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Monitoring Carbon Dioxide from Space:Retrieval Algorithm and Flux Inversion Based on GOSAT Data and Using CarbonTracker-China

查看全文 作　　者：Dongxu [1]YANG;Huifang [2]ZHANG;Yi [1]LIU;Baozhang [2,3,4]CHEN;Zhaonan [1]CAI;Daren [1]Lü 高影响力作者 机构地区：[1]Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;[2]State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;[3]University of Chinese Academy of Sciences, Beijing 100049, China;[4]Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing 210023, China高影响力机构 出　　处：《Advances in Atmospheric Sciences》索引2017年第34卷第8期,共12页高影响力期刊 基　　金：funded by the Strategic Priority Research Program-Climate Change:Carbon Budget and Relevant Issues(Grant No.XDA05040200);the National Key Research and Development Program of China(Grant No.2016YFA0600203);the National Natural Science Foundation of China(Grant Nos.41375035 and 31500402);the Chinese Academy of Sciences Strategic Priority Program on Space Science(Grant No.XDA04077300) 摘　　要：Monitoring atmospheric carbon dioxide(CO_2) from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of 'The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change: Carbon Budget and Relevant Issues'. The carbon flux inversion system is composed of two separate parts: the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing(IAPCAS), and Carbon Tracker-China(CT-China), developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite(GOSAT) measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%–30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO_2(column-averaged CO_2dry-air mole fraction) is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO_2 product is used in carbon flux estimation by CT-China. The net ecosystem CO_2 exchange is-0.34 Pg C yr^(-1)(±0.08 Pg C yr^(-1)), with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion. 关 键 词：中国科学院 二氧化碳 反演系统 检索算法 碳通量 追踪 监测 数据质量控制
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