Dataset: Model results of 1-D global mixed layer depth ecosystem model, OGCM/OCMIP-Doney, 2003 (U.S. JGOFS Synthesis & Modeling Phase project results)

The preliminary analysis of the WOCE/JGOFS global
ocean carbon survey has contributed greatly to an improved understanding
of the mean and perturbed state of the ocean carbon cycle.  The global
carbon data set and associated new data analysis techniques have helped
to clarify among other issues the air-sea CO₂ flux fields, the
natural dissolved inorganic carbon background distributions, and the long-term
uptake patterns of anthropogenic carbon.  A decade long, one-time
global survey, however, is less useful for constraining the temporal variability
of the ocean, for which we will have to turn to more directed measurement
programs and numerical models.  Here, I propose to evaluate the impact
of interannual climate variability on the ocean carbon system using a state
of the art numerical global ocean circulation model, the NCAR CSM Ocean
Model (NCOM), driven with synoptic atmospheric forcing data sets either
from the NCEP reanalysis (1957-1996) or the coupled NCAR Climate System
Model.

The analysis of the resulting model variability in the air-sea CO₂
flux and subsurface dissolved inorganic carbon distribution will be focused
on two related questions: 

1. what is the oceanic contribution to the observed variability in the atmospheric
   CO₂ growth rate?, and 
2. what type of sampling strategy is needed to quantify the long-term uptake
   of anthropogenic carbon given the natural background variability? 

Particular emphasis will be given to examining the physical and biological
mechanisms governing variability in the model and their relevance to the
real ocean.  Oceanic and atmospheric carbon observations will be used
extensively to validate both the mean state and variability of the ocean
carbon model in collaboration with a number of co-investigators (D. Schimel,
NCAR; I. Fung, UC Berkeley; R. Wanninkhof, NOAA/AOML).  This study
will provide also a framework for interpreting the WOCE/JGOFS global CO₂
survey and designing optimal future sampling networks.