Keywords
biogeochemical cycle, modelling, scale, ensemble simulation, spatial and temporal variance
Start Date
1-7-2006 12:00 AM
Abstract
Upscaling the spatial and temporal changes of carbon stocks and fluxes from sites to regions is challenging owing to the spatial and temporal variances and 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 develop the General Ensemble Biogeochemical Modeling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. GEMS relies on 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 (NPP) from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The modeling philosophy embedded in GEMS makes it ideal for incorporating and assimilating information with various uncertainties at a range of spatio-temporal resolutions. The application of GEMS to quantify the contemporary terrestrial carbon dynamics in the United States is presented as an example of GEMS applications.
Upscaling Terrestrial Carbon Dynamics From Sites To Regions With Uncertainty Measures: The GEMS Experience
Upscaling the spatial and temporal changes of carbon stocks and fluxes from sites to regions is challenging owing to the spatial and temporal variances and 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 develop the General Ensemble Biogeochemical Modeling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. GEMS relies on 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 (NPP) from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The modeling philosophy embedded in GEMS makes it ideal for incorporating and assimilating information with various uncertainties at a range of spatio-temporal resolutions. The application of GEMS to quantify the contemporary terrestrial carbon dynamics in the United States is presented as an example of GEMS applications.
