Some statistical considerations associated with the data assimilation of precipitation observations
Some statistical considerations associated with the data assimilation of precipitation observations
复制标题
与降水观测数据同化相关的一些统计考虑
DOI：
10.1002/qj.49712656217
复制
发表时间：
2000
影响因子：
8.9
通讯作者：
Zhan
中科院分区：
文献类型：
--
作者：
R. Errico;L. Fillion;D. Nychka;Zhan
贝叶斯定理应用于分析给定降水量的单次观测的空气体积中的温度和湿度的问题，利用非对流降水模型和场的先验估计。使用不同的统计和形状的概率分布的结果进行检查。这些分布包括正态分布、截断正态分布和对数正态分布，并对零值进行了特殊处理。除了观测的不确定性之外，还考虑了模型制定的不确定性。后验分布是多模态的，因为模型的公式使用了条件表达式。尽管观测结果表明存在降水，但该模型可将主导模式预测为非降水板岩。后验分布的均值和众数敏感地依赖于假设的统计量和基础分布的形状。结果表明，通常的成本函数的最小化不应该被傲慢地用于同化降水观测。
Bayes's theorem is applied to the problem of analysing temperature and moisture in a volume of air given a single observation of precipitation amount, utilizing a model of non‐convective precipitation and prior estimates of the fields. Results using different statistics and shapes of probability distributions are examined. These include normal, truncated normal, and log normal distributions with special treatment of the value zero. The uncertainly of the model's formulation is considered in addition to uncertainty of observations. The posterior distribution is multi‐modal due to the model's formulation using a conditional expression. The dominant mode may be predicted as a non‐precipitating slate by the model, although the observation indicates precipitation is present. Means and modes of posterior distributions depend sensitively both on the assumed statistics and the shapes of the underlying distributions. The results suggest that the usual minimization of a cost‐function should not be used cavalierly to assimilate precipitation observations.