Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series - Publication - Bridge of Knowledge

Search

Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series

Abstract

Advanced processing of collected global navigation satellite systems (GNSS) observations allows for the estimation of zenith tropospheric delay (ZTD), which in turn can be converted to the integrated water vapour (IWV). The proper estimation of GNSS IWV can be affected by the adopted GNSS processing strategy. To verify which of its elements cause deterioration and which improve the estimated GNSS IWV, we conducted eight reprocessings of 20 years of GPS observations (01.1996–12.2015). In each of them, we applied a different mapping function, the zenith hydrostatic delay (ZHD) a priori value, the cut-off angle, software, and the positioning method. Obtained in such a way, the ZTD time series were converted to the IWV using the meteorological parameters sourced from the ERA-Interim. Then, based on them, the long-term parameters were estimated and compared to those obtained from the IWV derived from the radio sounding (RS) observations. In this paper, we analyzed long-term parameters such as IWV mean values, linear trends, and amplitudes of annual and semiannual oscillations. A comparative analysis showed, inter alia, that in terms of the investigation of the IWV linear trend the precise point positioning (PPP) method is characterized by higher accuracy than the differential one. It was also found that using the GPT2 model and the higher elevation mask brings benefits to the GNSS IWV linear trend estimation.

Citations

  • 1 8

    CrossRef

  • 0

    Web of Science

  • 1 9

    Scopus

Authors (4)

Cite as

Full text

download paper
downloaded 76 times
Publication version
Accepted or Published Version
License
Creative Commons: CC-BY open in new tab

Keywords

Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
Remote Sensing no. 10, edition 4, pages 1 - 25,
ISSN: 2072-4292
Language:
English
Publication year:
2018
Bibliographic description:
Baldysz Z., Nykiel G., Figurski M., Araszkiewicz A.: Assessment of the Impact of GNSS Processing Strategies on the Long-Term Parameters of 20 Years IWV Time Series// Remote Sensing. -Vol. 10, iss. 4 (2018), s.1-25
DOI:
Digital Object Identifier (open in new tab) 10.3390/rs10040496
Bibliography: test
  1. Baldysz, Z.; Nykiel, G.; Figurski, M.; Szafranek, K.; Kroszczynski, K. Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS DATA Processing. Acta Geophys. 2015, 63, 1103-1125. [CrossRef] open in new tab
  2. Baldysz, Z.; Nykiel, G.; Araszkiewicz, A.; Figurski, M.; Szafranek, K. Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring. Atmos. Meas. Tech. 2016, 9, 4861-4877. [CrossRef] open in new tab
  3. Hagemann, S.; Bengtsson, L. On the determination of atmospheric water vapor from GPS measurements. J. Geophys. Res. 2003, 108, 4678. [CrossRef] open in new tab
  4. Morland, J.; Collaud Coen, M.; Hocke, K.; Jeannet, P.; Matzler, C. Tropospheric water vapour above Switzerland over the last 12 years. Atmos. Chem. Phys. 2009, 9, 5975-5988. [CrossRef] open in new tab
  5. Guerova, G.; Jones, J.; Dousa, J.; Dick, G.; de Haan, S.; Pottiaux, E.; Bock, O.; Pacione, R.; Elgered, G.; Vedel, H.; et al. Review of the state of the art and future prospects of the ground-based gnss meteorology in Europe. Atmos. Meas. Tech. 2016, 9, 5385-5406. [CrossRef] open in new tab
  6. Yong, W.; Binyun, Y.; Debao, W.; Yanping, L. Zenith Tropospheric Delay from GPS monitoring climate change of Chinese Mainland, Education Technology and Training. In Proceedings of the 2008 International Workshop on Geoscience and Remote Sensing, ETT and GRS 2008, Shanghai, China, 21-22 December 2008. [CrossRef] open in new tab
  7. Bevis, M.; Businger, S.; Herring, T.; Rocken, C.; Anthes, R.; Ware, R. GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system. J. Geophys. Res. 1992, 97, 15787-15801. [CrossRef] open in new tab
  8. Wang, J.; Zhang, L. Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products. J. Geodesy 2009, 83, 209-217. [CrossRef] open in new tab
  9. Nilsson, T.; Elgered, G. Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data. J. Geophys. Res. 2008, 113, D19101. [CrossRef] open in new tab
  10. Ning, T.; Elgered, G.; Willen, U.; Johansson, J.M. Evaluation of the atmospheric water vapour content in a regional climate model using ground-based GPS measurements. J. Geophys. Res. 2013, 118, 329-339. [CrossRef] open in new tab
  11. Guerova, G.; Bettems, J.-M.; Brockmann, E.; Matzler, C. Assimilation of the GPS-derived integrated water vapouur (IWV) in the MeteoSwiss numerical weather prediction model. Phys. Chem. Earth Parts 2004, 29, 177-186. [CrossRef] open in new tab
  12. Nykiel, G.; Wolak, P.; Figurski, M. Atmospheric opacity estimation based on IWV derived from GNSS observations for VLBI applications. GPS Solut. 2018, 22, 9. [CrossRef] open in new tab
  13. Ning, T.; Wang, J.; Elgered, G.; Dick, G.; Wickert, J.; Bradke, M.; Sommer, M.; Sommer, M.; Querel, R.; Smale, D. The uncertainty of the atmospheric integrated water vapour estimated from GNSS observations. Atmos. Meas. Tech. 2016, 9, 79-92. [CrossRef] open in new tab
  14. Tregoning, P.; Herring, T.A. Impact of a priori zenith hydrostatic delay errors on GPS estimates of station heights and zenith total delays. Geophys. Res. Lett. 2006, 33. [CrossRef] open in new tab
  15. Boehm, J.; Heinkelmann, R. Schuh H Short note: A global model of pressure and temperature for geodetic applications. J. Geodesy 2007. [CrossRef] open in new tab
  16. Vey, S.; Dietrich, R.; Fritsche, M.; Rülke, A.; Rothacher, M.; Steigenberger, P. Influence of mapping functions parameters on global GPS network analyses: Comparison between NMF and IMF. Geophys. Res. Lett. 2006, 33, L01814. [CrossRef] open in new tab
  17. Niell, A.E. Global mapping functions for the atmospheric delay at radio wavelengths. J. Geophys. Res. 1996, 101, 3227-3246. [CrossRef] open in new tab
  18. Niell, A.E. Improved atmospheric mapping functions for VLBI and GPS. Earth Planet Space 2000, 52, 699-702. [CrossRef] open in new tab
  19. Steigenberger, P.; Boehm, J.; Tesmer, V. Comparison of GMF/GPT with VMF1/ECMWF and Implications for Atmospheric Loading. J. Geodesy 2009, 83, 943. [CrossRef] open in new tab
  20. Boehm, J.; Niell, A.; Tregoning, P.; Schuh, H. Global mapping function (GMF): A new empirical mapping function based on numerical weather model data. Geophys. Res. Lett. 2006, 33, L07304. [CrossRef] open in new tab
  21. Remote Sens. 2018, 10, 496 24 of 25 open in new tab
  22. Boehm, J.; Werl, B.; Schuh, H. Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. J. Geophys. Res. 2006, 111, B02406. [CrossRef] open in new tab
  23. Thomas, I.D.; King, M.A.; Clarke, P.J.; Penna, N.T. Precipitable water vapor estimates from homogeneously reprocessed GPS data: An intertechnique comparison in Antarctica. J. Geophys. Res. 2011, 116. [CrossRef] open in new tab
  24. Schmid, R.; Steigenberger, P.; Gendt, G.; Ge, M.; Rothacher, M. Generation of a consistent absolute phase center correction model for GPS receiver and satellite antennas. J. Geodesy 2007, 81, 781-798. [CrossRef] open in new tab
  25. Elósegui, P.; Davis, J.L.; Jaldehag, R.T.K.; Johansson, J.M.; Niell, A.E.; Shapiro, I.I. Geodesy using the global positioning system: The effects of signal scattering on estimates of site position. J. Geophys. Res. 1995, 100, 9921-9934. [CrossRef] open in new tab
  26. Vey, S.; Dietrich, R.; Fritsche, M.; Rülke, A.; Steigenberger, P.; Rothacher, M. On the homogeneity and interpretation of precipitable water time series derived from global GPS observations. J. Geophys. Res. 2009, 114, D10101. [CrossRef] open in new tab
  27. Dousa, J.; Vaclavovic, P.; Elias, M. Tropospheric products of the second GOP European GNSS reproessing (1996-2014). Atmos. Meas. Tech. 2017, 10, 3589-3607. [CrossRef] open in new tab
  28. Bruyninx, C.; Habrich, H.; Söhne, W.; Kenyeres, A.; Stangl, G.; Völksen, C. Enhancement of the EUREF Permanent Network Services and Products. Geodesy Planet Earth 2012, 136, 27-35. [CrossRef] open in new tab
  29. Ning, T.; Elgered, G. Trends in Atmopsheric Water Vapour Content From Ground-Based GPS: The Impact of the Elevation Cutoff Angle. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2012, 5. [CrossRef] open in new tab
  30. Dee, D.P.; Uppala, S.M.; Simmons, A.J.; Berrisford, P.; Poli, P.; Kobayashi, S.; Andrae, U.; Balmaseda, M.A.; Balsamo, G.; Bauer, P.; et al. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 2011, 137, 553-597. [CrossRef] open in new tab
  31. Dach, R.; Lutz, S.; Walser, P.; Fridez, P. Bernese GNSS Software Version 5.2; User Manual; Astronomical Institute, University of Bern: Bern, Germany, 2015; ISBN 978-3-906813-05-9.
  32. King, R.; Herring, T.; Mccluscy, S. Documentation for the GAMIT GPS Analysis Software 10.4; Technology Report; Massachusetts Institute of Technology: Cambridge, MA, USA, 2010. open in new tab
  33. Davis, J.L.; Herring, T.A.; Shapiro, I.I.; Rogers, E.E.; Elgered, G. Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length. Radio Sci. 1985, 20, 1593-1607. [CrossRef] open in new tab
  34. Rüger, J.M. Refractive Index Formulae for Radio Waves. In Proceedings of the FIG XXII International Congress, Washington, DC, USA, 19-26 April 2002. open in new tab
  35. Saastamoinen, J. Atmospheric correction for the troposphere and stratosphere in ranging satellites. In The Use of Artificial Satellites for Geodesy, Geophysical Monography No. 15; American Geophysical Union: Washington, DC, USA, 1972; pp. 247-251. open in new tab
  36. Bevis, M.; Businger, S.; Chiswell, S.; Herring, T.A.; Anthes, R.A.; Rocken, C.; Ware, R.H. GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water. J. Appl. Meteorol. Climatol. 1994, 33, 379-386. [CrossRef] open in new tab
  37. Mendes, V.B. Modeling the neutral-atmospheric propagation delay in radiometric space techniques. UNB Geodesy and Geomatics Engineering Technical Report, No. 199. Available online: http://www2.unb.ca/gge/ Pubs/TR199.pdf (accessed on 1 March 2018).
  38. Solbrig, P. Untersuchungen Uber Die Nutzung Numerischerwettermodelle Zurwasserdampf Bestimmungmit Hilfe des Global Positioning System. Ph.D. Thesis, Institute of Geology and Navigation, University FAF Munich, Neubiberg, Germany, 2000.
  39. Schueler, T.; Posfay, A.; Hein, G.W.; Biberger, R. A global analysis of the mean atmospheric temperature for GPS water vapour estimation. C5: Atmospheric effects. In Proceedings of the IONGPS2001-14th International Technical Meeting of Satellite Division of the Institute of Navigation, Salt Lake City, UT, USA, 11-14 September 2001.
  40. Herring, T.A. Modeling Atmospheric Delays in the Analysis of Space Geodetic Data. In Proceedings of the Refraction of Transatmospheric Signals in Geodesy, Delft, The Netherlands, 19-22 March 1992; Geod.: The Hague, The Netherlands, 1992. open in new tab
  41. Chen, G.; Herring, A. Effects of atmospheric azimuthal asymmetry on the analysis of space geodetic data. J. Geophys. Res. 1997, 102, 20489-20502. [CrossRef] open in new tab
  42. Uppala, S.M.; KÅllberg, P.W.; Simmons, A.J.; Andrae, U.; Bechtold, V.D.C.; Fiorino, M.; Gibson, J.K.; Haseler, J.; Hernandez, A.; Kelly, G.A.; et al. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 2005, 131, 2961-3012. [CrossRef] open in new tab
  43. Remote Sens. 2018, 10, 496 25 of 25 open in new tab
  44. Pacione, R.; Araszkiewicz, A.; Brockmann, E.; Dousa, J. EPN-Repro2: A reference GNSS tropospheric data set over Europe. Atmos. Meas. Tech. 2017, 10, 1689-1705. [CrossRef] open in new tab
  45. Lagler, K.; Schindelegger, M.; Bohm, J.; Krasna, H.; Nillson, T. GPT2: Empirical slant delay model for radio space geodetic techniques. Geophys. Res. Lett. 2013, 40, 1069-1079. [CrossRef] [PubMed] open in new tab
  46. Steigenberger, P.; Lutz, S.; Dach, R.; Schaer, S.; Jäggi, A. CODE Repro2 Product Series for the IGS; Astronomical Institut, University of Bern: Bern, Germany, 2016.
  47. Hernández-Pajares, M.; Juan, J.M.; Sanz, J.; Orús, R. Second-order ionospheric term in GPS: Implementation and impact on geodetic estimates. J. Geophys. Res. 2007, 112, B08417. [CrossRef] open in new tab
  48. Petrie, E.J.; King Moore, P.; Lavallee, D.A. Higher-order ionospheric effects on the GPS reference frame and velocities. J. Geophys. Res. 2010, 115, B03417. [CrossRef] open in new tab
  49. Lomb, N. Least-squares frequency analysis of unequally spaced data. Astrophys. Space Sci. 1976, 39, 448-462. [CrossRef] open in new tab
  50. Klein Baltink, H.; van der Marel, H.; Hoeven, A.G.H. Integrated atmospheric water vapor estimates from a regional GPS network. J. Geophys. Res. 2002, 107. [CrossRef] open in new tab
  51. Wang, J.; Zhang, L.; Dai, A.; Van Hove, T.; Van Baelen, J. A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J. Geophys. Res. 2007, 112, D11107. [CrossRef] open in new tab
  52. Kirkland, E.J. Bilinear Interpolation. In Advanced Computing in Electron Microscopy; Springer: Boston, MA, USA, 2010. open in new tab
  53. Bock, O.; Willis, P.; Wang, J.; Mears, C. A high-quality, homogenized, global, long-term (1993-2008) DORIS precipitable water data set for climate monitoring and model verification. J. Geophys. Res. Atmos. 2014, 119, 7209-7230. [CrossRef] open in new tab
  54. Rothacher, M. Estimation of Station Heights with GPS. Int. Assoc. Geodesy Symp. 2002, 124, 81-90. [CrossRef] open in new tab
  55. Fund, F.; Morel, L.; Mocquet, A.; Boehm, J. Assessment of ECMWF-derived tropospheric delay models within the EUREF Permanent Network. GPS Solut. 2010, 15, 39-48. [CrossRef] open in new tab
  56. Zhai, P.; Eskride, R.E. Analyses of Inhomogeneities in Radiosonde Temperature and Humidity Time Series. J. Clim. 1996, 9, 884-896. [CrossRef] open in new tab
Verified by:
Gdańsk University of Technology

seen 180 times

Recommended for you

Meta Tags