Articles | Volume 12, issue 1
Atmos. Meas. Tech., 12, 345–361, 2019

Special issue: Advanced Global Navigation Satellite Systems tropospheric...

Atmos. Meas. Tech., 12, 345–361, 2019

Research article 18 Jan 2019

Research article | 18 Jan 2019

4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF

Witold Rohm et al.

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Revised manuscript not accepted
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Cited articles

Barker, D., Huang, X. Y., Liu, Z., Auligné, T., Zhang, X., Rugg, S., Ajjaji, R., Bourgeois, A., Bray, J., Chen, Y. E., Demirtas, M., Guo, Y. R., Henderson, T., Huang, W., Lin, H. C., Michalakes, J., Rizvi, S., and Zhang, X.: The weather research and forecasting model's community variational/ensemble data assimilation system: WRFDA, B. Am. Meteorol. Soc., 93, 831–843,, 2012. 
Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A. J., and Xiao, Q. N.: A Three-Dimensional Variational Data Assimilation System for MM5: Implementation and Initial Results, Mon. Weather Rev., 132, 897–914,<0897:ATVDAS>2.0.CO;2, 2004. 
Benjamin, S. G., Brown, J. M., Brundage, K. J., Dévényi, D., Grell, G. A., Kim, D., Schwartz, B. E., Smirnova, T. G., Smith, T. L., Weygandt, S. S., and Manikin, G. S.: RUC20 – The 20-km version of the Rapid Update Cycle, NWS Tech. Proced. Bull., 490, 1–30, available at: (last access: 17 August 2018), 2002. 
Benjamin, S. G., Weygandt, S. S., Brown, J. M., Hu, M., Alexander, C. R., Smirnova, T. G., Olson, J. B., James, E. P., Dowell, D. C., Grell, G. A., Lin, H., Peckham, S. E., Smith, T. L., Moninger, W. R., Kenyon, J. S., and Manikin, G. S.: A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh, Mon. Weather Rev., 144, 1669–1694,, 2016. 
Bennitt, G. V. and Jupp, A.: Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models, Mon. Weather Rev., 140, 2706–2719,, 2012. 
Short summary
Assimilation of satellite navigation data into a popular weather model is yet another example of how to turn non-meteorological data into valuable information about the current state of the troposphere. Results show that observations from ground-based GPS receivers can improve humidity and rain forecasts in most severe weather events. It is another reason to extend the adoption of GPS data into weather forecasting across Europe.