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Trends of tropical tropospheric ozone from 20 years of European satellite measurements and perspectives for the Sentinel-5 Precursor

机译:来自20年的欧洲卫星测量和哨兵-5前体的热带对流层臭氧潮流趋势

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In preparation of the TROPOMI/S5P launch in early 2017, a tropospheric ozone retrieval based on the convective cloud differential method was developed. For intensive tests we applied the algorithm to the total ozone columns and cloud data of the satellite instruments GOME, SCIAMACHY, OMI, GOME-2A and GOME-2B. Thereby a time series of 20 years (1995–2015) of tropospheric column ozone was generated. To have a consistent total ozone data set for all sensors, one common retrieval algorithm, namely GODFITv3, was applied and the L1 reflectances were also soft calibrated. The total ozone columns and the cloud data were input into the tropospheric ozone retrieval. However, the tropical tropospheric column ozone (TCO) for the individual instruments still showed small differences and, therefore, we harmonised the data set. For this purpose, a multilinear function was fitted to the averaged difference between SCIAMACHY's TCO and those from the other sensors. The original TCO was corrected by the fitted offset. GOME-2B data were corrected relative to the harmonised data from OMI and GOME-2A. The harmonisation leads to a better agreement between the different instruments. Also, a direct comparison of the TCO in the overlapping periods proves that GOME-2A agrees much better with SCIAMACHY after the harmonisation. The improvements for OMI were small. Based on the harmonised observations, we created a merged data product, containing the TCO from July 1995 to December 2015. A first application of this 20-year record is a trend analysis. The tropical trend is 0.7?±?0.12?DUdecade?1. Regionally the trends reach up to 1.8?DUdecade?1 like on the African Atlantic coast, while over the western Pacific the tropospheric ozone declined over the last 20 years with up to 0.8?DUdecade?1. The tropical tropospheric data record will be extended in the future with the TROPOMI/S5P data, where the TCO is part of the operational products.
机译:在2017年初准备Tropomi / S5P发射时,开发了一种基于对流云差分方法的对流层臭氧检索。对于密集测试,我们将算法应用于卫星仪器Gome,Sciamachy,OMI,Gome-2a和Gome-2b的总臭氧列和云数据。因此,产生了20年(1995-2015)的对流层柱臭氧的时间序列。为了使所有传感器具有一致的总臭氧数据,应用了一个常见的检索算法,即GODFITV3,L1反射也很软校准。总臭氧色谱柱和云数据被输入到对流层臭氧检索中。然而,各个仪器的热带对流层柱臭氧(TCO)仍然表现出较小的差异,因此,我们协调数据集。为此目的,多线性函数安装在Sciamachy的TCO和其他传感器之间的平均差异。原始TCO被安装的偏移纠正。相对于来自OMI和GOME-2A的统一数据校正GME-2B数据。协调导致不同仪器之间更好的协议。此外,在重叠期间的TCO直接比较证明,在协调后,Gome-2a在脚印中同意更好。 OMI的改进很小。根据协调的意见,我们创建了一个由1995年7月至2015年12月的TCO的合并数据产品。本20年的第一次申请是趋势分析。热带趋势为0.7?±0.12?Dudecade?1。地区趋势达到1.8倍?DUDECADE?1就像非洲大西洋海岸一样,而在西太平洋上,对象臭氧在过去20年中均下降,高达0.8?DUDECADE?1。热带对流层数据记录将在未来延长Tropomi / S5P数据,其中TCO是运营产品的一部分。

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