CAJ | 학술논문

针对GOSAT(Greenhouse gases Observing Satellite)近红外波段数据进行的大气二氧化碳含量反演，提出了贝叶斯理论中误差矩阵的构建方法并进行了分析验证。首先模拟不同的初始估计值、不同的先验信息误差矩阵Sa和测量误差矩阵Sε构建结果对CO2反演的影响，然后据此挑选出Sa和Sε的优劣两种构建结果组合分别对2009年塔克拉玛干沙漠地区的部分GOSAT观测数据进行反演验证。研究结果表明先验信息方差越大或测量误差越小，反演结果趋于一致，反之结果则较为离散，表现出明显的规律性。实际大气遥感研究中准确的误差矩阵难以获取，此研究有助于进一步选取准确值并提高反演精度。
침대GOSAT(Greenhouse gases Observing Satellite)근홍외파단수거진행적대기이양화탄함량반연，제출료패협사이론중오차구진적구건방법병진행료분석험증。수선모의불동적초시고계치、불동적선험신식오차구진Sa화측량오차구진Sε구건결과대CO2반연적영향，연후거차도선출Sa화Sε적우렬량충구건결과조합분별대2009년탑극랍마간사막지구적부분GOSAT관측수거진행반연험증。연구결과표명선험신식방차월대혹측량오차월소，반연결과추우일치，반지결과칙교위리산，표현출명현적규률성。실제대기요감연구중준학적오차구진난이획취，차연구유조우진일보선취준학치병제고반연정도。
Based on the retrieval of atmospheric carbon dioxide using infrared spectral data detected by GOSAT, a method of building error matrixes of Bayesian theory was proposed and validated. Firstly, the effect on retrieval results by different initial guesses, different building results of priori information error matrix Sa and measurement error matrix Sε was simulated, and then two combinations of Sa and Sεbuilding results were validated in the retrieval using part of GOSAT measurements of Taklimakan desert during 2009. The result shows that the retrieved results are more concentrate in the case of bigger priori information variance or smaller measurement error, and the retrieved results are dispersed under the converse circumstance. It is difficult to get real error matrixes in atmospheric remote sensing, therefore, this study will be significant for getting more accurate error matrixes and improving retrieval precision.