DORIS Tropospheric Estimation at IGN: Current Strategies, GPS Intercomparisons and Perspectives
We reprocessed DORIS for all of 2010, using the latest model and strategy improvements to estimate Zenith Tropospheric Delays (ZTDs), as well as tropospheric horizontal gradients for about 60 ground stations. These results were compared to recent GPS-based estimates obtained at the Jet Propulsion Laboratory (JPL). After discussing some of the data processing options and current limitations of the DORIS data, we show that the DORIS-GPS comparisons possess a high degree of correlation (average being 0.97), and that total zenith delay estimates from the two techniques agree at the 3 mm level on average with 8.6 mm total RMS, with better results being obtained when a 5° elevation cutoff angle is used for DORIS. While these DORIS results cannot be used for real-time weather prediction, they could contribute to scientific investigations for climatology, thanks to the homogenous tracking network of the DORIS system, as well as the long-term history of the observation time series.
KeywordsDORIS GPS Horizontal tropospheric gradients Zenith tropospheric delay
Part of this work was supported by the Centre National d’Etudes Spatiales (CNES). Part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Navigation, under a contract with the National Aeronautics and Space Administration. It is based on observations with DORIS embarked on SPOTs, TOPEX/Poseidon, Envisat, Jason-2 and Cryosat-2 satellites. This paper is IPGP contribution number 3286.
- 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) (art. B09401)Google Scholar
- Boehm 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(7)Google Scholar
- Byun SH, Bar-Sever YE (2009) A new type of troposphere zenith path delay product of the International GNSS service. J Geod 83(3–4):367–373Google Scholar
- Perfettini H, Avouac JP, Ruegg JC (2005) Geodetic displacements and aftershocks following the 2001 Mw = 8.4 Peru earthquake, implications for the mechanics of the earthquake cycle along subduction zones. J Geophys Res 110(B9)Google Scholar
- 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 Geophys Res 81:781–798Google Scholar
- Snadjrova K, Boehm J, Willis P, Haas R, Schuh H (2006) Multi-technique comparison of tropospheric zenith delays derived from CONT02 campaign. J Geod 79(10–11):613–623Google Scholar
- Tregoning P, Herring TA (2006) Impact of a priori zenith hydrostatic delay errors on GPS estimates of station heights and zenith total delays. Geophys Res Lett 33(23), art. L23303Google Scholar
- Vigny C, Socquet A, Peyrat S, Ruegg JC, Metois M, Madariaga R, Morvan S, Lancieri M, Lacassin R, Campos J, Carrizo D, Bejar-Pizarro M, Barrientos S, Armijo R, Aranda C, Valderas-Bermejo MC, Otrega I, Bondoux F, Baize S, Lyon-Caen H, Pavez A, Vilotte JP, Bevis M, Brooks B, Smalley R, Parra H, Baez JC, Nlanco M, Cimbaro S, Kendrick E (2011) The 2010 Mw 8.8 Maule megathrust earthquake of central Chile, monitored by GPS. Science 332(6036):1417–1421CrossRefGoogle Scholar
- Willis P, Bar-Sever YE, Bock O (2012) Estimating horizontal tropospheric gradients in DORIS data processing, preliminary results. IAG Symp 136:1011–1017Google Scholar