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Advances in Science and Research Contributions in Applied Meteorology and Climatology
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Volume 14
Adv. Sci. Res., 14, 271–278, 2017
https://doi.org/10.5194/asr-14-271-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Adv. Sci. Res., 14, 271–278, 2017
https://doi.org/10.5194/asr-14-271-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  11 Aug 2017

11 Aug 2017

Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy

Vincenzo Mazzarella et al.
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Revised manuscript not accepted
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Cited articles  
Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A., and Xiao, Q.: A Three-Dimensional Variational (3DVAR) data assimilation system for use with MM5: Implementation and initial results, Mon. Weather Rev., 132, 897–914, 2004.
Brown, B. G., Gotway, J. H., Bullock, R., Gilleland, E., Fowler, T., Ahijevych, D., and Jensen, T.: The Model Evaluation Tools (MET): Community tools for forecast evaluation, in: Preprints, 25th Conf. on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Phoenix, AZ, Amer. Meteor. Soc. A, 9, 6, 2009.
Chu, K., Xiao, Q., and Liu, C.: Experiments of the WRF three-/four-dimensional variational (3/4DVAR) data assimilation in the forecasting of Antarctic cyclones, Meteorol. Atmos. Phys., 120, 145–156, https://doi.org/10.1007/s00703-013-0243-y, 2013.
Davis, C., Brown, B., and Bullock, R.: Object-based verification of precipitation forecasts. Part I: methodology and application to mesoscale rain areas, Mon. Weather Rev., 134, 1772–1784, 2006.
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This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. Nine simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators. The assimilation of conventional observations with 4D-Var method improves the quantitative precipitation forecast (QPF) compared to 3D-Var.
This work aims to provide a comparison between three dimensional and four dimensional...
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