67100 Coppito AQ
The aim of the modern data assimilation systems is to provide the best estimate of the initial conditions, a requirement for an accurate weather forecast, through the use of huge amount of data acquired in situ or by remote-sensing. In the last years, the classical assimilation schemes, such as optimum interpolation (OI) or successive correction method (SCM), have been replaced by modern techniques with variational approach, 3D-Var and 4D-Var. The latters determine the best estimate of the atmospheric state at initial time, through the minimization of a cost function, which reduces the gap between observations and the trajectory forecasted by the model. 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 quantitative precipitation forecasts (QPF), reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through a traditional approach and an object-based method.
Vincenzo Mazzarella is a PhD student in the Department of Science and Technology of the University of Naples “Parthenope”. His research interest is focused on the assimilation of weather radar data and conventional observations from the Global Telecommunication System (GTS) in order to improve the quantitative precipitation forecast (QPF).