All Supporting Information may be found in the online version of this article.
GPT2: Empirical slant delay model for radio space geodetic techniques
Article first published online: 22 MAR 2013
©2013. American Geophysical Union. All Rights Reserved.
Geophysical Research Letters
Volume 40, Issue 6, pages 1069–1073, 28 March 2013
How to Cite
2013), GPT2: Empirical slant delay model for radio space geodetic techniques, Geophys. Res. Lett., 40, 1069–1073, doi:10.1002/grl.50288., , , , and (
- Issue published online: 27 APR 2013
- Article first published online: 22 MAR 2013
- Accepted manuscript online: 4 MAR 2013 09:41AM EST
- Manuscript Accepted: 23 FEB 2013
- Manuscript Revised: 18 FEB 2013
- Manuscript Received: 11 JAN 2013
- Austrian Science Fund (FWF). Grant Numbers: P20902-N10, P23143-N21
- Tropospheric delay;
- Tropospheric mapping function
 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.