Journal of Geodesy

, Volume 85, Issue 2, pp 75–91 | Cite as

Evaluation of the impact of atmospheric pressure loading modeling on GNSS data analysis

  • Rolf Dach
  • Johannes Böhm
  • Simon Lutz
  • Peter Steigenberger
  • Gerhard Beutler
Original Article

Abstract

In recent years, several studies have demonstrated the sensitivity of Global Navigation Satellite System (GNSS) station time series to displacements caused by atmospheric pressure loading (APL). Different methods to take the APL effect into account are used in these studies: applying the corrections from a geophysical model on weekly mean estimates of station coordinates, using observation-level corrections during data analysis, or solving for regression factors between the station displacement and the local pressure. The Center for Orbit Determination in Europe (CODE) is one of the global analysis centers of the International GNSS Service (IGS). The current quality of the IGS products urgently asks to consider this effect in the regular processing scheme. However, the resulting requirements for an APL model are demanding with respect to quality, latency, and—regarding the reprocessing activities—availability over a long time interval (at least from 1994 onward). The APL model of Petrov and Boy (J Geophys Res 109:B03405, 2004) is widely used within the VLBI community and is evaluated in this study with respect to these criteria. The reprocessing effort of CODE provides the basis for validating the APL model. The data set is used to solve for scaling factors for each station to evaluate the geophysical atmospheric non-tidal loading model. A consistent long-term validation of the model over 15 years, from 1994 to 2008, is thus possible. The time series of 15 years allows to study seasonal variations of the scaling factors using the dense GNSS tracking network of the IGS. By interpreting the scaling factors for the stations of the IGS network, the model by (2004) is shown to meet the expectations concerning the order of magnitude of the effect at individual stations within the uncertainty given by the GNSS data processing and within the limitations due to the model itself. The repeatability of station coordinates improves by 20% when applying the effect directly on the data analysis and by 10% when applying a post-processing correction to the resulting weekly coordinates compared with a solution without taking APL into account.

Keywords

Atmospheric pressure loading GNSS processing Model validation Terrestrial reference frame 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Altamimi Z, Collilieux X, Legrand J, Garayt B, Boucher C (2007) ITRF2005: a new release of the International Terrestrial Reference Frame based on time series of station positions and Earth orientation parameters. J Geophys Res 112(B9): 401–419. doi:10.1029/2007JB004949 CrossRefGoogle Scholar
  2. Beutler G, Brockmann E, Gurtner W, Hugentobler U, Mervart L, Rothacher M, Verdun A (1994) Extended orbit modeling techniques at the CODE processing center of the International GPS Service for Geodynamics (IGS): theory and initial results. Manuscr Geodaetica 19(6): 367–386Google Scholar
  3. Blewitt G (2003) Self-consistency in reference frames, geocenter definition, and surface loading of the solid earth. J Geophys Res 108(B2): 2103. doi:10.1029/2002JB002082 CrossRefGoogle Scholar
  4. Bock D, Noomen R, Scherneck HG (2005) Atmospheric pressure loading displacement of SLR stations. J Geodyn 39: 247–266. doi:10.1016/j.jog.2004.11.004 CrossRefGoogle Scholar
  5. Böhm J, Niell A, Tregoning P, Schuh H (2006a) 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
  6. Böhm J, Werl B, Schuh H (2006b) Troposphere mapping functions for GPS and VLBI from ECMWF operational analysis data. J Geophys Res 111: B02406. doi:10.1029/2005JB003629 CrossRefGoogle Scholar
  7. Böhm J, Heinkelmann R, Schuh H (2007) Short note: a global model of pressure and temperature for geodetic applications. J Geod 81(10): 679–683. doi:10.1007/s00190-007-0135-3 CrossRefGoogle Scholar
  8. Böhm J, Heinkelmann R, Mendes Cerveira PJ, Schuh H (2009) Atmospheric loading corrections at the observation level in VLBI analysis. J Geod 83(11): 1107–1113. doi:10.1007/s00190-009-0329-y CrossRefGoogle Scholar
  9. Collilieux X, Altamimi Z, Coulot D, van Dam T, Ray J (2010) Impact of loading effects on determination of the International Terrestrial Reference Frame. Adv Space Res 45(1): 144–154. doi:10.1016/j.asr.2009.08.024 CrossRefGoogle Scholar
  10. Dach R, Beutler G, Bock H, Fridez P, Gäde A, Hugentobler U, Jäggi A, Meindl M, Mervart L, Prange L, Schaer S, Springer T, Urschl C, Walser P (2007) Bernese GPS software version 5.0. Astronomical Institute, University of Bern, SwitzerlandGoogle Scholar
  11. Dach R, Springer T, Altamimi Z (2008) Experiment on impact of constrained orbit parameters on station coordinates. In: International GNSS Service: Analysis Center Workshop. Miami Beach, Florida, USAGoogle Scholar
  12. Dow J, Neilan R, Rizos C (2009) The International GNSS Service in a changing landscape of Global Navigation Satellite Systems. J Geod 83(3–4): 191–198. doi:10.1007/s00190-008-0300-3 CrossRefGoogle Scholar
  13. Farrell WE (1972) Deformation of the Earth by surface loads. Rev Geophys Space Phys 10: 761–797. doi:10.1029/RG010i003p00761 CrossRefGoogle Scholar
  14. Ferland R, Piraszewski M (2009) The IGS-combined station coordinates, Earth rotation parameters and apparent geocenter. J Geod 83(3–4): 385–392. doi:10.1007/s00190-008-0295-9 CrossRefGoogle Scholar
  15. Kaniuth K, Vetter S (2006) Estimating atmospheric pressure loading regression coefficients from GPS observations. GPS Solut 10(2): 126–134. doi:10.007/s10291-005-0014-4 CrossRefGoogle Scholar
  16. Kouba J (2008) Implementation and testing of the gridded Vienna Mapping Function 1 (VMF1). J Geod 82(4–5): 193–205. doi:10.1007/s00190-007-0170-0 CrossRefGoogle Scholar
  17. MacMillan DS, Gipson JM (1994) Atmospheric pressure loading parameters from very long baseline interferometry observations. J Geophys Res 99(B9): 18,081–18,087. doi:10.1029/94JB01190 CrossRefGoogle Scholar
  18. Manabe S, Sato T, Sakai S, Yokoyama K (1991) Atmospheric loading effect on VLBI observations. In: AGU Chapman conference on geodetic VLBI: monitoring global change. NOAA technical report NOS 137, NGS 49, U.S. Department of Commerce, NOAA/NOS, Rockville, MD, pp 111–122Google Scholar
  19. McCarthy D, Petit G (2004) IERS Conventions (2003). IERS technical note 32. Bundesamt für Kartographie und Geodäsie, Frankfurt am MainGoogle Scholar
  20. Ostini L, Dach R, Meindl M, Schaer S, Hugentobler U (2008) FODITS: a new tool of the Bernese GPS software. In: Ihde J, Hornik H (eds) EUREF symposium, no. 18, June 18–20, 2008, Brussels, Belgium. EUREF Publication (in print)Google Scholar
  21. Petrov L, Boy JP (2004) Study of the atmospheric pressure loading signal in very long baseline interferometry observations. J Geophys Res 109: B03405. doi:10.1029/2003JB002500 CrossRefGoogle Scholar
  22. Rabbel W, Zschau J (1985) Static deformations and gravity changes at the Earth’s surface due to atmospheric loading. J Geophys 56: 81–99Google Scholar
  23. Schaer S, Dach R, Meindl M (2008) CODE analysis strategy summary. http://www.aiub.unibe.ch/download/CODE/CODE.ACN
  24. Schmid R, Steigenberger P, Gendt G, Ge M, Rothacher M (2007) Generation of a consistent absolute phase center correction model for GPS receiver and satellite antennas. J Geod 81(12): 781–798. doi:10.1007/s00190-007-0148-y CrossRefGoogle Scholar
  25. Steigenberger P, Böhm J, Tesmer V (2009a) Comparison of GMF/GPT with VMF1/ECMWF and implications for atmospheric loading. J Geod 83(10): 943–951. doi:10.1007/s00190-009-0311-8 CrossRefGoogle Scholar
  26. Steigenberger P, Schaer S, Lutz S, Dach R, Ostini L, Hugentobler U, Bock H, Jäggi A, Meindl M, Thaller D (2009b) CODE. EGU General Assembly, Vienna, Austria, pp 19–24Google Scholar
  27. Tesmer V, Böhm J, Meisel B, Rothacher M, Steigenberger P (2008) Atmospheric loading coefficients determined from homogeneously reprocessed GPS and VLBI height time series. In: Finkelstein A Behrend D (eds) Measuring the future. Proceedings of the 5th IVS general meeting, pp 307–313Google Scholar
  28. Tregoning P, van Dam T (2005) Atmospheric pressure loading corrections applied to GPS data at the observation level. Geophys Res Lett 32: L22310. doi:10.1029/2005GL024104 CrossRefGoogle Scholar
  29. Tregoning P, Watson C (2009) Atmospheric effects and spurious signals in GPS analyses. J Geophys Res 114: B09403. doi:10.1029/2009JB006344 CrossRefGoogle Scholar
  30. van Dam T, Herring TA (1994) Detection of atmospheric pressure loading using Very Long Baseline Interferometry measurements. J Geophys Res 99(B3): 4505–4517. doi:10.1029/93JB02658 CrossRefGoogle Scholar
  31. van Dam T, Wahr J, Milly PCD, Shmakin AB, Blewitt G, Lavalee D, Larson K (2001) Crustal displacements due to continental water loading. Geophys Res Lett 28(4): 651–654. doi:10.1029/2000GL012120 CrossRefGoogle Scholar
  32. van Dam T, Plag HP, Francis O, Gegout P (2003) GGFC special bureau for loading: current status and plans. In: Richter B, Schwegmann W, Dick WR (eds) Proceedings of the IERS workshop on combination research and global geophysical fluids. IERS technical note, no. 30. Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main, pp 180–198Google Scholar
  33. Wessel P, Smith WHF (1998) New, improved version of Generic Mapping Tools released. EOS Trans Am Geophys Union 79(47): 579CrossRefGoogle Scholar
  34. Zumberge JF, Heflin MB, Jefferson DC, Watkins MM, Webb FH (1994) Precise point positioning for the efficient and robust analysis of GPS data from large networks. J Geophys Res 102(B3): 5005–5017. doi:10.1029/96JB03860 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Rolf Dach
    • 1
  • Johannes Böhm
    • 2
  • Simon Lutz
    • 1
  • Peter Steigenberger
    • 3
  • Gerhard Beutler
    • 1
  1. 1.Astronomical InstituteUniversity of BernBernSwitzerland
  2. 2.Institute of Geodesy and GeophysicsVienna University of TechnologyViennaAustria
  3. 3.Institut für Astronomische und Physikalische GeodäsieTechnische Universität MünchenMunichGermany

Personalised recommendations