Performance of HAILCAST and the Lightning Potential Index in simulating hailstorms in Croatia in a mesoscale model – Sensitivity to the PBL and microphysics parameterization schemes

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Hailstorms, although extremely damaging severe weather hazards, remain a very challenging phenomenon to predict. To better understand dynamic processes and model performance, which can be helpful in forecasting hailstorms, three selected hailstorms in Croatia are simulated with the WRF model at convection-permitting (1 km) grid spacing using the HAILCAST module. In addition, the performance of the Lightning Potential Index (LPI) algorithm in representing the observed lightning activity during the selected hailstorms is analyzed. A multiphysics ensemble of 12 sensitivity simulations with the combinations of four different microphysics and three different planetary boundary layer parameterization (PBL) schemes is adopted to assess the forecasting ability of HAILCAST and LPI and their sensitivity to the choice of microphysics and PBL parameterization schemes. First, the model's ability to reproduce surface measurements of 2-m temperature, 2-m relative humidity, 2-m equivalent potential temperature and 10-m wind are examined using root mean square error (RMSE) decomposition. Then, the LPI is assessed against lightning observations via the object-based Structure-Amplitude-Location (SAL) method. Finally, an upscaled neighborhood verification method is proposed to assess HAILCAST against hail observations from the Croatian hailpad network. The results show that the observed hail and lightning activity is represented well by the model. There is a greater sensitivity to the choice of microphysics scheme than the PBL scheme, with National Severe Storms Laboratory double-moment scheme (NSSL2) microphysics scheme differing the most among the entire sensitivity ensemble. Nonetheless, both HAILCAST and LPI show promising performance in simulating observed hail and lightning activity, although HAILCAST tends to overestimate the area affected by hail. Nonetheless, the discrepancies between model configurations highlight the importance of simulating convection correctly to obtain a meaningful forecast of hail and lightning.