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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
15 Jul 2016
Review status
This discussion paper has been under review for the journal Atmospheric Measurement Techniques (AMT). The revised manuscript was not accepted.
Evaluation of IWV from the numerical weather prediction WRF model with PPP GNSS processing for Bulgaria
Tzvetan Simeonov1,a, Dmitry Sidorov2,b, Felix Norman Teferle2, Georgi Milev3, and Guergana Guerova1 1Faculty of Physics, Sofia University "St. Kliment Ohridski", Bulgaria
2Université du Luxembourg, Luxembourg
3Space Research and Technology Center - Bulgarian Academy of Sciences, Bulgaria
anow at: GeoForschungsZentrum (GFZ) Potsdam, Germany
bnow at: Astronomical Institute University of Bern, Switzerland
Abstract. Global Navigation Satellite Systems (GNSS) meteorology is an established operational service providing hourly updated GNSS tropospheric products to the National Meteorologic Services (NMS) in Europe. In the last decade through the ground-based GNSS network densification and new processing strategies like Precise Point Positioning (PPP) it has become possible to obtain sub-hourly tropospheric products for monitoring severe weather events. In this work one year (January–December 2013) of sub-hourly GNSS tropospheric products (Zenith Total Delay) are computed using the PPP strategy for seven stations in Bulgaria. In order to take advantage of the sub-hourly GNSS data to derive Integrated Water Vapour (IWV) surface pressure and temperature with similar temporal resolution is required. As the surface observations are on 3 hourly basis the first step is to compare the surface pressure and temperature from numerical weather prediction model Weather Forecasting and Research (WRF) with observations at three synoptic stations in Bulgaria. The mean difference between the two data-sets for 1) surface pressure is less than 0.5 hPa and the correlation is over 0.989, 2) temperature the largest mean difference is 1.1 °C and the correlation coefficient is over 0.957 and 3) IWV mean difference is in range 0.1–1.1 mm. The evaluation of WRF on annual bases shows IWV underestimation between 0.5 and 1.5 mm at five stations and overestimation at Varna and Rozhen. Varna and Rozhen have also much smaller correlation 0.9 and 0.76. The study of the monthly IWV variation shows that at those locations the GNSS IWV has unexpected drop in April and March respectively. The reason for this drop is likely problems with station raw data. At the remaining 5 stations a very good agreement between GNSS and WRF is observed with high correlation during the cold part of 2013 i.e. March, October and December (0.95) and low correlation during the warm part of 2013 i.e. April to August (below 0.9). The diurnal cycle of the WRF model shows a dry bias in the range of 0.5-1.5 mm. Between 00 and 01 UTC the GNSS IWV tends to be underestimate IWV which is likely due to the processing window used. The precipitation efficiency from GNSS and WRF show very good agreement on monthly bases with a maximum in May-June and minimum in August–September. The annual precipitation efficiency in 2013 at Lovech and Burgas is about 6 %.

Citation: Simeonov, T., Sidorov, D., Teferle, F. N., Milev, G., and Guerova, G.: Evaluation of IWV from the numerical weather prediction WRF model with PPP GNSS processing for Bulgaria, Atmos. Meas. Tech. Discuss.,, 2016.
Tzvetan Simeonov et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
RC1: 'Review of manuscript AMT-2016-152', Anonymous Referee #1, 11 Aug 2016 Printer-friendly Version 
AC1: 'Reply to anonimous referee 1.', Tzvetan Simeonov, 18 Nov 2016 Printer-friendly Version Supplement 
RC2: 'initial review', Anonymous Referee #2, 07 Sep 2016 Printer-friendly Version 
AC2: 'Reply to anonimous referee 2.', Tzvetan Simeonov, 18 Nov 2016 Printer-friendly Version Supplement 
Tzvetan Simeonov et al.
Tzvetan Simeonov et al.


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