Linear combinations of simulated conetrations arising from each basis flux will then be optimized against observed concentrations to obtain regional flux estimates according to each model. These inversions will be performed using standard methods for each model, and sensitivity tests will be performed to quantify the degree of uncertainty in the resulting flux estimates that arises from differences in model transport, choice of observational data, and inverse methodology. We have analyzed Level 1 results for 15 modeling groups, and will submit the results to Science in March 2001. This is the first study to directly quantify the separate contributions of transport error and sparse observations to the uncertainty in regional carbon fluxes. Results show that carbon fluxes in some regions of the world are much better constrained by observations than others, with uncertainty dominated by sparse data especially over the tropical continents and by uncertain model transport over the northern midlatitudes.
Some regional fluxes are surprisingly robust across the very different transport scenarios tested.
We have presented results at a series of national and international meetings, including contribution of several papers to a special session at the Fall 2000 AGU meeting on combining models and observations to studying the carbon cycle. Future Work Besides the Science manuscript, we are preparing a series of papers on the Level 1 results for disciplinary journals. Level 2 analyses will include inversions across the suite of transport models for both seasonal and interannual variability, a test of the hypothesis advanced by Bousquet et al. that the interannual variability is better constrained than the mean state, and a further examination of the potential use of satellite and airborne measurements, as well as augmented surface-based data, in providing information on the state of the carbon cycle.