Statistical perspectives on stratospheric transport
Statistical perspectives on stratospheric transport
复制标题
平流层输送的统计观点
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
L. Sparling
中科院分区：
文献类型：
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作者：
L. Sparling
许多长寿命的平流层化学成分通过热带对流层顶进入平流层，通过布鲁尔-多布森环流在平流层中传输，并在平流层上部被光化学破坏。这些化学成分或“示踪剂”可用于追踪平流层风的混合和输送。我们对平流层环流的大部分理解都是基于卫星测量构建的示踪剂场的大尺度梯度和其他空间特征。本文提出的观点是不同的，但互补的，在运输方面的示踪剂概率分布函数。概率分布函数由测量值计算，与给定范围内示踪剂值所占的面积成比例。这篇论文的风格是教程，并与运输相关的现象的几个例子说明的想法，注释，总结要点或建议新的方向。这些例子说明了基于物理的统计分析如何能够在一定程度上说明平流层迁移和动态的某些方面，而这些方面用其他类型的分析可能并不明显或无法量化。的位置和时间上的统计数据的依赖性也被证明是重要的统计稳健性和卫星采样相关的实际问题。这里介绍的工作的一个重要动机是需要综合大气观测和大气模型产生的输出的大型和不断增长的数据库。
Many long‐lived stratospheric chemical constituents enter the stratosphere through the tropical tropopause, are transported throughout the stratosphere by the Brewer‐Dobson circulation, and are photochemically destroyed in the upper stratosphere. These chemical constituents, or “tracers,” can be used to track mixing and transport by the stratospheric winds. Much of our understanding about the stratospheric circulation is based on large‐scale gradients and other spatial features in tracer fields constructed from satellite measurements. The point of view presented in this paper is different, but complementary, in that transport is described in terms of tracer probability distribution functions. The probability distribution function is computed from the measurements and is proportional to the area occupied by tracer values in a given range. The flavor of this paper is tutorial, and the ideas are illustrated with several examples of transport‐related phenomena, annotated with remarks that summarize the main point or suggest new directions. The examples illustrate how physically based statistical analysis can shed some light on aspects of stratospheric transport and dynamics that may not be obvious or quantifiable with other types of analyses. The dependence of the statistics on location and time is also shown to be important for practical problems related to statistical robustness and satellite sampling. An important motivation for the work presented here is the need for synthesis of the large and growing database of observations of the atmosphere and output generated by atmospheric models.