Journal cover Journal topic
Advances in Science and Research The open-access proceedings of the European Meteorological Society (EMS)

Journal metrics

  • h5-index value: 12 h5-index 12
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
Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy
Vincenzo Mazzarella1,2, Ida Maiello3,2, Vincenzo Capozzi1, Giorgio Budillon1, and Rossella Ferretti2 1Department of Science and Technology, University of Naples “Parthenope”, Naples, Italy
2Centre of Excellence CETEMPS, Department of Physical and Chemical Sciences, University of L'Aquila, L'Aquila, Italy
3Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy
Abstract. 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. To evaluate the impact of the assimilation of reflectivity and radial velocity acquired from Monte Midia Doppler radar into the Weather Research Forecasting (WRF) model, the quantitative precipitation forecast (QPF) is used.

The two methods are compared for a heavy rainfall event that occurred in central Italy on 14 September 2012 during the first Special Observation Period (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment) campaign. This event, characterized by a deep low pressure system over the Tyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions, where rainfall maxima reached more than 150 mm 24 h−1.

To identify the best QPF, nine experiments are performed using 3D-Var and 4D-Var data assimilation techniques. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators: probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR). The assimilation of conventional observations with 4D-Var method improves the QPF compared to 3D-Var. In addition, the use of radar measurements in 4D-Var simulations enhances the performances of statistical scores for higher rainfall thresholds.


Citation: Mazzarella, V., Maiello, I., Capozzi, V., Budillon, G., and Ferretti, R.: Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy, Adv. Sci. Res., 14, 271-278, https://doi.org/10.5194/asr-14-271-2017, 2017.
Publications Copernicus
Download
Short summary
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...
Share