地面降水的多源数据辅助质量控制方法

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。

Quality Control Method for Multi Source Data of Surface Rainfall

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.