimilation methodologies have clearly established the benefits of ocean chlorophyll data assimilation from SeaWiFS. Here we intend to exploit the richness of MODIS-Aqua data products by assimilating water-leaving radiances, the core of ocean color derived geophysical products. Immediate benefits of radiance assimilation is improved surface energy representation, which will help quantify the role of ocean biology in climate. The larger scientific objective is elucidation of optically active substances in the oceans, including phytoplankton functional groups and colored dissolved organic matter. There is no guarantee that we will achieve success in this ambitious latter objective, but the potential rewards are very large, and may feed back into promoting methods for quantifying these substances from space or possibly lead to new sensor designs for maximizing retrievals of these potential new products. All validated results from this proposal will be made publicly available through the GES-DAAC Giovanni location, with errors and error-distributions fully described. In a closely coupled assimilation system, we have the potential of 1) providing enhanced model performance and outputs, and 2) providing value-enhanced MODIS-Aqua data products, especially with respect to new derived products and spatially-complete daily fields.
