Improved Troposphere Blind Models Based on Numerical Weather Data

The troposphere blind model RTCA MOPS is the minimum operational performance standard for global positioning systems. With a standard deviation of 2.3% of the ZTD, it enables us to mitigate the main part of the tropospheric effect on GNSS signals. Nevertheless, the comparison of RTCA MOPS with modern troposphere models like the ESA model or GPT2 shows the limitation of RTCA MOPS and points out the potential of modern troposphere blind models based on climatological series derived from numerical weather data. The ESA model profits from a more advanced wet delay model and a higher spatial resolution. GPT2 shows the smallest mean bias on surface level in comparison to ray-tracing and IGS data and profits from additional mapping function coefficients – especially if the user is interested in tropospheric delay at low elevation angles. A revision of GPT2 - called GPT2w - combines the benefits of both aforementioned models. Copyright © 2014 Institute of Navigation.

[1]  T. Nilsson,et al.  GPT2: Empirical slant delay model for radio space geodetic techniques , 2013, Geophysical research letters.

[2]  J. Saastamoinen.  Atmospheric Correction for the Troposphere and Stratosphere in Radio Ranging Satellites , 2013 .

[3]  A. Niell.  Global mapping functions for the atmosphere delay at radio wavelengths , 1996 .

[4]  P. Jones,et al.  Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850 , 2006 .

[5]  Ana Karabatic,et al.  Near real-time estimation of tropospheric water vapour content from ground based GNSS data and its potential contribution to weather now-casting in Austria , 2011 .

[6]  H. Schuh,et al.  Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data , 2006 .

[7]  Jurgen Neuberg,et al.  Unprecedented pressure increase in deep magma reservoir triggered by lava‐dome collapse , 2006 .

[8]  H. Schuh,et al.  Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium‐Range Weather Forecasts operational analysis data , 2006 .

[9]  Rtca . Sc,et al.  Minimum operational performance standards for GPS local area augmentation system airborne equipment , 2000 .

[10]  H. Schuh,et al.  Short Note: A global model of pressure and temperature for geodetic applications , 2007 .

[11]  Harald Schuh,et al.  Ray‐traced tropospheric delays in VLBI analysis , 2012 .

[12]  Jan Askne,et al.  Estimation of tropospheric delay for microwaves from surface weather data , 1987 .

[13]  H. D. Black,et al.  Correcting satellite Doppler data for tropospheric effects , 1984 .