Dataset: 3-D Ecosystem Model of the Ross Sea
Deployment: USJGOFS_SMP

A dynamic 3-dimensional model of the coupled sea ice/ice edge/open water ecosystem in the  southwestern Ross Sea will be developed to investigate the complex interactions between environmental forcing and the production (primary and secondary) and fate of biogenic carbon. The model will simulate the depth-dependent physical and biological dynamics within sea ice and the open ocean,  including the marginal ice zone (MIZ), and will include components which describe 1) radiative transfer within the sea ice and the water column, 2) water column stratification as it is influenced by surface winds and sea ice meltwater, 3) physicochemical properties of sea ice and the water column (i.e. temperature, salinity, nutrient concentration, etc.), and 4) biological dynamics, including the activity of microalgae, grazers, and a simple microbial loop.  The availability of remotely sensed data sets will be crucial to model development and performance assessment and includes SeaWiFS and/or ADEOS/OCTS surface pigments, AVHRR sea surface temperatures, and SSM/I and/or RADARSAT sea ice coverage.  The primary objective of  this research will be to understand the principal processes that control the flux of carbon (and related biologically active chemical substances) from surface waters to the deep ocean in the southwestern Ross Sea, the site of the Southern Ocean Joint Global Ocean Flux Study (SOJGOFS).  This will be achieved principally through the use of a 3-dimensional coupled physical/biological ocean/sea ice ecosystem model of the southwestern Ross Sea which will synthesize observational data collected both in the field (during SOJGOFS and ROAVERRS) and remotely via satellite.  It is anticipated that a better understanding of ecosystem structure in the southwestern Ross Sea will be gained during the course of this research and that the insights gained can be adapted to the Southern Ocean and perhaps to other oceanic regions as well.  This will allow us to better predict and prepare for the effects of fluctuations in the global climate system in the future.