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GPT2: empirical slant delay model for radio space geodetic techniques
Verfasser / Verfasserin Lagler, K. ; Schindelegger, Michael ; Böhm, Johannes In der Gemeinsamen Normdatei der DNB nachschlagen ; Krásná, Hana ; Nilsson, T.
Erschienen in
Geophysical research letters, 2013, Jg. 40, H. 6, S. 1069-1073
Published version
DokumenttypAufsatz in einer Zeitschrift
URNurn:nbn:at:at-ubtuw:3-2394 Persistent Identifier (URN)
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GPT2: empirical slant delay model for radio space geodetic techniques [0.43 mb]
Zusammenfassung (Englisch)

Up to now, state-of-the-art empirical slant delay modeling for processing observations from radio space geodetic techniques has been provided by a combination of two empirical models. These are GPT (Global Pressure and Temperature) and GMF (Global Mapping Function), both operating on the basis of long-term averages of surface values from numerical weather models. Weaknesses in GPT/GMF, specifically their limited spatial and temporal variability, are largely eradicated by a new, combined model GPT2, which provides pressure, temperature, lapse rate, water vapor pressure, and mapping function coefficients at any site, resting upon a global 5 grid of mean values, annual, and semi-annual variations in all parameters. Built on ERA-Interim data, GPT2 brings forth improved empirical slant delays for geophysical studies. Compared to GPT/GMF, GPT2 yields a 40% reduction of annual and semi-annual amplitude differences in station heights with respect to a solution based on instantaneous local pressure values and the Vienna mapping functions 1, as shown with a series of global VLBI (Very Long Baseline Interferometry) solutions.

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