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Comparison of ground-based remote sensing and in-situ observations of CO, CH4 and O3, accounting for representativeness uncertainty

机译:地面遥感与CO,CH4和O3的实地观测的比较,考虑了代表性不确定性

摘要

The EC project NORS (Demonstration Network Of ground-based Remote Sensing Observations in support of the GMES Atmospheric Service) aims at demonstrating the value of ground-based remote sensing data for quality assessment and improvement of the GMES products. As part of NORS CO, CH4, O3 and NO2 tropospheric products as obtained by ground-based remote sensing within the Network for the Detection of Atmospheric Composition Change (NDACC) are compared to continuous surface in-situ measurements that are reported on common international reference scales within the Global Atmospheric Watch (GAW) Programme. However, a direct comparison between the different methods is hindered by different sampling volumes, introducing uncertainties due to representativeness.Here we present a novel method that utilises high-resolution, backward Lagrangian particle dispersion modelling to characterise the transport history of different sampling volumes. Sampling volumes are defined as infinitesimally small point volumes for the in-situ observations and as separate profile segments with horizontal and vertical extent for the remote sensing observations. The characterisation is then used (a) to filter times for which a direct comparison between in-situ and remote sensing data is unfavourable (large representativeness uncertainty) and (b) to construct vertical profiles from the in-situ observations, taking additional information from large scale atmospheric composition models into account. These so called “in-situ” profiles are supposed to be more comparable to the remote sensing profile as the surface value itself, while conserving the high accuracy information of the latter and projecting it onto the profile. Therefore, these profiles allow for a more direct comparison and validation of the remotely sensed profiles.The technique was first applied at two of the four NORS demonstration sites (Jungfraujoch, Switzerland and Izana, Spain) and to the comparison of remote sensing Fourier-transform infrared spectrometer (FTIR) measurements of CO, CH4, and O3 with the responding in-situ observations. While previous studies generally showed good agreement between the two kinds of observation, considerable amounts of scatter were evident. Selecting only situations with relatively small representativeness uncertainty reduces this scatter. Folding the “in-situ” profiles with the averaging kernels of the FTIR retrieval gives a more realistic comparison result that is not influenced by any a-priori assumptions. Results are also discussed with respect to season, time of day and weather type.
机译:EC项目NORS(支持GMES大气服务的地面遥感观测示范网络)旨在证明地面遥感数据对GMES产品质量评估和改进的价值。作为NORS CO的一部分,将通过大气层变化检测网络(NDACC)内的地面遥感获得的CH4,O3和NO2对流层产物与国际通用参考文献报道的连续地表原位测量结果进行了比较。在全球大气监视计划(GAW)计划中进行缩放。然而,不同方法之间的直接比较会受到不同采样量的阻碍,由于代表性的原因导致不确定性。在这里,我们提出了一种利用高分辨率,后向拉格朗日粒子弥散模型来表征不同采样量传输历史的新方法。对于原位观测,采样体积定义为无穷小的点体积,对于遥感观测,采样体积定义为水平和垂直范围的单独轮廓段。然后使用特征描述(a)过滤不宜在原地与遥感数据之间进行直接比较的时间(较大的代表性不确定性),以及(b)从原地观测中构造垂直剖面,并从中获取更多信息考虑到大型大气成分模型。这些所谓的“原位”轮廓被认为与遥感轮廓更可比,因为它是表面值本身,同时保留了后者的高精度信息并将其投影到轮廓上。因此,这些配置文件允许对遥感配置文件进行更直接的比较和验证。该技术首先应用于四个NORS演示站点中的两个(瑞士的少女峰(Jungfraujoch)和西班牙的伊萨纳(Izana)),并用于遥感傅里叶变换的比较红外光谱仪(FTIR)对CO,CH4和O3的测量以及相应的原位观察结果。虽然先前的研究通常显示出两种观测之间的良好一致性,但明显的散射是明显的。只选择代表性相对不确定性较小的情况可以减少这种分散。用FTIR检索的平均内核折叠“原位”轮廓可以得到更现实的比较结果,不受任何先验假设的影响。还讨论了有关季节,一天中的时间和天气类型的结果。

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