Refined Estimates of the Eastern North American Carbon Budget: Multi-Objective Model Calibration and Data Assimilation
College: Agricultural, Consumer and Environmental Sciences
Award year: 2009-2010
There is a clear and growing demand for scientists to produce quantitative estimates of current and future impacts of climate change on terrestrial ecosystems that include robust estimates of uncertainty and risk. This project applies Bayesian statistical techniques to calibrate a sophisticated terrestrial ecosystem model, the Ecosystem Demography model (ED2.1), to thousands of sites simultaneously in eastern North America with multiple data constraints at each site derived from vegetation inventories, eddy-covariance, or remote sensing. Posterior parameter estimates are used to construct model predictive credible intervals and to conduct sensitivity/elasticity analyses. Next, data assimilation techniques are applied to estimate the current ecosystem state and fluxes for the study region. Finally, model forecasts will be generated for different climate change scenarios accounting for the uncertainties in the model, the initial conditions, and future climate. The successful completion of this project will result in a clear improvement of our understanding of the North American carbon cycle and the potential impacts of climate change in terms of an improvement in the spatial resolution, and improvement in the connection between models and data, and an improvement in the estimation of model uncertainty.