A comparison of the practical predictability of hail with initial perturbations of climatological and flow-dependent uncertainty in ensembles

The practical predictability of hail precipitation rates is significantly influenced by initial meteorological perturbations, stemming from various uncertainty sources. This study thoroughly assessed the predictability of hail precipitation rates in both climatologically and flow-dependent perturbed ensembles (CEns and FEns). These ensembles incorporated initial meteorological uncertainties derived from ERA-20C and ECMWF operational ensembles, respectively. Leveraging the Weather Research and Forecasting (WRF) model, we conducted cloud-resolving simulations of an idealized hailstorm. The practical predictability of hail responded comparably to both climatological and flow-dependent uncertainties is revealed across the entire ensemble of 50 members. However, a notable difference emerged when comparing the peak hail precipitation rates among the top 10 (Top10) and bottom 10 (Bottom10) members. From a thermodynamic perspective, the primary source of uncertainty in hail precipitation lies in the significant variations in temperature stratification, particularly at -20℃ and -40℃. On the microphysical front, perturbations within CEns generated greater uncertainty in the process of rainwater collection by hail, significantly contributing to the microphysical growth mechanisms of hail. Furthermore, the findings reveal a stronger dependency of hail precipitation uncertainty on thermodynamic perturbations compared to kinematic perturbations. These insights enhance the comprehension of the practical predictability of hail and contribute significantly to the understanding of ensemble forecasting for hail events.