and Water Management
and Water Management
Research and Operational ApplicationsISSN: 2299-3835 eISSN: 2353-5652
Meteorology Hydrology and Water Management
An assessment of the quality of near-real time GNSS observations as a potential data source for meteorology
Natalia Dymarska, Witold Rohm, Jan Sierny, Jan Kapłon, Tomasz Kubik, Maciej Kryza, Jerzy Jutarski, Jacek Gierczak, Ryszard Kosierb
Meteorol. Hydrol. Water Manage. (2017) vol. 5; (1): 3-13
Online publication date: 2017-01-18
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.
Keywords:ZTD estimation, data validation, GNSS meteorology
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