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On 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 in. in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Córdoba Province, Argentina. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Córdoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm’s observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-in. (11.38 cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-in. (18 cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 in. (18.8–23.7 cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events.

In Australia, hailstorms present considerable public safety and economic risks, where they are considered the most damaging natural hazard in terms of annual insured losses. Despite these impacts, the current climatological distribution of hailfall across the continent is still comparatively poorly understood. This study aims to supplement previous national hail climatologies, such as those based on environmental proxies or satellite radiometer data, with more direct radar-based hail observations. The heterogeneous and incomplete nature of the Australian radar network complicates this task and prompts the introduction of some novel methodological elements. We introduce an empirical correction technique to account for hail reflectivity biases at C band, derived by comparing overlapping C- and S-band observations. Furthermore, we demonstrate how object-based hail swath analysis may be used to produce resolution-invariant hail frequencies, and describe an interpolation method used to create a spatially continuous hail climatology. The maximum estimated size of hail (MESH) parameter is then applied to a mixture of over 50 operational radars in the Australian radar archive, resulting in the first nationwide, radar-based hail climatology. The spatiotemporal distribution of hailstorms is examined, including their physical characteristics, seasonal and diurnal frequency, and regional variations of such properties across the continent.

The layered structures inside hailstones provide a direct indication of their shape and properties at various stages during growth. Given the myriad of different trajectories that can exist, and the sensitivity of rime deposit type to environmental conditions, it must be expected that many different perturbations of hailstone properties occur within a single hailstorm; however, some commonalities are likely in the shared early stages of growth, for hailstones of similar size (especially those that grow along similar trajectories) and final growth near the melting level. It remains challenging to extract this information from a large sample of hailstones because of the time required to prepare cross sections and accurately measure individual layers. To reduce the labour and potential errors introduced by manual analysis of hailstones, an automated method for measuring layers from cross section photographs is introduced and applied to a set of hailstones collected in Melbourne, Australia. This work is motivated by new hail growth simulation tools that model the growth of layers within individual hailstones, for which accurate measurements of observed hailstone cross sections can be applied as validation. A first look at this new type of evaluation for hail growth simulations is demonstrated.

The central east coast of Australia is frequently impacted by large hail and damaging winds associated with severe convective storms, with individual events recording damages exceeding AUD 1 billion. These storms present a significant challenge for forecasting because of their development in seemingly marginal environments. They often have been observed to intensify upon approaching the coast, with case studies and climatological analyses indicating that interactions with the sea breeze are key to this process. The relative importance of the additional lifting and vorticity along the sea-breeze front in comparison with the change to a cooler, moister air mass with stronger low-level shear behind the front has yet to be investigated. Here, the role of the sea-breeze air mass is isolated using idealized numerical simulations of storms developing in a horizontally homogeneous environment. The base-state substitution (BSS) modeling technique is utilized to introduce the sea-breeze air mass following initial storm development. Relative to a simulation without BSS, the storm is longer lived and more intense, ultimately developing supercell characteristics including increased updraft rotation, deviant motion to the left of the mean wind vector, and a strong reflectivity gradient on the inflow edge. Separately simulating the changes in the thermodynamic and wind fields reveals that the enhanced storm longevity and intensity are primarily due to the latter. The change in the low-level environmental winds slows gust-front propagation, allowing the storm to continue to ingest warm, potentially buoyant environmental air. At the same time, increased low-level shear promotes the development of persistent updraft rotation that causes the storm to make a transition from a multicell to a supercell.

Linear precipitation systems are a prominent contributor to rainfall over Melbourne, Australia, and the surrounding region. These systems are often convective in nature, frequently associated with cold fronts, and in some cases can lead to significant rainfall and flash flooding. Various types of linearly organized systems (e.g., squall lines, quasi-linear convective systems) have been the subject of much research in the United States and elsewhere, but thus far relatively little analysis has been done on linear systems in Australia. To begin to understand rainfall extremes and how they may change in this region in the future, it is useful to explore the contribution of these types of systems and the characteristics that define them. To this end, we have examined the recently developed Australian Radar Archive (AURA), identifying objects that meet a specific set of relevant criteria, and used multiple methods to identify heavy and extreme daily rainfall. We found that on average, days with linear systems contribute over half of the total rainfall and 70%–85% of heavy/extreme rainfall in the Melbourne region. The linear systems that occur on heavy rainfall days tend to be larger, slower-moving, and longer-lived, while those on extreme rainfall days also tend to be more intense and have a greater degree of southward propagation than linear systems on other days.

Observations made by weather radars play a central role in many aspects of meteorological research and forecasting. These applications commonly require that radar data be supplied on a Cartesian grid, necessitating a coordinate transformation and interpolation from the radar’s native spherical geometry using a process known as gridding. In this study, we introduce a variational gridding method and, through a series of theoretical and real data experiments, show that it outperforms existing methods in terms of data resolution, noise filtering, spatial continuity, and more. Known problems with existing gridding methods (Cressman weighted average and nearest neighbor/linear interpolation) are also underscored, suggesting the potential for substantial improvements in many applications involving gridded radar data, including operational forecasting, hydrological retrievals, and three-dimensional wind retrievals.

Three-dimensional wind retrievals from ground-based Doppler radars have played an important role in meteorological research and nowcasting over the past four decades. However, in recent years, the proliferation of open-source software and increased demands from applications such as convective parameterizations in numerical weather prediction models has led to a renewed interest in these analyses. In this study, we analyze how a major, yet often-overlooked, error source effects the quality of retrieved 3D wind fields. Namely, we investigate the effects of spatial interpolation, and show how the common practice of pregridding radial velocity data can degrade the accuracy of the results. Alternatively, we show that assimilating radar data directly at their observation locations improves the retrieval of important dynamic features such as the rear flank downdraft and mesocyclone within supercells, while also reducing errors in vertical vorticity, horizontal divergence, and all three velocity components.

This study uses ship-based weather radar observations collected from research vessel Investigator to evaluate the Australian weather radar network calibration monitoring technique that uses spaceborne radar observations from the NASA Global Precipitation Mission (GPM). Quantitative operational applications such as rainfall and hail nowcasting require a calibration accuracy of ±1 dB for radars of the Australian network covering capital cities. Seven ground-based radars along the western coast of Australia and the ship-based OceanPOL radar are first calibrated independently using GPM radar overpasses over a 3-month period. The calibration difference between the OceanPOL radar (used as a moving reference for the second step of the study) and each of the seven operational radars is then estimated using collocated, gridded, radar observations to quantify the accuracy of the GPM technique. For all seven radars the calibration difference with the ship radar lies within ±0.5 dB, therefore fulfilling the 1 dB requirement. This result validates the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks (provided that the spaceborne radar maintains a high calibration accuracy). The analysis of the day-to-day and hourly variability of calibration differences between the OceanPOL and Darwin (Berrimah) radars also demonstrates that quantitative comparisons of gridded radar observations can accurately track daily and hourly calibration differences between pairs of operational radars with overlapping coverage (daily and hourly standard deviations of ∼ 0.3 and ∼ 1 dB, respectively).

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.