Model-Data Assimilation for Quantifying Carbon Sources and Sinks

Shuguang Liu, ARTS, contractor to U.S. Geological Survey Earth Resources and Observation (EROS) Center, sliu@usgs.gov (Presenting)
Zhengpeng Li, ARTS, contractor to U.S. Geological Survey Earth Resources and Observation (EROS) Center, zli@usgs.gov
Mingshi Chen, ARTS, contractor to U.S. Geological Survey Earth Resources and Observation (EROS) Center, mchen@usgs.gov
Thomas Loveland, U.S. Geological Survey Earth Resources and Observation (EROS) Center, loveland@usgs.gov
Larry Tieszen, U.S. Geological Survey Earth Resources and Observation (EROS) Center, tieszen@usgs.gov

Estimating the dynamic evolution of the magnitude, spatial patterns, mechanisms, and uncertainty of carbon sources and sinks at the regional scale is challenging because of the spatial and temporal covariance of driving variables and the uncertainties in both the model and the input data. Although various modeling approaches have been developed to facilitate the upscaling process, few deal with error transfer from model input to output and error propagation in time and space. We developed the General Ensemble Biogeochemical Modeling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. GEMS relies on well-tested site-scale biogeochemical models (e.g., the Erosion-Deposition-Carbon Model (EDCM) and CENTURY) to simulate the carbon dynamics at the site scale. The spatial deployment of the site-scale model in GEMS is based on the spatial and temporal joint frequency distribution of major driving variables (e.g., land cover and land use change, climate, soils, disturbances, and management). At the site scale, GEMS uses stochastic ensemble simulations to incorporate input uncertainty and to quantify uncertainty transfer from input to output. Using data assimilation techniques, GEMS simulations can be constrained by field and satellite observations or census data including estimates of net primary productivity from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The GEMS-EDCM has been applied to quantify the spatial and temporal distributions of the terrestrial carbon sources and sinks in the United States.