Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia

This paper first analyses the precision of tropospheric zenith total delay (ZTD) values obtained from the empirical models GPT2 and GPT2w, and the numerical weather models (NWM) from Australian Bureau of Meteorology (BoM), and European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of...

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Main Authors: Deo, M., El-Mowafy, Ahmed
Format: Journal Article
Published: Taylor & Francis Asia Pacific (Singapore) 2019
Online Access:http://hdl.handle.net/20.500.11937/68729
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author Deo, M.
El-Mowafy, Ahmed
author_facet Deo, M.
El-Mowafy, Ahmed
author_sort Deo, M.
building Curtin Institutional Repository
collection Online Access
description This paper first analyses the precision of tropospheric zenith total delay (ZTD) values obtained from the empirical models GPT2 and GPT2w, and the numerical weather models (NWM) from Australian Bureau of Meteorology (BoM), and European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of these ZTD values with IGS ZTD product at four sites showed that the ZTDs from NWM datasets were more precise than the empirical models. The ZTD from BoM data gave the best results, with mean errors between -0.034 m to 0.029 m and standard deviations better than 0.045 m. Next, the PPP convergence time and achievable accuracy using the BoM NWM constrained ZTD by including them as pseudo-observations with a pre-set precision was compared to the case of estimating the troposphere. This resulted in a slight enhancement in convergence time, and improvements in vertical positioning accuracy was found at all the four tested sites at 0.036–0.058 m after 2 min, 0.023–0.038 m after 3 min and 0.013–0.020 m after 5 min of PPP initialisation.
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spelling curtin-20.500.11937-687292020-01-17T05:19:48Z Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia Deo, M. El-Mowafy, Ahmed This paper first analyses the precision of tropospheric zenith total delay (ZTD) values obtained from the empirical models GPT2 and GPT2w, and the numerical weather models (NWM) from Australian Bureau of Meteorology (BoM), and European Centre for Medium-Range Weather Forecasts (ECMWF). Comparison of these ZTD values with IGS ZTD product at four sites showed that the ZTDs from NWM datasets were more precise than the empirical models. The ZTD from BoM data gave the best results, with mean errors between -0.034 m to 0.029 m and standard deviations better than 0.045 m. Next, the PPP convergence time and achievable accuracy using the BoM NWM constrained ZTD by including them as pseudo-observations with a pre-set precision was compared to the case of estimating the troposphere. This resulted in a slight enhancement in convergence time, and improvements in vertical positioning accuracy was found at all the four tested sites at 0.036–0.058 m after 2 min, 0.023–0.038 m after 3 min and 0.013–0.020 m after 5 min of PPP initialisation. 2019 Journal Article http://hdl.handle.net/20.500.11937/68729 10.1080/14498596.2018.1472046 Taylor & Francis Asia Pacific (Singapore) fulltext
spellingShingle Deo, M.
El-Mowafy, Ahmed
Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title_full Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title_fullStr Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title_full_unstemmed Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title_short Comparison of advanced troposphere models for aiding reduction of PPP convergence time in Australia
title_sort comparison of advanced troposphere models for aiding reduction of ppp convergence time in australia
url http://hdl.handle.net/20.500.11937/68729