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Non-Gaussian Bayesian retrieval of tropical upper tropospheric cloud ice and water vapour from Odin-SMR measurements

机译:基于Odin-SMR测量的热带高对流层云冰和水蒸气的非高斯贝叶斯检索

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Improved Odin-SMR retrievals of upper tropospheric water are presented. The new retrieval algorithm retrieves humidity and cloud ice mass simultaneously and takes into account of cloud inhomogeneities. Both these aspects are introduced for microwave limb sounding inversions for the first time. A Bayesian methodology is applied allowing for a formally correct treatment of non-unique retrieval problems involving non-Gaussian statistics. Cloud structure information from CloudSat is incorporated into the retrieval algorithm. This removes a major limitation of earlier inversion methods where uniform cloud layers were assumed and caused a systematic retrieval error. The core part of the retrieval technique is the generation of a database that must closely represent real conditions. Good agreement with Odin-SMR observations indicates that this requirement is met. The retrieval precision is determined to be about 5–17% RHi and 65% for humidity and cloud ice mass, respectively. For both quantities, the vertical resolution is about 5 km and the best retrieval performance is found between 11 and 15 km. New data show a significantly improved agreement with CloudSat cloud ice mass retrievals, at the same time consistency with the Aura MLS humidity results is maintained. The basics of the approach presented can be applied for all passive cloud observations and should be of broad interest. The results can also be taken as a demonstration of the potential of down-looking sub-mm radiometry for global measurements of cloud ice properties.
机译:提出了对流层上层水的改进的Odin-SMR反演。新的检索算法可同时检索湿度和云冰量,并考虑了云的不均匀性。这两个方面都是首次针对微波肢体声音反演引入的。使用贝叶斯方法可以对涉及非高斯统计的非唯一检索问题进行形式上正确的处理。来自CloudSat的云结构信息被合并到检索算法中。这消除了早期反演方法的主要局限性,在早期反演方法中,假设了均匀的云层并导致了系统性的检索错误。检索技术的核心部分是必须紧密代表实际情况的数据库的生成。与Odin-SMR观测值的良好一致性表明已满足此要求。对于湿度和云冰量,取回精度分别确定为大约5–17%RHi和65%。对于这两个量,垂直分辨率约为5 km,最佳的检索性能在11至15 km之间。新数据表明,与CloudSat云冰质量反演的协议有了显着改善,同时保持了与Aura MLS湿度结果的一致性。提出的方法的基础可以应用于所有被动云观测,应该引起广泛的兴趣。该结果还可以用作向下观测亚毫米辐射测量技术进行全球云冰特性测量的潜力的证明。

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