基于GPS水汽反演和GPS-IR技术的降水分析及降水判定研究

利用GPS水汽反演技术和GPS-IR技术进行降水分析及降水判定研究。首先，考虑到降水发生前后大气水汽含量、地面反射特性、GPS对流层延迟、信噪比(signal-to-noise ratio, SNR)振幅(A)会发生变化，分析GPS-PWV和SNR-A与降水的相关性，并联合两者进行降水判定。结果表明，降水量与GPS-PWV正相关，与SNR-A负相关；加入SNR-A数据可提高降水判定的预报率和正确率。基于SNR-A序列的波谷和GPS-PWV序列的波峰进行降水判定，判定降水的预报率约为70%~82%，正确率约为50%~60%。

Precipitation Analysis and Judgment Based on GPS Water Vapor Retrieval and GPS-IR

This paper uses GPS water vapor retrieval and GPS-interferometric reflectometry (GPS-IR) technology for precipitation analysis and judgment. First, considering that before and after precipitation occurs, and that atmospheric water vapor content, ground reflection characteristics, GPS tropospheric delay, and signal-to-noise ratio (SNR) amplitude (A) will change, we analyze the correlation between GPS-PWV/SNR-A and precipitation, and combine the two to determine precipitation. The results show that precipitation is positively correlated with GPS-PWV and negatively correlated with SNR-A. The addition of SNR-A data can improve the forecast rate and accuracy for precipitation judgment. Based on the troughs of SNR-A sequence and the peaks of GPS-PWV sequence, in this work the forecast rate of precipitation judgment is about 70%-82% and the accuracy rate of precipitation judgment is about 50%-60%.