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An assessment of the quality of near-real time GNSS observations as a potential data source for meteorology

Dymarska N., Rohm W., Sierny J., Kapłon J., Kubik T., Kryza M., Jutarski J., Gierczak J., Kosierb R.

Meteorology Hydrology and Water Management. Research and Operational Applications

2017

Vol. 5, Iss. 1

3--13

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 ZTD validated against reference ZTD data: the International GNSS Service (IGS) from a precise 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.

Co pomierzy dron?

Lewandowski P., Gołuch P., Jóźków G., Borsuk E., Dymarska N., Rohm W., Podhorecki D., Siekanko B.

Geodeta : magazyn geoinformacyjny

2015

nr 8

14--21