Abstract Global Navigation Satellite System (GNSS) remote sensing precipitable water vapour (PWV) data from November 2015 to March 2019 were combined with snowfall observation data and used to analyse PWV characteristics in Liaoning Province during the snow season (from November to March the following year) and their relationship with snowfall. The potential of using GNSS for PWV measurements was demonstrated using sounding data with a correlation coefficient higher than 0.9 and a mean bias error lower than 0.5 mm. According to the GNSS PWV data gathered at 30-min intervals from 68 GNSS stations in Liaoning during the snow season, the monthly PWV average was highest in November and lowest in January. Negative correlations were found between PWV and altitude. Most of the water vapour was concentrated in the low layer of the atmosphere, and the contribution of this vapour to the PWV was higher during the snow season than in summer. A total of 43 snow cases were identified using the snowfall records from 53 GNSS stations, and the characteristics of PWV during these snowfalls were analysed. An increase in PWV was observed before snowfall events. Moreover, the influence of synoptic systems and air mass origins on PWV was analysed based on National Centers for Environmental Prediction (NCEP) reanalysis data and the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results show that the water vapour condition was better when the synoptic systems or air masses came from areas south of Liaoning.


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    Titel :

    Analysis of precipitable water vapour characteristics from GNSS measurements during the snow season in Liaoning Province, China


    Beteiligte:
    Yang, Lei (Autor:in) / Sun, Li (Autor:in) / Wang, Dongdong (Autor:in) / Zhang, Yue (Autor:in)

    Erschienen in:

    Advances in Space Research ; 67 , 8 ; 2347-2358


    Erscheinungsdatum :

    2021-01-14


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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