Severe Hailstorms Research Articles

Polarimetric radar observations of the Jersey tornadic supercell on 1–2 November 2023

AbstractA large tornado and severe hailstorm struck Jersey, Channel Islands, just before midnight on 1–2 November 2023. Radar data are analysed to explore the morphology of the parent supercell thunderstorm. A tornado debris cloud was evident in polarimetric fields, collocated with a reflectivity ‘debris ball’. The debris cloud comprised a small region of exceptionally low correlation coefficient (<0.8) collocated with differential reflectivity ≤0dB. In vertical section, the debris signature comprised a column of low correlation coefficient and high reflectivity that tilted north‐northeast with height and extended to at least 2km above ground level.

Assessing the performance of WRF model in simulating severe hailstorm events over Assam and Bihar, India

Assessing the performance of WRF model in simulating severe hailstorm events over Assam and Bihar, India

Climatology of severe hail potential in Europe based on a convection-permitting simulation

We present a new approach to identify severe hailstorms in a convection-permitting climate model, and build a climatology of severe hail potential in Europe using an ingredients-based approach based on a 20-year long hindcast simulation. Severe hail in Europe occurs mostly in southern regions (up to 40 times a year per 10,000 km2 around Northern Italy), and from May to August. It peaks from afternoon to evening hours on land, whilst sea areas are prone to hail at any time of the day. The Mediterranean Sea experiences severe hailstorms mostly in autumn: the central Mediterranean has the highest frequency among all regions studied, and may be considered as an unknown alley for hailstorms in Europe. Results derived from the high-resolution model are in very good agreement with existing hail climatologies constructed from observations, including the fine scale spatial variation. We conclude that our approach provides a reliable proxy for studying future changes in severe hail in convection-permitting simulations.

Major Role of Marine Heatwave and Anthropogenic Climate Change on a Giant Hail Event in Spain

AbstractA severe hailstorm that occurred in Spain on 30 August 2022, caused material and human damage, including one fatality due to giant hailstones up to 12 cm in diameter. By applying a pseudo‐global warming approach, here we evaluate how a simultaneous marine heatwave (and anthropogenic climate change) affected a unique environment conductive to such giant hailstones. The main results show that the supercell development was influenced by an unprecedented amount of convective available energy, with significant contributions from thermodynamic factors. Numerical simulations where the marine heatwave is not present show a notable reduction in the hail‐favorable environments, related mainly to modifications in thermodynamic environment. Our simulations also indicate that the environment in a preindustrial‐like climate would be less favorable for convective hazards and thus the hailstorm event would likely not have been as severe as the observed one, being possible to perform a novel attribution of such kind.

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.

Severe convective storms’ reproduction: empirical analysis from the marked self-exciting point processes point of view

The paper focuses on the evaluation of hailstorms’ and thunderstorms winds’ events in the United States of America, in the period from 1996 to 2022, under the marked spatio-temporal self-exciting point processes point of view. The aim of the present article is the assessment and description of the spatio-temporal spontaneous and reproducing activity of severe hailstorms’ and thunderstorms winds’ processes. The present application shows how the spatio-temporal pattern is well-fitted and clearly explainable, according to the flexible semi-parametric ETAS model fitting.

The Jersey tornado and hailstorm of 1–2 November 2023

AbstractA powerful tornado affected eastern parts of Jersey, Channel Islands, on the night of Wednesday 1 and Thursday 2 November 2023, associated with a supercell thunderstorm. As well as spawning the tornado, the parent thunderstorm also produced a severe hailstorm, with hailstones upwards of 5cm in diameter documented. A TORRO site investigation, assisted by staff from Jersey Met, concluded that the tornado produced a continuous damage path across the east of the island of around 8km in length, with a width of up to 500m. The tornado was assigned a provisional rating of T6 on the International Tornado Intensity Scale.

Effects of Defoliation at Different Fertility Stages on Material Accumulation, Physiological Indices and Yield of Cotton

In recent years, severe hailstorms have caused damage to cotton leaves and stalks. In order to identify the effects of cotton leaf damage on its dry matter accumulation, protective enzyme activity and yield in different periods, in this experiment, different intensities of hail were simulated by manual leaf cutting. In this study, the effects of leaf damage on dry matter accumulation, chlorophyll fluorescence, POD (peroxidase), SOD (superoxide dismutase) and MDA levels (malondialdehyde), and yield of cotton were studied in field experiments at three stages (bud, full bud and flower boll stages) and in sub-plots with different artificial defoliation intensities (0%, 25%, 50%, 75% and 100%). Removing the leaf sources had differently sized effects on the “sink” at each stage, and these are ordered as follows: flowering and boll stage > full bud stage > pregnancy stage. The greater the intensity of leaf removal, the greater the impact on the “sink”. Among them, after removing 50% of the leaves at the full bud stage, the total dry matter of the cotton plant increased by 12.46% compared to that of the control, and the boll formation rate per plant increased by 14.99%, resulting in overcompensation. Mo, Vj and φDo all showed a tendency to decrease and then increase with the increase in defoliation intensity at different periods of the treatment, and the lowest values of Mo, Vj and φDo, and the largest values of φpo, ψo and φEo were found in the 50% defoliation treatment at the gestational bud stage. The values of ψo and φEo were at the maximum in the 25% defoliation treatment at the full bud stage. The values of Mo and Vj in the different defoliation treatments at the bolling stage showed a tendency to increase and then decrease with the increase in defoliation intensity, with the highest values in the 25% treatment and the smallest values of φpo, ψo and φEo in the 25% defoliation treatment. The POD enzyme activity level was elevated in the defoliation treatments at the three different periods, and the highest value was observed in the 50% defoliation group at the full bud and boll stages, which is a reflection of supercompensation. The SOD enzyme activity level tended to increase with the intensity of defoliation, and defoliation at the gestational and full bud stages first enhanced and then weakened the stress on the cotton plants. The differences between treatments decreased after 12 weeks. The stress of defoliation on cotton plants was weakened at the boll stage. With the increase in defoliation intensity, the content of MDA showed a gradual increasing trend. The cotton MDA content was higher than that of the other treatments at 75% defoliation at both the post-fertilized bud and full bud stage.

Hodographs and Skew Ts of Hail-Producing Storms

Abstract Environments associated with severe hailstorms, compared to those of tornadoes, are often less apparent to forecasters. Understanding has evolved considerably in recent years; namely, that weak low-level shear and sufficient convective available potential energy (CAPE) above the freezing level is most favorable for large hail. However, this understanding comes only from examining the mean characteristics of large hail environments. How much variety exists within the kinematic and thermodynamic environments of large hail? Is there a balance between shear and CAPE analogous to that noted with tornadoes? We address these questions to move toward a more complete conceptual model. In this study, we investigate the environments of 92 323 hail reports (both severe and nonsevere) using ERA5 modeled proximity soundings. By employing a self-organizing map algorithm and subsetting these environments by a multitude of characteristics, we find that the conditions leading to large hail are highly variable, but three primary patterns emerge. First, hail growth depends on a favorable balance of CAPE, wind shear, and relative humidity, such that accounting for entrainment is important in parameter-based hail prediction. Second, hail growth is thwarted by strong low-level storm-relative winds, unless CAPE below the hail growth zone is weak. Finally, the maximum hail size possible in a given environment may be predictable by the depth of buoyancy, rather than CAPE itself.

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network

Abstract Geostationary satellite imagers provide historical and near-real-time observations of cloud-top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to Next Generation Weather Radar (NEXRAD) estimated maximum expected size of hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are made where satellites observe cold clouds, indicative of convection, located in favorable storm environments. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. Statistical distributions of convective parameters from satellite and reanalysis show separation between nonsevere and severe hailstorm classes for predictors that include overshooting cloud-top temperature and area characteristics, vertical wind shear, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a likelihood estimate with a critical success index of 0.511 and Heidke skill score of 0.407, which is exceptional among analogous hail studies. Furthermore, applications of the DNN to case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-yr Geostationary Operational Environmental Satellite (GOES) image database from GOES-12/13 to derive a hail frequency and severity climatology, which denotes the central Great Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied.

Impacts of a Severe Hailstorm on a White-Tailed Deer Population in East-Central Alabama

Impacts of a Severe Hailstorm on a White-Tailed Deer Population in East-Central Alabama

Hailstorms and rainstorms versus supercells—a regional analysis of convective storm types in the Alpine region

The behaviour of severe thunderstorms, particularly supercells, in complex terrain is still poorly understood. Utilising 6 years of radar-, lightning- and radiosounding-based thunderstorm data in the domain of the Swiss radar network, we study different thunderstorm types in separate topographical regions. We classify the storms as ordinary thunderstorms, intense and severe rainstorms, hail and severe hailstorms and supercellular storms. After identifying the overlaps between the storm categories of rainstorms, hailstorms and supercells, the life cycles of several intensity metrics are investigated. This analysis allows the identification of predictors for intensification within severe storm life cycles. One of the most important predictors is the detection of a mesocyclone in a supercell before the onset or intensification of hail. We then divide the radar domain into sub-regions ranging from the Northwestern Po Valley, the Southern Prealps, main Alpine ridge, Northern Prealps, Swiss Plateau and Jura. This regional split separates storms in different terrain complexities. An investigation of the intensity distribution of storms in each region shows a clear intensity decrease over the main Alpine ridge, intermediate values over the moderately complex Prealpine regions and peaks for the flat Po Valley and Swiss Plateau. In contrast, the highest frequency of storms is found in the Prealpine regions on each side, with a lower frequency in the flat areas and a minimum in convective activity over the main Alpine ridge.

Effects of Microphysics Parameterizations on Forecasting a Severe Hailstorm of 30 April 2021 in Eastern China

On the evening of 30 April 2021, a severe hailstorm swept across eastern China, causing catastrophic gale and damaging hailstones. This hailstorm event was directly caused by two mesoscale convective systems associated with strong squall lines, with mid-level cold advection from the northeast cold vortex, and strong low-level convergence associated with the low-level vortex and wind shear line. Double nesting of the high-resolution weather research and forecasting model (9–1 km) is utilized to simulate this hailstorm with five microphysics schemes. The radar-based maximum estimated size of hail (MESH) algorithm, differential reflectivity and fractions skill scores were used to quantitatively evaluate the precision. All schemes basically captured the two squall lines that swept through eastern China, although they appeared one or two hours earlier than observation. Particularly, Goddard and Thompson performed better in the MESH swath and fractions skill scores among the five different schemes. However, Thompson most realistically captured the reflectivity pattern, intensity and vertical structure of mesoscale convective systems. Its high-reflectivity column corresponded to the maximum center of the hail mixing ratio within the updraft region, which is consistent with the characteristics of a pulse-type hailstorm in its mature phase.

Characteristics of Summer Hailstorms Observed by Radar and Himawari-8 in Beijing, China

Severe hailstorms frequently occurred in Beijing between May and August 2021, leading to extensive hail damage. These hailstorms were observed by radar and satellite data, and reported by surface observers. In this study, the spectral and cloud microphysical characteristics of typical Beijing events in 2021 were analyzed using Himawari-8 satellite products and ground-based S-band weather radar data obtained from the Beijing Meteorological Bureau. The relationship between Himawari-8 brightness temperature differences (BTD) and radar reflectivity was also investigated. The results revealed that the significant spectral depression of brightness temperatures (BTs) in hail clouds was observed by a satellite. Furthermore, the stronger the radar reflectivity was, the more rapidly BTD decreased, with a nonlinear relationship between them. The results of cloud physical characteristics show that, for cloud-top heights above 10 km, the cloud effective radius was about 25 μm, with a cloud-top temperature of 225 K during these hail events. By means of Gaussian fitting, the BT threshold value (11.2 μm) was determined by satellite at 230 K, with a BTD focused on 1.9 K when hailstorms occurred. These results will help us better understand the characteristics of hailstorms, while also providing information for future hail suppression in Beijing.

Storm splitting process and the associated mechanisms for a long-lived hailstorm

Storm splitting poses a great challenge in storm tracking and forecasting. However, most of previous studies have focused on the effect of warm rain microphysics on storm splitting, that of ice microphysics, especially hail microphysics on hailstorm splitting remain unknown. The storm splitting and associated mechanisms for a long-lived severe hailstorm occurred on 19 June 2017 in Beijing are investigated in this study based on radar observations and simulated results from a three-dimensional cloud model with hail-bin microphysics. The results show that the hailstorm experienced twice splitting. Both right-moving and left-moving cells strengthened in the first splitting, while only the right-moving cell strengthened in the secondary splitting. It is found that the clockwise-curved hodograph environment initially creates asymmetric negative pressure perturbations at the low levels. With the development of the storm, the negative pressure perturbations are strengthened, lifted, and evolved as vertically clockwise- or anticlockwise-rotating low-pressure centers, which significantly enhance both upward and outward pressure gradient forces at the levels where the low-pressure centers are located, and selectively induce the updraft development on the flanks of the storm, resulting in the low-level upward-curved updraft splitting structure. In the mature and decaying stage of the storm, strong downward propagating gravity waves excited by high graupel/hail loading through buoyancy oscillations are found to have a critical role in the subsequent rapid updraft splitting prior to the graupel/hail-induced downdraft. Both the gravity waves and graupel/hail-induced downdraft have important roles in the hailstorm splitting rather than rain-induced downdraft as proposed in previous studies.

The summer 2021 Switzerland hailstorms: weather situation, major impacts and unique ­observational data

On 28 June and 8 July 2021, all the ingredients for severe convection were present and resulted in severe hailstorms over Switzerland, causing historic damage, as recorded by several insurance companies. The return periods of those events locally exceeded 70–100 years according to the new Swiss hail climatology. A coherent and comprehensive picture of those hailstorms is given by a unique combination of hail observing systems: automatic hail sensors, crowdsourced reports and radar-based algorithms. (Figure: Sturmarchiv Schweiz/www.sturmarchiv.ch © Martin Hotz, Steinhausen.)

A Hail of a Night in Mexico

When a severe hailstorm hit Mexico’s capital last week, citizens began to wonder whether climate change could be the cause. But is that the right question to ask?

Simulation of a Hailstorm Event over Bangladesh using WRF Model

An attempt is made to simulate a pre-monsoon hailstorm event over Bangladesh using the high-resolution Weather Research and Forecasting (WRF) model. A severe hailstorm event embedded with multi-cell thunderstorm occurred over the North-central region of Bangladesh and adjacent West Bengal state of India on 30 March 2018, which moved towards the South-East direction up to its highest intensity stage during 0900-1030 UTC is selected for the study. The WRF model is used to investigate the dynamical and thermodynamical characteristics of the selected hail producing thunderstorm event. The model is run on a double nested domain at 9 and 3 km horizontal resolutions using the Kain-Fritsch (new Eta) cumulus and Mellor-Yamada Nakanishi and Niino Level 2.5 (MYNN2) planetary boundary layer parameterization schemes. The analysis of the accumulated hail, mean sea level pressure, vertical wind shear, vertical (w) component of wind, relative humidity along with low level wind, convective available potential energy (CAPE) and convective inhibition energy (CINE), rainfall (mm) parameters are investigated. Rainfall is compared with that of observed value. The high amount of relative humidity (>90%), CAPE (>3000 JKg-1) and vertical wind shear (>40 ms-1) help to form severe convective storm which vertically developed upto 150 hPa level. In addition, the high value of w component of winds (~0.4 ms-1) helps updraft process which is favorable for hail formation. The present combination of parameterization schemes of model is found suitable to capture the selected hailstorm event reasonably well, but more similar hailstorm events need to be studied to make any final conclusions. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 123-130

Combined Space- and Ground-Based GNSS Monitoring of Two Severe Hailstorm Cases in Bulgaria

Abstract Monitoring atmospheric conditions that lead to severe weather events is critical to their timely and accurate prediction and can help prevent of large economic losses. Bulgaria, located in southeastern Europe, has the highest mean number of thunderstorms and hailstorms. These events generally occur between April and September with a peak in July. In this study, both radio occultation (RO) and ground-based observations from the Global Navigation Satellite Systems (GNSS) were used to study two severe hailstorms that occurred in 2014 and 2019. In both storms, a cold upper-air pool was detected in addition to a large specific humidity anomaly between 2 and 6 km. In the hailstorm that occurred in July 2014, there was an RO temperature anomaly between 10 and 14 km as well as a positive specific humidity anomaly between 4 and 6 km. The integrated vapor transport (IVT) reanalysis from ERA5, indicated that the high specific humidity over the Mediterranean could be tracked to an atmospheric river over the North Atlantic, which was connected to a tropical cyclone. In the hailstorm that occurred in May 2019, elevated IVT values were observed before the storm. During this storm, a negative temperature anomaly peak was observed in the RO profile at 11.3 km as well as a positive specific humidity anomaly between 2 and 4.5 km. The WRF Model and the ERA5 dataset could reproduce the temperature profiles for both storms relatively well; however, they tended to underestimate specific humidity. The RO profiles were complemented by ground-based GNSS tropospheric delays with high temporal resolution. The evaluation of the WRF with ground-based GNSS tropospheric products revealed a time delay between the modeled and observed developments of both hailstorms.

A case study of a severe hailstorm in Mendoza, Argentina, during the RELAMPAGO-CACTI field campaign

Storms in central Argentina are known for producing large and severe hail. Environmental conditions and strong interaction with topography in this region provide unique conditions for the initiation and intensification of severe storms. The RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations) and CACTI (Clouds, Aerosols, and Complex Terrain Interactions) field campaigns deployed between October 2018 and April 2019 over west-central Argentina have collected unprecedented periods of intensive observation in the region. During the Intense Observation Period (IOP) number 10 (November 26, 2018), 4 cm diameter hail was reported over wide areas of the province of Mendoza. This was the first time a severe hailstorm was measured with multi-platform observations in Mendoza as the IOP deployment included multiple atmospheric soundings, observations from the Center for Severe Weather Research (CSWR) Doppler on Wheel radars (DOWs) and high temporal resolution satellite data from the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM) onboard GOES-16. High-temporal frequency soundings and surface observations collected prior to the convection initiation are analyzed, allowing a detailed description of the pre-convective environment. The establishment of the upslope flow and the role of boundary layer processes that resulted in the development of the severe hailstorm are also analyzed. In addition, several GOES-16 ABI and GLM derived products are investigated, in order to test their ability to forecast convective initiation and provide hail proxies in the region.