Ground GNSS Atmospheric Sensing

  • Shuanggen Jin
  • Estel Cardellach
  • Feiqin Xie
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 19)


The tropospheric delay is one of major error sources in GNSS positioning, which contributes a bias in height of several centimeters even when simultaneously recorded meteorological data are used in tropospheric models. Nowadays, GNSS has been widely used to determine the zenith tropospheric delay (ZTD) as well as precipitable water vapor (PWV). In this chapter, the theory and methods of ZTD and PWV estimations are introduced from ground GNSS observations. The seasonal, secular and diurnal variations of ZTD and PWV are presented in detail as well their applications in the atmosphere.


Precipitable Water Vapor Zenith Total Delay Zenith Total Delay International VLBI Service Zenith Hydrostatic Delay 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bevis M, Businger S, Herring TA, Rocken C, Anilies RA, Ware RH (1992) GPS meteorology: remote sensing of atmospheric water vapor using the Global Positioning System. J Geophys Res 97:15787–15801CrossRefGoogle Scholar
  2. Bevis M, Businger S, Chiswell S et al (1994) GPS meteorology: mapping Zenith Wet Delays onto precipitable water. J Appl Meteorol 33:379–386CrossRefGoogle Scholar
  3. Boehm J, Schuh H (2004) Vienna mapping functions in VLBI analyses. Geophys Res Lett 31:L01603. doi: 10.1029/2003GL018984 CrossRefGoogle Scholar
  4. Boehm J, Niell A, Tregoning P, Schuh H (2006) Global Mapping Function (GMF): a new empirical mapping function based on numerical weather model data. Geophys Res Lett 33:L07304. doi: 10.1029/2005GL025546 CrossRefGoogle Scholar
  5. Chapman S, Lindzen RS (1970) Atmospheric tides: thermal and gravitational. Gordon and Breach, New York, 200 ppGoogle Scholar
  6. Dach R, Dietrich R (2000) Influence of the ocean loading effect on GPS derived precipitable water vapor. Geophys Res Lett 27(18):2953–2956CrossRefGoogle Scholar
  7. Dai A, Wang J (1999) Diurnal and semidiurnal tides in global surface pressure fields. J Atmos Sci 56:3874–3891CrossRefGoogle Scholar
  8. Dai A, Wang J, Ware RH, Van Hove T (2002) Diurnal variation in water vapor over North America and its implications for sampling errors in radiosonde humidity. J Geophys Res 107(D10):4090. doi: 10.1029/2001JD000642 CrossRefGoogle Scholar
  9. Davis JL, Herring TA, Shapiro I, Rogers A, Elgered G (1985) Geodesy by radio interferometry effects of atmospheric modeling errors on estimates of baseline length. Radio Sci 20(6):1593–1607CrossRefGoogle Scholar
  10. Deblonde G, Macpherson S, Mireault Y et al (2005) Evaluation of GPS precipitable water over Canada and the IGS network. J Appl Meteorol 44(1):153–166CrossRefGoogle Scholar
  11. Duan J, Bevis M, Fang P et al (1996) GPS meteorology: direct estimation of the absolute value of precipitable water. J Appl Meteorol 35:830–838CrossRefGoogle Scholar
  12. Emardson TR, Elgered G, Johansson JM (1998) Three months of continuous monitoring of atmospheric water vapor with a network of GPS receivers. J Geophys Res 103:1807–1820CrossRefGoogle Scholar
  13. Feng K, Zhang J, Zhang Y, Yang Z, Chao W (1978) The numerical calculation method. National Defense Industry Press, Beijing, 311 ppGoogle Scholar
  14. Haase J, Ge M, Vedel H, Calais E (2003) Accuracy and variability of GPS tropospheric delay measurements of water vapor in the western Mediterranean. J Appl Meteorol 42(11):1547–1568CrossRefGoogle Scholar
  15. Hagemann S, Bengtsson L, Gendt G (2003) On the determination of atmospheric water vapor from GPS measurements. J Geophys Res 108(D21):4678. doi: 10.1029/2002JD003235 CrossRefGoogle Scholar
  16. Herring TA (1992) Modeling atmospheric delays in the analysis of space geodetic data. In: De Munck JC, Spoelstra TATh (eds) Refraction of transatmospheric signals in Geodesy. Netherland Geodetic Commission Publications in Geodesy, 36, pp 157–164Google Scholar
  17. Humphreys TE, Kelley MC, Huber N, Kintner PM Jr (2005) The semidiurnal variation in GPS-derived zenith neutral delay. Geophys Res Lett 32:L24801. doi: 10.1029/2005GL024207 CrossRefGoogle Scholar
  18. Jin SG, Park PH (2005) A new precision improvement of zenith tropospheric delay estimates by GPS. Curr Sci 89(6):997–1000Google Scholar
  19. Jin SG, Li Z, Cho J (2008) Integrated water vapor field and multi-scale variations over China from GPS measurements. J Appl Meteorol Clim 47:3008–3015. doi: 10.1175/2008JAMC1920.1 CrossRefGoogle Scholar
  20. Jin SG, Luo OF, Ren C (2010) Effects of physical correlations on long-distance GPS positioning and zenith tropospheric delay estimates. Adv Space Res 46(2):190–195. doi: 10.1016/j.asr.2010.01.017 CrossRefGoogle Scholar
  21. King RW, Bock Y (1999) Documentation for the GAMIT GPS analysis software. Massachusetts Institute of Technology, Cambridge, MAGoogle Scholar
  22. Manuel H, Juan J, Sanz J et al (2001) A new strategy for real-time integrated water vapor determination in WADGOPS networks. Geophys Res Lett 28(17):3267–3270CrossRefGoogle Scholar
  23. Marini JW (1972) Correction of satellite tracking data for an arbitrary tropospheric profile. Radio Sci 7(2):223–231CrossRefGoogle Scholar
  24. Niell AE (1996) Global mapping functions for the atmospheric delay at radio wavelengths. J Geophys Res 101(B2):3227–3246CrossRefGoogle Scholar
  25. Niell AE, Coster AJ, Solheim FS, Mendes VB, Toor PC, Langley RB, Upham CA (2001) Comparison of measurements of atmospheric wet delay by radiosonde, water vapor radiometer, GPS, and VLBI. J Atmos Ocean Technol 18:830–850CrossRefGoogle Scholar
  26. Pramualsakdikul S, Haas R, Elgered G, Scherneck HG (2007) Sensing of diurnal and semi-diurnal variability in the water vapor content in the tropics using GPS measurements. Meteorol Appl 14:403–412. doi: 10.1002/met.39 CrossRefGoogle Scholar
  27. Saastamoinen J (1972) Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites. In: The use of artificial satellites for geodesy, Geophysical monograph series 15. American Geophysical Union, Washington, pp 247–251Google Scholar
  28. Snajdrova K, Boehm J, Willis P, Haas R, Schuh H (2005) Multi-technique comparison of tropospheric zenith delays derived during the CONT02 campaign. J Geod 79(10–11):613–623. doi: 10.1007/s00190-005-0010-z Google Scholar
  29. Tregoning P, Boers R, O’Brien D (1998) Accuracy of absolute precipitable water vapor estimates from GPS observations. J Geophys Res 103(28):701–710Google Scholar
  30. Wang J, Zhang LY, Dai A, Van Hove T, Van Baelen J (2007) A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J Geophys Res 112:D11107. doi: 10.1029/2006JD007529 CrossRefGoogle Scholar
  31. Watson C, Tregoning P, Coleman R (2006) Impact of solid Earth tide models on GPS coordinate and tropospheric time series. Geophys Res Lett 33:L08306. doi: 10.1029/2005GL025538 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Shuanggen Jin
    • 1
  • Estel Cardellach
    • 2
  • Feiqin Xie
    • 3
  1. 1.Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghaiChina People’s Republic
  2. 2.Institut d’Estudis Espacials de Catalunya (ICE/IEEC-CSIC)BarcelonaSpain
  3. 3.Texas A&M University-Corpus ChristiCorpus ChristiUSA

Personalised recommendations