首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space. Part 2: Algorithm intercomparison in the GOSAT data processing for CO_2 retrievals over TCCON sites
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Effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space. Part 2: Algorithm intercomparison in the GOSAT data processing for CO_2 retrievals over TCCON sites

机译:大气光散射对太空中温室气体光谱观察的影响。第2部分:GOSAT数据处理中用于TCCON站点CO_2检索的算法比对

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This report is the second in a series of companion papers describing the effects of atmospheric light scattering in observations of atmospheric carbon dioxide (CO_2) by the Greenhouse gases Observing SATellite (GOSAT), in orbit since 23 January 2009. Here we summarize the retrievals from six previously published algorithms; retrieving column-averaged dry air mole fractions of CO_2 (X_(CO2)) during 22 months of operation of GOSAT from June 2009. First, we compare data products from each algorithm with ground-based remote sensing observations by Total Carbon Column Observing Network (TCCON). Our GOSAT-TCCON coincidence criteria select satellite observations within a 5°radius of 11 TCCON sites. We have compared the GOSAT-TCCON X_(CO2) regression slope, standard deviation, correlation and determination coefficients, and global and station-to-station biases. The best agreements with TCCON measurements were detected for NIES 02.xx and RemoTeC. Next, the impact of atmospheric light scattering on XCO2 retrievals was estimated for each data product using scan by scan retrievals of light path modification with the photon path length probability density function (PPDF) method. After a cloud pre-filtering test, approximately 25% of GOSAT soundings processed by NIES 02.xx, ACOS B2.9, and UoL-FP: 3G and 35% processed by RemoTeC were found to be contaminated by atmospheric light scattering. This study suggests that NIES 02.xx and ACOS B2.9 algorithms tend to overestimate aerosol amounts over bright surfaces, resulting in an underestimation of X_(CO2) for GOSAT observations. Cross-comparison between algorithms shows that ACOS B2.9 agrees best with NIES 02.xx and UoL-FP: 3G while RemoTeC X CO2 retrievals are in a best agreement with NIES PPDF-D. Key PointsWe summarize GOSAT CO_2 retrievals from six previously published algorithmsCO_2 retrievals from each algorithm were compared with ground-based TCCON dataAn algorithm cross-comparison has been performed
机译:该报告是一系列伴随论文中的第二篇,描述了自2009年1月23日以来在轨道上的温室气体观测卫星(GOSAT)观测大气中光散射对大气中二氧化碳(CO_2)的影响。六个先前发布的算法;从2009年6月开始运行GOSAT的22个月中,检索了各列平均CO_2(X_(CO2))的干燥空气摩尔分数。首先,我们将每种算法的数据产物与总碳柱观测网络(地面)进行的基于地面的遥感观测进行比较( TCCON)。我们的GOSAT-TCCON符合标准选择了11个TCCON站点的5°半径范围内的卫星观测。我们比较了GOSAT-TCCON X_(CO2)回归斜率,标准偏差,相关性和确定系数以及全局和站间偏差。对于NIES 02.xx和RemoTeC,检测到与TCCON测量的最佳协议。接下来,使用光子路径长度概率密度函数(PPDF)方法对光路修改进行逐次扫描检索,从而评估了每种数据产品的大气光散射对XCO2检索的影响。经过云层预过滤测试后,发现NIES 02.xx,ACOS B2.9和UoL-FP处理的GOSAT测深约25%:3G和RemoTeC处理的35%受大气光散射污染。这项研究表明,NIES 02.xx和ACOS B2.9算法倾向于高估明亮表面上的气溶胶含量,从而导致低估了GOSAT观测的X_(CO2)。算法之间的交叉比较表明,ACOS B2.9与NIES 02.xx和UoL-FP:3G最为吻合,而RemoTeC X CO2检索与NIES PPDF-D则具有最佳契合。关键点我们总结了六种先前发布的算法的GOSAT CO_2检索结果将每种算法的CO_2检索结果与基于地面的TCCON数据进行了比较进行了算法交叉比较

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