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 

机构地区：[1]College of Geomatics and Geoinformation,Guilin University of Technology,Guilin 541004,China [2]Guangxi Key Laboratory of Spatial Information and Geomatics,Guilin 541004,China.3 School of Geodesy and Geomatics,Wuhan University,Wuhan 430079,China.

出　　处：《Satellite Navigation》2021年第1期175-191,共17页卫星导航（英文）

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).

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.

关 键 词：GNSS Precipitable water vapor Heavy rainfall Spatiotemporal characteristic Atmospheric weighted mean temperature 

分 类 号：P426.6[天文地球—大气科学及气象学]