Articles | Volume 23, issue 11
https://doi.org/10.5194/nhess-23-3319-2023
https://doi.org/10.5194/nhess-23-3319-2023
Research article
 | 
01 Nov 2023
Research article |  | 01 Nov 2023

The impact of global navigation satellite system (GNSS) zenith total delay data assimilation on the short-term precipitable water vapor and precipitation forecast over Italy using the Weather Research and Forecasting (WRF) model

Rosa Claudia Torcasio, Alessandra Mascitelli, Eugenio Realini, Stefano Barindelli, Giulio Tagliaferro, Silvia Puca, Stefano Dietrich, and Stefano Federico

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Cited articles

Barker, D. M., Huang, W., Guo, Y. R., and Xiao, Q. N.: A Three-Dimensional (3DVAR) Data Assimilation System For Use With MM5: Implementation and Initial Results, Mon. Weather Rev., 132, 897–914, https://doi.org/10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2, 2004. 
Barker, D., Huang, X.-Y., Liu, Z., Auligné, T. , Zhang, X., Rugg, S., Ajjaji, R., Bourgeois, A., Bray, J., Chen, Y., 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, https://doi.org/10.1175/BAMS-D-11-00167.1, 2012. 
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, https://doi.org/10.1175/MWR-D-15-0242.1, 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, https://doi.org/10.1175/MWR-D-11-00156.1, 2012. 
Bennitt, G. V., Johnson, H. R., Weston, P. P., Jones, J., and Pottiaux, E.: An assessment of ground-based GNSS Zenith Total Delay observation errors and their correlations using the Met Office UKV model, Q. J. Roy. Meteor. Soc., 143, 2436–2447, https://doi.org/10.1002/qj.3097, 2017. 
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This work shows how local observations can improve precipitation forecasting for severe weather events. The improvement lasts for at least 6 h of forecast.
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