Assessing the Impact of Physical Configuration and Lead Time on WRF Forecasting of an Extreme Wind Event

The central region of Argentina is known to be a source of some most extreme weather events in the world, which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts. This may cause severe property damage and even loss of human life. Nevertheless, there is a lack of studies that evaluate the performance of the numerical weather prediction (NWP) models such as weather research and forecasting (WRF) model in anticipating this type of weather in the region. This study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer (PBL) and microphysics parameterization schemes under varied lead times in predicting an extreme wind event (gusts > 30 m s⁻¹) in Central Argentina. The results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme event. It is found that no single combination outperforms the others, although there is a slight tendency for Combination A, which utilizes the Mellor–Yamada–Janjic (MYJ) parameterization for the PBL and the Eta similarity parameterization for the surface layer, to more accurately capture the extreme wind speed. Compared with wind gust observations at five weather stations, the wind gust parameterization predicted the intensity and occurrence time of the peak wind, with an acceptable bias (time of peak < ±1 h). Analysis of grid configurations (resolutions of 4 vs 9/3/1 km) revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular event. With regard to lead time, a shorter lead time does not necessarily result in more accurate forecasts. Nevertheless, it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.