A New Characterization of Rain and Clouds: Results from a Statistical Inversion of Count Data
A New Characterization of Rain and Clouds: Results from a Statistical Inversion of Count Data
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雨和云的新表征：计数数据统计反演的结果
DOI：
10.1175/jas3950.1
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发表时间：
2007
影响因子：
3.1
通讯作者：
A. R. Jameson
中科院分区：
文献类型：
--
作者：
A. R. Jameson
气象学中的大多数变量在统计上是不均匀的。因此，来自几个不同位置的数据的统计可以被认为是包含在几个贡献概率密度函数（PDF）中的信息的融合，这些概率密度函数具有不同的参数集、不同的参数形式和不同的平均值。因此，这些数据的频率分布通常是多模态的。然而，通常，为了实现更好的采样，对这些变量的测量在广泛不同的位置收集的整个数据集进行处理，好像数据在统计上是均匀的，也就是说，好像它们完全由一个PDF和一组具有一个平均值的参数表征。相反，是否有一种更好的方法来处理数据，使其与这种统计异质性相一致？这个问题是解决在这里使用统计反演技术开发的塔兰托拉贝叶斯方法的基础上。在真实的雨，一个16小时和其他3分钟长的disdrometer测量的两个例子，揭示了存在多个平均值的计数在所有不同的滴大小。在这两种情况下，非均匀的雨可以分解成5 - 7个统计上均匀的成分，每个成分的特点是自己的稳定滴大小分布。像层状雨和对流雨这样的概念，可以根据每种成分对雨的贡献给出更精确的含义。此外，这一发现允许将统计异质性明确纳入某些分析理论。
Most variables in meteorology are statistically heterogeneous. The statistics of data from several different locations, then, can be thought of as an amalgamation of information contained in several contributing probability density functions (PDFs) having different sets of parameters, different parametric forms, and different mean values. The frequency distribution of such data, then, will often be multimodal. Usually, however, in order to achieve better sampling, measurements of these variables over an entire set of data gathered at widely disparate locations are processed as though the data were statistically homogeneous, that is, as though they were fully characterized by just one PDF and one single set of parameters having one mean value. Is there, instead, a better way of treating the data in a manner that is consistent with this statistical heterogeneity? This question is addressed here using a statistical inversion technique developed by Tarantola based upon Bayesian methodology. Two examples of disdrometer measurements in real rain, one 16 h and the other 3 min long, reveal the presence of multiple mean values of the counts at all the different drop sizes. In both cases the heterogeneous rain can be decomposed into five–seven statistically homogeneous components, each characterized by its own steady drop size distribution. Concepts such as stratiform versus convective rain can be given more precise meaning in terms of the contributions each component makes to the rain. Furthermore, this discovery permits the explicit inclusion of statistical heterogeneity into some analytic theories.