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This work aims to provide a comparison between three\uddimensional and four dimensional variational data assimilation methods\ud(3D-Var and 4D-Var) for a heavy rainfall case in central Italy. To evaluate\udthe impact of the assimilation of reflectivity and radial velocity acquired\udfrom Monte Midia Doppler radar into the Weather Research Forecasting (WRF)\udmodel, the quantitative precipitation forecast (QPF) is used.  The two methods are compared for a heavy rainfall event that occurred in\udcentral Italy on 14 September 2012 during the first Special Observation\udPeriod (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment)\udcampaign. This event, characterized by a deep low pressure system over the\udTyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions,\udwhere rainfall maxima reached more than 150 mm 24 h<sup>−1</sup>.  To identify the best QPF, nine experiments are performed using 3D-Var and\ud4D-Var data assimilation techniques. All simulations are compared in terms\udof rainfall forecast and precipitation measured by the gauges through three\udstatistical indicators: probability of detection (POD), critical success\udindex (CSI) and false alarm ratio (FAR). The assimilation of conventional\udobservations with 4D-Var method improves the QPF compared to 3D-Var. In\udaddition, the use of radar measurements in 4D-Var simulations enhances the\udperformances of statistical scores for higher rainfall thresholds

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