Assimilation of Stratospheric Chemical Tracer Observations Using a Kalman Filter. Part I: Formulation
Assimilation of Stratospheric Chemical Tracer Observations Using a Kalman Filter. Part I: Formulation
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使用卡尔曼滤波器同化平流层化学示踪观测。
DOI：
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发表时间：
2000
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影响因子：
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通讯作者：
P. Lyster
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文献类型：
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作者：
R. Ménard;S. Cohn;Lang‐Ping Chang;P. Lyster
这篇两篇文章的第一部分描述了卡尔曼滤波系统的形成，该系统用于将平流层化学成分的肢体探测观测同化为示踪剂输送模式。该系统基于二维等熵近似，允许实现完整的卡尔曼滤波，并在真实数据环境中彻底研究其行为。同化实验中使用了来自高层大气研究卫星上的两台仪器的数据集，它们的观察几何形状非常不同。稳健的卡方诊断用于将观测-负-预报残差的统计数据与过滤算法计算的统计数据进行比较，以帮助制定过滤器的统计输入，以及调整协方差参数和验证同化结果。在这项研究中，发现与标准(离散)卡尔曼滤波公式有两个显著的偏离是重要的。首先，人们发现标准卡尔曼滤波……
Abstract The first part of this two-part article describes the formulation of a Kalman filter system for assimilating limb-sounding observations of stratospheric chemical constituents into a tracer transport model. The system is based on a two-dimensional isentropic approximation, permitting a full Kalman filter implementation and a thorough study of its behavior in a real-data environment. Datasets from two instruments on the Upper Atmosphere Research Satellite with very different viewing geometries are used in the assimilation experiments. A robust chi-squared diagnostic, which compares statistics of the observed-minus-forecast residuals with those calculated by the filter algorithm, is used to help formulate the statistical inputs to the filter, as well as to tune covariance parameters and to validate the assimilation results. Two significant departures from the standard (discrete) Kalman filter formulation were found to be important in this study. First, it was discovered that the standard Kalman filt...