Near Real Time Estimation of Integrated Water Vapour from GNSS Observations in Hungary
Meteorological products derived from Global Navigation Satellite Systems (GNSS) observations have been routinely used for numerical weather prediction in several regions of the world. Hungary would like to join these activities exploiting meteorological usage of the dense GNSS CORS (Continuously Operating Reference Station) network operated by the Institute of Geodesy, Cartography and Remote Sensing for positioning applications.
This paper introduces the near real-time processing system of GNSS observations for meteorological purposes in Hungary. The hourly observations of 35 Hungarian permanent GNSS CORSs are processed. This network is extended beyond the country with about 50 stations covering Eastern and Central Europe. The data analysis is being done using the Bernese V5.0 GPS data processing software. The Hungarian CORS network has an average baseline length of 60 km, thus the precipitable water vapour (PW) can be estimated with a high spatial resolution.
The estimation of the PW from the zenith wet delay (ZWD) is carried out in near real-time. Firstly, the zenith hydrostatic delays (ZHD) are subtracted from the total delays. The wet delays are then scaled to precipitable water vapour values.
The GNSS derived PW values were validated using radiosonde observations over Central Europe using the observations of a 47-day-long period (April 14–May 31, 2011). The results showed that the estimated PW values agree with radiosonde observations at the level of ±1.5 mm in terms of standard deviation. In this comparison a bias of +1.0 mm was observed. Following the validation phase, our analysis will be connected to the continental E-GVAP project (GNSS Water Vapour Programme of the Network of European Meteorological Services, EUMETNET).
KeywordsCORS GNSS meteorology Integrated water vapour Numerical weather prediction Radiosounding
The authors acknowledge the kindly support of the Hungarian Research Fund under the contract number K-83909. This study is linked with the “Development of quality-oriented and harmonized R + D + I strategy and functional model at BME” project. This project is supported by the New Hungary Development Plan (Project ID: TÁMOP-4.2.1/B-09/1/KMR-2010-0002). The authors would like to thank the comments of the three anonymous reviewers, their help to improve the quality of this paper is highly appreciated.
- Aune B, Strabala KI, Lindstrom S, Huang A (2008) The direct broadcast version of the CIMSS regional assimilation system for global users. In: International EOS/NPP direct readout meeting 2008, Bangkok, 31 March–4 April 2008. http://dbmeeting.sci.gsfc.nasa.gov/files2008/DBCRAS_DB2008.ppt
- Bosy J, Rohm W, Sierny J (2010) The concept of near real time atmosphere model based on the GNSS and meteorological data from the ASG-EUPOS reference stations. Acta Geodyn Geomater 7:253–263Google Scholar
- Dach R, Hugentobler U, Fridez, P, Meindl M (2007) Bernese GPS software, version 5.0. Astronomical Institute, University of BernGoogle Scholar
- Igondova M, Cibulka D (2010) Precipitable water vapour and zenith total delay time series and models over Slovakia and vicinity. Contrib Geophys Geod 40:299–312Google Scholar
- International Standard Organization (1975) Standard atmosphere. ISO 2533:1975Google Scholar
- Nash J, Oakley T, Vömel H, Wei L (2011) WMO intercomparison of high quality radiosonde systems. WMO instruments and observing methods, report no. 107. p. 248Google Scholar
- Pidwirny M (2006) The hydrologic cycle. In: Fundamentals of physical geography, 2nd edn (June 8, 2012). http://www.physicalgeography.net/fundamentals/8b.html
- Rózsa S, Weidinger T, Gyöngyösi AZ, Kenyeres A (2012) The role of the GNSS infrastructure in the monitoring of atmospheric water vapor. Időjárás, Q J Hung Meteorol Serv 116(1):1–20Google Scholar
- Vedel H (2006) E-GVAP meteorology and geodesy synergy. Presented at the EUREF symposium held in Vienna, 1–3 June 2005. http://egvap.dmi.dk/doc/presentations/egvap+euref.pdf
- World Meteorological Organization (WMO) (2008) Guide to meteorological instrument and methods of observations. WMO-No. 8, p 681Google Scholar