Projections of Land-Use Change and the Carbon-Cycle
Steven
Smith, JGCRI (UMd & PNNL), ssmith@pnl.gov
(Presenting)
The terrestrial carbon cycle has been substantially altered by human activities and this alteration is continuing globally. Projecting the future behavior of the carbon-cycle, therefore, requires a coupled analysis of the carbon-cycle and the socio-economic forces driving land-use changes. Such an analysis is also required in order to consistently produce projections of land-use related emissions of carbon-dioxide and other compounds. Finally, analysis of carbon management options requires that the close coupling between the carbon- and socio-economic systems be explicitly considered.
This proposal will address these issues by using remote sensing information to improve long-term projections of land-use emissions, particularly CO2, CO, and CH4, and to provide for the analysis of the implications of land-use changes for atmospheric greenhouse gas concentrations, atmospheric chemistry, and carbon management. This will be accomplished within the -MiniCAM framework, the state of the art integrated assessment modeling framework developed at the Joint Global Change Research Institute (JGCRI - Umd and PNNL). Remote sensing data products and the results of models driven by remote sensing data will be used to improve the representation of the carbon-cycle and the Earth's land-surface characteristics. Critical to this project is the use of spatially resolved data products and earth system model outputs which will allow analysis of different regions and sub-regions as needed. This will enable global and regional analysis of carbon dynamics, carbon sequestration potential, and coupled dynamics of the carbon-cycle and the socio-economic systems that are driving land-use and climate changes. Both parametric uncertainty and uncertainty due to different model spatial definitions will be quantified. A particular focus will be analysis of the coupled carbon-cycle and socio-economic system as represented in the JGCRI integrated assessment framework. The result will be long-term emissions projections that are substantially improved over available data in terms of spatial and temporal detail, consistency with remote sensing data, and integration with socio-economic drivers. The capabilities developed through this proposal will be integrated into the JGCRI integrated assessment frameworks that will be used on a routine basis in future work for government agencies.