北京测绘2026，Vol.40Issue(8)：1102-1112,11.DOI:10.19580/j.cnki.1007-3000.2026040099
基于奇异谱分析的暴雨过程GNSS-PWV异常变化分析
Analysis of rainstorm GNSS-PWV anomalous variations based on singular spectrum analysis
摘要
Abstract
This paper employed the singular spectrum analysis(SSA)method to reveal the patterns of anomalous variations in global navigation satellite system(GNSS)-derived precipitable water vapor(PWV)during rainstorm processes,providing both data and theoretical support for the monitoring and early warning of,short-duration heavy precipitation.Taking typical rainstorm events in the Beijing region as the study subjects,hourly GNSS observation data from the BJFS station were used to construct time series of PWV and its increments.The study integrated Beijing radiosonde observation data,hourly precipi-tation data,and 100-m wind field data from the fifth-generation global atmospheric reanalysis dataset(ERA5)of the European Centre for Medium-Range Weather Forecasts(ECMWF),combined with time-lag correlation analysis and SSA,to character-ize the anomalous variations of GNSS-PWV during rainstorms.Results show that the GNSS-retrieved PWV exhibits good con-sistency with radiosonde measurements,with a mean difference of 0.08 mm and a standard deviation of 1.2 mm.For the three individual rainstorm cases analyzed,the optimal time lags between raw PWV and precipitation are+5 h,-2 h,and-12 h,respectively,indicating that the precursor lead time of rainstorm exhibits significant differences across individual cases.After SSA decomposition,the mesoscale oscillation components(RC2-3)show the strongest correlation with precipitation,with correlation coefficients increasing to 0.479,0.561,and 0.546,respectively,and the optimal time lags converging toward near-zero lag.The results indicate that,prior to Beijing rainstorms,GNSS-derived PWV can effectively capture atmospheric water-vapor anomalies,whose precursor duration is jointly regulated by the scale of moisture transport and convective trigger-ing mechanisms.Compared with the raw PWV series,the mesoscale components extracted by SSA more precisely character-ize imminent precipitation precursor signals,providing a useful reference for developing short-lead-time GNSS-based water vapor rainstorm early warning models.关键词
全球导航卫星系统(GNSS)/可降水量(PWV)/暴雨/水汽异常/奇异谱分析(SSA)/时滞相关Key words
global navigation satellite system(GNSS)/precipitable water vapor(PWV)/rainstorm/water vapor anomaly/singular spectrum analysis(SSA)/time-lag correlation分类
天文与地球科学引用本文复制引用
史林睿..基于奇异谱分析的暴雨过程GNSS-PWV异常变化分析[J].北京测绘,2026,40(8):1102-1112,11.基金项目
宁夏回族自治区重点研发计划(2024BEG03025) （2024BEG03025）
