C. Diekmann, M. Schneider, B. Ertl, F. Hase, O. García, F. Khosrawi, E. Sepúlveda, P. Knippertz, P. Braesicke
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From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. 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引用次数: 6
摘要
摘要我们提出了一个全球和多年的对流层{H2O, δD}对的星载数据集,该数据集基于EUMETSAT(欧洲气象卫星利用组织)Metop卫星上的最底热红外传感器IASI(红外大气探测干涉仪)的辐射测量。该数据集是Schneider等人(2021b)中提出的MUSICA (MUlti-platform remote Sensing of Isotopologues for investigation the Cycle of Atmospheric water) IASI完整产品数据集的后测扩展。从独立检索的H2O和δD代理状态、它们的先验设置和约束以及IASI完整产品数据集提供的误差协方差中,我们生成了H2O和δD对的最优估计产品。为了提高干燥条件下的检索灵敏度,对导出{H2O, δD}对的标准MUSICA方法进行了后验化简。通过将这种改进的水同位素后处理应用于所有无云的MUSICA IASI检索,得到了2014年10月至2019年6月整个期间的{H2O, δD}对数据集,每天两次覆盖全球(当地早晚立交时间)。总的来说,该数据集涵盖了超过12亿个单独处理的观测数据。反演结果对自由对流层内{H2O, δD}对的变化最为敏感,高达30%的反演结果包含{H2O, δD}对乘积的垂直剖面信息。在应用适当的质量过滤器后,热带和亚热带夏季地区出现了数量最多的可靠对数据,但对于高纬度地区也有相当数量的可靠数据。本文选择了热带大西洋和西非的典型时间序列,以说明MUSICA IASI {H2O, δD}对数据在大气水分途径研究中的潜力。最后,数据集引用DOI 10.35097/415 (Diekmann et al., 2021)。
Abstract. We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021).