The Golden (British Columbia, Canada) meteorite fall occurred on October 4, 2021 at 0534 UT with the first recovered fragment (1.3 kg) landing on an occupied bed. The associated fireball was recorded by numerous cameras permitting reconstruction of its trajectory and orbit. The fireball entered the atmosphere at a 54° angle from the horizontal at a speed of 18 km s⁻¹. The fireball reached a peak brightness of −14, having first become luminous at a height of >84 km and ending at 18 km altitude. Analysis of the infrasonic record of the bolide produced an estimated mass of kg while modeling of the fireball light curve suggests an initial mass near 70 kg. The fireball experienced a major flare near 31 km altitude where more than half its mass was lost in the form of dust and gram‐sized fragments under a dynamic pressure of 3.3 MPa. The strength and fragmentation behavior of the fireball were similar to those reported for other meteorite‐producing fireballs (Borovička et al., 2020). Seven days after the fireball occurred, an additional 0.9 kg fragment was recovered during the second day of dedicated searching guided by initial trajectory and dark flight calculations. Additional searching in the fall and spring of 2021–2022 located no additional fragments. The meteorite is an unbrecciated, low‐shock (S2) ordinary chondrite of intermediate composition, typed as an L/LL5 with a grain density of ~3530 k gm⁻³, an average bulk density of 3150 kg m⁻³ and calculated porosity of ~10%. From noble gas measurements, the cosmic ray exposure age is 25 ± 4 Ma while gas retention ages are all >2 Ga. Short‐lived radionuclides and noble gas measurements of the pre‐atmospheric size overlap with estimates from infrasound and light curve modeling producing a preferred pre‐atmospheric mass of 70–200 kg. The orbit of Golden has a high inclination (23.5°) and is consistent with delivery from the inner main belt. The highest probability (60%) of an origin is from the Hungaria group. We propose that Golden may originate among the background S‐type asteroids found interspersed in the Hungaria region. The current collection of 18 L/LL—chondrite orbits shows a strong preference for origins in the inner main belt, suggesting multiple parent bodies may be required to explain the diversity in CRE ages and shock states.

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.

Understanding the relationship between fire behavior and the driving weather conditions is critical for fire management and long-term fire risk assessment. In this study, we focus on two wildfire events: the Split wildfire in Croatia and the Forcett–Dunalley wildfire in Tasmania, Australia. The antecedent weather in both events included extremely dry conditions and higher-than-average air temperatures in the months prior to the events. The synoptic patterns in both events consisted of a large surface pressure gradient, which generated strong wind, driving the fire’s spread. The Weather Research and Forecasting (WRF) model was utilized to simulate fire weather conditions during the development of the two events. In the innermost domain of WRF, resolution is 500 m with explicit moisture calculation only, and there are 66 vertical levels, with about 20 of them to resolve the boundary layer. The WRF simulations are well verified by station observations, including upper-level wind speeds. The convergence line pattern in the Tasmanian event, which was conducive to intense plume development, has been well simulated. Only a slight discrepancy was identified in the simulation of the coastal change in wind direction in the Croatian event. It is identified that in the Split case, bura wind was highly coupled with an upper-level trough, which induced subsidence of the upper-level dry and cold air to the surface, causing rapid drying of the fuel. During the Forcett–Dunalley fire, the atmosphere was unstable, which enabled deep pyrocumulonimbus development. In general, the development from ignition to the timing of the most extreme fire intensity in both events was largely determined by the evolution of the surface to upper-level meteorological drivers. While these extreme meteorological conditions would impact fire-fighting strategies such as aircraft operations, a model-based estimate of the high-risk areas is critical. Our findings would also benefit an estimate of the climatology of fire events with similar behavior and thus a long-term fire risk assessment.

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 Weather Research and Forecasting (WRF) and Consortium for Small Scale Modeling (COSMO) simulations, with embedded HAILCAST and Lightning Potential Index (LPI) diagnostics at kilometer-scale grid spacing (~2.2 km). In addition, a 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 revealed that both HAILCAST and LPI are able to reproduce the areas and intensities affected by hail and lightning. Moreover, the 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, the promising results 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 climates.