中文摘要：

到 2010 年 12 月的从 2010 年 1 月的大气的公司 ₂ 集中用模型和结果与观察卫星(GOSAT ) 的卫星气体相比的 GEOS-Chem (观察系统化学的戈达德地球) 被模仿并且基于地面观察网络(TCCON ) 数据的全部的碳列。公司 ₂ 集中通常基于 GOSAT 卫星检索比 GEOS-Chem 模仿的那些高，这被发现。在在 1 月和 4 月的陆地区域上的差别从 1 ～ 2 ppm ，并且在 6 月和 8 月有主要差别。在在在撒哈拉沙漠的 6 月，以及南方的北半球的高纬度，差别比 5 ppm 大。在北半球的高纬度，模型结果比 GOSAT 检索高，当在南美洲卫星数据是更高的时。在在 8 月的北半球和 Saharan 区域的高纬度的差别的趋势对 6 月相反。最大的关联系数在 4 月被发现，到达 0.72，但是在 6 月和 8 月是更小的。在 1 月，关联系数仅仅是 0.36。在 GEOS-Chem 数据和 TCCON 观察之间的比较比在 GEOS 和 GOSAT 之间的比较显示出更好的结果。关联系数在 0.42 之间变化了(达尔文) 并且 0.92 (Izana ) 。结果的分析显示在卫星观察和模型模拟之间的矛盾取决于卫星检索模型输入参数的模型模拟输入，以及失配的数据不确引起的倒置错误。

英文摘要：

Atmospheric CO2 concentrations from January 2010 to December 2010 were simulated using the GEOS-Chem（Goddard Earth Observing System-Chemistry） model and the results were compared to satellite Gases Observing Satellite（GOSAT） and ground-based the Total Carbon Column Observing Network（TCCON） data. It was found that CO2 concentrations based on GOSAT satellite retrievals were generally higher than those simulated by GEOS-Chem. The differences over the land area in January and April ranged from 1 to 2 ppm, and there were major differences in June and August. At high latitudes in the Northern Hemisphere in June, as well as south of the Sahara, the difference was greater than 5 ppm. In the high latitudes of the Northern Hemisphere the model results were higher than the GOSAT retrievals, while in South America the satellite data were higher. The trend of the difference in the high latitudes of the Northern Hemisphere and the Saharan region in August was opposite to June. Maximum correlation coefficients were found in April, reaching 0.72, but were smaller in June and August. In January, the correlation coefficient was only 0.36. The comparisons between GEOS-Chem data and TCCON observations showed better results than the comparison between GEOS and GOSAT. The correlation coefficients ranged between 0.42（Darwin） and 0.92（Izana）. Analysis of the results indicated that the inconsistency between satellite observations and model simulations depended on inversion errors caused by data inaccuracies of the model simulation＇s inputs, as well as the mismatch of satellite retrieval model input parameters.