基于贝叶斯理论的集合降水概率预报方法研究

韩焱红; 矫梅燕; 陈静; 陈法敬

###

DOI:10.7519/j.issn.1000-0526.2013.01.001

气象:2013,39(1):1-10

查看/发表评论过刊浏览高级检索 HTML

←前一篇 | 后一篇→

码上扫一扫！

下载全文

基于贝叶斯理论的集合降水概率预报方法研究

韩焱红¹, 矫梅燕², 陈静³, 陈法敬³

(1.南京信息工程大学大气科学学院，南京 210044;2.中国气象局，北京 100081;3.中国气象局数值预报中心，北京 100081)

Study on the Method of Rainfall Ensemble Probability Forecast Based on Bayesian Theory and Its Preliminary Experiments

HAN Yanhong¹, JIAO Meiyan², CHEN Jing³, CHEN Fajing³

(1.School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044;2.China Meteorological Administration, Beijing 100081;3.CMA Numerical Prediction Centre, Beijing 100081)

摘要

图/表

参考文献

相似文献

本文已被：浏览 1531次下载 3668次
投稿时间：2012-04-25 修订日期：2012-09-03

中文摘要: 将贝叶斯理论应用到集合降水概率预报方法研究中。采用集合预报资料和历史观测资料，通过建立贝叶斯产品处理技术（Bayesian Processor of output，BPO）降水概率预报模型，将一组集合成员降水确定预报值修订为一组贝叶斯降水概率分布或概率密度的预报，并获得表征每个集合成员预报能力有效信息评分（Informativeness Score，IS）。基于IS值对集合成员概率预报信息融合，得到集成贝叶斯降水概率预报，并采用连续等级概率评分（Continuous Ranked Probablity Score, CRPS）方法检验试验结果。结果表明，基于BPO方法得到的集成贝叶斯降水概率预报可靠性高于由集合预报得到的直接概率预报。

中文关键词: 贝叶斯理论, 降水集合预报, 概率预报, 试验

Abstract:The paper applies BPO (Bayesian Processor of Output) method based on Bayesian theory to the method of rainfall ensemble probability forecast. Using ensemble prediction data and historical observational data, we develop a rainfall probability forecast model, and then revise a set of precipitation predicted value into a set of Bayesian precipitation probability forecast in the form of continuous probability distribution or continuous probability density. Besides, we obtain a group value of Informativeness Score (IS), which can express the prediction ability of each ensemble member. Furthermore, we fuse the probability forecast results of each member into an integration Bayesian precipitation probability forecast on the basis of IS and test the results with Continuous Ranked Probablity Score (CRPS). Experiment results show that the reliability of integration Bayesian precipitation probability forecast is higher than ensemble direct probability forecast.

keywords: Bayesian theory, precipitation ensemble forecast, probability forecast, experiments

文章编号： 中图分类号： 文献标志码：

基金项目:国家自然科学基金（41075035）资助

作者	单位
韩焱红	南京信息工程大学大气科学学院，南京 210044
矫梅燕	中国气象局，北京 100081
陈静	中国气象局数值预报中心，北京 100081
陈法敬	中国气象局数值预报中心，北京 100081

Author Name	Affiliation
HAN Yanhong	School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044
JIAO Meiyan	China Meteorological Administration, Beijing 100081
CHEN Jing	CMA Numerical Prediction Centre, Beijing 100081
CHEN Fajing	CMA Numerical Prediction Centre, Beijing 100081

引用文本：
韩焱红,矫梅燕,陈静,陈法敬,2013.基于贝叶斯理论的集合降水概率预报方法研究[J].气象,39(1):1-10.
HAN Yanhong,JIAO Meiyan,CHEN Jing,CHEN Fajing,2013.Study on the Method of Rainfall Ensemble Probability Forecast Based on Bayesian Theory and Its Preliminary Experiments[J].Meteor Mon,39(1):1-10.