###
气象:2016,42(3):363-371
本文二维码信息
码上扫一扫!
地面降水的多源数据辅助质量控制方法
(1.中国气象局气象探测中心,北京 100081;2.中国气象局气象干部培训学院,北京 100081)
Quality Control Method for Multi Source Data of Surface Rainfall
(1.Meteorological Observation Centre of CMA, Beijing 100081;2.China Meteorological Administration Training Centre, Beijing 100081)
摘要
图/表
参考文献
相似文献
本文已被:浏览 1291次   下载 2092
投稿时间:2015-03-07    修订日期:2016-01-11
中文摘要: 文章在分析气温变化、风速变化、相对湿度、温度露点差、雷达和自动站降雨量差值的基础上,提出了针对自动站观测小时降雨量的多要素综合质量控制方法,包括雷达和自动站相结合的综合检验方法(MRAWS)以及仅使用自动站资料的综合检验方法(MAWS),并与时空一致性检验方法(MTS)进行比较。结果表明:使用多要素的综合检验方法(MRAWS和MAWS)明显优于仅使用降雨量资料的MTS。此外,虽然MAWS检验结果略低于MRAWS,但在缺少雷达探测资料的情况下MAWS可对降雨量数据进行有效检验。进一步地分析表明,MRAWS和MAWS方法仅适用于判别有无降水,对降水量值的正确性判断能力存在不足。
Abstract:Based on the analysis of radar and automatic weather station (AWS) data, a quality control (QC) method for multi source data of surface rainfall is presented in this study. The QC methods include MRAWS which combines the radar and AWS data and MAWS which only uses AWS data. At the same time, the two methods are compared with the spatio temporal QC method (MTS). The analysis results show that the performance of MRAWS and MAWS is significantly better than that of MTS, because MRAWS and MAWS are able to utilize more observational elements effectively. Although the result of MAWS is slightly worse than that of MRAWS due to the absence of radar data, MAWS is also an effective QC method for surface rainfall. But further analysis suggests that the methods of MRAWS and MAWS are likely to be applied only in judging whether rainfall occurs or not, for they are not good enough to evaluate the rainfall correctly.
文章编号:     中图分类号:    文献标志码:
基金项目:公益性行业(气象)科研专项(GYHY20150621)及中国气象局气象关键技术集成与应用项目(CMAGJ2014M70)共同资助
引用文本:
张乐坚,俞小鼎,李峰,储凌,2016.地面降水的多源数据辅助质量控制方法[J].气象,42(3):363-371.
ZHANG Lejian,YU Xiaoding,LI Feng,CHU Ling,2016.Quality Control Method for Multi Source Data of Surface Rainfall[J].Meteor Mon,42(3):363-371.