Synthesis of Remote Sensing and Field Observations to Model and Understand Disturbance and Climate Effects on the Carbon Balance of Oregon & Northern California

Beverly Law ; David Turner ; Warren Cohen ; Mathias Goeckede

关键词: BOUNDARY LAYERS;    CARBON;    CARBON CYCLE;    CLIMATES;    DISTURBANCES;    ECOSYSTEMS;    INVENTORIES;    LAND USE;    MANAGEMENT;    PRODUCTION;    REGIONAL ANALYSIS;    REMOTE SENSING;    SIMULATION;    SYNTHESIS terrestrial carbon processes;    carbon cycle science;    regional carbon modeling;   

DOI  :  10.2172/928601
RP-ID  :  DOE/ER/63917-4
PID  :  OSTI ID: 928601
Others  :  TRN: US201006%%466

学科分类：环境科学（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

The goal is to quantify and explain the carbon (C) budget for Oregon and N. California. The research compares "bottom -up" and "top-down" methods, and develops prototype analytical systems for regional analysis of the carbon balance that are potentially applicable to other continental regions, and that can be used to explore climate, disturbance and land-use effects on the carbon cycle. Objectives are: 1) Improve, test and apply a bottom up approach that synthesizes a spatially nested hierarchy of observations (multispectral remote sensing, inventories, flux and extensive sites), and the Biome-BGC model to quantify the C balance across the region; 2) Improve, test and apply a top down approach for regional and global C flux modeling that uses a model-data fusion scheme (MODIS products, AmeriFlux, atmospheric CO2 concentration network), and a boundary layer model to estimate net ecosystem production (NEP) across the region and partition it among GPP, R(a) and R(h). 3) Provide critical understanding of the controls on regional C balance (how NEP and carbon stocks are influenced by disturbance from fire and management, land use, and interannual climate variation). The key science questions are, "What are the magnitudes and distributions of C sources and sinks on seasonal to decadal time scales, and what processes are controlling their dynamics? What are regional spatial and temporal variations of C sources and sinks? What are the errors and uncertainties in the data products and results (i.e., in situ observations, remote sensing, models)?