An exceptionally deep upper-air sounding launched from Kiruna airport (67.82∘ N, 20.33∘ E) on 30 January 2016 stimulated the current investigation of internal gravity waves excited during a minor sudden stratospheric warming (SSW) in the Arctic winter 2015/16. The analysis of the radiosonde profile revealed large kinetic and potential energies in the upper stratosphere without any simultaneous enhancement of upper tropospheric and lower stratospheric values. Upward-propagating inertia-gravity waves in the upper stratosphere and downward-propagating modes in the lower stratosphere indicated a region of gravity wave generation in the stratosphere. Two-dimensional wavelet analysis was applied to vertical time series of temperature fluctuations in order to determine the vertical propagation direction of the stratospheric gravity waves in 1-hourly high-resolution meteorological analyses and short-term forecasts. The separation of upward- and downward-propagating waves provided further evidence for a stratospheric source of gravity waves. The scale-dependent decomposition of the flow into a balanced component and inertia-gravity waves showed that coherent wave packets preferentially occurred at the inner edge of the Arctic polar vortex where a sub-vortex formed during the minor SSW.

General awareness and overall interest regarding hailstorms and hail properties in Europe have increased significantly in the last several decades and have resulted in numerous local, national, and even Europe‐wide studies on hail and hail properties. To contribute to this field, we determined the hail climatology in the northeastern (NE) Adriatic region and analyzed its spatial and temporal patterns and performed an objectively derived weather type analysis of ERA5 daily mean data and instability indices. We studied the NE Adriatic region due to its focus on agricultural activities and on quality wine production. Our results are based on approximately 60 years of high spatial resolution measurements collected from 27 stations across complex terrain. The results show (i) high levels of spatial variability, (ii) significant annual variations, and (iii) hail throughout the whole year that (iv) intensifies in summer months. Furthermore, redistribution of hail among seasons (in particular, from summer to spring) was detected. Most significant changes were visible in the June–October period, with a negative trend of −0.06 hail days/year, and the period from November to March exhibited a positive trend of 0.13 hail cases/year. We found that deep cyclonic systems in front of and above our domain were most responsible for hail generation, often supported by southwesterly winds. Additionally, the vast majority of observed hail events occurred in unstable and sheared environments.

In this study, an investigation of a new thunderstorm intensity index (TSII) derived from lightning data is performed, along with its relationship to rain, wind, hail and waterspouts as well as instability indices (CAPE, LI, KI, and DLS). The study area is located in the northeastern Adriatic and includes various terrain types in a relatively small area (coastal, flatlands, hills and valleys, and mountain regions). The investigated period covers 11 years (2008–2018). The mathematical algorithm standing behind the TSII is based on the well-established methodology of lightning jump, allowing us to recognize areas where intensification in thunderstorms occurred. Our results suggest that these areas (with a positive TSII) experience significantly higher rain intensities and have higher total amounts of precipitation compared with areas where thunderstorms did not generate a TSII. Moreover, 76% of thunderstorm hail cases were associated with the presence of a TSII within a 15 km distance. The maximum reported wind speed also has higher values on a day with a TSII. Out of 27 waterspout events associated with lightning, 77% were related to a TSII. Due to the good spatial (3 km × 3 km) and high temporal (2 min) resolution of lightning data, the TSII can recognize even a local and short-lived intense system that is often misread by radars and satellites due to their inferior temporal resolution. The TSII is designed to be used as a climatological and diagnostic variable that could serve in lieu of more established data sources (e.g., station measurements and observations, radar imagery, etc.) if they are unavailable.

Hail is a significant convective weather hazard, often causing considerable crop and property damage across the world. Although extremely damaging, hail still remains a challenging phenomenon to model and forecast, given the limited computational resolution and the gaps in understanding the processes involved in hail formation. Here, eight hailstorms occurring over the Alpine‐Adriatic region are analyzed using simulations with the Weather Research and Forecasting (WRF) and the Consortium for Small Scale Modeling (COSMO) models, with embedded HAILCAST and Lightning Potential Index (LPI) diagnostics at kilometer‐scale grid spacing (∼2.2 km). In addition, a systematic model intercomparison study is performed to investigate the ability of the different modeling systems in reproducing such convective extremes, and to further assess the uncertainties associated with simulations of such localized phenomena. The results are verified by hailpad observations over Croatia, radar estimates of hail over Switzerland, and lightning measurements from the LINET network. The analysis reveals that both HAILCAST and LPI are able to reproduce the affected area and intensities of hail and lightning. Moreover, hail and lightning fields produced by both models are similar, although a slight tendency of WRF to produce smaller hail swaths with larger hailstones and higher LPI compared to COSMO is visible. It is found that these differences can be explained by systematic differences in vertical profiles of microphysical properties and updraft strength between the models. Overall, results are promising and indicate that both HAILCAST and LPI could be valuable tools for real‐time forecasting and climatological assessment of hail and lightning in current and changing climate.

Hail is a significant convective storm hazard in Croatia, often causing property and crop damage. The existing analysis, based on hailpad network data, shows that western and central regions of Croatia have a significant frequency of high-intensity hail events.Advances in computational power and recent developments in atmospheric modeling have enabled the use of convection-permitting models (CPM) that can partially resolve deep convective events such as thunderstorms and rain showers. However, hail remains a difficult phenomenon to model or forecast since CPMs are still not able to fully resolve processes involved in producing hail. One way to address this issue is by embedding a physically-based one-dimensional hail model called HAILCAST within a CPM. Here, the HAILCAST model is embedded within the Weather Research and Forecasting (WRF) model.The selected hail event is analyzed using WRF-HAILCAST model simulations. HAILCAST forecasts the maximum expected hail diameter using a profile of the vertical updraft, temperature, liquid and ice water content from a given WRF timestep and grid columns. Here, a set of numerical convection-permitting experiments are performed to assess the sensitivity of the results to different microphysics and planetary boundary layer (PBL) parameterization schemes and to provide guidance for WRF-HAILCAST tuning. The results are verified by observational (hailpad, hail observations) data as well as with radar, lightning and satellite measurements where available.