Dataset: Coagulation model results
Deployment: USJGOFS_SMP

Research topic: Development of upper-ocean aggregation models useful for interpreting and predicting carbon fluxes

Understanding the mechanisms and rates of carbon removal from surface waters remains an important goal of the Joint Global Oceanographic Flux Study (JGOFS).  Particle formation and sinking is an important process for such removal.  Much of the particulate fraction in surface waters is in the form of small cells having slow sinking rates.  For these cells to sink more rapidly, they need to be packaged into larger particles.  Fecal pellet production by animals provides one way of doing this; aggregate formation another.  Because aggregates are the dominant form of sedimenting particles, understanding the processes that form and destroy aggregates is crucial for JGOFS to achieve its goal.

This proposal seeks to obtain support to develop models that will increase our understanding of the processes affecting organic matter export from the surface mixed layer.  To this end, the models will combine particle aggregation models with plankton food web models.  We propose to use data sets from the JGOFS process and time-series studies to determine and refine the ability of the models to predict carbon export.

The approach will be to combine the techniques we have refined in modeling algal blooms with food web models of the surface mixed layer to understand the effect that aggregation has on carbon export flux. We will work with a two dimensional particle size spectrum that will allow us to differentiate the effects of collisions with a marine snow particle from those with fecal pellet of the same mass. We expect to determine the key parameters governing the vertical particle flux from the mixed layer.

We will use data collected during the JGOFS field programs to refine the models. Combining the simulation results with JGOFS field data will increase our understanding of the processes affecting vertical export fluxes and improve the accuracy of flux predictions made using the models. The results of this work will increase significantly our ability to accurately describe the movement of organic material from the surface to the deeper parts of the ocean.