Hail Damage Research Articles

Hail hazard modeling with uncertainty analysis and roof damage estimation of residential buildings in North America

This research presents a statistical approach for hail risk modeling that incorporates the uncertainties of hail model prediction to provide insight into assessing the roof damage of a residential house in hail events. By quantifying the inherent uncertainties in evaluating hailstorm characteristics, this study extends the current existing hail models. The hail data are sourced from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) in the U.S. In the modeling process, the largest hail diameter reported in the CoCoRaHS database serves as a primary input variable to estimate the number of observations for the largest hail diameter, hailstorm duration, and hit rate. The assessment of hail risk in this study focuses on the probability of hail damage and resultant repair costs for five types of roofs in North America (unrated roof and impact-resistant roofs with UL 2218 rating classes 1 to 4). The probability of hail damage is calculated as the failure probability by integrating all individual hailstone hits having variable diameters during a hailstorm with fragility curves, which estimate the probability that hailstones will fracture asphalt shingles (allowing water infiltration) or that they dislodge enough granules to cause visible damage requiring replacement for aesthetic reasons. The results reveal that an impact-resistant roof (impact-resistant rating classes 1 to 4) is associated with lower hail risks, with 60 % to 98 % reduction on average compared to unrated roofs. This study provides a comprehensive uncertainty modeling approach for hail hazard and risk, enabling better-informed decision-making and risk management strategies.

Determination of performance characteristics of spacer fabric vehicle covers

AbstractHailstorms today have the potential to damage almost every object in their path. Efforts are been made to prevent hailstorms, which can be quite severe. However, a completely successful result has not been achieved. Automobiles are the ones most damaged by hailstorms. In order to protect automobiles from this damage, various protective fabrics have been studied on and patents have been obtained. Spacer fabrics are one of the materials that have the potential to be used as protectors. In this study, an experimental device that can test the performance of spacer fabrics against hail and simulate hail damage has been designed and manufactured. At the same time, suggestions for the preparation of artificial hail grains that can be used in different studies are presented. With 25 mm and 30 mm diameter artificial hail grains, experiments were carried out on spacer fabrics of different thicknesses with the same weave structure. The same diameters of artificial hail grains were also tested without covering and the amount of damage in all experiments was measured. As a result, it was compared which fabric provided how much protection against artificial hailstones of different diameters.

Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density

Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density

Evaluating the yield of surviving plants from early‐season hail damage in corn: A field survey

AbstractEconomic losses due to hailstorms across US corn fields occur every year. Hailstorms result in leaf defoliation, decreasing photosynthetic area and impairing carbon assimilation and crop yield for all corn (Zea mays L.) development stages. However, more attention is often given to stand reductions rather than damage to stems or leaf defoliation. During the 2014 growing season, a natural hail event affected many areas of eastern Nebraska. Twelve affected corn fields were surveyed and included in this study. An injury score scale (1–5) was developed based on various injury and severity levels before the V6 (6‐leaf corn growth stage) (six‐collared leaves). Scores were assigned to affected fields approximately 10–15 days after the hailstorm. At the end of the growing season, ears were harvested, and grain yield per plant was determined. The highest grain yield (p < 0.05) was recorded with plants that were affected but retained a main stem in good condition, albeit defoliation was present (score 1, lowest damage category). In contrast, when the main stem was cut and the plant had poor regrowth (score 3), yields were reduced by approximately 53% compared to plants with an injury score of 1. A significant negative linear relationship (R2 = 0.63, p < 0.01) between injury score and yield was observed (higher injury score from hail events resulted in lower yields). Based on these results, corn yield reduction due to plant injury from hail events before V6 should not be only attributed to stand reductions. Our findings indicate an opportunity to adjust the US evaluation standards for early‐season hail damage events in corn fields.

Defoliation level and timing affect popcorn yield traits in the Midwestern United States

Popcorn [Zea mays (L.) var. Everta] is an important field crop in the Midwestern United States. However, hailstorms are a major threat to ensuring high yield because of their effects on leaf photosynthesis, pollination, and stalk lodging. A multi-state study spanning six site-years (2020–2023) was conducted in two locations (Ohio and Nebraska) to determine how defoliation intensity at different stages affects yield loss in popcorn and compare these losses with current values in the National Crop Insurance Service (NCIS) Corn Loss Instructions. At each location the study was conducted in a randomized complete block design with four replicates. The treatments consisted of the combination of four levels of leaf loss (25, 50, 75 and 100 % leaf blade area removal) imposed at five developmental stages: V8 (10-leaf), V13 (15-leaf), VT, R2, and R4. The evaluated traits were plant population, grain yield, stalk lodging, and 100-kernel weight. All evaluated traits were affected by defoliation, except plant population. The treatments 100 % defoliation at VT and R2 stages were the most damaging in terms of grain yield reduction, number of ears per plant and 100-kernel weight for both locations. In Ohio, the greatest stalk lodging was observed at 100 %-R2 and in Nebraska, at 75 %-VT. For both locations, the actual yield losses in the defoliated treatments were lower than values currently listed in the NCIS Popcorn Leaf Loss Chart. These results indicate leaf loss chart values should be updated to accurately reflect yield losses from popcorn defoliation events. This evaluation did not impose damage to stalks (e.g., bruising) or to plant whorls as may be expected in natural events. Future research should incorporate other forms of plant damage such as those described to provide a better emulation of hail damage.

Comparative effects of two elicitors on the essential oil biosynthesis of simulated hail-damaged rose geranium (Pelargonium graveolens L’Hér. cv. ‘BOURBON’)

Extreme abiotic stress factors such as hail, defoliation, salinity, and moisture stress can affect the biosynthesis of essential oils. To mitigate this, most commercial farmers globally use agricultural crop insurance; however, this is not the case for most smallholder and emerging farmers in southern Africa, as agricultural insurance tends to be expensive when included in the production system. Therefore, this study aimed to investigate the comparative effects between two elicitors: abscisic acid (ABA) and methyl jasmonate (MeJA) on essential oil biosynthesis of simulated hail-damaged rose geranium (Pelargonium graveolens L’Hér.) as an alternative strategy to improve the essential oil biosynthesis following severe hail damage of rose geranium. The study was conducted in a 72 m2 temperature-controlled greenhouse, using a 4 x 2 factorial treatment design arranged in a randomized complete block design. Treatments comprised four levels of two elicitors at 75 µM (ABA), 150 μM (ABA), 10 mM (MeJA), and 20 mM (MeJA), applied in two different application periods (daily application for either 7 or 14 days). The simulation of hail damage was through 100% defoliation, with decapitation of the terminal buds. A significant interaction was observed between the elicitor treatment, and length of the period of application on essential oil yield (mass), where the highest yield was observed when MeJA (10 mM) was applied for seven consecutive days compared to the 14-day treatment. Geraniol esters were partially improved by the application of MeJA at 10 mM. Application of the two elicitors improved citronellol, geraniol, and linalool, regardless of the length of the period of application. The citronellol to geraniol ratio, a determining factor of essential oil quality, was 2.7:1 when MeJA was applied at 10 mM, significantly better than any application level of ABA. Therefore, it could be concluded that the application of MeJA at 10 mM may improve the essential oil biosynthesis of hail-damaged rose geranium plants compared to ABA at any level, and this may be adopted as a possible mitigating strategy by the emerging farmers and growers in southern Africa for improving the biosynthesis of rose geranium post hail damage. On the other hand, where growers are interested in higher contents of linalool and citronellol, ABA may be used at any level. Key words: Defoliation, essential oil, yield, phytohormone, citronellol, geraniol, linalool

Protective covers impact honey bee colony performance and access to outside resources

Protective crop covers are used extensively to protect high-value crops from bird and hail damage, however, these structures may present challenges for honey bees (Apis mellifera L.), the main pollinators in these systems. Some studies have indicated that protective covers result in declines in colony size and resource storage, but few replicated field trials exist. To determine the impact of protective cropping structures on honey bee brood production and resource storage, 14 honey bee colonies were placed inside and outside of protective covers on four blueberry (Vaccinium corymbosum and V. virgatum) farms in northern New South Wales, Australia. We measured changes in brood production, pollen and honey storage, hive weight and ambient hive temperature fortnightly over a 12-week period. Brood production, pollen and honey storage, and hive weight all displayed greater reductions within four weeks of placement under net cover, compared to hives outside of net cover. Although brood and honey metrics gradually increased in all hives during the remainder of the 12-week monitoring period, hives located under protective netting had relatively smaller gains in brood production and pollen storage when compared to hives located outside the protective covering. Hives under protective netting that were in the shade and/or whose entrances were facing south were most impacted by the end of the monitoring period. Our findings highlight the need for protected crop management strategies to consider pollinator health as well as crop pollination needs so that both bee health and pollination services are maintained in these systems.

Diversity, Community Structure, and Antagonism of Endophytic Fungi from Asymptomatic and Symptomatic Mongolian Pine Trees.

Diplodia tip blight, caused by Diplodia sapinea (=Sphaeropsis sapinea), are widely distributed in Honghuaerji, Inner Mongolia, China, causing severe damage on natural Mongolian pine (Pinus sylvestris var. mongolica). D. sapinea is an endophyte that becomes pathogenic under conditions of drought, hail damage, or temperature-associated stress. The role of the endophytic community inhabiting different pine tissues in the expression of disease is still unknown. In this study, the diversity and community structure of endophytic fungi among asymptomatic and symptomatic Mongolian pine were detected using culture-based isolation and high-throughput sequencing (HTS), and the potential antagonistic endophytes against D. sapinea were also screened. The results indicated that 198 and 235 strains of endophytic fungi were isolated from different tissues of symptomatic and asymptomatic Mongolian pine, respectively. D. sapinea was the most common endophyte isolated from the current-year needles and shoots of symptomatic trees, and Diplodia was also the most common in the HTS data. There were no significant differences in the endophytic fungal species richness among asymptomatic and symptomatic trees, but there were differences observed within specific sampled tissues. The ANOSIM analysis confirmed that the endophytic fungi community structure significantly differed between sampling tissues among symptomatic and asymptomatic Mongolian pine. Furthermore, the antagonism study revealed Penicillium fructuariae-cellae with the ability to inhibit the growth of D. sapinea in vitro, and the potential performance of this fungus, acting as biological control agent, was evaluated under greenhouse. Our findings can pave the way to a better understanding of the interactions between D. sapinea, other endophytic fungi and their hosts, and provide helpful information for more efficient disease management strategies.

An open-source radar-based hail damage model for buildings and cars

Abstract. Severe hailstorms result in substantial damage to buildings and vehicles, necessitating the quantification of associated risks. Here, we present a novel open-source hail damage model for buildings and cars based on single-polarization radar data and 250 000 geolocated hail damage reports in Switzerland from 2002 to 2021. To this end, we conduct a detailed evaluation of different radar-based hail intensity measures at 1 km resolution and find that the maximum expected severe hail size (MESHS) outperforms the other measures, despite a considerable false-alarm ratio. Asset-specific hail damage impact functions for buildings and cars are calibrated based on MESHS and incorporated into the open-source risk modelling platform CLIMADA. The model successfully estimates the correct order of magnitude for the number of damaged building in 91 %, their total cost in 77 %, the number of damaged vehicles in 74 %, and their total cost in 60 % of over 100 considered large hail events. We found considerable uncertainties in hail damage estimates, which are largely attributable to limitations of radar-based hail detection. Therefore, we explore the usage of crowdsourced hail reports and find substantially improved spatial representation of severe hail for individual events. By highlighting the potential and limitations of radar-based hail size estimates, particularly MESHS, and the utilization of an open-source risk modelling platform, this study represents a significant step towards addressing the gap in risk quantification associated with severe hail events in Switzerland.

Non-target impacts of hail netting and insecticides on natural enemy abundance and diversity in a Midwestern U.S. commercial apple orchard

A variety of exclusion systems for integrated pest management (IPM) have become viable alternatives to traditional insecticide use in tree fruit production globally. Exclusion netting has been particularly effective as a control strategy for several insect pests of apple. In Minnesota, USA, hail netting, used to protect high-value fruit from hail damage, was recently shown to effectively exclude the two major insect pests: codling moth (Cydia pomonella L.) and apple maggot (Rhagoletis pomonella Walsh). The present study aimed to determine the impact of single-row, drape-style hail netting (DrapeNet®) on the natural enemy community and how this compared to the impact of insecticides used by a Minnesota grower. Sampling occurred during 2021 and 2022 at two orchard locations in Minnesota using yellow sticky traps. Natural enemies were identified to the family level, and these data were examined to determine family richness, diversity, and relative abundance. Compared to unnetted rows, rows covered with hail netting had a significant reduction in both family richness and predator abundance, as measured by yellow sticky traps. The overall abundance of the three most common predator families, Anthocoridae, Empididae, and Coccinellidae, along with other families, was significantly reduced under netting. By contrast, using Simpson's diversity index we found that family diversity was significantly higher under netting, while the insecticides used did not affect diversity. These findings indicate that non-target effects of netting include a general reduction in the abundance of natural enemies and the disproportionate exclusion of Anthocoridae. However, predator diversity was higher under netting, indicating that biological control services could remain intact under netting even with modest use of insecticides.

Recovery from hail damage in primocane raspberry

Recovery from hail damage in primocane raspberry

Radar and environment-based hail damage estimates using machine learning

Abstract. Large hail events are typically infrequent, with significant time gaps between occurrences at specific locations. However, when these events do happen, they can cause rapid and substantial economic losses within a matter of minutes. Therefore, it is crucial to have the ability to accurately observe and understand hail phenomena to improve the mitigation of this impact. While in situ observations are accurate, they are limited in number for an individual storm. Weather radars, on the other hand, provide a larger observation footprint, but current radar-derived hail size estimates exhibit low accuracy due to horizontal advection of hailstones as they fall, the variability of hail size distributions (HSDs), complex scattering and attenuation, and mixed hydrometeor types. In this paper, we propose a new radar-derived hail product developed using a large dataset of hail damage insurance claims and radar observations. We use these datasets coupled with environmental information to calculate a hail damage estimate (HDE) using a deep neural network approach aiming to quantify hail impact, with a critical success index of 0.88 and a coefficient of determination against observed damage of 0.79. Furthermore, we compared HDE to a popular hail size product (MESH), allowing us to identify meteorological conditions that are associated with biases on MESH. Environments with relatively low specific humidity, high CAPE and CIN, low wind speeds aloft, and southerly winds at the ground are associated with a negative MESH bias, potentially due to differences in HSD, hail hardness, or mixed hydrometeors. In contrast, environments with low CAPE, high CIN, and relatively high specific humidity aloft are associated with a positive MESH bias.

Simulacija oštećenja od grada na regeneraciju i prinos soje (Glycine max (L.) Merr.)

The most common mechanical damage to soybean in the agroecological conditions of Serbia occurs after the appearance of hail, floods or due to damage from wild animals and insects. In recent years, extreme temperatures accompanied by drought have been increasingly recorded during the summer months, as well as the appearance of hail, which has become frequent during the growing season of spring crops. The aim of this work was to determine the consequences and the extent of yield reduction if hail occurs in the generative stages of soybean development. The occurrence of hail in the R1 (beginning bloom) and R3 (beginning pod) stages of development in the form of plant damage was simulated. This paper will present the results of how three soybean varieties reacted after simulated hail damage in two stages of generative development and what the effects were on yield, height, number of fertile nodes, as well as percentage of plant regeneration. The trial was set up in 2020 as a two-factorial experiment in three replications. Three soybean varieties were sown in late April. In order to simulate hail damage, the plants were cut to a height of 15 cm to ensure at least two nodes and enable the regeneration of the plants. The stage of development of soybean, i.e. the moment of hail damage, had a direct impact on the yield, the number of regenerated plants, as well as the number of fertile nodes.

Investigation on radar characteristics of hailstorms seeded with the glaciogenic reagent in Romania

An operational hail suppression program has been based in Romania since 2005. The program is designed to reduce hail damage in the most vulnerable agricultural areas (protected areas) of the country. An exploratory analysis of volume-scan, S-band and C-band radars data, using a storm cell tracking software, was conducted to calculate six radar-derived parameters associated with hail from 51 seeded storms during the summers of 2017 to 2022. All selected hailstorms had a lifetime of more than one hour, which was divided into three stages: before seeding, during seeding, and after seeding. The statistical t-test was used to test the null hypothesis of no seeding effect. Comparing values before seeding and during seeding, the data support claims that seeding causes an increase in most of the analysed parameters. These can indicate the stimulation of the development of seeded clouds, due to the so-called dynamic effect. After seeding, a decrease in the values of all the parameters analysed was observed (with decreases in average values ranging between 10% to 15%). Furthermore, a spatial analysis of hail kinetic energy shows that areas with values over 300 J/m2 are lower in the protected areas compared to the neighbouring ones where the clouds have not been seeded.

Mapping hailstorm damage on winter wheat (Triticum aestivum L.) using a microscale UAV hyperspectral approach

Hailstorms pose a direct threat to agriculture, often causing yield losses and worsening farmers’ agricultural activity. Traditional methods of hail damage estimation, conducted by insurance field inspectors, have been questioned due to their complexity, partial subjectivity, and lack of accounting for spatial variability. Therefore, remote sensing integration in the estimation process could provide a valuable aid. The focus of this study was on winter wheat (Triticum aestivum L.) and its response to damage in the near-infrared (NIR) spectral region, with a particular emphasis on the study of brown pigments as a proxy for yield damage estimation and mapping. An experiment was conducted during two cropping seasons (2020–2021 and 2021–2022) at two sites, simulating hail damage at critical flowering and milky stages using a specifically designed prototype machinery with low, medium, and high damage gradients compared to undamaged conditions in plots with a minimum of 400 m2 area. After the damage simulation, hyperspectral visible-NIR reflectance was measured with Unmanned Aerial Vehicle (UAV) flights, and measurements of chlorophyll and of leaf area index (LAI) were contextually taken. Final yield per treatment was recorded using a combine. An increase in absorbance in the NIR region (780–950 nm) was observed and evaluated using a spectral mixture analysis (SMA) after selecting representative damaged and undamaged vegetation spectra to map the damage. The abundance of damaged endmember pixels per treatment resulted in a good relationship with the final yield (R2 = 0.73), identifying the most damaged areas. The absorbance feature was further analysed with a newly designed multispectral index (TAI), which was tested against a selection of indices and resulted in the highest relationship with the final yield (R2 = 0.64). Both approaches were effective in highlighting the absorbance feature over different dates and development stages, defining an effective mean for hailstorm damage mapping in winter wheat.

Hail: Mechanisms, Monitoring, Forecasting, Damages, Financial Compensation Systems, and Prevention

Hail has long caused extensive damage and economic loss in places inhabited by humans. Climate change is expected to lead to different types of damage due to the geographic characteristics of each continent. Under changing environment, hail is becoming increasingly unstable and is causing damage that is difficult to repair, making it essential to study the occurrence of hail and hail-damage. Hail formation has been studied at the micro- and macrophysical scales as well as thermal and dynamical scales. Hail forms in various sizes, and the scale of damage varies with size. Hail precipitation occurs suddenly and is localized, making it is difficult to observe and predict. Nonetheless, techniques to measure and forecast hail precipitation are improving in accuracy. Hail-damage management and financial compensation systems are used to mitigate the severe economic losses caused by hail fallen in rural and urban areas. This review most comprehensively considers hail research, focusing on the mechanisms, observation and prediction methods, damage, social compensation systems for hail damage, and hail-disaster prevention, suggesting future study directions briefly.

Advanced characterisation of photovoltaics for hail resistance

Climate change is intensifying severe weather events, especially in alpine environments where hailstorms are more frequent and intense. In particular, hail damage seriously affects photovoltaic systems. The severity of hailstorms as well as impact responses are important factors in mitigating loss, so the first research area that needs to be addressed is the resistance of photovoltaic modules to hail. According to IEC 61215 standard, a PV module should resist at the minimum to the impact of a hailstone of 25 mm launched at 80 km/h, while the Swiss VKF standard demands a minimum of 30 mm, practically making it 40 mm or more. The hail test stand is being enhanced to support larger diameters and higher speed, enabling module manufacturers to assess their products with adequate safety margins. Larger ice ball requires evaluating sample preparation, repeatability, representativity, and the ability to handle high speeds and masses in order to minimise uncertainty in impact energy. In this preliminary study, ice ball samples with diameters of 25, 40, and 70 mm were tested on a Hopkinson bar at speeds from 20 to 140 m/s and temperatures from −5 °C to −20 °C. The effects of impact velocity, loading rate, and impact time were examined. Finally, the first tests on PV modulus with large ice ball and high velocity are presented.

A ten-year statistical radar analysis of an operational hail suppression program in Alberta

Hailstorms represent a significant natural hazard worldwide and can result in severe socioeconomic impacts. In Canada, the province of Alberta experiences the highest rate of hail occurrences causing tremendous damage to cities, properties, vehicles and crops. Cloud seeding is often adopted to reduce the hailstorm impacts; however, the efficacy of this mitigation measure is still unclear. In this study, a ten-year set of hailstorm events (2011−2020) in Alberta was analyzed using radar-based records to evaluate the potential effects of seeding. The radar completed a full volume-scan every four minutes, and a three-dimensional radar reflectivity threshold-based method was utilized to identify hailstorms. A single 3D storm is tracked over time and the ensemble is called a “storm track” in this contribution. 176 storm tracks persisting for more than one hour were considered for further analysis. We used two radar-derived metrics as proxies for hail damage potential, namely, VILmax (Vertically Integrated Liquid calculated from the maximum reflectivity profile in the storm) and hail mean coverage area (defined as the mean area with reflectivity greater than 60 dBZ). Seeding was performed by releasing silver iodide aerosols from aircraft, and seeded scans of the storm were identified based on the location and seeding time. The efficacy of seeding was evaluated by comparing the characteristics of the storms before, during and after seeding. Results show that for nearly 60% of cases, the median values of the largest (quantile 99) VILmax and mean area corresponding to the seeded scans are lower than those of the unseeded portions. For around 8% and 20% of cases, there is no change, while for approximately 17% to 30% of cases, the values are higher. The effects of seeding are more pronounced after 30 min than at the initiation of seeding. Furthermore, statistical analyses using Mann-Whitney and Wilcoxon's tests reveal that differences in VILmax and mean area between the seeded and unseeded scan groups are statistically significant. These findings suggest that cloud seeding could potentially influence the hail damage potential of storms, particularly those with high VILmax values.

Remote sensing hail damage on maize crops in smallholder farms using data acquired by remotely piloted aircraft system

Smallholder farmers reside in marginal environments typified by dryland maize-based farming systems. Despite the significant contribution of smallholder farmers to food production, they are vulnerable to extreme weather events such as hailstorms, floods and drought. Extreme weather events are expected to increase in frequency and intensity under climate change, threatening the sustainability of smallholder farming systems. Access to climate services and information, as well as digital advisories such as Robust spatially explicit monitoring techniques from remotely piloted aircraft systems (RPAS), could be instrumental in understanding the impact and extent of crop damage. It could assist in providing adequate response mechanisms suitable for bolstering crop productivity in a spatially explicit manner. This study, therefore, sought to evaluate the utility of drone-derived multispectral data in estimating crop productivity elements (Equivalent water thickness (EWT), Chlorophyll content, and leaf area index (LAI)) in maize smallholder croplands based on the random forest regression algorithm. A hailstorm occurred in the study area during the reproductive stages 2 to 3 and 3 to 4. EWT, Chlorophyll content, and LAI were measured before and after the storm. Results of this study showed that EWT, Chlorophyll content, and LAI could be optimally estimated based on the red edge and its spectral derivatives. Specifically, EWT was estimated to a rRMEs 2.7% and 59%, RMSEs of 5.31 gm−2 and 27.35 gm-2, R2 of 0.88 and 0.77, while chlorophyll exhibited rRMSE of 28% and 25%, RMSEs of 87.4 µmol m−2 and 76.2 µmol m−2 and R2 of 0.89 and 0.80 and LAI yielded a rRMSE of 10.9% and 15.2%, RMSEs of 0.6 m2/m2 and 0.19 m2/m2 before and after the hail damage, respectively. Overall, the study underscores the potential of RPAS-based remote sensing as a valuable resource for assessing crop damage and responding to the impact of hailstorms on crop productivity in smallholder croplands. This offers a means to enhance agricultural resilience and adaptability under climate change.

Changes in hail hazard across Australia: 1979–2021

Hail damage is a leading cause of insured losses in Australia, but changes in this hazard have not been robustly quantified. Here, we provide a continental-scale analysis of changes in hail hazard in Australia. A hail proxy applied to reanalysis data shows that from 1979–2021 annual hail-prone days decreased over much of Australia but increased in some heavily populated areas. For example, the annual number of hail-prone days increased by ~40% around Sydney and Perth, the largest cities on Australia’s east and west coasts, respectively. Changes in atmospheric instability have driven the trends. Radar observations, while covering shorter time spans and a more limited area than the reanalysis, corroborate the broad pattern of results. This study shows consistent hail-frequency trends in radar indicators and atmospheric environments and demonstrates substantial increases in hail frequency in major Australian cities where hail impacts are most significant.