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Advances in Earth Science >

2016 , Vol. 31 >Issue 11: 1105 - 1110

DOI: https://doi.org/10.11867/j.issn.1001-8166.2016.11.1105

Orginal Article

Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data

  • Weimin Ju ,
  • Hongliang Fang ,
  • Xiangjun Tian ,
  • Fei Jiang ,
  • Wenfeng Zhan ,
  • Yang Liu ,
  • Zhengxing Wang ,
  • Jianfeng He ,
  • Shaoqiang Wang ,
  • Shushi Peng ,
  • Yongguang Zhang ,
  • Yanlian Zhou ,
  • Binghao Jia ,
  • Dongxu Yang ,
  • Yu Fu ,
  • Rong Li ,
  • Jingxian Liu ,
  • Haikun Wang ,
  • Guicai Li ,
  • Zhuoqi Chen
Expand
  • 1.Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing 210023, China
    2.Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3.Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    4.College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
    5.School of Geographic and Oceanographic, Nanjing University, Nanjing 210023, China
    6.School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
    7.School of the Environment, Nanjing University, Nanjing 210023, China
    8. National Satellite Meteorological Centre, Beijing 100081, China
    9.College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China

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

地球科学进展 编辑部, 2016,
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Abstract

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.

Key words： Synergic Inversion; Joint Assimilation; Carbon Assimilation System; Spatial and temporal patterns.

Cite this article

Weimin Ju , Hongliang Fang , Xiangjun Tian , Fei Jiang , Wenfeng Zhan , Yang Liu , Zhengxing Wang , Jianfeng He , Shaoqiang Wang , Shushi Peng , Yongguang Zhang , Yanlian Zhou , Binghao Jia , Dongxu Yang , Yu Fu , Rong Li , Jingxian Liu , Haikun Wang , Guicai Li , Zhuoqi Chen . Study on the Global Carbon Assimilation System Based on Multisource Remote Sensing Data[J]. Advances in Earth Science, 2016 , 31(11) : 1105 -1110 . DOI: 10.11867/j.issn.1001-8166.2016.11.1105

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