Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points

Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points

Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristic...

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Autores principales: Xiang Dong, Fang Sun, Qinglin Zhu, Leke Lin, Zhenwei Zhao, Chen Zhou
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
GPS
refractive index
wet delay
water vapor
relevance vector machine
Meteorology. Climatology
QC851-999
Acceso en línea:https://doaj.org/article/4a5e92dba71946bbacaa69c5ab3fc33f
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spelling oai:doaj.org-article:4a5e92dba71946bbacaa69c5ab3fc33f2021-11-25T16:45:09ZTropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points10.3390/atmos121114682073-4433https://doaj.org/article/4a5e92dba71946bbacaa69c5ab3fc33f2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4433/12/11/1468https://doaj.org/toc/2073-4433Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively.Xiang DongFang SunQinglin ZhuLeke LinZhenwei ZhaoChen ZhouMDPI AGarticleGPSrefractive indexwet delaywater vaporrelevance vector machineMeteorology. ClimatologyQC851-999ENAtmosphere, Vol 12, Iss 1468, p 1468 (2021)
institution DOAJ
collection DOAJ
language EN
topic GPS
refractive index
wet delay
water vapor
relevance vector machine
Meteorology. Climatology
QC851-999
spellingShingle GPS
refractive index
wet delay
water vapor
relevance vector machine
Meteorology. Climatology
QC851-999
Xiang Dong
Fang Sun
Qinglin Zhu
Leke Lin
Zhenwei Zhao
Chen Zhou
Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
description Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively.
format article
author Xiang Dong
Fang Sun
Qinglin Zhu
Leke Lin
Zhenwei Zhao
Chen Zhou
author_facet Xiang Dong
Fang Sun
Qinglin Zhu
Leke Lin
Zhenwei Zhao
Chen Zhou
author_sort Xiang Dong
title Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
title_short Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
title_full Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
title_fullStr Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
title_full_unstemmed Tropospheric Refractivity Profile Estimation by GNSS Measurement at China Big-Triangle Points
title_sort tropospheric refractivity profile estimation by gnss measurement at china big-triangle points
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/4a5e92dba71946bbacaa69c5ab3fc33f
work_keys_str_mv AT xiangdong troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
AT fangsun troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
AT qinglinzhu troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
AT lekelin troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
AT zhenweizhao troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
AT chenzhou troposphericrefractivityprofileestimationbygnssmeasurementatchinabigtrianglepoints
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