Research On Ground-Based GPS Atmospheric Water Vapor Method And Influencing Factors

The accuracy of the data obtained from the weighted average temperature and the final precision ephemeris during the inversion of ground-based GPS water vapor can be applied in numerical weather prediction.However,the time delay of the final precision ephemeris cannot meet the real-time requirements of weather forecast.Obtaining the atmospheric weighted average temperature based on the general atmospheric weighted average temperature model cannot obtain the same accuracy in each region,and will have an impact on the accuracy of water vapor inversion.China's water vapor resolving network has been initially established,but many sites cannot obtain site-based meteorological elements based on historical reasons.If the temperature and pressure model in GPS positioning is used,although the same water vapor variation trend can be obtained,the accuracy varies greatly.In this paper,based on the national water vapor station network and sounding observation data set up by the Hong Kong Satellite Reference Station Network and the National Weather Service,the ground water vapor inversion methods and the related factors of the impact are analyzed.The main research content is as follows:The research background and development status of GPS meteorology are described.The principle of GPS system applied to water vapor detection is introduced,and the reliability of water vapor inversion data accuracy is mainly demonstrated and analyzed.Based on the real-time demand of real-time water vapor inversion,water vapor inversion was realized by using ultra-fast ephemeris forecasting,and its reliability was studied.The results show that the inversion accuracy of water vapor and the precision star can be obtained by using the ultra-fast ephemeris forecasting.The accuracy of the results obtained by the calendar is comparable.Analyze the influence of atmospheric weighted average temperature on water vapor inversion results,Using Hong Kong's sounding station's 10-year sounding data to establish a weighted average temperature model for Hong Kong,comparing with commonly used Bevis model and Wang Xiaoying's regression experience model,proved that the accuracy of the model fitted in this paper is obviously better than the accuracy of the above two models.Combined with GPS measured data verified that the model can improve the accuracy of water vapor inversion in Hong Kong.Based on the data set of GPS weather observations from June 2016 to August 2016,the paper proposes an anti-distance weighted interpolation method for increasing height correction to obtain meteorological observation data of experimental stations.The interpolated data in 25 interpolated areas was processed to obtain the interpolated values,which are compared with the measured values at the experimental site.Results verifies that this method can be used to invert moisture data.The meteorological data interpolation method proposed in this paper is applied to Hong Kong region,and it is proved that the accuracy of water vapor inversion obtained from meteorological data obtained by this method is better than that of GPT2 model.