作者简介:居为民(1963-),男,江苏海安人,教授,主要从事全球变化研究.E-mail:juweimin@nju.edu.cn
收稿日期: 2016-09-21
修回日期: 2016-11-01
网络出版日期: 2016-11-20
基金资助
国家重点研发计划项目“基于多源卫星遥感的高分辨率全球碳同化系统研究”(编号:2016YFA0600200)资助
版权
Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data
First author:Ju Weimin(1963-), male, Haian County, Jiangsu Province, Professor. Research areas include global change.E-mail:juweimin@nju.edu.cn
Received date: 2016-09-21
Revised date: 2016-11-01
Online published: 2016-11-20
Supported by
Project supported by the National Key Research and Development Program of China“Study on the global carbon assimilation system based on multisource remote sensing data under the national key research and development programs for global change and adaptation”(No.2016YFA0600200)
Copyright
2016年4月签署的“巴黎协定”的目标是到21世纪下半叶全球人为碳排放与生态系统碳汇持平,为了实现这一目标需要精确计量全球不同地区的碳通量,而全球碳同化系统是有效的技术手段。为此,国家科学技术部在“十三五”期间部署的国家重点研发计划“全球变化及应对”专项资助了“基于多源卫星遥感的高分辨率全球碳同化系统研究”项目。将发展生物圈和大气圈关键参数多源遥感协同反演技术体系、多源卫星与地面观测数据联合碳同化算法,进而建立耦合生态系统模型的高分辨率全球碳同化系统,联合同化多源观测数据,优化生态系统模型关键参数、光合和呼吸碳通量、重点区域人为源碳通量,定量揭示全球陆地生态系统和重点区域人为源碳通量时空格局、生态系统碳源汇驱动机制,为全球变化与应对专项目标的实现和国家决策提供技术与数据支持。
居为民 , 方红亮 , 田向军 , 江飞 , 占文凤 , 刘洋 , 王正兴 , 何剑锋 , 王绍强 , 彭书时 , 张永光 , 周艳莲 , 贾炳浩 , 杨东旭 , 符瑜 , 李荣 , 柳竟先 , 王海鲲 , 李贵才 , 陈卓奇 . 基于多源卫星遥感的高分辨率全球碳同化系统研究[J]. 地球科学进展, 2016 , 31(11) : 1105 -1110 . DOI: 10.11867/j.issn.1001-8166.2016.11.1105
The Paris agreement signed in April, 2016 aims to balance global anthropogenic carbon emissions and terrestrial carbon sinks by the middle of the 21st century. To fulfill this goal, it is necessary to calculate carbon fluxes of different regions reliably. The global carbon assimilation system is an effective technique for achieving this goal. The Ministry of Science and Technology of China supports the project entitled as study on the global carbon assimilation system based on multisource remote sensing data through the national key research and development programs for global change and adaptation during the thirteen-five period. This project will develop synergic inversion techniques for retrieving key parameters of biological and atmospheric cycles and for assimilating multisource remote sensing and ground based data. Then, the high resolution global carbon assimilation system coupled with an ecological model will be constructed. This system is able to assimilate jointly multisource observation data and to optimize key model parameters, photosynthesis and respiration carbon fluxes of global terrestrial ecosystems, and anthropogenic carbon emission fluxes of key regions. This system will be used to study quantitatively the spatial and temporal patterns of carbon fluxes of global terrestrial ecosystems and anthropogenic carbon emission fluxes of key regions and to identify the mechanisms driving the global terrestrial carbon sinks and sources. The outputs of this study will be helpful for the fulfillment of the key research and development programs for global change and adaptation and provide valuable data and technical support for the decision-making in China.
[1] | Ciais P, Sabine C, Bala G, et al.Carbon and other biogeochemical cycles[C]∥Stocker T F, Qin D, Plattner G K, et al, eds.Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York:Cambridge University Press,2013. |
[2] | Peters W, Jacobson A R, Sweeney C, et al.An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker[J].PNAS, 2007,104(48):18 925-18 930. |
[3] | Peters W, Krol M C, van der Werf G R, et al. Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations[J]. Global Change Biology,2010,16(4):1 317-1 337. |
[4] | Zhang S, Zheng X, Chen J M, et al.A global carbon assimilation system using a modified ensemble Kalman filter[J]. Geoscientific Model Development, 2015, 8: 805-816, doi:10.5194/gmd-8-805-2015. |
[5] | Yang D, Liu Y, Cai Z,et al.An advanced carbon dioxide retrieval algorithm for satellite measurements and its application to GOSAT observations[J]. Chinese Science Bulletin,2015, 60(23):2 063-2 066. |
[6] | Chevallier F, Palmer P I, Feng L, et al.Toward robust and consistent regional CO2 flux estimates from in situ and spaceborne measurements of atmospheric CO2[J].Geophysical Research Letters, 2014,41:1 065-1 070, doi: 10.1002/2013GL058772. |
[7] | Houweling S, Baker D, Basu S,et al.An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements[J]. Journal of Geophysical Research—Atmopshere,2015,120: 5 253-5 266, doi: 10.1002/2014JD022962. |
[8] | Kemp S, Scholze M, Ziehn T,et al.Limiting the parameter space in the Carbon Cycle Data Assimilation System (CCDAS)[J]. Geoscientific Model Development, 2014, 7: 1 609-1 619, doi:10.5194/gmd-7-1609-2014. |
[9] | Scholze M, Kaminski T, Knorr W, et al.Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle[J].Remote Sensing of Environment, 2016, 180: 334-345, doi: 10.1016/j.rse.2016.02.058. |
[10] | Parazoo N, Bowman K, Fisher J B,et al.Terrestrial gross primary production inferred from satellite fluorescence and vegetation models[J]. Global Change Biology,2014, 20: 3 103-3 121,doi: 10.1111/gcb.12652. |
[11] | Zhang Y G, Guanter L, Berry J A, et al.Estimation of vegetation photosynthetic capacity from space-based measurement of chlorophyll fluorescence for terrestrial biosphere models[J].Global Change Biology,2014, 20: 3 727-3 742,doi:10.1111/gcb.12664. |
[12] | Koffi E N, Rayner P J, Norton A J, et al.Investigating the usefulness of satellite-derived fluorescence data in inferring gross primary productivity within the carbon cycle data assimilation system[J]. Biogeosciences,2015, 12: 4 067-4 084, doi: 10.5194/bg-12-4067-2015. |
[13] | Zhang S, Yi X, Zheng X, et al.Global carbon assimilation system using a local ensemble Kalman filter with multiple ecosystem models[J]. Journal of Geophysical Research—Biogeosciences, 2014,119, doi:10.1002/2014JG002792. |
[14] | Chen Jingming, Ju Weimin, Liu Ronggao, et al.Remote Sensing and Optimization Calculation Methods of Global Terrestrial Carbon Sinks[M]. Beijing: Science Press, 2015:371. |
[14] | [陈镜明,居为民,刘荣高,等. 全球陆地碳汇的遥感和优化计算方法[M]. 北京:科学出版社,2015:371.] |
[15] | Tian X, Feng X.A non-linear least squares enhanced POD-4DVar algorithm for data assimilation[J].Tellus A, 2015, 67,doi: 10.3402/tellusa.v67.25340. |
[16] | Tian X, Xie Z, Liu Y, et al.A joint data assimilation system (Tan-Tracker) to simultaneously estimate surface CO2 fluxes and 3-D atmospheric CO2 concentrations from observations[J].Atmospheric Chemistry and Physics, 2014, 14:13 281-13 293,doi:10.5194/acp-14-13281-2014. |
[17] | Zhang H F, Chen B Z, van der Laan-Luijkx I T, et al. Net terrestrial CO2 exchange over China during 2001-2010 estimated with an ensemble data assimilation system for atmospheric CO2[J].Journal of Geophysical Research—Atmosphere, 2014, 119(6): 3 500-3 515. |
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