A multi hazard extreme weather event in Southern Italy: Assessment and sensitivity tests of the WRF model

Abstract

A deep convective system affected the southern Mediterranean on 3–4 December 2022 causing heavy rains and wind gusts over three Italian regions (Sicily, Calabria, and Apulia) and a tornado in Calabria. We study the forecast sensitivity of this multi-hazard weather event to different physical parameterizations and configuration settings of the WRF (Weather Research and Forecasting) model, used at convection permitting horizontal resolution; in particular, we performed sensitivity tests on the role of the initial and boundary conditions, on the Sea Surface Temperature (SST), on the model horizontal resolution and on the cumulus parameterization. Moreover, a 6 h rapid update data assimilation analysis (3DVAR)/forecast cycle was investigated to further study the short-term forecast capabilities of the modeling system. Most of the WRF configurations are able to well simulate the characteristics of the weather system, even if there are differences among the configurations, especially at the local scale, which causes differences in forecast performances. We found that the quality of the forecast is sensitive to the initial and boundary conditions with the best members having a probability of detection around 30–40 % for rainfall intensities of 40–50 mm/6 h. Most of the forecasts decrease their performance for larger precipitation thresholds, with few exceptions. Specifically, we found that increasing the horizontal resolution was beneficial for the case study as the probability of detection remains larger than 0.2 for rainfall thresholds larger than 60 mm/6 h and up to 100 mm/6 h. In addition, the forecast with lightning and radar reflectivity data assimilation has a probability of detection larger than 0.4 for the same intense thresholds; in both cases false alarms are not increased. For the tornado simulation, no improvement was found adopting 3DVAR. A possible forecasting strategy for severe weather events is outlined.