Application of SCIAMACHY and MOPITT CO total column measurements to evaluate model results over biomass burning regions and Eastern China
Application of SCIAMACHY and MOPITT CO total column measurements to evaluate model results over biomass burning regions and Eastern China
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DOI：
10.5194/acp-11-6083-2011
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发表时间：
2011-06
影响因子：
6.3
通讯作者：
Cheng Liu;S. Beirle;T. Butler;Jane Liu;P. Hoor;P. Jöckel;M. P. D. Vries;A. Pozzer;C. Frankenberg;M. Lawrence;J. Lelieveld;U. Platt;T. Wagner
中科院分区：
文献类型：
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作者：
Cheng Liu;S. Beirle;T. Butler;Jane Liu;P. Hoor;P. Jöckel;M. P. D. Vries;A. Pozzer;C. Frankenberg;M. Lawrence;J. Lelieveld;U. Platt;T. Wagner
我们开发了一个新的CO垂直柱密度产品从近红外观测的SCIAMACHY仪器机载ENVISAT。对于CO垂直柱密度的时间和空间可变偏移的校正，我们应用符合MOPITT（第4版）的海洋观测的基础上的归一化程序。由此产生的归一化的SCIAMACHY CO数据非常适合于调查的CO分布在大陆，重要的排放源位于。我们只使用SCIAMACHY观测有效云分数低于20%。由于云的剩余影响仍然很大（高达100%），我们应用了一个云校正方案，该方案明确考虑了单个观测的云分数，云顶高度和表面反射率。使用MOPITT数据和云校正的归一化程序大大提高了与独立数据集的一致性。我们将新的SCIAMACHY CO数据集以及MOPITT仪器的观测结果与三个全球大气化学模型（MATCH，EMAC在低分辨率和高分辨率下以及GEOS-Chem）的结果进行了比较;这种比较的重点是具有强CO排放（来自生物质燃烧或人为来源）的地区。比较表明，在大多数这些地区的季节性周期一般被捕获，但模拟CO垂直柱密度系统小于卫星观测，特别是相对于SCIAMACHY观测。由于SCIAMACHY对大气的最低部分比MOPITT更敏感，这表明特别是在接近地面的地方，模型模拟系统地低估了真实的大气CO浓度，这可能是由于当前排放清单低估了CO排放量造成的。然而，对于一些生物质燃烧区域，例如7月至8月的中非，模型结果也高于卫星观测结果。
We developed a new CO vertical column density product from near IR observations of the SCIAMACHY instrument onboard ENVISAT. For the correction of a temporally and spatially variable offset of the CO vertical column densities we apply a normalisation procedure based on coincident MOPITT (version 4) observations over the oceans. The resulting normalised SCIAMACHY CO data is well suited for the investigation of the CO distribution over continents, where important emission sources are located. We use only SCIAMACHY observations for effective cloud fractions below 20 %. Since the remaining effects of clouds can still be large (up to 100 %), we applied a cloud correction scheme which explicitly considers the cloud fraction, cloud top height and surface albedo of individual observations. The normalisation procedure using MOPITT data and the cloud correction substantially improve the agreement with independent data sets. We compared our new SCIAMACHY CO data set, and also observations from the MOPITT instrument, to the results from three global atmospheric chemistry models (MATCH, EMAC at low and high resolution, and GEOS-Chem); the focus of this comparison is on regions with strong CO emissions (from biomass burning or anthropogenic sources). The comparison indicates that over most of these regions the seasonal cycle is generally captured well but the simulated CO vertical column densities are systematically smaller than those from the satellite observations, in particular with respect to SCIAMACHY observations. Because SCIAMACHY is more sensitive to the lowest part of the atmosphere compared to MOPITT, this indicates that especially close to the surface the model simulations systematically underestimate the true atmospheric CO concentrations, probably caused by an underestimation of CO emissions by current emission inventories. For some biomass burning regions, however, such as Central Africa in July–August, model results are also found to be higher than the satellite observations.