首页> 外文OA文献 >Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura
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Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura

机译:GOME-2 / MetOp-A总臭氧柱与传感器GOME / ERS-2,SCIAMACHY / ENVISAT和OMI / Aura的测量之间的地球物理验证和长期一致性

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摘要

The main aim of the paper is to assess the consistency of five years of Global Ozone Monitoring Experiment-2/Metop-A [GOME-2] total ozone columns and the long-term total ozone satellite monitoring database already in existence through an extensive inter-comparison and validation exercise using as reference Brewer and Dobson ground-based measurements. The behaviour of the GOME-2 measurements is being weighed against that of GOME (1995–2011), Ozone Monitoring Experiment [OMI] (since 2004) and the Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY [SCIAMACHY] (since 2002) total ozone column products. Over the background truth of the ground-based measurements, the total ozone columns are inter-evaluated using a suite of established validation techniques; the GOME-2 time series follow the same patterns as those observed by the other satellite sensors. In particular, on average, GOME-2 data underestimate GOME data by about 0.80%, and underestimate SCIAMACHY data by 0.37% with no seasonal dependence of the differences between GOME-2, GOME and SCIAMACHY. The latter is expected since the three datasets are based on similar DOAS algorithms. This underestimation of GOME-2 is within the uncertainty of the reference data used in the comparisons. Compared to the OMI sensor, on average GOME-2 data underestimate OMI_DOAS (collection 3) data by 1.28%, without any significant seasonal dependence of the differences between them. The lack of seasonality might be expected since both the GOME data processor [GDP] 4.4 and OMI_DOAS are DOAS-type algorithms and both consider the variability of the stratospheric temperatures in their retrievals. Compared to the OMI_TOMS (collection 3) data, no bias was found. We hence conclude that the GOME-2 total ozone columns are well suitable to continue the long-term global total ozone record with the accuracy needed for climate monitoring studies.
机译:本文的主要目的是通过广泛的内部评估来评估五年全球臭氧监测实验2 / Metop-A [GOME-2]总臭氧柱和长期总臭氧卫星监测数据库的一致性。 -比较和验证练习,以Brewer和Dobson的地面测量为参考。 GOME-2测量的行为与GOME(1995-2011年),臭氧监测实验[OMI](自2004年起)和扫描成像吸收光谱仪对大气CartograpHY [SCIAMACHY](自2002年起)的总臭氧柱进行了权衡。产品。根据地面测量的背景事实,使用一套已建立的验证技术对臭氧总柱进行了内部评估; GOME-2时间序列遵循的模式与其他卫星传感器观察到的模式相同。特别是,平均而言,GOME-2数据低估了GOME数据约0.80%,而SCIAMACHY数据则低估了0.37%,而对GOME-2,GOME和SCIAMACHY之间差异的季节依赖性不高。由于这三个数据集都基于相似的DOAS算法,因此希望使用后者。 GOME-2的这种低估在比较中使用的参考数据的不确定性之内。与OMI传感器相比,平均GOME-2数据低估了OMI_DOAS(集合3)数据1.28%,而它们之间的差异没有任何明显的季节性依赖性。由于GOME数据处理器[GDP] 4.4和OMI_DOAS都是DOAS类型的算法,并且都考虑了平流层温度的变化性,因此可能缺乏季节性。与OMI_TOMS(集合3)数据相比,没有发现偏差。因此,我们得出的结论是,GOME-2总臭氧塔非常适合以气候监测研究所需的准确性继续长期的全球总臭氧记录。

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