JGOFS/SMP: Modeling Microbial Proceses and Dissolved Organic Matter: A Case Study at the US-JGOFS Time Series Station ALOHA

Universities Space Research Association, Washington DC

Investigators

Abstract

Modeling microbial processes and dissolved organic matter: a case study at the US-JGOFS time series Station ALOHA The development of coupled physical-biological models of ocean biogeochemistry is hampered by several critical knowledge gaps. Plankton models have attempted to incorporate the "microbial loop" and dissolved organic substances, but have done so using formulations that are highly uncertain, do not take into consideration a great deal of new information that has emerged over the past decade, and have not been shown to have greater predictive power than simple empirical formulations used in e.g. the Ocean Carbon Cycle Model Intercomparison Project protocols. As these processes play a significant role in biogeochemical cycling in the oceans, the development of more realistic models of this component of the community is critical to the development of global models that have a mechanistic basis for predicting elemental budgets. Of the JGOFS time-series study sites, the Hawaii Ocean Time-Series (HOT) has received the least attention from modelers. Observations at HOT deviate strongly from established paradigms of plankton ecology (seasonal convection, nitrate-based production, metazoan zooplankton as primary consumers) that are to some extent assumed in plankton models. The HOT data base provides an unprecedented opportunity to validate a more realistic model, as observations of dissolved organic substances have been made routinely throughout the HOT project, and significant interannual variability in these has been observed. Although there are significant uncertainties associated with one dimensional (depth-time) simulation, the high computational cost of three dimensional simulations makes extensive validation experiments with biological submodels impractical in such a context. In addition, the HOT data base is itself Eulerian, and significant interannual variability in ocean biogeochemistry has already been observed. To provide a meaningful simulation of such variability requires a mechanistic model not only of plankton population biology, but of the interface between biology and chemistry that is found in the decomposer loop. The PIs will use the HOT database to develop and test such a model.