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A high-accuracy method for simulating the XCO2 global distribution using GOSAT retrieval data

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Abstract

A high-accuracy surface modeling (HASM) method based on the fundamental theorem of surfaces, is developed to simulate XCO2 surfaces using the GOSAT retrieval XCO2 data. Two tests are designed to investigate the simulation accuracy. The first test divides the existing satellite retrieval XCO2 data into training points and testing points, and simulates the XCO2 surface using the training points while computing the simulation error using the testing points. The absolute mean error (MAE) of the testing points is 1.189 ppmv, and the corresponding values of the comparison methods, Ordinary Kriging, IDW, and Spline are 1.203, 1.301, and 1.355 ppmv, respectively. The second test simulates the XCO2 surface using all the satellite retrieval points and uses the TCCON (Total Carbon Column Observing Network) site observation values as the ture values. For the six typical TCCON sites, the HASM simulation MAE is 1.688 ppmv, and the satellite retrieval MAE at the same sites is 2.147 ppmv. These results indicate that HASM can successfully simulate XCO2 surfaces based on satellite retrieval data.

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Acknowledgments

We thank the members of the GOSAT Project (JAXA, NIES and Ministry of the Environment, Japan) for providing GOSAT Level 2 data products. TCCON data were obtained from the TCCON Data Archive, operated by the California Institute of Technology from the website at http://tccon.ipac.caltech.edu/, and we thank all the Pis’ support and helpful suggestions about the paper. This work was supported by the National High-Tech R&D Program of the Ministry of Science and Technology of China (Grant Nos. 2013AA122003, 2011AA12A104-3), the Research Projects of Chuzhou University (Grant No. 2015QD08), the Key Program of National Natural Science Foundation of China (Grant No. 91325204), the National Fundamental R&D Program of the Ministry of Science and Technology of China (Grant No. 2013FY111600-4), the European Commission’s Seventh Framework Programme “PANDA” (Grant No. FP7-SPACE-2013-1), the Public Industry-Specific Fund for Meteorology (Grant No. GYHY201106045) and the 4th and 5th GOSAT/TANSO Joint Research Project.

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Authors and Affiliations

  1. Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou, 239000, China

    MingWei Zhao, Chun Wang & Ling Jiang

  2. National Satellite Meteorology Center, China Meteorological Administration, Beijing, 100081, China

    XingYing Zhang

  3. State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    TianXiang Yue

  4. Anhui Institute of Economics, Hefei, 230051, China

    JingLu Sun

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  1. MingWei Zhao
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Correspondence to XingYing Zhang or TianXiang Yue.

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Zhao, M., Zhang, X., Yue, T. et al. A high-accuracy method for simulating the XCO2 global distribution using GOSAT retrieval data. Sci. China Earth Sci. 60, 143–155 (2017). https://doi.org/10.1007/s11430-016-0069-7

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  • DOI: https://doi.org/10.1007/s11430-016-0069-7

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