Spatiotemporal characteristics of GNSS-derived precipitable water vapor during heavy rainfall events in Guilin,China

作     者：Liangke Huang Zhixiang Mo Shaofeng Xie Lilong Liu Chuanli Kang Shitai Wang 

作者机构：College of Geomatics and GeoinformationGuilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Spatial Information and GeomaticsGuilin 541004China.3 School of Geodesy and GeomaticsWuhan UniversityWuhan 430079China. 

出 版 物：《Satellite Navigation》 (卫星导航（英文）)

年 卷 期：2021年第2卷第1期

页      面：175-191页

核心收录：

学科分类：0810[工学-信息与通信工程] 07[理学] 0706[理学-大气科学] 0816[工学-测绘科学与技术] 0825[工学-航空宇航科学与技术] 

基　　金：the National Natural Foundation of China(41704027,41664002,41864002) the Guangxi Natural Science Foundation of China(2017GXNSFBA198139,2017GXNSFDA198016,2018GXNSFAA281182,2018GXNSFAA281279) the“Ba Gui Scholars”program of the provincial government of Guangxi,and the Open Fund of Hunan Natural Resources Investigation and Monitoring Engineering Technology Research Center(No:2020-9). 

主　　题：GNSS Precipitable water vapor Heavy rainfall Spatiotemporal characteristic Atmospheric weighted mean temperature 

摘      要：Precipitable Water Vapor(PWV),as an important indicator of atmospheric water vapor,can be derived from Global Navigation Satellite System(GNSS)observations with the advantages of high precision and all-weather capacity.GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in mete-orology,particularly for severe weather conditions,for water vapor is not well sampled in the current meteorological observing systems.In this study,an empirical atmospheric weighted mean temperature(Tm)model for Guilin is estab-lished using the radiosonde data from 2012 to 2017.Then,the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017.The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square(RMS)of−0.51 and 2.12 K,respectively,compared with other widely used models.Moreover,the GNSS PWV estimates are validated with the data at Guilin radiosonde station.Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of−0.9 and 3.53 mm,respectively.Finally,an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed.It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements,and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall.It also reveals the moisture variation in several regions of Guilin during a heavy rainfall,which is significant for the moni-toring of rainfalls and weather forecast.