GNSS tropospheric gradients with high temporal resolution and their effect on precise positioning

Journal of Geophysical Research

Volumn 121, Issue 2, 2016, Pages 912-930

  Lu, Cuixian ^a   Li, Xingxing ^a   Li, Zhenhong ^b   Heinkelmann, Robert ^a   Nilsson, Tobias ^a   Dick, Galina ^a   Ge, Maorong ^a   Schuh, Harald ^a  

^a GFZ GERMAN RESEARCH CENTRE FOR GEOSCIENCES   (Germany)

^b NEWCASTLE UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GNSS; GRADIENT ANALYSIS; IMAGE RESOLUTION; METEOROLOGY; NOWCASTING; NUMERICAL MODEL; RADIOMETER; REMOTE SENSING; SPATIOTEMPORAL ANALYSIS; TROPOSPHERE;

EID: 84958225247     PISSN: 01480227     EISSN: 21562202     Source Type: Journal    
DOI: 10.1002/2015JD024255     Document Type: Article

References (33)

1. Bar-Sever, Y. E., P. M. Kroger, and J. A. Borjesson (1998), Estimating horizontal gradients of tropospheric path delay with a single GPS receiver, J. Geophys. Res., 103(B3), 5019–5035, doi:10.1029/97JB03534.
2. Bevis, M., S. Businger, T. Herring, C. Rocken, R. Anthes, and R. Ware (1992), GPS meteorology: Remote sensing of atmospheric water vapor using GPS, J. Geophys. Res., 97, 15,787–15,801.
3. Bevis, M., S. Businger, T. Chiswell, A. Herring, R. Anthes, C. Rocken, and R. Ware (1994), GPS meteorology: Mapping zenith wet delays onto precipitable water, J. Appl. Meteorol., 33, 379–386.
4. Böhm, J., A. Niell, P. Tregoning, and H. Schuh (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.
5. Chen, G., and T. A. Herring (1997), Effects of atmospheric azimuth asymmetry on the analysis of space geodetic data, J. Geophys. Res., 102(B9), 20,489–20,502, doi:10.1029/97JB01739.
6. Dousa, J., and P. Vaclavovic (2014), Real-time zenith tropospheric delays in support of numerical weather prediction applications, Adv. Space Res., 53(9), 1347–1358.
7. Duan, J., et al. (1996), GPS meteorology: Direct estimation of the absolute value of precipitable water, J. Appl. Meteorol., 35, 830–838.
8. Elgered, G., and P. O. J. Jarlemark (1998), Ground-based microwave radiometry and long-term observations of atmospheric water vapor, Radio Sci., 33(3), 707–717, doi:10.1029/98RS00488.
9. Elgered, G., H. Plag, H. van der Marel, S. Barlag, and J. Nash (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.
10. Fang, P., M. Bevis, Y. Bock, S. Gutman, and D. Wolfe (1998), GPS meteorology: Reducing systematic errors in geodetic estimates for zenith delay, Geophys. Res. Lett., 25, 3583–3586.
11. Gendt, G., G. Dick, C. Reigber, M. Tomassini, Y. Liu, and M. Ramatschi (2004), Near real time GPS water vapor monitoring for numerical weather prediction in Germany, J. Meteorol. Soc. Jpn., 82, 361–370.
12. Ghoddousi-Fard, R., P. Dare, and R. Langley (2009), Tropospheric delay gradients from numerical weather prediction models: Effects on GPS estimated parameters, GPS Solut., 13(4), 281–291.
13. Gradinarsky, L., J. Johansson, H. Bouma, H. Scherneck, and G. Elgered (2002), Climate monitoring using GPS, Phys. Chem. Earth, 27(4–5), 335–340, doi:10.1016/S1474-7065(02)00009-8.
14. Iwabuchi, T., S. Miyazaki, K. Heki, I. Naito, and Y. Hatanaka (2003), An impact of estimating tropospheric delay gradients on tropospheric delay estimations in the summer using the Japanese nationwide GPS array, J. Geophys. Res., 108(D10), 4315, doi:10.1029/2002JD002214.
15. Karabatic, A., R. Weber, and T. Haiden (2011), Near real-time estimation of tropospheric water vapour content from ground based GNSS data and its potential contribution to weather now-casting in Austria, Adv. Space Res., 47, 1691–1703.
16. Kouba, J. (2009), A Guide to Using International GNSS Service (IGS) Products. [Available at http://igscb.jpl.nasa.gov/igscb/resource/pubs/UsingIGSProductsVer21.pdf.]
17. Li, X., G. Dick, M. Ge, S. Heise, J. Wickert, and M. Bender (2014), Real-time GPS sensing of atmospheric water vapor: Precise point positioning with orbit, clock and phase delay corrections, Geophys. Res. Lett., 41, 3615–3621, doi:10.1002/2013GL058721.
18. Li, X., F. Zus, C. Lu, G. Dick, T. Ning, M. Ge, J. Wickert, and H. Schuh (2015a), Retrieving of atmospheric parameters from multi-GNSS in real time: Validation with water vapor radiometer and numerical weather model, J. Geophys. Res. Atmos., 120, 7189–7204, doi:10.1002/2015JD023454.
19. Li, X., M. Ge, X. Dai, X. Ren, M. Fritsche, J. Wickert, and H. Schuh (2015b), Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo, J. Geod., 89(6), 607–635.
20. Li, X., X. Zhang, X. Ren, M. Fritsche, J. Wickert, and H. Schuh (2015c), Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou, Sci. Rep., 5, 8328, doi:10.1038/srep08328.
21. Li, X., F. Zus, C. Lu, T. Ning, G. Dick, M. Ge, J. Wickert, and H. Schuh (2015d), Retrieving high-resolution tropospheric gradients from multi-constellation GNSS observations, Geophys. Res. Lett., 42, 4173–4181, doi:10.1002/2015GL063856.
22. Li, Z., J.-P. Muller, and P. Cross (2003), Comparison of precipitable water vapor derived from radiosonde, GPS, and Moderate-Resolution Imaging Spectroradiometer measurements, J. Geophys. Res., 108(D20), 4651, doi:10.1029/2003JD003372.
23. MacMillan, D. (1995), Atmospheric gradients from very long baseline interferometry observations, Geophys. Res. Lett., 22(9), 1041–1044, doi:10.1029/95GL00887.
24. Meindl, M., S. Schaer, U. Hugentobler, and G. Beutler (2004), Tropospheric gradient estimation at CODE: Results from Global Solutions, J. Meteorol. Soc. Jpn., 82, 331–338, doi:10.2151/jmsj.2004.331.
25. Miyazaki, S., T. Iwabuchi, K. Heki, and I. Naito (2003), An impact of estimating tropospheric delay gradients on precise positioning in the summer using the Japanese nationwide GPS array, J. Geophys. Res., 108(B7), 2335, doi:10.1029/2000JB000113.
26. Montenbruck, O., P. Steigenberger, R. Khachikyan, G. Weber, R. B. Langley, L. Mervart, and U. Hugentobler (2014), IGS-MGEX: Preparing the ground for multi-constellation GNSS science, Inside GNSS, 9(1), 42–49.
27. Nilsson, T., and G. Elgered (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.
28. Poli, P., P. Moll, F. Rabier, G. Desroziers, B. Chapnik, L. Berre, S. B. Healy, E. Andersson, and F.-Z. El Guelai (2007), Forecast impact studies of zenith total delay data from European near real-time GPS stations in Météo France 4DVAR, J. Geophys. Res., 112, D06114, doi:10.1029/2006JD007430.
29. Rocken, C., T. Van Hove, and R. Ware (1997), Near real-time sensing of atmospheric water vapor, Geophys. Res. Lett., 24, 3221–3224.
30. 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.
31. Shoji, Y. (2013), Retrieval of water vapor inhomogeneity using the Japanese nationwide GPS array and its potential for prediction of convective precipitation, J. Meteorol. Soc. Jpn., 91, 43–62.
32. Zumberge, J. F., M. B. Heflin, D. C. Jefferson, M. M. Watkins, and F. H. Webb (1997), Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res., 102(B3), 5005–5017.
33. Zus, F., G. Dick, J. Dousa, S. Heise, and J. Wickert (2014), The rapid and precise computation of GPS slant total delays and mapping factors utilizing a numerical weather model, Radio Sci., 49, 207–216, doi:10.1002/2013RS005280.