Advertisement

GPS Solutions

, Volume 17, Issue 1, pp 29–39 | Cite as

GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica

  • G. Esteban Vázquez BEmail author
  • Dorota A. Grejner-Brzezinska
Original Article

Abstract

Three permanent GPS tracking stations in the trans Antarctic mountain deformation (TAMDEF) network were used to estimate precipitable water vapor (PWV) using measurement series covering the period of 2002–2005. TAMDEF is a National Science Foundation funded joint project between The Ohio State University and the United States Geological Survey. The TAMDEF sites with the longest GPS data spans considered in this research are Franklin Island East (FIE0), the International GNSS Service site McMurdo (MCM4), and Cape Roberts (ROB1). For the experiment, PWV was extracted from the ionosphere-free double-difference carrier phase observations, processed using the adjustment of GPS ephemerides (PAGES) software. The GPS data were processed with a 30 s sampling rate, 15-degree cutoff angle, and precise GPS orbits disseminated by IGS. The time-varying part of the zenith wet delay is estimated using the Marini mapping function, while the constant part is evaluated using the corresponding Marini tropospheric model. Previous studies using TAMDEF data for PWV estimation show that the Marini mapping function performs the best among the models offered by PAGES. The data reduction to compute the zenith wet delay follows the step piecewise linear strategy, which is subsequently transformed to PWV. The resulting GPS-based PWV is compared to the radiosonde observations and to values obtained from the Antarctic mesoscale prediction system (AMPS). This comparison revealed a consistent bias of 1.7 mm between the GPS solution and the radiosonde and AMPS reference values.

Keywords

GPS PWV Radiosonde AMPS TAMDEF Antarctica 

Notes

Acknowledgments

The authors would like to thank Dr. Matthew A. Lazzara and Shelley L. Knuth from the Space Science and Engineering Center, University of Wisconsin-Madison, for providing the radiosonde PWV data series for McMurdo. Thanks to Dr. Mark Schenewerk for his valuable comments on dealing with troposphere in PAGES. Special thanks go to Dr. Terry Wilson and Mike Willis from the School of Earth Sciences at OSU and the United States Geological Survey Antarctic Mapping group for providing the TAMDEF data. This research was supported by a National Science Foundation grant.

References

  1. Bevis M, Businger S, Herring TA, Rocken C, Anthes RA, Ware RH (1992) GPS meteorology: remote sensing of atmospheric water vapor using the global positioning system. J Geophys Res 97:l5787–l15801CrossRefGoogle Scholar
  2. Bevis M, Businger S, Chiswell SR, Herring TA, Anthes RA, Rocken C, Ware RH (1994) GPS meteorology: mapping zenith wet delay onto precipitable water. J Appl Meteorol 33:379–386CrossRefGoogle Scholar
  3. Bevis M, Chiswell S, Businger S (1996) Estimating wet delays using numerical weather analyses and predictions. Radio Sci 31(3):477–487CrossRefGoogle Scholar
  4. Bromwich DH, Fogt RL (2004) Strong trends in the skill of the ERA-40 and NCEP/NCAR reanalyses in the high and middle latitudes of the Southern Hemisphere, 1958–2001. J Clim 17:4603–4619CrossRefGoogle Scholar
  5. Bromwich DH, Monaghan AJ, Powers JG, Manning KW (2005) Real-time forecasting for the Antarctic: an evaluation of the Antarctic Mesoscale Prediction System (AMPS). Mon Weather Rev 133:579–603CrossRefGoogle Scholar
  6. Chao C (1973) A model for tropospheric calibration from daily surface and radiosonde balloon measurement. Technical Memorandum, pp 391–350. Jet Propulsion Laboratory, Pasadena CaliforniaGoogle Scholar
  7. Davis JL, Herring TA, Shapiro I, Rogers AE, Elgered G (1985) Geodesy by radio interferometry: effects of atmospheric modeling errors on estimates of baseline length. Radio Sci 20(6):1593–1607CrossRefGoogle Scholar
  8. Dodson AH, Shardlow PJ, Hubbard LCM, Elegered G, Jarlemark POJ (1996) Wet Tropospheric effects on precise relative GPS height determination. J Geod 70(4):188–202CrossRefGoogle Scholar
  9. Eckl MC, Snay RA, Soler TA, Cline MW, Mader GL (2001) Accuracy of GPS-derived relative positions as a function of interstation distance and observation-session duration. J Geod 75:633–640CrossRefGoogle Scholar
  10. Emardson TR, Simons M, Webb FH (2003) Neutral atmospheric delay in interferometric synthetic aperture radar applications: statistical description and mitigation. J Geophys Res 108(B5):2231. doi: 10.1029/2002JB001781 CrossRefGoogle Scholar
  11. Fogt RL, Bromwich DH (2008) Atmospheric moisture and cloud cover characteristics forecast by AMPS. Weather Forecast 23:914–930CrossRefGoogle Scholar
  12. Ifadis IM (2000) A new approach to mapping the atmospheric effect for GPS observations. Earth Planets Space 52:703–708Google Scholar
  13. Lancaster P, Salkauskas K (1986) Curve and surface fitting: an introduction. Academic Press, Harcourt Brace Jovanovich, New YorkGoogle Scholar
  14. Liou YA, Teng YT (2001) Comparison of precipitable water observations in the near tropics by GPS, microwave radiometer, and radiosondes. J Appl Meteorol 40:5–15CrossRefGoogle Scholar
  15. Liu J, Sun Z, Liang H, Xu X, Wu P (2005) Precipitable water vapor on the Tibetan Plateau estimated by GPS, water vapor radiometer, radiosonde, and numerical weather prediction analysis and its impact on the radiation budget. J Geophys Res 110:D17106CrossRefGoogle Scholar
  16. Mader GL, Schenewerk MS, Ray JR, Kass WG, Spofford PR, Dulaney RL, Pursell DG (1995) GPS orbit and earth orientation parameter production at NOAA for the International GPS service for geodynamics for 1994. In: Zumberge JF et al (eds) International GPS service/or geodynamics 1994 annual report. California Institute of Technology, Pasadena, CA, Jet Propulsion Lab, pp 197–212Google Scholar
  17. Marini JW (1972) Correction of satellite tracking data for an arbitrary tropospheric profile. Radio Sci 7(2):223–231CrossRefGoogle Scholar
  18. Marshall J, Schenewerk M, Snay R (2001) The effect of the MAPS weather model on GPS-determined ellipsoidal heights. GPS Solut 5(1):1–14CrossRefGoogle Scholar
  19. Powers JG, Monaghan AJ, Cayette AM, Bromwich DH, Kuo Y-H, Manning KW (2003) Real-time mesoscale modeling over Antarctica: the Antarctic Mesoscale Prediction System (AMPS). Bull Am Meteor Soc 84:1533–1545CrossRefGoogle Scholar
  20. Schenewerk M (2004) Workshop in PAGES. The Ohio State University, Columbus OHGoogle Scholar
  21. Schenewerk MS, Marshall J, Dillinger W (2001) Vertical ocean loading deformations derived from a global GPS network. J Geod Soc Jpn 47(1):237–242Google Scholar
  22. Troller M (2004) GPS-based determination of the integrated and spatially distributed water vapor in the troposphere. Geodätisch-geophysikalische Arbeiten in der Schweiz, vol 67. Swiss Geodetic CommissionGoogle Scholar
  23. Vázquez GE (2009) Geodesy in Antarctica: a pilot study based on the TAMDEF GPS network, Victoria Land, Antarctica. PhD Thesis, Geodetic Science Department, The Ohio State University, Columbus, OHGoogle Scholar
  24. Vázquez GE, Brzezinska D (2005) Precipitable water vapor from GPS in Antarctica: opportunities from the TAMDEF GPS network, Victoria Land. Poster at the AGU Fall Meeting. San Francisco CAGoogle Scholar
  25. Vey S, Dietrich R (2008) Validation of the atmospheric water vapour content from NCEP using GPS observations over Antarctica. In: Capra A, Dietrich R (eds) Geodetic and geophysical observations in Antarctica–an overview in the IPY perspective. Springer, Berlin, pp 125–136CrossRefGoogle Scholar
  26. Vey S, Dietrich R, Johnsen K-P, Miao J, Heygster G (2004) Comparison of tropospheric water vapour over Antarctica derived from AMSU-data, ground-based GPS data and the NCEP/NCAR reanalysis. J Meteorol Soc Jpn 82:259–267CrossRefGoogle Scholar
  27. 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:D21101CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • G. Esteban Vázquez B
    • 1
    Email author
  • Dorota A. Grejner-Brzezinska
    • 2
  1. 1.Earth Science SchoolThe Autonomous University of SinaloaCuliacánMexico
  2. 2.Satellite Positioning and Inertial Navigation (SPIN) LaboratoryThe Ohio State UniversityColumbusUSA

Personalised recommendations