Supercell Thunderstorms 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.

Novel Comparison of Pyrocumulonimbus Updrafts to Volcanic Eruptions and Supercell Thunderstorms Using Optical Flow Techniques

AbstractConvective dynamics in a supercell thunderstorm, a volcanic eruption, and two pyrocumulonimbus (pyroCb) events are compared by computing cloud‐top divergence (CTD) with an optical flow technique called Deepflow. Visible 0.64‐μm imagery sequences from Geostationary Operational Environmental Satellites (GOES)‐R series Advanced Baseline Imager (ABI) are used as input into the optical flow algorithm. CTD is computed after post‐processing of the retrieved motions. Analysis is performed on specific image times, as well as the full time series of each case. Multiple CTD‐based parameters, such as the maximum and the two‐dimensional area exceeding a specified CTD threshold, are examined along with the optical flow‐retrieved wind speed. CTD is shown to accurately and quantitatively represent the behavior and magnitude of different deep convective phenomena, including distinguishing between convective pulses within each individual event. CTD captures updraft intensification as well as differences in convective activity between two pyroCb events and individual updraft pulses occurring within a single pyroCb event. Finally, the characteristics of high‐altitude smoke plumes injected by two separate pyroCb pulses are linked to CTD using ultraviolet aerosol index and satellite imagery. Optical flow‐derived parameters can therefore be applied to individual pyroCbs in real‐time, with potential to characterize pyroCb smoke source inputs for downstream smoke modeling applications and to facilitate future tools supporting air quality modeling and firefighting efforts.

How Does Vertical Wind Shear Influence Updraft Characteristics and Hydrometeor Distributions in Supercell Thunderstorms?

Abstract Vertical wind shear is known to affect supercell thunderstorms by displacing updraft hydrometeor mass downshear, thereby facilitating the storms’ longevity. Shear also impacts the size of supercell updrafts, with stronger shear leading to wider, less dilute, and stronger updrafts with likely greater hydrometeor production. To more clearly define the role of shear across different vertical layers on hydrometeor concentrations and displacements relative to supercell updrafts, a suite of idealized numerical model simulations of supercells was conducted. Shear magnitudes were systematically varied across the 0–1, 1–6, and 6–12 km AGL layers, while the thermodynamic environment was held fixed. Simulations show that as shear magnitude increases, especially from 1 to 6 km, updrafts become wider and less dilute with an increase in hydrometeor loading, along with an increase in the low-level precipitation area/rate and total precipitation accumulation. Even with greater updraft hydrometeor loading amid stronger shear, updrafts are more intense in stronger shear simulations due to larger thermal buoyancy owing to wider, less dilute updraft cores. Furthermore, downshear hydrometeor displacements are larger in environments with stronger 1–6-km shear. In contrast, there is relatively less sensitivity of hydrometeor concentrations and displacements to variations in either 0–1- or 6–12-km shear. Results are consistent across free tropospheric relative humidity sensitivity simulations, which show an increase in updraft size and hydrometeor mass with increasing free tropospheric relative humidity owing to a reduction in entrainment-driven dilution for wider updrafts in moister environments. Significance Statement Rotating thunderstorms, known as supercells, are able to persist for multiple hours. One common explanation is that large changes in wind speed and/or direction with height, or shear, transport rain/hail away from supercell updrafts, supporting their maintenance. The strong shear within supercell environments, however, may also lead to greater rail/hail amounts, thereby leading to weaker storms due to this extra mass of water/ice within updrafts. Furthermore, the impact of shear across different height layers on supercell rain/hail characteristics has not been thoroughly investigated. In this study, computer simulations of supercells were conducted to determine that shear occurring between 1 and 6 km above ground level has a large impact on rain/hail distribution in supercells and that stronger shear in this layer leads to wider/stronger supercells with greater rain/hail accumulations at the surface. Additionally, some of the extra mass of water/ice is transported farther away from updrafts due to the stronger environmental storm-relative winds.

SWIRL: The First Australian Operational Radar-Based 3D Wind Analysis System

Abstract In this paper, the first Australian operational radar-based three-dimensional (3D) wind analysis system named Synthetic Wind Information from Radar and Lidar (SWIRL) is described and evaluated. SWIRL employs a variational minimization formulation to combine results from four individual wind retrieval techniques of varied complexity to derive 3D winds in single-Doppler and multi-Doppler radar regions: a variational version of the traditional velocity azimuth display (VVAD) and double VAD (DVAD) techniques, a single-Doppler wind retrieval technique using optical flow horizontal wind proxies, and a multi-Doppler 3D wind retrieval technique. The SWIRL 3D wind components are evaluated against wind profiler observations and radar simulations using a very high-resolution (50 m) numerical simulation of a supercell thunderstorm. We find that SWIRL can retrieve very accurate horizontal winds, especially below 2-km height in the multi-Doppler regions, with mean absolute errors on wind speed and direction < 2 m s−1 and 10° on average and <2.5 m s−1 and 15°–20° 90% of the time. These errors do not increase noticeably with wind speed, highlighting the suitability of these retrieved winds to be used for damaging and destructive wind detection and nowcasting. The single-Doppler retrieval using optical flow is also found to provide reasonably accurate winds at these heights. The accurate retrieval of convective-scale updrafts and downdrafts, even using multi-Doppler information, is still a major challenge, with mean absolute errors of vertical velocity of about 50% on average. This can be attributed to the limitations of the current radar technology used operationally, imposing slow antenna speeds. Significance Statement Damaging and destructive winds have the potential to inflict significant damage to properties and assets and, tragically, result in loss of life. Efficient direction of emergency services to affected areas is essential for a prompt return to normal conditions. Wind farm operators require precise information on anticipated wind shifts to reduce the risk of energy grid failures. Strong winds also contribute to compound weather events, such as water ingress through hail-damaged roofs or structural damage to buildings caused by hailstones. The purpose of this work was to equip Australia with the first operational wind monitoring system, based on operational radar observations, to serve all these critical applications (and more).

The influence of thunderstorm type on extreme near-surface wind speeds: Iowa case study

The derecho of August 10, 2020 that impacted Iowa and neighboring states is the costliest thunderstorm disaster in U.S. history. A derecho, which features prolonged and destructive winds, is a type of thunderstorm which has different near-surface wind generating mechanisms than typically assumed in wind engineering. The derecho event prompted two research questions with respect to wind engineering: (1) should derechos, and more broadly thunderstorm type, be considered separately? and (2) how unique is this particular derecho event?Wind speeds for design in the U.S. are currently estimated using an approach where probability distributions of all thunderstorm winds are analyzed through a mixed distribution. Using Automated Surface Observing System (ASOS) and radar data from the National Weather Service, thunderstorm events with ASOS wind speeds >58 mph (26 m/s) were classified by thunderstorm type: single-cell, multicellular, or supercell thunderstorms in Iowa. An extreme value analysis was done on each thunderstorm type. Multicellular thunderstorms, like the August 2020 derecho, dominate the extreme wind climatology in Iowa. Evaluating the uniqueness of the derecho event required a post-damage assessment. Analysis from failed and unfailed street signs and nearby anemometry was used to estimate peak wind speeds approaching 120 mph (50 m/s).

Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground

Abstract. Hail is a major threat associated with severe thunderstorms, and estimating the hail size is important for issuing warnings to the public. For the validation of existing operational, radar-derived hail estimates, ground-based observations are necessary. Automatic hail sensors, for example within the Swiss Hail Network, record the kinetic energy of hailstones to estimate the hail sizes. Due to the small size of the observational area of these sensors (0.2 m2), the full hail size distribution (HSD) cannot be retrieved. To address this issue, we apply a state-of-the-art custom trained deep learning object detection model to drone-based aerial photogrammetric data to identify hailstones and estimate the HSD. Photogrammetric data of hail on the ground were collected for one supercell thunderstorm crossing central Switzerland from southwest to northeast in the afternoon of 20 June 2021. The hail swath of this intense right-moving supercell was intercepted a few minutes after the passage at a soccer field near Entlebuch (canton of Lucerne, Switzerland) and aerial images were taken by a commercial DJI drone, equipped with a 45-megapixel full-frame camera system. The resulting images have a ground sampling distance (GSD) of 1.5 mm per pixel, defined by the focal length of 35 mm of the camera and a flight altitude of 12 m above the ground. A 2-dimensional orthomosaic model of the survey area (750.4 m2) is created based on 116 captured images during the first drone mapping flight. Hail is then detected using a region-based convolutional neural network (Mask R-CNN). We first characterize the hail sizes based on the individual hail segmentation masks resulting from the model detections and investigate the performance using manual hail annotations by experts to generate validation and test data sets. The final HSD, composed of 18 207 hailstones, is compared with nearby automatic hail sensor observations, the operational weather-radar-based hail product MESHS (Maximum Expected Severe Hail Size) and crowdsourced hail reports. Based on the retrieved data set, a statistical assessment of sampling errors of hail sensors is carried out. Furthermore, five repetitions of the drone-based photogrammetry mission within 18.65 min facilitate investigations into the hail-melting process on the ground.

Simulated WSR-88D Observations of the Streamwise Vorticity Current

The streamwise vorticity current (SVC) has been shown in recent research to have a role in the tornadogenesis process in some supercells. Although field experiments have succeeded in observing the feature using mobile radars, limited knowledge exists on how/if SVCs can be observed using operational radars. To explore this possibility, simple radar emulation software was used to create simulated Weather Surveillance Radar 1988 Doppler (WSR-88D) radar images of an SVC in a high-resolution numerical simulation of a supercell thunderstorm. This proof-of-concept approach shows that SVCs likely can be observed in an operational setting under idealized circumstances. Two analysis times from the simulation are used to compare the signatures of both a weak and a strong SVC. This study suggests that results are highly contingent on radar viewing angle, and quality observations of the SVC may only be possible when a storm is within 45 km of the radar site. In Plan Position Indicator (PPI) scans, SVCs are found to be associated with inflow winds that penetrate more rearward with height downstream of the mesocyclone. Range Height Indicator (RHI) reconstructions show a reflectivity billow that resembles a density current head containing a Kelvin-Helmholtz (KH) billow, as well as a radial velocity couplet co-located with the SVC. A vertical shear product is introduced to visualize low-level vertical wind shear in the vicinity of the SVC to facilitate identification of the feature without interrogation of multiple elevation angles of radial velocity data.

Radar Characteristics of Supercell Thunderstorms Traversing the Appalachian Mountains

Abstract The evolution of supercell thunderstorms traversing complex terrain is not well understood and remains a short-term forecast challenge across the Appalachian Mountains of the eastern United States. Although case studies have been conducted, there has been no large multicase observational analysis focusing on the central and southern Appalachians. To address this gap, we analyzed 62 isolated warm-season supercells that occurred in this region. Each supercell was categorized as either crossing (∼40%) or noncrossing (∼60%) based on their maintenance of supercellular structure while traversing prominent terrain. The structural evolution of each storm was analyzed via operationally relevant parameters extracted from WSR-88D radar data. The most significant differences in radar-observed structure among storm categories were associated with the mesocyclone; crossing storms exhibited stronger, wider, and deeper mesocyclones, along with more prominent and persistent hook echoes. Crossing storms also moved faster. Among the supercells that crossed the most prominent peaks and ridges, significant increases in base reflectivity, vertically integrated liquid, echo tops, and mesocyclone intensity/depth were observed, in conjunction with more frequent large hail and tornado reports, as the storms ascended windward slopes. Then, as the supercells descended leeward slopes, significant increases in mesocyclone depth and tornado frequency were observed. Such results reinforce the notion that supercell evolution can be modulated substantially by passage through and over complex terrain. Significance Statement Understanding of thunderstorm evolution and severe weather production in regions of complex terrain remains limited, particularly for storms with rotating updrafts known as supercell thunderstorms. This study provides a systematic analysis of numerous warm season supercell storms that moved through the central and southern Appalachian Mountains. We focus on operationally relevant radar characteristics and differences among storms that maintain supercellular structure as they traverse the terrain (crossing) versus those that do not (noncrossing). Our results identify radar characteristics useful in distinguishing between crossing and noncrossing storms, along with typical supercell evolution and severe weather production as storms cross the more prominent peaks and ridges of the central and southern Appalachian Mountains.

Idealized Simulations of a Supercell Interacting with an Urban Area

Idealized simulations with a cloud-resolving model are conducted to examine the impact of a simplified city on the structure of a supercell thunderstorm. The simplified city is created by enhancing the surface roughness length and/or surface temperature relative to the surroundings. When the simplified city is both warmer and has larger surface roughness relative to its surroundings, the supercell that passes over it has a larger updraft helicity (at both midlevels and the surface) and enhanced precipitation and hail downwind of the city, all relative to the control simulation. The storm environment within the city has larger convective available potential energy which helps stimulate stronger low-level updrafts. Storm relative helicity (SRH) is actually reduced over the city, but enhanced in a narrow band on the northern edge of the city. This band of larger SRH is ingested by the primary updraft just prior to passing over the city, corresponding with enhancement to the near-surface mesocyclone. Additional simulations in which the simplified city is altered by removing either the heat island or surface roughness length gradient reveal that the presence of a heat island is most closely associated with enhancements in updraft helicity and low-level updrafts relative to the control simulation.

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.

Supercell Thunderstorms in Complex Topography—How Mountain Valleys with Lakes Can Increase Occurrence Frequency

Abstract This study investigates the effects of lakes in mountainous terrain on the evolution of supercell thunderstorms. With a newly developed radar-based, mesocyclone-detection algorithm, a recent study has characterized the occurrence and evolution of supercell thunderstorms in the Swiss Alpine region. That study highlights the influence of orography on both storm intensity and occurrence frequency. To disentangle the different influential factors, an idealized modeling framework is established here using the mesoscale model CM1. The modeling scenarios are based on a high-CAPE environment with unidirectional shear, where a warm bubble serves to initiate the convection. Mimicking the environment of the southern Prealps in central Europe, scenarios with a high mountain ridge, valleys, and lakes are explored. The effect on the supercells of the slopes, high-altitude terrain, and moisture sources emphasizes the highly localized nature of terrain effects, leading to a heterogeneous intensity life cycle with transitory enhancement and weakening of the supercell. The dynamic and thermodynamic impact of mountain valleys with lakes increases the range of atmospheric conditions that supports supercellular development through horizontal vorticity production, increased storm relative helicity, and higher moisture content. This influence results in a systematic location dependence of the frequency, intensity, and lifetime of supercells, as also found in observations.

The Influence of Midlevel Shear and Horizontal Rotors on Supercell Updraft Dynamics

Abstract Large midlevel (3–6 km AGL) shear is commonly observed in supercell environments. However, any possible influence of midlevel shear on an updraft has been relatively unexplored until now. To investigate, we ran 10 simulations of supercells in a range of environments with varying midlevel shear magnitudes. In most cases, larger midlevel shear results in a storm motion that is faster relative to the low-level hodograph, meaning that larger midlevel shear leads to stronger low-level storm-relative flow. Because they are physically connected, we present an analysis of the effects of both midlevel shear and low-level storm-relative flow on supercell updraft dynamics. Larger midlevel shear does not lead to an increase in cohesive updraft rotation. The tilting of midlevel environmental vorticity does lead to localized areas of larger vertical vorticity on the southern edge of the updraft, but any dynamical influence of this is overshadowed by that of much larger horizontal vorticity in the same area associated with rotor-like circulations. This storm-generated horizontal vorticity is the primary driver behind lower nonlinear dynamic pressure on the southern flank of the midlevel updraft when midlevel shear and low-level storm-relative flow are larger, which leads to a larger nonlinear dynamic pressure acceleration in those cases. Storm-generated horizontal vorticity is responsible for the lowest nonlinear dynamic pressure anywhere in the midlevel updraft, unless the mesocyclone becomes particularly intense. These results clarify the influence of midlevel shear on a supercell thunderstorm, and provide additional insight on the role of low-level storm-relative flow on updraft dynamics. Significance Statement Persistent rotation in supercell thunderstorms results from the tilting of horizontal spin into the vertical direction. This initially horizontal spin is the result of shear, which is a change in wind speed and/or direction with height. More shear in the layer 0–3 km above ground level is well understood to lead to stronger rotation within the storm, but the influence of shear in the 3–6-km layer is unclear and is investigated here. We find that horizontal spin originating in the 3–6-km layer has little impact on vertically oriented thunderstorm rotation. Instead, intense regions of horizontal spin that are generated by the storm itself (rather than having originated from the background environment) dominate storm dynamics at midlevels.

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.

Investigating the Development and Characteristics of Streamwise Vorticity Currents Produced by Outflow Surges in Simulated Supercell Thunderstorms

Abstract Streamwise vorticity currents (SVCs) have been hypothesized to enhance low-level mesocyclones within supercell thunderstorms and perhaps increase the likelihood of tornadogenesis. Recent observational studies have confirmed the existence of SVCs in supercells and numerical simulations have allowed for further investigation of SVCs. A suite of 19 idealized supercell simulations with varying midlevel shear orientations is analyzed to determine how SVC formation and characteristics may differ between storms. In our simulations, SVCs develop on the cold side of left-flank convergence boundaries and their updraft-relative positions are partially dependent on downdraft location. The magnitude, duration, and mean depth of SVCs do not differ significantly between simulations or between SVCs that precede tornado-like vortices (TLVs) and those that do not. Trajectories initialized within SVCs reveal two primary airstreams, one that flows through an SVC for the majority of its length, and another that originates in the modified inflow in the forward flank and then merges with the SVC. Vorticity budgets calculated along trajectories reveal that the first airstream exhibits significantly greater maximum streamwise vorticity magnitudes than the second airstream. The vorticity budgets also indicate that stretching of horizontal streamwise vorticity is the dominant contributor to the large values of streamwise vorticity within the SVCs. TLV formation does not require the development of an SVC beforehand; 44% of TLVs in the simulations are preceded by SVCs. When an SVC occurs, it is followed by a TLV 53% of the time, indicating not all SVCs lead to TLV formation. Significance Statement Streamwise vorticity currents (SVCs) are features within thunderstorms hypothesized to strengthen updraft rotation and increase the likelihood of tornado formation. SVCs in a suite of 19 thunderstorm simulations are analyzed to investigate how they develop, if their characteristics differ between storms, and how often they precede tornado production. The rotation in an SVC is amplified as air accelerates toward the updraft, which is the main process contributing to SVC formation. The likelihood of SVCs may vary with differences in the winds 3–6 km above the ground. These findings may aid in developing strategies for better observing SVCs.

Forecast Applications of GLM Gridded Products: A Data Fusion Perspective

Abstract The recently deployed GOES-R series Geostationary Lightning Mapper (GLM) provides forecasters with a new, rapidly updating lightning data source to diagnose, forecast, and monitor atmospheric convection. Gridded GLM products have been developed to improve operational forecast applications, with variables including flash extent density (FED), minimum flash area (MFA), and total optical energy (TOE). While these gridded products have been evaluated, there is a continual need to integrate these products with other datasets available to forecasters such as radar, satellite imagery, and ground-based lightning networks. Data from the Advanced Baseline Imager (ABI), Multi-Radar Multi-Sensor (MRMS) system, and one ground-based lightning network were compared against gridded GLM imagery from GOES-East and GOES-West in case studies of two supercell thunderstorms, along with a bulk study from 13 April to 31 May 2019, to provide further validation and applications of gridded GLM products from a data fusion perspective. Increasing FED and decreasing MFA corresponded with increasing thunderstorm intensity from the perspective of ABI infrared imagery and MRMS vertically integrated reflectivity products, and was apparent for more robust and severe convection. Flash areas were also observed to maximize between clean-IR brightness temperatures of 210–230 K and isothermal reflectivity at −10°C of 20–30 dBZ. TOE observations from both GLMs provided additional context of local GLM flash rates in each case study, due to their differing perspectives of convective updrafts. Significance Statement The Geostationary Lightning Mapper (GLM) is a lightning sensor on the current generation of U.S. weather satellites. This research shows how data from the space-based lightning sensor can be combined with radar, satellite imagery, and ground-based lightning networks to improve how forecasters monitor thunderstorms and issue warnings for severe weather. The rate of GLM flashes detected and the area they cover correspond well with radar and satellite signatures, especially in cases of intense and severe thunderstorms. When the GLM observes the same thunderstorm from the GOES-East and GOES-West satellites, the optical energy (brightness) of the flashes may help forecasters interpret the types of flashes observed from each sensor.

Using Ensemble Sensitivity Analysis to Identify Storm Characteristics Associated with Tornadogenesis in High-Resolution Simulated Supercells

Abstract This study aims to objectively identify storm-scale characteristics associated with tornado-like vortex (TLV) formation in an ensemble of high-resolution supercell simulations. An ensemble of 51 supercells is created using Cloud Model version 1 (CM1). The first member is initialized using a base state populated by the Rapid Update Cycle (RUC) proximity sounding near El Reno, Oklahoma, on 24 May 2011. The other 50 ensemble members are created by randomly perturbing the base state after a supercell has formed. There is considerable spread between ensemble members, with some supercells producing strong, long-lived TLVs, while others do not produce a TLV at all. The ensemble is analyzed using the ensemble sensitivity analysis (ESA) technique, uncovering storm-scale characteristics that are dynamically relevant to TLV formation. In the rear flank, divergence at the surface southeast of the TLV helps converge and contract existing vertical vorticity, but there is no meaningful sensitivity to rear-flank outflow temperature. In the forward flank, warm temperatures within the cold pool are important to TLV production and magnitude. The longitudinal positioning of strong streamwise vorticity is also a clear indicator of TLV formation and strength, especially within 5 min of when the TLV is measured. Significance Statement Tornadoes that form in supercell thunderstorms (long-lived storms with a rotating updraft) are heavily influenced by the features created by the storm itself, such as the temperature of a downdraft. In this study, many different iterations of a strong supercell thunderstorm are simulated, in which tornado-like features are formed at different times with widely different strengths. A statistical method is used to identify what the storms had in common when they produced a tornado-like feature, and what they had in common when one failed to form. This study is important because it highlights which storm features are most influential to tornado formation using an objective method, with results that can be used when observing supercells in the field.

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.

Supercell Low-Level Mesocyclones: Origins of Inflow and Vorticity

Abstract The development and intensification of low-level mesocyclones in supercell thunderstorms have often been attributed, at least in part, to augmented streamwise vorticity generated baroclinically in the forward flank of supercells. However, the ambient streamwise vorticity of the environment (often quantified via storm-relative helicity), especially near the ground, is particularly skillful at discriminating between nontornadic and tornadic supercells. This study investigates whether the origins of the inflow air into supercell low-level mesocyclones, both horizontally and vertically, can help explain the dynamical role of environmental versus storm-generated vorticity in the development of low-level mesocyclone rotation. Simulations of supercells, initialized with wind profiles common to supercell environments observed in nature, show that the air bound for the low-level mesocyclone primarily originates from the ambient environment (rather than from along the forward flank) and from very close to the ground, often in the lowest 200–400 m of the atmosphere. Given that the near-ground environmental air comprises the bulk of the inflow into low-level mesocyclones, this likely explains the forecast skill of environmental streamwise vorticity in the lowest few hundred meters of the atmosphere. The low-level mesocyclone does not appear to require much augmentation from the development of additional horizontal vorticity in the forward flank. Instead, the dominant contributor to vertical vorticity within the low-level mesocyclone is from the environmental horizontal vorticity. This study provides further context to the ongoing discussion regarding the development of rotation within supercell low-level mesocyclones. Significance Statement Supercell thunderstorms produce the majority of tornadoes, and a defining characteristic of supercells is their rotating updraft, known as the “mesocyclone.” When the mesocyclone is stronger at lower altitudes, the likelihood of tornadoes increases. The purpose of this study is to understand if the rotation of the mesocyclone in supercells is due to horizontal spin present in the ambient environment or whether additional horizontal spin generated by the storm itself primarily drives this rotation. Our results suggest that inflow air into supercells and low-level mesocyclone rotation are mainly due to the properties of the environmental inflow air, especially near the ground. This hopefully provides further context to how our community views the development of low-level mesocyclones in supercells.

The Influence of Convection Initiation Strength on Subsequent Simulated Supercell Evolution

Abstract Recent studies have shown how very small differences in the background environment of a supercell can yield different outcomes, particularly in terms of tornado production. In this study, we use a novel convection initiation technique to simulate six supercells with a focus on their early development. Each experiment is identical, except for the strength of thermal forcing for the initial convection initiation. Each experiment yields a mature supercell, but differences in storm-scale characteristics like updraft speed, cold pool temperature deficit, and vertical vorticity development abound. Of these, the time when the midlevel updraft strengthens is most strongly related to initiation strength, with stronger thermal forcing favoring quicker updraft development. The same is true for the low-level updraft, with the additional relationship that stronger thermal forcing also tends to yield stronger low-level updrafts for around the first 2 h of the simulations. The experiments with faster updraft development tend to be associated with more rapid surface vortex intensification; however, cold pool evolution differs between simulations with weaker versus stronger thermal forcing. Stronger thermal forcing also yields deviant rightward storm motion earlier in the supercell’s life cycle that remains more consistent for the duration of the simulation. These results highlight the range of supercellular outcomes that are possible across a background environment due to differences in storm-scale initiation strength. They are also of potential importance for predicting the paths and tornado potential of supercells in real time. Significance Statement Despite a better understanding of processes related to tornado production in supercell thunderstorms, forecasters still have difficulty discriminating between tornadic and nontornadic supercells in close proximity to each other within the same severe weather event. In this study, we use six simulations of supercells to examine how these different outcomes can occur. Our results show that, given the same background environment, a storm that is more strongly initiated will exhibit faster updraft development and, possibly, quicker tornado production. The opposite can be said for storms that are more weakly initiated. Differences in initiation strength are also associated with different storm motions. These findings inspire future work to better relate supercell evolution to characteristics of initiation and the environment.

Polarimetric Radar Observations of a Long-Lived Supercell and Associated Tornadoes on 10–11 December 2021

Abstract We present environmental and polarimetric radar observations of a long-lived December supercell that tracked approximately 750 km from Arkansas to northern Kentucky. The storm was associated with two long-track EF4 tornadoes, one of which was among the longest-tracked tornadoes recorded in the United States. The supercell’s life cycle is documented from 2000 UTC 10 to 0700 UTC 11 December 2021, using data from five operational polarimetric weather radars. After convection initiation in central Arkansas, it took nearly 4 h for a supercell to develop. Afterward, the storm’s ZDR column and arc became anomalously large leading up to genesis of the first EF4 tornado. During this time, the storm’s environment had moderate convective available potential energy (CAPE) and strong deep-layer shear. A cell interaction at about 0200 UTC disrupted the supercell updraft, weakening the ZDR arc and column, and initiating the largest radar-implied hailfall event observed with this storm. The remnant circulation associated with the first EF4 tornado did not fully dissipate, and it appeared to merge with the low-level mesocyclone on the nose of a rear-flank downdraft surge likely initiated by the hailfall. It is hypothesized that this merger was important to the intensification of the storm’s second EF4 tornado, which lasted nearly 3 h and traveled approximately 267 km. During the second EF4 tornado the storm experienced decreasing CAPE and increasing storm relative helicity. Increasing interactions with other cells eventually weakened the storm, and its original updraft was obscured before the storm’s remnants dissipated in northern Kentucky. Significance Statement In December 2021, a long-lived supercell thunderstorm produced two long-track, violent tornadoes, including one that produced historic damage across western Kentucky. Radar observations indicate that, once the storm became a supercell, its updraft became anomalously large relative to similar storms studied prior. Simultaneously its storm-relative inflow strengthened markedly, supporting the first long-lived tornado. Interactions with a developing thunderstorm disrupted the supercell’s updraft, leading to hail fallout and updraft weakening. The remnant circulation associated with the first strong tornado merged with the supercell’s updraft and became a rotation source for the second long-track tornado, which persisted for nearly 3 h. Eventually interactions with other thunderstorms weakened the supercell.