Integrating Remote Sensing, Field Observations, and Models to Understand Disturbance and Climate Effects on the Carbon Balance of the West Coast U.S.

B.E. Law ; D. Turner ; M. Goeckede

关键词: ALGORITHMS;    BIOSPHERE;    CARBON;    CLIMATES;    DISTURBANCES;    ECOSYSTEMS;    INVENTORIES;    METEOROLOGY;    PRODUCTIVITY;    REGIONAL ANALYSIS;    REMOTE SENSING;    STORAGE;    TERRESTRIAL ECOSYSTEMS;    WATER regional carbon balance;    NEP;    biomass;    eddy cov;   

DOI  :  10.2172/980758
RP-ID  :  DOE/ER/64361-3
PID  :  OSTI ID: 980758
Others  :  TRN: US201215%%334

学科分类：环境科学（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

GOAL: To develop and apply an approach to quantify and understand the regional carbon balance of the west coast states for the North American Carbon Program. OBJECTIVE: As an element of NACP research, the proposed investigation is a two pronged approach that derives and evaluates a regional carbon (C) budget for Oregon, Washington, and California. Objectives are (1) Use multiple data sources, including AmeriFlux data, inventories, and multispectral remote sensing data to investigate trends in carbon storage and exchanges of CO2 and water with variation in climate and disturbance history; (2) Develop and apply regional modeling that relies on these multiple data sources to reduce uncertainty in spatial estimates of carbon storage and NEP, and relative contributions of terrestrial ecosystems and anthropogenic emissions to atmospheric CO2 in the region; (3) Model terrestrial carbon processes across the region, using the Biome-BGC terrestrial ecosystem model, and an atmospheric inverse modeling approach to estimate variation in rate and timing of terrestrial uptake and feedbacks to the atmosphere in response to climate and disturbance. APPROACH: In performing the regional analysis, the research plan for the bottom-up approach uses a nested hierarchy of observations that include AmeriFlux data (i.e., net ecosystem exchange (NEE) from eddy covariance and associated biometric data), intermediate intensity inventories from an extended plot array partially developed from the PI's previous research, Forest Service FIA and CVS inventory data, time since disturbance, disturbance type, and cover type from Landsat developed in this study, and productivity estimates from MODIS algorithms. The BIOME-BGC model is used to integrate information from these sources and quantify C balance across the region. The inverse modeling approach assimilates flux data from AmeriFlux sites, high precision CO2 concentration data from AmeriFlux towers and four new calibrated CO2 sites, reanalysis meteorology and various remote sensing products to generate statewide estimates of biosphere carbon exchange from the atmospheric point of view.