Exploring the potential of HAILCAST and LPI in km-resolution simulations over the Alpine-Adriatic region

<p>The Alpine and Adriatic regions are hotspots of frequent hail and lightning. Hail and lightning are associated with severe convective storms that happen under the large-scale forcing of surface fronts, upper-level fronts, convergence zones, or local thermal-topographic forcing. Convection-resolving models are run at the km-scale resolution, which improves the representation of topography. Moreover, they can explicitly resolve deep convection, thus reducing the uncertainties related to the use of deep convection parameterization in lower resolution models. Both aspects are beneficial for studying processes that drive severe convective storms over mountainous regions.<br><br>In this study, we analyze convection-resolving simulations of 8 heavy convective events performed with the COSMO-crCLIM model (GPU version of the Consortium for Small-scale Modeling) at 2.2 km horizontal grid spacing over the Alpine-Adriatic region. The cases are selected according to their impacts (size of hailstones, number of lightning strikes and damages), and the simulations are driven by the ERA5 reanalysis. For the simulation of hail and lightning, we use the one-dimensional hail growth model HAILCAST and the lightning potential index (LPI) implemented into the COSMO model, and compare results with observed hail properties and lightning flashes. In addition, we look into key variables for hail formation, including temperature, humidity, CAPE and CIN, and bulk wind shear. By performing a detailed analysis, we identify several environments that are favorable for strong convection and associated hail and lightning, such as a "loaded-gun" sounding, conditionally unstable layer and intrusion of dry air aloft. Evaluation of model simulations with available observations demonstrates overall very good performance of the model for the simulation of precipitation, hail and lightning. However, results depend upon the predictability of the cases, with lower predictability for deep convection events driven by local thermal-topographic forcing.&#160;<br><br>Our findings indicate that HAILCAST and LPI can diagnose hail and lightning associated with severe weather events. Recently, we have started to assess changes in the occurrence and severity of such events with multi-seasonal simulations under current and future climate conditions using the pseudo-global warming (PGW) approach.</p>