基于SCIAMACHY反演数据的全球CO2浓度时空变化特征研究

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。

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

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.