小波分解辅助的珠海CORS水汽监测技术分析

Analysis on Zhuhai CORS Water Vapor Monitoring Technology Assisted by Wavelet Decomposition

依托城市连续运行基准站(continuously operating reference station, CORS)系统,利用全球导航卫星系统(global navigation satellite system, GNSS)水汽探测技术可实时获取高精度、高时空分辨率的水汽产品。这些水汽信息是新一代CORS系统的革新产品,可为未来的精准气象服务奠定基础。为了探究小波变换对GNSS可降水量(GNSS-precipitable water vapor, GNSS-PWV)时间序列的处理效果,针对2019年7月18日至7月26日发生的多次降水事件,收集了相应日期珠海CORS水汽监测系统得到的GNSS-PWV时间序列,采用db4和sym4小波对上述时间序列数据进行了分解和重构。实验结果表明,相比db4小波,sym4小波对GNSS-PWV时间序列的降噪效果更好,并且经其处理后的GNSS-PWV高频分量可更清晰直观地展示降水前水汽的异常突变。

Based on the urban continuously operating refe-rence station(CORS) system, the real-time water vapor pro-ducts with high accuracy and high spatio-temporal resolution can be obtained by global navigation satellite system(GNSS) water vapor detection technique. The water vapor information is an innovative product of the new generation CORS system, which can lay the foundation for precise weather service in the future. To investigate the processing effect of the wavelets transform on GNSS-precipitable water vapor(GNSS-PWV) time-series, we collected GNSS-PWV time-series from Zhuhai CORS water vapor monitoring system on corresponding dates on which the multiple precipitation events occurred from July 18 to July 26, 2019. The db4 and sym4 wavelets are used to decompose and reconstruct the above time-series data. The experimental results show that, compared with the db4 wavelet, the sym4 wavelet has a better denoising effect on GNSS-PWV time series, and the high-frequency GNSS-PWV component after being processed can show the abnormal mutation of water vapor before precipitation more clearly and intuitively.