Supercell Storm Research Articles

The remarkable Jersey hailstorm of 1–2 November 2023: description and comparison with other cool season, dual‐hazard storms

AbstractAround midnight on 1/2 November 2023, Jersey (Channel Islands) was impacted by a supercell storm which produced both a tornado, rated T6/IF3, and very large hail. This article presents details of that remarkable hailstorm and places it into context by investigating severe hail events during the October–March cool season in the UK and Crown Dependencies of Jersey, Guernsey, and the Isle of Man. The storm is compared to previous ‘dual‐hazard’ events during the cool season, where both a tornado and severe hail were produced.

Analysis of a Case of a Classical Supercell Storm in Bihar, India: Observation and Tracking

In this study, we use the S-band Doppler Weather Radar to analyze the weather of a prolonged classical supercell storm that occurred on April 7, 2018, across the Indian state of Bihar. In the early morning hours of April 7th, 2018, a supercell storm with its origins in a colliding cloud mass produced in the Himalayan foothills invaded the Himalayan foothills from the North-West of Bihar via East Uttar Pradesh. The echo top increased to over 14 kilometers as it moved through the Bihar districts of Siwan and Gopalganj. As it followed, the storm shifted direction, heading northwest. Maximum radar reflectivity reached up to 61 dBz at 11: 32 IST observation (seen from Doppler Weather Radar, Patna), which may be the highest reflectivity ever recorded at DWR (Doppler Weather Radar) Station, Patna. It stopped being a supercell at 13: 30 IST and convert into a multicellular storm. A strange hook echo could be seen off the Storm's back in the Vertical Integrated Liquid profile. The supercell had two linked outflows, one to the northeast and one to the southeast. The Supercell's inverted "V"-shaped front flank was another characteristic feature. Within a small vertical band along the echo wall, reflectance reached over 60 dB at its highest. There was significant divergence near the peak of the supercell storm, with the speed differential between the updraft and downdraft reaching around 60 m/s. The system lasted for about 7 to 8 hours, damaging hailstorms occurred often along the path. Hail stones larger than 6-7 mm in diameter were spotted (as per the observed report). This particular cell was determined to be a supercell based on its internal structure, reflectivity, duration, and ground-level weather pattern. The incidence, timing, and development of the storms were all accurately predicted by the convective outlook products 2 to 3 hours in advance.

Evaluation of Lightning Flash Rate Parameterizations in a Cloud‐Resolved WRF‐Chem Simulation of the 29–30 May 2012 Oklahoma Severe Supercell System Observed During DC3

AbstractEighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud‐resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly‐developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model‐simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model‐simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor‐based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

The impact of aerosols and model grid spacing on a supercell storm from Swabian MOSES 2021

AbstractThe supercell storm that occurred in southwestern Germany on June 23, 2021, had an exceptionally long lifetime of 7.5 hr, travelled a distance of nearly 190 km, and produced large amounts of hail. During that summer, the Swabian MOSES field campaign was held in that area, and several hydro‐meteorological measurements are available, as the storm passed directly over the main observation site. We present hindcasts of this event with the Icosahedral Non‐hydrostatic model using two horizontal grid spacings (i.e., 2 km, 1 km) with a single‐moment and an advanced double‐moment microphysics scheme. Numerical results show that all 2 km model realizations do not simulate convective precipitation at the correct location and time. For the 1 km grid spacing, changes in aerosol concentration resulted in large changes in convective precipitation. Only the 1 km run assuming a low cloud condensation nuclei (CCNs) concentration is able to realistically capture the storm, whereas no supercell is simulated in the more polluted scenarios. Observed aerosol particle concentrations indicate that CCNs values were the lowest of the month, which suggests that the low aerosol concentration is a reasonable assumption. The thermodynamic structure of the pre‐convective environment, as well as other observations, showed the best agreement to this model run as well, indicating that the good representation of the supercell was obtained for the right reason. The automatic tracking of individual clouds revealed that more convective cells with longer lifetimes are simulated at finer resolution. We also find a negative aerosol–precipitation effect that is not only due to a reduced collision–coalescence process, but also to weaker cold‐rain processes. These findings demonstrate the benefits of using an aerosol‐aware double‐moment microphysics scheme for convective‐scale predictability and that the use of different CCNs concentrations can determine whether a supercell is successfully simulated or not.

A New Pathway for Tornadogenesis Exposed by Numerical Simulations of Supercells in Turbulent Environments

Abstract A simulation of a supercell storm produced for a prior study on tornado predictability is reanalyzed for the purpose of examining the fine-scale details of tornadogenesis. It is found that the formation of a tornado-like vortex in the simulation differs from how such vortices have been understood to form in previous numerical simulations. The main difference between the present simulation and past ones is the inclusion of a turbulent boundary layer in the storm’s environment in the present case, whereas prior simulations have used a laminar boundary layer. The turbulent environment contains significant near-surface vertical vorticity (ζ > 0.03 s−1 at z = 7.5 m), organized in the form of longitudinal streaks aligned with the southerly ground-relative winds. The ζ streaks are associated with corrugations in the vertical plane in the predominantly horizontal, westward-pointing environmental vortex lines; the vortex-line corrugations are produced by the vertical drafts associated with coherent turbulent structures aligned with the aforementioned southerly ground-relative winds (longitudinal coherent structures in the surface layer such as these are well known to the boundary layer and turbulence communities). The ζ streaks serve as focal points for tornadogenesis, and may actually facilitate tornadogenesis, given how near-surface ζ in the environment can rapidly amplify when subjected to the strong, persistent convergence beneath a supercell updraft. Significance Statement In high-resolution computer simulations of supercell storms that include a more realistic, turbulent environment, the means by which tornado-like vortices form differs from the mechanism identified in prior simulations using a less realistic, laminar environment. One possibility is that prior simulations develop intense vortices for the wrong reasons. Another possibility could be that tornadoes form in a wide range of ways in the real atmosphere, even within supercell storms that appear to be similar, and increasingly realistic computer simulations are finally now capturing that diversity.

Understanding the Effects of Aerosols on Electrification and Lightning Polarity in an Idealized Supercell Thunderstorm via Model Emulation

AbstractAerosol effects on the lightning intensity and polarity of a continental supercell storm were investigated using a three‐dimensional lightning scheme within the Weather Research and Forecasting model. We find that both intra‐cloud (IC) and cloud‐to‐ground (CG) flashes are enhanced by the increasing number of cloud condensation nuclei (CCN), especially the percentage of positive CG (+CG) strokes peaking at 42%. Electrical characteristics of the storm varied in different aerosol scenarios through microphysical processes. Added aerosols increase the number of cloud droplets and ice‐phase hydrometeors. The greater ice‐crystal concentration and larger graupel size ensure sufficient charge separation, leading to higher charge density and more lightning discharges. In addition, an inverted polarity charge structure with a strong positive‐charge region in the mid‐levels was formed mainly due to the positively charged graupel in the presence of higher supercooled cloud water content. Positive lightning channels originating from this positive‐charge region propagated to the ground, producing more +CG strokes. When the aerosol concentration was low, the charge density in the upper positive‐charge region was much lower due to smaller ice‐particle content. Consequently, there were barely any +CG strokes. Most of the negative CG flashes deposited positive charge in the lower negative‐charge region.

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

Diagnosing Factors Leading to an Incorrect Supercell Thunderstorm Forecast

Abstract On 28 April 2019, hourly forecasts from the operational High-Resolution Rapid Refresh (HRRR) model consistently predicted an isolated supercell storm late in the day near Dodge City, Kansas, that subsequently was not observed. Two convection-allowing model (CAM) ensemble runs are created to explore the reasons for this forecast error and implications for severe weather forecasting. The 40-member CAM ensembles are run using the HRRR configuration of the WRF-ARW Model at 3-km horizontal grid spacing. The Gridpoint Statistical Interpolation (GSI)-based ensemble Kalman filter is used to assimilate observations every 15 min from 1500 to 1900 UTC, with resulting ensemble forecasts run out to 0000 UTC. One ensemble only assimilates conventional observations, and its forecasts strongly resemble the operational HRRR with all ensemble members predicting a supercell storm near Dodge City. In the second ensemble, conventional observations plus observations of WSR-88D radar clear-air radial velocities, WSR-88D diagnosed convective boundary layer height, and GOES-16 all-sky infrared brightness temperatures are assimilated to improve forecasts of the preconvective environment, and its forecasts have half of the members predicting supercells. Results further show that the magnitude of the low-level meridional water vapor flux in the moist tongue largely separates members with and without supercells, with water vapor flux differences of 12% leading to these different outcomes. Additional experiments that assimilate only radar or satellite observations show that both are important to predictions of the meridional water vapor flux. This analysis suggests that mesoscale environmental uncertainty remains a challenge that is difficult to overcome. Significance Statement Forecasts from operational numerical models are the foundation of weather forecasting. There are times when these models make forecasts that do not come true, such as 28 April 2019 when successive forecasts from the operational High-Resolution Rapid Refresh (HRRR) model predicted a supercell storm late in the day near Dodge City, Kansas, that subsequently was not observed. Reasons for this forecast error are explored using numerical experiments. Results suggest that relatively small changes to the prestorm environment led to large differences in the evolution of storms on this day. This result emphasizes the challenges to operational severe weather forecasting and the continued need for improved use of all available observations to better define the atmospheric state given to forecast models.

СТРУКТУРА ПОЛОСЫ ОБНОВЛЕНИЯ В МОЩНЫХ КОНВЕКТИВНЫХ ШТОРМАХ

Based on several examples of radar observations in the North Caucasus and the Republic of Moldova, the renewal of deep convective cloud systems (storms) due to feeder clouds are investigated. It is shown that the direction of the renewal band coincides with the storm evolution vector. The structure of the renewal band for multicell and supercell storms differs, because the supercells contain the mesocyclones that generate convergent flows around the center of rotation. A new phenomenon was found: two multicell storms merged at a node of a mesoscale convective structure and then split up and continued to develop along divergent trajectories. The study results are applicable in hail protection, precipitation redistribution operations, and storm warning of the population.

Application of multi-source data in a tornado process in Jiangsu province

This paper analyzes the weather background and triggering mechanism before the occurrence of an EF3 tornado on 14 May 2021, in southern Jiangsu, using multi-source data. Results show that 1) the tornado occurred in the warm and humid area inside the low-level shear line and the inverted trough at the surface, the southeast wind field to the east of the surface convergence line and high value area of water vapor flux on the left side of low altitude jet axis exit zone. 2) The intensity of the heavy rainfall supercell storm was strengthened after entering the Taihu Lake, and mesocyclones were detected with decreasing heights and increasing shear strengths which leading to the formation of the tornado parent storm. Tornado vortex storm bottom height dropped to 0.3km, the shear value increased to 169.1 × 10−3 s-1, strong echoes above 60 dBZ reached to the ground, the difference between the lowest elevation Radial velocity (LLDV) and the maximum Radial velocity (MXDV) reached up to the largest value when tornado occurred. 3) The strong convergence of the ground and the enhancement of mesoscale frontal zone resulted in the strong development of thunderstorm cells. The deep rear inflow behind the heavy precipitation supercell storm passed through the stratiform cloud area and produced strong updraft due to the convergence of wind direction and wind speed. The updrafts generated vertical vorticity under the influence of wind shear, which was further stretched in the middle layer of the troposphere to form the core of the tornado. 4) The flat underlying surface, abundant water vapor, lake surface thermal boundary, and strong wind convergence on the east bank of Taihu Lake provided favorable conditions for the occurrence of the tornado. The centers of the mesocyclones in the lower and middle layers were close to each other in the horizontal direction, which provided stable and vertical updrafts for the mesocyclones and strengthened the suction effect of the mesocyclones on the low-level vortices, facilitating the formation of the tornado.

Spatial distribution and precipitation intensity of supercells: Response to terrain asymmetry in the Western Carpathians, Central Europe

Empirically based research presents a challenge posing a question as to how much the complex terrain affects the behavior of actual supercell storms. An investigation took place in the Western Carpathians in Central Europe during warm seasons over a period of 5 years. The occurrence of 62 supercells was identified by mesocyclone/supercell features in two-dimensional radar products. Specifically, in the fields of Doppler radial velocity and reflectivity factor. Statistical qualities of radar reflectivity at 2–6 km above mean sea level and around approximate mesocyclone centers within 5, 10 and 15-km radius were perceived as an estimated precipitation intensity descriptor. Reflectivity data were compared with several terrain attributes such as elevation, slope angle and curvature. Results suggest that supercells were spatially bonded to the mountains, e.g., through initiation sites that were predominantly placed over leeward slopes. A mountain-related propagation pattern of storms based on their translation speed was observed as well. Overall, storms did not appear to be unable to traverse significantly higher terrain, and they did not become stronger or weaker while doing so. Most of their maximum precipitation intensity was situated in the lowlands. The accumulation of precipitation intensity revealed, though, that the largest values were concentrated over two elevated regions. The general relation between changing precipitation intensity and the terrain was not found and remained insignificant, suggesting that terrain-related effects may impact the precipitation intensity of storms rather on a case-by-case basis. The strongest, if moderate positive correlation of 0.4 was assigned to the pairs of fast-moving supercells and current elevation of the ground within 15-km radius along the paths of the storms.

Dynamical Analyses of a Supercell Tornado in Eastern China Based on a Real-Data Simulation

Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a Meiyu frontal system. To investigate the dynamical process of the tornado, a numerical simulation was performed using four one-way nested grids within the Advanced Regional Prediction System (ARPS). Data from a nearby operational S-band Doppler radar are assimilated using a 4D ensemble Kalman filter (4DEnKF) at 5 min intervals. Forecasts are run with a nested 50 m grid, capturing the tornado embedded within the supercell storm with a reasonable agreement with observations. The tornadogenesis processes within the simulation results are analyzed in detail, including the three-dimensional evolution of the tornado vortex. It is found that a cold surge within the rear flank downdraft region plays a key role in instigating tornadogenesis when the leading edge of the cold surge approaches a near-ground convergence center located underneath the main updraft, and the enhancement of the convergence center caused by the descending of the low-level mesocyclone is the direct cause of the rapid increase in tornado vorticity. Backward trajectories are calculated based on model output, and the origins of the parcels feeding the intensifying tornado vortex are identified. It is found that parcels from the mid-level of the rear flank downdraft region follow the cold surge, descending to the ground under the influence of the downdraft in the cold surge, and then entering the convergence center, merging into the core of the tornado and being lifted up. Vertical profiles of the mass and vorticity fluxes into the core of the tornado vortex are examined, and it is found that the near-ground airflow contributes significantly to the growth of the tornado vorticity, with the contribution increasing as it gets closer to the ground.

Simultaneous Multiscale Data Assimilation Using Scale‐ and Variable‐Dependent Localization in EnVar for Convection Allowing Analyses and Forecasts: Methodology and Experiments for a Tornadic Supercell

AbstractThis study introduces a simultaneous multiscale data assimilation method by implementing model space spatial scale‐dependent localization (SDL) and variable‐dependent localization (VDL) within an ensemble variational system. This method updates all resolved scales by assimilating all observations at once. The impact of such an approach is examined by a series of radar data assimilation experiments. Single‐observation experiments show that SDL concurrently and more properly updates the storm and its ambient environments compared to a traditional single scale localization (SSL) for radar data assimilation. Including VDL on top of SDL (SDLVDL) realistically decreases the spatial coverage and intensity of moisture increments compared to SDL. Comparisons are then performed on the analyses and forecasts of the 8 May 2003 Oklahoma City supercell storm. Results show that SDL improves the analyses and forecasts during the data assimilation cycling by producing more realistic enhanced low‐level convergences than SSL. SDLVDL obtains more accurate analyses and subsequent forecasts for moisture than SDL. SDLVDL yields the best performance in reflectivity forecasts and storm maintenance. Compared to SSL, SDL has higher forecast skills before 2230 UTC and produces degraded forecasts in the later lead time.

Study of the correlation between electrical activity and the microphysics and dynamsics of a real severe event using the WRF‐ELEC model

AbstractAtmospheric electrical activity is one of the most damaging meteorological phenomena. Studies suggest that storm electrical discharges are correlated with severe weather events such as hail, strong surface winds, etc. To study these correlations, in addition to real data, numerical simulations can be used. In this work, we investigated the electrical activity of simulated thunderstorms using the WRF‐ELEC model over a case study of the RELAMPAGO field campaign (11 December 2018) associated with the occurrence of generalized deep moist convection in central Argentina including some supercell storms. The WRF‐ELEC model successfully reproduced the convective event. A tracking algorithm was used to individualize different convective cells and to study the relationship between their electric activity and different microphysical and kinematic variables. The model reproduced the expected correlations and time lags between these variables. In particular, the model showed that the best correlation occurred between the graupel and hail mass and the electric activity of the storms; this is expected given the key role of these microphysical species in the charge separation processes. Also, 5 m·s−1 updraft volume and cloud top temperature (CTT) temporal evolutions presented good correlations with the electrical activity. Maximum updraft show a less but still good correlation with the electrical activity. We also investigated the correlation between the electrical activity and the hail and graupel concentration near the surface (as an indicator of hail precipitation) and the near‐surface winds and we found that correlation is strong. In particular, for near‐surface ice, we determined that peaks in electrical activity precede peaks in hail and graupel precipitation and that electrical activity could be used as a proxy of this high‐impact weather event.

Unraveling the dynamics of an intense pre-monsoon hailstorm and summer monsoon deep convective system over the central Himalayas using a VHF radar

Himalayan region being influenced by extratropical and monsoon weather systems coupled with orographically forced convection, are frequently impacted by severe thunderstorms. Negligible ground based observations over this region have restricted the analysis of these storms up to coarse statistical features utilising reanalysis data and space-borne radar missions. High spatiotemporal resolution of the Very High Frequency (VHF) radars makes them well suited for the study of large convective storms. In this context, a 206.5 MHz ARIES ST Radar (ASTRAD) facility at Nainital (29.4oN, 79.5°E, 1793 m amsl) has been used to probe mesoscale dynamics of severe deep convective systems in the pre-monsoon and monsoon season for the first time over the Himalayan region. Pre-monsoon event on May 5, 2020 was observed to have characteristic features of a supercell storm resulting in a nearly two hour long hailstorm (∼1430–1630 IST). Vigorous updrafts with maxima of 15.5 ms-1 were observed extending from the mid-troposphere to up to the lower stratosphere region and downdrafts up to 15.7 ms−1 were detected in the lower troposphere within the hailstorm. Hodographs during peak convective activity revealed strongly ‘veered’ winds up to upper troposphere with Storm Relative Helicity maxima of 484 m2s−2. The strength of convection was moderate (updrafts maxima of 4.5 ms−1) in summer monsoon case on September 2, 2020. In this case, trailing stratiform region is observed with double bright band structure in the radar reflectivity factor. Weakening of the stratified stable layer structures in the UTLS region have been observed for both the case in the regions of strong updraft gradients. Spectral and hodograph analysis of the quasi sinusoidal undulations in the wind components fluctuations revealed the presence of upward propagating short-period gravity waves in the Upper Troposphere and the Lower Stratosphere (UTLS) region for both the cases. The observed period of oscillation was 35.6 min and 27 min with vertical wavelengths of ∼8.4 km and ∼ 5.7 km for the May 5 and September 2 case respectively. Momentum flux enhancement of 30–40 times was observed during convection with extremely large values during the hailstorm indicating enhanced flux exchange between troposphere and stratosphere. The findings of this study will aid the forecasting of these storms and improve their simulation in the mesoscale models, particularly over this Himalayan region having complex topography.

Trailing Horizontal Vortices in Observed and Numerically Simulated Tornadoes

Abstract High-resolution numerical simulations of supercell storms reveal complex distributions of vorticity in the vicinity of tornadoes, especially when visualized in three dimensions. As in the simulations, quasi-horizontal vortices (HVs) are occasionally observed near tornadoes, as condensation tubes wrapping around the tornadoes. In this study, visual observations of a violent tornado and visualizations of a high-resolution simulation based on the same tornado case are combined to document distinct HV structures, which trail the tornado very close to the ground toward its right flank (with respect to the tornado’s forward motion), hereafter referred to as “trailing HVs.” The analysis shows that trailing HVs are larger and stronger than HVs typically observed around tornadoes. Still, their sense of rotation matches that of other documented HVs, which is consistent with vorticity generation by surface drag and/or baroclinic torques along internal boundaries of relatively warm rear-flank downdrafts. Interestingly, trailing HVs may display smaller spiral vortices circulating their periphery, which can evolve into more complex structures. Visualizations of three-dimensional vorticity show that the trailing HVs are organized through entanglement of large and small HVs along nearby rear-flank internal boundaries. The internal boundaries also serve as focus for along-boundary stretching of vorticity that becomes mostly streamwise at the location of the trailing HV, resulting in HV strengthening. The spiral vortices are associated with the same entangling processes responsible for the parent (larger) trailing HV structure. Moreover, the analysis suggests that trailing HVs may reinforce the surface wind speeds on the right flank of the tornado.

Ensemble Cloud Model Application in Simulating the Catastrophic Heavy Rainfall Event

An attempt has been made in the present research to simulate a deadly flash-flood event over the City of Skopje, Macedonia on 6 August 2016. A cloud model ensemble forecast method is developed to simulate a super-cell storm's initiation and evolutionary features. Sounding data are generated using an ensemble approach, that utilizes a triple-nested WRF model. A three-dimensional (3-D) convective cloud model (CCM) with a very fine horizontal grid resolution of 250-m is initialized, using the initial representative sounding data, derived from the WRF 1-km forecast outputs. CCM is configured and run with an open lateral boundary conditions LBC, allowing explicit simulation of convective scale processes. This preliminary study showed that the ensemble approach has some advantages in the generation of the initial data and the model initialization. The applied method minimizes the uncertainties and provides a more qualitative-quantitative assessment of super-cell storm initiation, cell structure, evolutionary properties, and intensity. A high-resolution 3-D run is capable to resolve detailed aspects of convection, including high-intensity convective precipitation. The results are significant not only from the aspect of the cloud model's ability to provide a qualitative-quantitative assessment of intense precipitation but also for a deeper understanding of the essence of storm development, its vortex dynamics, and the meaning of micro-physical processes for the production and release of large amounts of precipitation that were the cause of the catastrophic flood in an urban area. After a series of experiments and verification, such a system could be a reliable tool in weather services for very short-range forecasting (nowcasting) and early warning of weather disasters.

A Method for Correcting Staggered Pulse Repetition Time (PRT) and Dual Pulse Repetition Frequency (PRF) Processor Errors in Research Radar Datasets

Abstract Mobile weather radars at high frequencies (C, X, K, and W bands) often collect data using staggered pulse repetition time (PRT) or dual pulse repetition frequency (PRF) modes to extend the effective Nyquist velocity and mitigate velocity aliasing while maintaining a useful maximum unambiguous range. These processing modes produce widely dispersed “processor” dealiasing errors in radial velocity estimates. The errors can also occur in clusters in high shear areas. Removing these errors prior to quantitative analysis requires tedious manual editing and often produces “holes” or regions of missing data in high signal-to-noise areas. Here, data from three mobile weather radars were used to show that the staggered PRT errors are related to a summation of the two Nyquist velocities associated with each of the PRTs. Using observations taken during a mature mesoscale convective system, a landfalling tropical cyclone, and a tornadic supercell storm, an algorithm to automatically identify and correct staggered PRT processor errors has been developed and tested. The algorithm creates a smooth profile of Doppler velocities using a Savitzky–Golay filter independently in radius and azimuth and then combined. Errors are easily identified by comparing the velocity at each range gate to its smoothed counterpart and corrected based on specific error characteristics. The method improves past dual PRF correction methods that were less successful at correcting “grouped” errors. Given the success of the technique across low, moderate, and high radial shear regimes, the new method should improve research radar analyses by affording the ability to retain as much data as possible rather than manually or objectively removing erroneous velocities.

Distinguishing between Hodographs of Severe Hail and Tornadoes

Abstract Hodographs are valuable sources of pattern recognition in severe convective storm forecasting. Certain shapes are known to discriminate between single cell, multicell, and supercell storm organization. Various derived quantities such as storm-relative helicity (SRH) have been found to predict tornado potential and intensity. Over the years, collective research has established a conceptual model for tornadic hodographs (large and “looping,” with high SRH). However, considerably less attention has been given to constructing a similar conceptual model for hodographs of severe hail. This study explores how hodograph shape may differentiate between the environments of severe hail and tornadoes. While supercells are routinely assumed to carry the potential to produce all hazards, this is not always the case, and we explore why. The Storm Prediction Center (SPC) storm mode dataset is used to assess the environments of 8958 tornadoes and 7256 severe hail reports, produced by right- and left-moving supercells. Composite hodographs and indices to quantify wind shear are assessed for each hazard, and clear differences are found between the kinematic environments of hail-producing and tornadic supercells. The sensitivity of the hodograph to common thermodynamic variables was also examined, with buoyancy and moisture found to influence the shape associated with the hazards. The results suggest that differentiating between tornadic and hail-producing storms may be possible using properties of the hodograph alone. While anticipating hail size does not appear possible using only the hodograph, anticipating tornado intensity appears readily so. When coupled with buoyancy profiles, the hodograph may assist in differentiating between both hail size and tornado intensity.

Doppler Lidar and Mobile Radiosonde Observation-Based Evaluation of Warn-on-Forecast System Predicted Near-Supercell Environments during TORUS 2019

Abstract Observational data collection is extremely hazardous in supercell storm environments, which makes for a scarcity of data used for evaluating the storm-scale guidance from convection allowing models (CAMs) like the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS). The Targeted Observations with UAS and Radar of Supercells (TORUS) 2019 field mission provided a rare opportunity to not only collect these observations, but to do so with advanced technology: vertically pointing Doppler lidar. One standing question for WoFS is how the system forecasts the feedback between supercells and their near-storm environment. The lidar can observe vertical profiles of wind over time, creating unique datasets to compare to WoFS kinematic predictions in rapidly evolving severe weather environments. Mobile radiosonde data are also presented to provide a thermodynamic comparison. The five lidar deployments (three of which observed tornadic supercells) analyzed show WoFS accurately predicted general kinematic trends in the inflow environment; however, the predicted feedback between the supercell and its environment, which resulted in enhanced inflow and larger storm-relative helicity (SRH), were muted relative to observations. The radiosonde observations reveal an overprediction of CAPE in WoFS forecasts, both in the near and far field, with an inverse relationship between the CAPE errors and distance from the storm. Significance Statement It is difficult to evaluate the accuracy of weather prediction model forecasts of severe thunderstorms because observations are rarely available near the storms. However, the TORUS 2019 field experiment collected multiple specialized observations in the near-storm environment of supercells, which are compared to the same near-storm environments predicted by the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS) to gauge its performance. Unique to this study is the use of mobile Doppler lidar observations in the evaluation; lidar can retrieve the horizontal winds in the few kilometers above ground on time scales of a few minutes. Using lidar and radiosonde observations in the near-storm environment of three tornadic supercells, we find that WoFS generally predicts the expected trends in the evolution of the near-storm wind profile, but the response is muted compared to observations. We also find an inverse relationship of errors in instability to distance from the storm. These results can aid model developers in refining model physics to better predict severe storms.