Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency
Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency
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DOI：
10.1175/amsmonographs-d-16-0007.1
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发表时间：
2017-10
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通讯作者：
G. McFarquhar;D. Baumgardner;A. Bansemer;S. Abel;J. Crosier;J. French;P. Rosenberg;A. Korolev;Alfons Schwarzoenboeck;D. Leroy;UM Junshik;WU Wei;A. Heymsfield;C. Twohy;A. Detwiler;P. Field;A. Neumann;R. Cotton;D. Axisa;Jiayin Dong
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文献类型：
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作者：
G. McFarquhar;D. Baumgardner;A. Bansemer;S. Abel;J. Crosier;J. French;P. Rosenberg;A. Korolev;Alfons Schwarzoenboeck;D. Leroy;UM Junshik;WU Wei;A. Heymsfield;C. Twohy;A. Detwiler;P. Field;A. Neumann;R. Cotton;D. Axisa;Jiayin Dong
机载探测器对云特性的现场观测通过其在过程研究、参数化开发以及模拟评估和遥感检索中的作用，在冰云研究中发挥着关键作用。为了确定云特性如何随环境条件变化，必须使用由不同小组处理的不同现场项目期间收集的现场数据。然而，由于用于处理测量的算法和代码多种多样，因此比较结果可能具有挑战性。因此，了解特定探针的局限性和处理算法引入的不确定性至关重要。由于目前还没有关于如何处理原位测量的普遍接受的框架，因此需要一个通用参考来描述最常用的算法及其优点和缺点。本文回顾了用于处理来自散装水探测器、单粒子光散射光谱仪和云成像探测器的数据的方法，重点是冰相的测量。由于目前对分析数据的最佳方式尚未达成共识，因此特别关注处理算法中的不确定性、警告和假设如何影响派生产品。改进原位数据分析和解释的建议包括：建立单个处理算法的通用参考库，更好地记录这些算法中使用的假设，开发和维护用于处理原位观测的可持续社区软件，以及进行更多将不同算法与相同基准数据集进行比较的研究。
In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.