REVIEW PAPER
An assessment of the quality of near-real time GNSS observations as a potential data source for meteorology
 
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1
Wrocław University of Environmental and Life Sciences, Institute of Geodesy and Geoinformatics, Grunwaldzka 53, 50-357 Wrocław, Poland
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Wroclaw University of Environmental and Life Sciences, Institute of Geodesy and Geoinformatics, Grunwaldzka 53, 50-357 Wroclaw, Poland
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Wrocław University of Science and Technology, Department of Computer Engineering, Faculty of Electronics, Poland
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University of Wrocław, Department of Climatology and Atmosphere Protection, Poland
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Institute of Meteorology and Water Management, Parkowa 30, 51- 616 Wrocław, Poland
CORRESPONDING AUTHOR
Natalia Dymarska   

Wrocław University of Environmental and Life Sciences, Institute of Geodesy and Geoinformatics, Grunwaldzka 53, 50-357 Wrocław, Poland, Grunwaldzka, 53, 50-357 Wrocław, Poland
Publication date: 2017-01-18
 
Meteorol. Hydrol. Water Manage. 2017;5(1):3–13
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ABSTRACT
The Global Navigation Satellite System (GNSS) can be used to determine accurate and high-frequency atmospheric parameters, such as Zenith Total Delay (ZTD) or Precipitable Water Vapour (PW), in all-weather conditions. These parameters are often assimilated into Numerical Weather Prediction (NWP) models and used for nowcasting services and climate studies. The effective usage of the ZTDs obtained from a ground-based GNSS receiver’s network in a NWP could fill the gap of insufficient atmospheric water vapour state information. The supply of such information with a latency acceptable for NWP assimilation schemes requires special measures in the GNSS data processing, quality control and distribution. This study is a detailed description of the joint effort of three institutions – Wrocław University of Environmental and Life Sciences, Wrocław University, and the Institute of Meteorology and Water Management – to provide accurate and timely GNSS-based meteorological information. This paper presents accuracy analyses of near real-time GNSS solution, Weather Research and Forecasting (WRF) model, and radiosonde profiles. Data quality statistics were performed for five GNSS stations in Poland over a time span of almost a year (2015). The comparison of near real-time ZTD and IGS shows a mean ZTD station bias of less than 3 mm with a related standard deviation of less than 10 mm. The bias between near real-time ZTD and WRF ZTD is in the range of 5 – 11 mm and the overall standard deviation is slightly higher than 10 mm. Finally, the comparison of the investigated ZTD against radiosonde showed an average bias at a level of 10 mm, whereas the standard deviation does not exceed 14 mm. Considering the data quality, we assess that the NRT ZTD can be assimilated into NWP models.