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Abstract
Tornadoes produced by right-moving supercells (RMs) and quasi-linear convective systems (QLCSs) are compared across the contiguous United States for the period 2003–21, based on the maximum F/EF-scale rating per hour on a 40-km horizontal grid. The frequency of QLCS tornadoes has increased dramatically since 2003, while the frequency of RM tornadoes has decreased during that same period. The finding of prior work that the most common damage rating for QLCS tornadoes at night is EF1 persists in this larger, independent sample. A comparison of WSR-88D radar attributes between RM and QLCS tornadoes shows no appreciable differences between EF0 tornadoes produced by either convective mode. Differences become apparent for EF1–2 tornadoes, where rotational velocity is larger and velocity couplet diameter is smaller for RM tornadoes compared to QLCS tornadoes. The frequency of tornadic debris signatures (TDSs) in dual-polarization data is also larger for EF1–2 RM tornadoes when controlling for tornadoes sampled relatively close to the radar sites and in those occurring during daylight versus overnight. The weaker rotational velocities, broader velocity couplet diameters, and lower frequencies of TDSs both close to the radar and at night for QLCS EF1 tornadoes suggest that a combination of inadequate radar sampling and occasional misclassification of wind damage may be responsible for the irregularities in the historical record of QLCS tornado reports.
Significance Statement
A comparison of radar attributes between tornadoes with right-moving supercells and squall-line mesovortices suggests some irregularities in squall-line tornado records in the contiguous United States. The irregularities appear to be the result of both inadequate radar sampling for the relatively shallow squall-line tornadoes and occasional misclassification of wind damage with the lack of other corroborating evidence, especially overnight.
Abstract
Tornadoes produced by right-moving supercells (RMs) and quasi-linear convective systems (QLCSs) are compared across the contiguous United States for the period 2003–21, based on the maximum F/EF-scale rating per hour on a 40-km horizontal grid. The frequency of QLCS tornadoes has increased dramatically since 2003, while the frequency of RM tornadoes has decreased during that same period. The finding of prior work that the most common damage rating for QLCS tornadoes at night is EF1 persists in this larger, independent sample. A comparison of WSR-88D radar attributes between RM and QLCS tornadoes shows no appreciable differences between EF0 tornadoes produced by either convective mode. Differences become apparent for EF1–2 tornadoes, where rotational velocity is larger and velocity couplet diameter is smaller for RM tornadoes compared to QLCS tornadoes. The frequency of tornadic debris signatures (TDSs) in dual-polarization data is also larger for EF1–2 RM tornadoes when controlling for tornadoes sampled relatively close to the radar sites and in those occurring during daylight versus overnight. The weaker rotational velocities, broader velocity couplet diameters, and lower frequencies of TDSs both close to the radar and at night for QLCS EF1 tornadoes suggest that a combination of inadequate radar sampling and occasional misclassification of wind damage may be responsible for the irregularities in the historical record of QLCS tornado reports.
Significance Statement
A comparison of radar attributes between tornadoes with right-moving supercells and squall-line mesovortices suggests some irregularities in squall-line tornado records in the contiguous United States. The irregularities appear to be the result of both inadequate radar sampling for the relatively shallow squall-line tornadoes and occasional misclassification of wind damage with the lack of other corroborating evidence, especially overnight.
Abstract
A conceptual model for sustained low-level mesocyclones is tested as a tornado forecast tool with observations and forecasts from the operational Eta Model. In the conceptual model, a balance between low-level storm inflow and outflow allows the development of a persistent low-level mesocyclone along the rear flank of a supercell thunderstorm, owing largely to the strength of the midlevel storm-relative winds. The present work draws on this conceptual model to identify preferred ranges of low- (model surface level), middle- (500 mb), and upper-level (250-mb) storm-relative wind speeds for 131 supercells, from gridded Eta Model fields. The observations reveal that the 500-mb storm-relative wind speed has a distinct lower bound of approximately 8 m s−1 for the tornadic supercells, while differences between surface-level and 250-mb storm-relative wind speeds for tornadic and nontornadic supercells are much less pronounced. The storm-relative wind speeds are also compared to the bulk Richardson number shear for the purpose of discriminating between tornadic and nontornadic supercells. Test results of storm-relative wind speed at the Eta Model surface level and at 500 mb, derived from gridded Eta forecast fields, demonstrate skill in distinguishing tornadic and nontornadic supercells in daily forecast operations at the Storm Prediction Center.
Abstract
A conceptual model for sustained low-level mesocyclones is tested as a tornado forecast tool with observations and forecasts from the operational Eta Model. In the conceptual model, a balance between low-level storm inflow and outflow allows the development of a persistent low-level mesocyclone along the rear flank of a supercell thunderstorm, owing largely to the strength of the midlevel storm-relative winds. The present work draws on this conceptual model to identify preferred ranges of low- (model surface level), middle- (500 mb), and upper-level (250-mb) storm-relative wind speeds for 131 supercells, from gridded Eta Model fields. The observations reveal that the 500-mb storm-relative wind speed has a distinct lower bound of approximately 8 m s−1 for the tornadic supercells, while differences between surface-level and 250-mb storm-relative wind speeds for tornadic and nontornadic supercells are much less pronounced. The storm-relative wind speeds are also compared to the bulk Richardson number shear for the purpose of discriminating between tornadic and nontornadic supercells. Test results of storm-relative wind speed at the Eta Model surface level and at 500 mb, derived from gridded Eta forecast fields, demonstrate skill in distinguishing tornadic and nontornadic supercells in daily forecast operations at the Storm Prediction Center.
Abstract
An experiment was conducted at the Storm Prediction Center (SPC) to assess the accuracy of subjective probability forecasts for tornadoes within individual convective watch areas. Probability forecasts for one or more and three or more tornadoes were produced for 166 severe weather watches during 1997 and 1998. Categorical forecasts of maximum tornado intensity, as indicated by F-scale damage ratings, were also performed. The probability and intensity forecasts were made in an operational setting prior to the issuance of each watch to simulate the decision making process that might be employed if the SPC were to begin including probabilities in their watch products. Results indicate considerable skill in forecasting tornado probabilities, though the maximum intensity forecasts were not particularly accurate. It is hypothesized that accurate tornado intensity forecasts will be difficult to achieve until storm-scale processes are more fully understood.
Abstract
An experiment was conducted at the Storm Prediction Center (SPC) to assess the accuracy of subjective probability forecasts for tornadoes within individual convective watch areas. Probability forecasts for one or more and three or more tornadoes were produced for 166 severe weather watches during 1997 and 1998. Categorical forecasts of maximum tornado intensity, as indicated by F-scale damage ratings, were also performed. The probability and intensity forecasts were made in an operational setting prior to the issuance of each watch to simulate the decision making process that might be employed if the SPC were to begin including probabilities in their watch products. Results indicate considerable skill in forecasting tornado probabilities, though the maximum intensity forecasts were not particularly accurate. It is hypothesized that accurate tornado intensity forecasts will be difficult to achieve until storm-scale processes are more fully understood.
Abstract
This study tests hypothetical correspondences between size of severe hail, WSR-88D derived vertically integrated liquid water (VIL), and an array of thermodynamic variables derived from computationally modified sounding analyses. In addition, these associations are documented for normalized VIL using various sounding parameters, and statistical predictive value is assigned to the various VIL-based and sounding variables. The database was gathered from Weather Service Radar-1988 Doppler (WSR-88D) units nationwide from cases identified during real-time operations and consists of over 400 hail events, each associated with a radar-observed VIL value and a modified observational sounding.
Some parameters are found to increase in the mean with larger hail-size categories. Specific hail size, however, varies widely across the spectra of VIL, thermodynamic sounding variables, and combinations thereof, with only a few exceptions. No operationally useful parameters of value in hail-size prediction were discovered in the database of VIL and thermodynamic sounding data. These largely antihypothetical findings are compared with hail forecasting and warning techniques developed in the WSR-88D era—few in number and mostly regionalized and informal in nature—and with more widespread and empirical forecasting assumptions involving many of the same variables.
Abstract
This study tests hypothetical correspondences between size of severe hail, WSR-88D derived vertically integrated liquid water (VIL), and an array of thermodynamic variables derived from computationally modified sounding analyses. In addition, these associations are documented for normalized VIL using various sounding parameters, and statistical predictive value is assigned to the various VIL-based and sounding variables. The database was gathered from Weather Service Radar-1988 Doppler (WSR-88D) units nationwide from cases identified during real-time operations and consists of over 400 hail events, each associated with a radar-observed VIL value and a modified observational sounding.
Some parameters are found to increase in the mean with larger hail-size categories. Specific hail size, however, varies widely across the spectra of VIL, thermodynamic sounding variables, and combinations thereof, with only a few exceptions. No operationally useful parameters of value in hail-size prediction were discovered in the database of VIL and thermodynamic sounding data. These largely antihypothetical findings are compared with hail forecasting and warning techniques developed in the WSR-88D era—few in number and mostly regionalized and informal in nature—and with more widespread and empirical forecasting assumptions involving many of the same variables.
Abstract
An overview of conditions associated with the Oklahoma–Kansas tornado outbreak of 3 May 1999 is presented, with emphasis on the evolution of environmental and supercellular characteristics most relevant to the prediction of violent tornado episodes. This examination provides a unique perspective of the event by combining analyses of remote observational data and numerical guidance with direct observations of the event in the field by forecasters and other observers. The 3 May 1999 outbreak included two prolific supercells that produced several violent tornadoes, with ambient parameters comparable to those of past tornado outbreaks in the southern and central Great Plains. However, not all aspects leading to the evening of 3 May unambiguously favored a major tornado outbreak. The problems that faced operational forecasters at the Storm Prediction Center are discussed in the context of this outbreak, including environmental shear and instability, subtle processes contributing to convective initiation, the roles of preexisting boundaries, and storm-relative flow. This examination reveals several specific aspects where conceptual models are deficient and/or additional research is warranted.
Abstract
An overview of conditions associated with the Oklahoma–Kansas tornado outbreak of 3 May 1999 is presented, with emphasis on the evolution of environmental and supercellular characteristics most relevant to the prediction of violent tornado episodes. This examination provides a unique perspective of the event by combining analyses of remote observational data and numerical guidance with direct observations of the event in the field by forecasters and other observers. The 3 May 1999 outbreak included two prolific supercells that produced several violent tornadoes, with ambient parameters comparable to those of past tornado outbreaks in the southern and central Great Plains. However, not all aspects leading to the evening of 3 May unambiguously favored a major tornado outbreak. The problems that faced operational forecasters at the Storm Prediction Center are discussed in the context of this outbreak, including environmental shear and instability, subtle processes contributing to convective initiation, the roles of preexisting boundaries, and storm-relative flow. This examination reveals several specific aspects where conceptual models are deficient and/or additional research is warranted.
Abstract
An analysis of 4 yr of Rapid Update Cycle-2 (RUC-2) derived soundings in proximity to radar-observed supercells and nonsupercells is conducted in an effort to answer two questions: 1) over what depth is the fixed-layer bulk wind differential (BWD; the vector difference between the wind velocity at a given level and the wind velocity at the surface) the best discriminator between supercell and nonsupercell environments and 2) does the upper-tropospheric storm-relative flow (UTSRF) discriminate between the environments of supercells and nonsupercells? Previous climatologies of sounding-based supercell forecast parameters have documented the ability of the 0–6-km BWD in delineating supercell from nonsupercell environments. However, a systematic examination of a wide range of layers has never been documented. The UTSRF has previously been tested as a parameter for discriminating between supercell and nonsupercell environments and there is some evidence that supercells may be sensitive to the UTSRF. However, this sensitivity may be a consequence of the correlation between UTSRF and the surface to midtropospheric BWD. Accurately assessing the ability of the UTSRF to distinguish between supercell and nonsupercell environments requires controlling for the surface to midtropospheric BWD.
It is shown that the bulk wind differential within the 0–5-km layer delineates best between supercell and nonsupercell environments. Analysis of the UTSRF demonstrates that even when not controlling for the BWD, the UTSRF has limited reliability in forecasting supercells. The lack of merit in using the UTSRF to forecast supercells is particularly evident when it is isolated from the BWD. Because the UTSRF and BWD are not independent, controlling for the BWD when examining the UTSRF reveals that the UTSRF is not a fundamental parameter that can be used to distinguish supercell from nonsupercell environments. Therefore, this work demonstrates that the UTSRF is an unreliable metric for forecasting supercell events.
Abstract
An analysis of 4 yr of Rapid Update Cycle-2 (RUC-2) derived soundings in proximity to radar-observed supercells and nonsupercells is conducted in an effort to answer two questions: 1) over what depth is the fixed-layer bulk wind differential (BWD; the vector difference between the wind velocity at a given level and the wind velocity at the surface) the best discriminator between supercell and nonsupercell environments and 2) does the upper-tropospheric storm-relative flow (UTSRF) discriminate between the environments of supercells and nonsupercells? Previous climatologies of sounding-based supercell forecast parameters have documented the ability of the 0–6-km BWD in delineating supercell from nonsupercell environments. However, a systematic examination of a wide range of layers has never been documented. The UTSRF has previously been tested as a parameter for discriminating between supercell and nonsupercell environments and there is some evidence that supercells may be sensitive to the UTSRF. However, this sensitivity may be a consequence of the correlation between UTSRF and the surface to midtropospheric BWD. Accurately assessing the ability of the UTSRF to distinguish between supercell and nonsupercell environments requires controlling for the surface to midtropospheric BWD.
It is shown that the bulk wind differential within the 0–5-km layer delineates best between supercell and nonsupercell environments. Analysis of the UTSRF demonstrates that even when not controlling for the BWD, the UTSRF has limited reliability in forecasting supercells. The lack of merit in using the UTSRF to forecast supercells is particularly evident when it is isolated from the BWD. Because the UTSRF and BWD are not independent, controlling for the BWD when examining the UTSRF reveals that the UTSRF is not a fundamental parameter that can be used to distinguish supercell from nonsupercell environments. Therefore, this work demonstrates that the UTSRF is an unreliable metric for forecasting supercell events.
Abstract
This paper investigates the relationships between short-term convective mode evolution, the orientations of vertical shear and mean wind vectors with respect to the initiating synoptic boundary, the motion of the boundary, and the role of forcing for ascent. The dominant mode of storms (linear, mixed mode, and discrete) was noted 3 h after convective initiation along cold fronts, drylines, or prefrontal troughs. Various shear and mean wind vector orientations relative to the boundary were calculated near the time of initiation. Results indicate a statistical correlation between storm mode at 3 h, the normal components of cloud-layer and deep-layer shear vectors, the boundary-relative mean cloud-layer wind vector, and the type of initiating boundary. Thunderstorms, most of which were initially discrete, tended to evolve more quickly into lines or mixed modes when the normal components of the shear vectors and boundary-relative mean cloud-layer wind vectors were small. There was a tendency for storms to remain discrete for larger normal shear and mean wind components. Smaller normal components of mean cloud-layer wind were associated with a greater likelihood that storms would remain within the zone of linear forcing along the boundary for longer time periods, thereby increasing the potential for upscale linear growth. The residence time of storms along the boundary is also dependent on the speed of the boundary. It was found that the boundary-relative normal component of the mean cloud-layer wind better discriminates between mode types than does simply the ground-relative normal component. The influence of mesoscale forcing for ascent and type of boundary on mode evolution was also investigated. As expected, it was found that the magnitude and nature of the forcing play a role in how storms evolve. For instance, strong linear low-level convergence often contributes to rapid upscale linear growth, especially if the boundary motion relative to the mean cloud-layer wind prevents storms from moving away from the boundary shortly after initiation. In summary, results from this study indicate that, for storms initiated along a synoptic boundary, convective mode evolution is modulated primarily by the residence time of storms within the zone of linear forcing, the nature and magnitude of linear forcing, and secondarily by the normal component of the cloud-layer shear.
Abstract
This paper investigates the relationships between short-term convective mode evolution, the orientations of vertical shear and mean wind vectors with respect to the initiating synoptic boundary, the motion of the boundary, and the role of forcing for ascent. The dominant mode of storms (linear, mixed mode, and discrete) was noted 3 h after convective initiation along cold fronts, drylines, or prefrontal troughs. Various shear and mean wind vector orientations relative to the boundary were calculated near the time of initiation. Results indicate a statistical correlation between storm mode at 3 h, the normal components of cloud-layer and deep-layer shear vectors, the boundary-relative mean cloud-layer wind vector, and the type of initiating boundary. Thunderstorms, most of which were initially discrete, tended to evolve more quickly into lines or mixed modes when the normal components of the shear vectors and boundary-relative mean cloud-layer wind vectors were small. There was a tendency for storms to remain discrete for larger normal shear and mean wind components. Smaller normal components of mean cloud-layer wind were associated with a greater likelihood that storms would remain within the zone of linear forcing along the boundary for longer time periods, thereby increasing the potential for upscale linear growth. The residence time of storms along the boundary is also dependent on the speed of the boundary. It was found that the boundary-relative normal component of the mean cloud-layer wind better discriminates between mode types than does simply the ground-relative normal component. The influence of mesoscale forcing for ascent and type of boundary on mode evolution was also investigated. As expected, it was found that the magnitude and nature of the forcing play a role in how storms evolve. For instance, strong linear low-level convergence often contributes to rapid upscale linear growth, especially if the boundary motion relative to the mean cloud-layer wind prevents storms from moving away from the boundary shortly after initiation. In summary, results from this study indicate that, for storms initiated along a synoptic boundary, convective mode evolution is modulated primarily by the residence time of storms within the zone of linear forcing, the nature and magnitude of linear forcing, and secondarily by the normal component of the cloud-layer shear.
Abstract
Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew T–logp diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10 000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3 × 3 nodes, resulting in a set of nine hodographs and nine skew T–logp diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and midlevel lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.
Abstract
Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew T–logp diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10 000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3 × 3 nodes, resulting in a set of nine hodographs and nine skew T–logp diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and midlevel lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.
Abstract
A sample of 1185 Rapid Update Cycle (RUC) model analysis (0 h) proximity soundings, within 40 km and 30 min of radar-identified discrete storms, was categorized by several storm types: significantly tornadic supercells (F2 or greater damage), weakly tornadic supercells (F0–F1 damage), nontornadic supercells, elevated right-moving supercells, storms with marginal supercell characteristics, and nonsupercells. These proximity soundings served as the basis for calculations of storm-relative helicity and bulk shear intended to apply across a broad spectrum of thunderstorm types. An effective storm inflow layer was defined in terms of minimum constraints on lifted parcel CAPE and convective inhibition (CIN). Sixteen CAPE and CIN constraint combinations were examined, and the smallest CAPE (25 and 100 J kg−1) and largest CIN (−250 J kg−1) constraints provided the greatest probability of detecting an effective inflow layer within an 835-supercell subset of the proximity soundings. Effective storm-relative helicity (ESRH) calculations were based on the upper and lower bounds of the effective inflow layer. By confining the SRH calculation to the effective inflow layer, ESRH values can be compared consistently across a wide range of storm environments, including storms rooted above the ground. Similarly, the effective bulk shear (EBS) was defined in terms of the vertical shear through a percentage of the “storm depth,” as defined by the vertical distance from the effective inflow base to the equilibrium level associated with the most unstable parcel (maximum θe value) in the lowest 300 hPa. ESRH and EBS discriminate strongly between various storm types, and between supercells and nonsupercells, respectively.
Abstract
A sample of 1185 Rapid Update Cycle (RUC) model analysis (0 h) proximity soundings, within 40 km and 30 min of radar-identified discrete storms, was categorized by several storm types: significantly tornadic supercells (F2 or greater damage), weakly tornadic supercells (F0–F1 damage), nontornadic supercells, elevated right-moving supercells, storms with marginal supercell characteristics, and nonsupercells. These proximity soundings served as the basis for calculations of storm-relative helicity and bulk shear intended to apply across a broad spectrum of thunderstorm types. An effective storm inflow layer was defined in terms of minimum constraints on lifted parcel CAPE and convective inhibition (CIN). Sixteen CAPE and CIN constraint combinations were examined, and the smallest CAPE (25 and 100 J kg−1) and largest CIN (−250 J kg−1) constraints provided the greatest probability of detecting an effective inflow layer within an 835-supercell subset of the proximity soundings. Effective storm-relative helicity (ESRH) calculations were based on the upper and lower bounds of the effective inflow layer. By confining the SRH calculation to the effective inflow layer, ESRH values can be compared consistently across a wide range of storm environments, including storms rooted above the ground. Similarly, the effective bulk shear (EBS) was defined in terms of the vertical shear through a percentage of the “storm depth,” as defined by the vertical distance from the effective inflow base to the equilibrium level associated with the most unstable parcel (maximum θe value) in the lowest 300 hPa. ESRH and EBS discriminate strongly between various storm types, and between supercells and nonsupercells, respectively.
