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Journal of Geodesy

, Volume 89, Issue 9, pp 843–856 | Cite as

Real-time retrieval of precipitable water vapor from GPS and BeiDou observations

  • Cuixian Lu
  • Xingxing LiEmail author
  • Tobias Nilsson
  • Tong Ning
  • Robert Heinkelmann
  • Maorong Ge
  • Susanne Glaser
  • Harald Schuh
Original Article

Abstract

The rapid development of the Chinese BeiDou Navigation Satellite System (BDS) brings a promising prospect for the real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV), which is of great benefit for supporting the time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a real-time ZTD/PWV processing method based on Global Positioning System (GPS) and BDS observations. The performance of ZTD and PWV derived from BDS observations using real-time precise point positioning (PPP) technique is carefully investigated. The contribution of combining BDS and GPS for ZTD/PWV retrieving is evaluated as well. GPS and BDS observations of a half-year period for 40 globally distributed stations from the International GNSS Service Multi-GNSS Experiment and BeiDou Experiment Tracking Network are processed. The results show that the real-time BDS-only ZTD series agree well with the GPS-only ZTD series in general: the RMS values are about 11–16 mm (about 2–3 mm in PWV). Furthermore, the real-time ZTD derived from GPS-only, BDS-only, and GPS/BDS combined solutions are compared with those derived from the Very Long Baseline Interferometry. The comparisons show that the BDS can contribute to real-time meteorological applications, slightly less accurately than GPS. More accurate and reliable water vapor estimates, about 1.3–1.8 mm in PWV, can be obtained if the BDS observations are combined with the GPS observations in the real-time PPP data processing. The PWV comparisons with radiosondes further confirm the performance of BDS-derived real-time PWV and the benefit of adding BDS to standard GPS processing.

Keywords

BeiDou GPS Precipitable water vapor Tropospheric delay Real-time precise point positioning VLBI Radiosonde 

Notes

Acknowledgments

We acknowledge IGS, MGEX, and BETN for providing the GPS and BDS data and IVS for providing the VLBI data. We also thank NOAA for the online provision of radiosonde data. One of the authors (C. Lu) is supported by the China Scholarship Council, which is gratefully acknowledged.

References

  1. Askne J, Nordius H (1987) Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci 22:379–386CrossRefGoogle Scholar
  2. Bender M, Dick G, Wickert J, Ramatschi M, Ge M, Gendt G, Rothacher M, Raabe A, Tetzlaff G (2009) Estimates of the information provided by GPS slant data observed in Germany regarding tomographic applications. J Geophys Res 114:D06303. doi: 10.1029/2008JD011008 Google Scholar
  3. Böhm 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 Google Scholar
  4. Böhm J, Böhm S, Nilsson T, Pany A, Plank L, Spicakova H, Teke K, Schuh H (2012) The new Vienna VLBI software VieVS, Geodesy for Planet Earth. In: Proceedings of the 2009 IAG symp, Buenos Aires, International Association of Geodesy Symposia Series, vol 136, pp 1007–1011Google Scholar
  5. Bevis M, Businger S, Herring T, Rocken C, Anthes R, Ware R (1992) GPS meteorology: remote sensing of atmospheric water vapor using GPS. J Geophys Res 97:15787–15801CrossRefGoogle Scholar
  6. Caissy M, Agrotis L, Weber G, Hernandez-Pajares M, Hugentobler U (2012) Coming soon: the International GNSS Real-Time Service, GPS World, vol 23(6), pp 52–58Google Scholar
  7. China Satellite Navigation Office (2012) BeiDou navigation satellite system signal in space interface control document. http://gge.unb.ca/test/beidou_icd_english.pdf
  8. Dow J, Neilan R, Rizos C (2009) The International GNSS Service in a changing landscape of Global Navigation Satellite Systems. J Geod 83:191–198. doi: 10.1007/s00190-008-0300-3 CrossRefGoogle Scholar
  9. Davis J, Herring T, 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):1593–1607. doi: 10.1029/RS020i006p01593 CrossRefGoogle Scholar
  10. Dousa J, Vaclavovic P (2014) Real-time zenith tropospheric delays in support of numerical weather prediction applications. Adv Space Res 53(9):1347–1358CrossRefGoogle Scholar
  11. Elgered G, Plag H, van der Marel H, Barlag S, Nash J (eds) (2005) COST 716: exploitation of ground-based GPS for climate and numerical weather prediction applications, Final Report, European Community, EUR 21639, ISBN 92-898-0012-7Google Scholar
  12. Fang P, Bevis M, Bock Y, Gutman S, Wolfe D (1998) GPS meteorology: reducing systematic errors in geodetic estimates for zenith delay. Geophys Res Lett 25:3583–3586CrossRefGoogle Scholar
  13. Gendt G, Dick G, Reigber C, Tomassini M, Liu Y, Ramatschi M (2004) Near real-time GPS water vapor monitoring for numerical weather prediction in Germany. J Meteorol Soc Jpn 82:361–370CrossRefGoogle Scholar
  14. Gutman S, Sahm R, Benjamin G, Schwartz E, Holub L, Stewart Q, Smith L (2004) Rapid retrieval and assimilation of ground based GPS-Met observations at the NOAA forecast systems laboratory: impact on weather forecasts. J Meteorol Soc Jpn 82:351–360CrossRefGoogle Scholar
  15. Ge M, Zhang H, Jia X, Song S, Wickert J (2012) What is achievable with the current COMPASS constellation? GPS World November, pp 29–34Google Scholar
  16. Haan S, Barlag S, Baltink H, Debie F (2004) Synergetic use of GPS water vapor and meteosat images for synoptic weather forecasting. J Appl Meterol 43:514–518CrossRefGoogle Scholar
  17. Heinkelmann R, Böhm J, Schuh H, Bolotin S, Engelhardt G, MacMillan D, Negusini M, Skurikhina E, Tesmer V, Titov O (2007) Combination of long time-series of troposphere zenith delays observed by VLBI. J Geod 81(6–8):483–501CrossRefGoogle Scholar
  18. Kouba J (2009) A guide to using International GNSS Service (IGS) Products. http://igscb.jpl.nasa.gov/igscb/resource/pubs/UsingIGSProductsVer21.pdf
  19. Lagler K, Schindelegger M, Boehm J, Krásná H, Nilsson T (2013) GPT2: Empirical slant delay model for radio space geodetic techniques. Geophys Res Lett 40:1069–1073. doi: 10.1002/grl.50288 CrossRefGoogle Scholar
  20. Li M, Li W, Shi C, Zhao Q, Su X, Qu L, Liu Z (2014a) Assessment of precipitable water vapor derived from ground-based BeiDou observations with Precise Point Positioning approach. Adv Space Res 55(1):150–162CrossRefGoogle Scholar
  21. Li X, Zhang X, Ge M (2011) Regional reference network augmented precise point positioning for instantaneous ambiguity resolution. J Geod 85:151–158CrossRefGoogle Scholar
  22. Li X, Ge M, Zhang H, Nischan T, Wickert J (2013a) The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS. Adv Space Res 51(6):1008–1018CrossRefGoogle Scholar
  23. Li X, Ge M, Zhang H, Wickert J (2013b) A method for improving uncalibrated phase delay estimation and ambiguity-fixing in real-time precise point positioning. J Geod 87(5):405–416CrossRefGoogle Scholar
  24. Li X, Ge M, Zhang X, Zhang Y, Guo B, Wang R, Klotz J, Wickert J (2013c) Real-time high-rate co-seismic displacement from ambiguity-fixed precise point positioning: application to earthquake early warning. Geophys Res Lett 40(2):295–300. doi: 10.1002/grl.50138 CrossRefGoogle Scholar
  25. Li X, Dick G, Ge M, Heise S, Wickert J, Bender M (2014b) Real-time GPS sensing of atmospheric water vapor: precise point positioning with orbit, clock and phase delay corrections. Geophys Res Lett 41(10):3615–3621CrossRefGoogle Scholar
  26. Li X, Zhang X, Ren X, Fritsche M, Wickert J, Schuh H (2015) Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou. Sci Rep 5:8328CrossRefGoogle Scholar
  27. Montenbruck O, Steigenberger P, Khachikyan R, Weber G, Langley RB, Mervart L, Hugentobler U (2014) IGS-MGEX: preparing the ground for multi-constellation GNSS science. Inside GNSS 9(1):42–49Google Scholar
  28. Nilsson T, Elgered G (2008) Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data. J Geophys Res 113:D19101. doi: 10.1029/2008JD010110 CrossRefGoogle Scholar
  29. Nothnagel A (2009) Conventions on thermal expansion modeling of radio telescopes for geodetic and astrometric VLBI. J Geod 83:787–792. doi: 10.1007/s00190-008-0284-z CrossRefGoogle Scholar
  30. Ning T, Haas R, Elgered G, Willén U (2012) Multi-technique comparisons of 10 years of wet delay estimates on the west coast of Sweden. J Geod 86(7):565–575. doi: 10.1007/s00190-011-0527-2 CrossRefGoogle Scholar
  31. Petit G, Luzum B (eds) (2010) IERS Conventions (2010), IERS Technical Note 36, Verlagdes Bundesamts für Kartographie und Geodäsie, Frankfurt am Main, Germany. http://tai.bipm.org/iers/conv2010/
  32. Ran C (2010) COMPASS Satellite System Development and Plan. In: Proceedings of The First China Satellite Navigation Conference, Beijing, China, 19–21 May 2010Google Scholar
  33. Rocken C, Van Hove T, Ware R (1997) Near real-time sensing of atmospheric water vapor. Geophys Res Lett 24:3221–3224CrossRefGoogle Scholar
  34. Schuh H, Behrend D (2012) VLBI: a fascinating technique for geodesy and astrometry. J Geodyn 61:68–80. doi: 10.1016/j.jog.2012.07.007
  35. Shi C, Zhao Q, Li M, Tang W, Hu Z, Lou Y, Zhang H, Niu X, Liu J (2012) Precise orbit determination of BeiDou Satellites with precise positioning. Sci China Earth Sci 55:1079–1086CrossRefGoogle Scholar
  36. Saastamoinen J (1973) Contributions to the theory of atmospheric refraction—part II. Refraction corrections in satellite geodesy. Bull Géod 47(1):13–34. doi: 10.1007/BF02522083
  37. Teke K, Boehm J, Nilsson T, Schuh H, Steigenberger P, Dach R, Heinkelmann R, Willis P, Haas R, Garcia-Espada S, Hobiger T, Ichikawa R, Shimizu S (2011) Multi-technique comparison of troposphere zenith delays and gradients during CONT08. J Geod 85:395–413. doi: 10.1007/s00190-010-0434-y CrossRefGoogle Scholar
  38. Wang J, Zhang L, Dai A (2005) Global estimates of water-vapor-weighted mean temperature of the atmosphere for GPS applications. J Geophys Res 110:D21101. doi: 10.1029/2005JD006215 CrossRefGoogle Scholar
  39. Wang X, Wang X, Dai Z, Ke F, Cao Y, Wang F, Song L (2014) Tropospheric wet refractivity tomography based on the BeiDou Satellite System. Adv Atmos Sci. doi: 10.1007/s00376-013-2311-0
  40. Xu A, Xu Z, Ge M, Xu X, Zhu H, Sui X (2013) Estimating zenith tropospheric delays from BeiDou navigation satellite system observations. Sensors 13:4514–4526CrossRefGoogle Scholar
  41. Yang Y, Li J, Xu J, Tang J, Guo H, He H (2011) Contribution of the compass satellite nagivation system to global PNT users. Chin. Sci. Bull. 56(26):2813–2819. doi: 10.1007/s11434-001-4627-4 CrossRefGoogle Scholar
  42. Yuan Y, Zhang K, Rohm W, Choy S, Norman R, Wang C (2014) Real-time retrieval of precipitable water vapor from GPS precise point positioning. J Geophys Res Atmos 119:10044–10057CrossRefGoogle Scholar
  43. Zumberge J, Heflin M, Jefferson D, Watkins M, Webb F (1997) Precise point positioning for the efficient and robust analysis of GPS data from large networks. J Geophys Res 102(B3):5005–5017CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Cuixian Lu
    • 1
  • Xingxing Li
    • 1
    Email author
  • Tobias Nilsson
    • 1
  • Tong Ning
    • 1
  • Robert Heinkelmann
    • 1
  • Maorong Ge
    • 1
  • Susanne Glaser
    • 2
  • Harald Schuh
    • 1
  1. 1.German Research Centre for Geosciences GFZPotsdamGermany
  2. 2.Technische Universitaet BerlinBerlinGermany

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