文献类型：会议论文

英文题名：IMPROVMENT OF BIOME-BGC MODEL BY INCORPORATION AND DATA ASSIMILATION

作者：Yan, Min[1] Tian, Xin[1] Li, Zengyuan[1] Chen, Erxue[1]

第一作者：Yan, Min

通信作者：Tian, X[1]

机构：[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

会议论文集：36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 10-15, 2016

会议地点：Beijing, PEOPLES R CHINA

语种：英文

外文关键词：carbon flux; Biome-BGC; GLASS LAI; EnKF

年份：2016

摘要：A strategy of data assimilation using the refined remote sensing product for the process-based model (Biome-BGC) in order to improve the simulated carbon fluxes was proposed. Firstly, we applied the optimized the remotesensing- based MODIS MOD_17 GPP (MOD_17) model to calibrate the process-based Biome-BGC model. This incorporation strategy for the parameterization of BiomeBGC has been proved to be more reliable in carbon fluxes' simulations. The calibrated Biome-BGC model agreed better with the Eddy covariance (EC) measurements (R-2 = 0.87, RMSE= 1.583 gC/m(2)/d) than the original model (R-2 = 0.72, RMSE= 2.419 gC/m(2)/d). Afterwards, two years (8-day during 2003 and 2004) Global LAnd Surface Satellite (GLASS) LAI products were applied to test the data assimilation procedure for the calibrated Biome-BGC using Ensemble Kalman Filter (EnKF). The results indicated that simulated LAI through assimilation agreed better with GLASS LAI, and the carbon fluxes are hoped to improve by further adaption of the filter.