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Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS

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Abstract

The revitalized Russian GLONASS system provides new potential for real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV) in order to support time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a method of real-time ZTD/PWV retrieval based on GLONASS and/or GPS observations. The performance of ZTD and PWV derived from GLONASS data using real-time precise point positioning (PPP) technique is carefully investigated and evaluated. The potential of combining GLONASS and GPS data for ZTD/PWV retrieving is assessed as well. The GLONASS and GPS observations of about half a year for 80 globally distributed stations from the IGS (International GNSS Service) network are processed. The results show that the real-time GLONASS ZTD series agree quite well with the GPS ZTD series in general: the RMS of ZTD differences is about 8 mm (about 1.2 mm in PWV). Furthermore, for an inter-technique validation, the real-time ZTD estimated from GLONASS-only, GPS-only, and the GPS/GLONASS combined solutions are compared with those derived from very long baseline interferometry (VLBI) at colocated GNSS/VLBI stations. The comparison shows that GLONASS can contribute to real-time meteorological applications, with almost the same accuracy as GPS. More accurate and reliable water vapor values, about 1.5–2.3 mm in PWV, can be achieved when GLONASS observations are combined with the GPS ones in the real-time PPP data processing. The comparison with radiosonde data further confirms the performance of GLONASS-derived real-time PWV and the benefit of adding GLONASS to stand-alone GPS processing.

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References

  • Askne J, Nordius H (1987) Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci 22:379–386

    Article  Google Scholar 

  • 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 97:15787–15801

    Article  Google Scholar 

  • 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 

  • 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 symposium, Buenos Aires, International Association of Geodesy Symposia Series, vol 136. pp 1007–1011

  • Bruyninx C (2007) Comparing GPS-only with GPS + GLONASS positioning in a regional permanent GNSS network. GPS Solut 11(2):97–106

    Article  Google Scholar 

  • Cai C, Gao Y (2013) Modeling and assessment of combined GPS/GLONASS precise point positioning. GPS Solut 17(2):223–236

    Article  Google Scholar 

  • Caissy M, Agrotis L, Weber G, Hernandez-Pajares M, Hugentobler U (2012) The international GNSS real-time service. GPS World 23(6):52–58

    Google Scholar 

  • Chen G, Herring T (1997) Effects of atmospheric azimuthal asymmetry on the analysis of space geodetic data. J Geophys Res 102(B9):20489–20502. doi:10.1029/97JB01739

    Article  Google Scholar 

  • Dach R, Schaer S, Hugentobler U (2006) Combined multi-system GNSS analysis for time and frequency transfer. Proc Eur Freq Time Forum 2006:530–537

  • Dach R, Schmid R, Schmitz M, Thaller D, Schaer S, Lutz S, Steigenberger P, Wübbena G, Beutler G (2011) Improved antenna phase center models for GLONASS. GPS Solut 15(1):49–65

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • De Haan S (2006) National/regional operational procedures of GPS water vapour networks and agreed international procedures. Rep WMO/TD-No, 1340:20. KNMI, Netherlands

  • Dousa J (2010) Precise near real-time GNSS analyses at geodetic observatory Pecny-precise orbit determination and water vapour monitoring. Acta Geodyn Geomater 7(157):7–17

    Google Scholar 

  • Dousa J, Vaclavovic P (2014) Real-time zenith tropospheric delays in support of numerical weather prediction applications. Adv Space Res 53(9):1347–1358

    Article  Google Scholar 

  • Dow J, Neilan R, Rizos C (2009) The International GNSS Service in a changing landscape of Global Navigation Satellite Systems. J Geod 83(3):191–198. doi:10.1007/s00190-008-0300-3

    Article  Google Scholar 

  • 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 92-898-0012-7

  • 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 82:361–370

    Article  Google Scholar 

  • 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 82:351–360

    Article  Google Scholar 

  • Haan S, Barlag S, Baltink H, Debie F (2004) Synergetic use of GPS water vapor and meteosat images for synoptic weather forecasting. J Appl Meteorol 43:514–518

    Article  Google Scholar 

  • 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):483–501

    Article  Google Scholar 

  • Kouba J (2009) A guide to using international GNSS service (IGS) products. http://igscb.jpl.nasa.gov/igscb/resource/pubs/UsingIGSProductsVer21.pdf

  • 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

    Article  Google Scholar 

  • Li X, Zhang X, Ge M (2011) Regional reference network augmented precise point positioning for instantaneous ambiguity resolution. J Geod 85:151–158

    Article  Google Scholar 

  • Li X, Ge M, Zhang H, Wickert J (2013a) A method for improving uncalibrated phase delay estimation and ambiguity-fixing in real-time precise point positioning. J Geod 87(5):405–416

    Article  Google Scholar 

  • Li X, Ge M, Zhang X, Zhang Y, Guo B, Wang R, Klotz J, Wickert J (2013b) 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

    Article  Google Scholar 

  • Li X, Dick G, Ge M, Heise S, Wickert J, Bender M (2014) Real-time GPS sensing of atmospheric water vapor: precise point positioning with orbit, clock and phase delay corrections. Geophys Res Lett 41(10):3615–3621

    Article  Google Scholar 

  • Li X, Zhang X, Ren X, Fritsche M, Wickert J, Schuh H (2015a) Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou. Sci Rep 5:8328

    Article  Google Scholar 

  • Li X, Ge M, Dai X, Ren X, Fritsche M, Wickert J, Schuh H (2015b) Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo. J Geod 89(6):607–635

    Article  Google Scholar 

  • Li X, Zus F, Lu C, Ning T, Dick G, Ge M, Wickert J, Schuh H (2015c) Retrieving high-resolution tropospheric gradients from multiconstellation GNSS observations. Geophys Res Lett 42:4173–4181. doi:10.1002/2015GL063856

    Article  Google Scholar 

  • Niell A, Coster A, Solheim F, Mendes V, Toor P, Langley R, Upham C (2001) Comparison of measurements of atmospheric wet delay by radiosonde, water vapor radiometer GPS, and VLBI. J Atmos Ocean Technol 18:830–850

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Rocken C, Van Hove T, Ware R (1997) Near real-time sensing of atmospheric water vapor. Geophys Res Lett 24:3221–3224

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Shi J, Xu C, Guo J, Gao Y (2015) Real-time GPS precise point positioning-based precipitable water vapor estimation for rainfall monitoring and forecasting. IEEE Trans Geosci Remote Sens 53(6):3452–3459. doi:10.1109/TGRS.2014.2377041

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Wanninger L (2011) Carrier-phase inter-frequency biases of GLONASS receivers. J Geod. doi:10.1007/s00190-011-0502-y

    Google Scholar 

  • 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 119:10044–10057

    Article  Google Scholar 

  • Zhang X, Li X, Guo F (2011) Satellite clock estimation at 1 Hz for real-time kinematic PPP applications. GPS Solut 15(4):315–324. doi:10.1007/s10291-010-0191-7

    Article  Google Scholar 

  • 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):5005–5017

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge IGS for providing the GPS and GLONASS data, IVS for providing the VLBI data, and 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.

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Correspondence to Xingxing Li.

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Lu, C., Li, X., Ge, M. et al. Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS. GPS Solut 20, 703–713 (2016). https://doi.org/10.1007/s10291-015-0479-8

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