气候变化研究进展 ›› 2017, Vol. 13 ›› Issue (2): 95-102.doi: 10.12006/j.issn.1673-1719.2016.152

• 气候系统变化 •    下一篇

基于SCIAMACHY反演数据的全球CO2浓度时空变化特征研究

赵明伟1,李晨晨1,张兴赢2,王春1,江岭1,孙京禄3   

  1. 1 滁州学院安徽地理信息集成应用协同创新中心,滁州 239000
    2 中国气象局国家卫星气象中心,北京 100081
    3 安徽省经济研究院,合肥 230051

  • 收稿日期:2016-08-01 修回日期:2016-09-20 出版日期:2017-03-30 发布日期:2017-03-30
  • 通讯作者: 赵明伟 E-mail:zhaomw@lreis.ac.cn
  • 基金资助:

    科技部863碳卫星项目;公益气象行业专项;高分辨率对地观测专项的气象行业应用示范项目;应用共性关键技术项

Study on the Spatial-Temporal Change Characteristics of Global CO2 Concentration Based on SCIAMACHY Retrievals

Zhao Mingwei1, Li Chenchen1, Zhang Xingying2, Wang Chun1, Jiang Ling1, Sun Jinglu3   

  1. 1 Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou 239000, China;
    2 National Satellite Meteorology Center, China Meteorological Administration, Beijing 100081, China;
    3 Anhui Institute of Economics, Hefei 230051, China

  • Received:2016-08-01 Revised:2016-09-20 Online:2017-03-30 Published:2017-03-30

摘要:

通过卫星观测光谱反演计算是当前观测全球CO2浓度水平,分析其变化趋势的重要手段,但是由于观测条件及反演方法的限制,基于卫星观测光谱反演计算只能得到离散的CO2浓度数据,需要借助空间插值方法才能获得空间连续的CO2浓度数据。本文以SCIAMACHY研究团队发布的XCO2浓度数据为基础数据,首先对比分析了空间分析中常用的3种经典插值方法(反距离加权法,克里格法,样条函数法)在XCO2空间内插中的精度,综合分析平均绝对值误差、绝对值误差最大值和均方根误差3个指标,结果表明反距离加权插值法为最优内插方法。基于该方法生成2003年1月—2012年4月共计112个月的全球大陆XCO2浓度分布数据集,并对全球大陆范围内XCO2浓度的时空变化特征进行分析,发现在此时段内全球各个大陆XCO2均表现出增加的趋势;在全球大陆平均水平上,XCO2浓度增加幅度为17.43×10-6,XCO2年平均值增加速率约为2×10-6,总体上呈现北半球增加速率高于南半球的特点。

关键词: SCIAMACHY, XCO2, 空间插值, 时空分析

Abstract:

Retrieval estimation based on satellite spectrum characteristics is the principle means to observe the global carbon dioxide concentration and analyze its spatial-temporal tendency today. However, only discrete carbon dioxide concentration data can be obtained limited to the observation condition and retrieval technique. So spatial interpolation method is needed to produce continuous carbon dioxide concentration in space. In this study, the XCO2 concentration data released by the SCIAMACHY research team was taken as the basic data, several classical interpolation methods (IDW, Kriging, and Spline) were compared in the XCO2 concentration interpolation, and the error statistical indicators (MAE, Max_AE, RMSE) showed that IDW was the optimal method for this research. Then, spatial distribution data of XCO2 concentration in the global continent from January 2003 to April 2012 were produced based on IDW, and its spatial-temporal tendency was also analyzed. The XCO2 concentration in global scale all showed an increased trend during this period, and on the average level of the global continent, the increase of XCO2 concentration was 17.43×10-6, the average increase rate of XCO2 was about 2×10-6 per year, and the rate of increase in the Northern Hemisphere was higher than that in the Southern Hemisphere.

Key words: SCIAMACHY, XCO2, spatial interpolation, spatial-temporal analysis

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