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Abstract
Convective surface winds in the contiguous United States are classified as severe at 50 kt (58 mi h−1, or 26 m s−1), whether measured or estimated. In 2006, NCDC (now NCEI) Storm Data, from which analyzed data are directly derived, began explicit categorization of such reports as measured gusts (MGs) or estimated gusts (EGs). Because of the documented tendency of human observers to overestimate winds, the quality and reliability of EGs (especially in comparison with MGs) has been challenged, mostly for nonconvective winds and controlled-testing situations, but only speculatively for bulk convective data. For the 10-yr period of 2006–15, 150 423 filtered convective-wind gust magnitudes are compared and analyzed, including 15 183 MGs and 135 240 EGs, both nationally and by state. Nonmeteorological artifacts include marked geographic discontinuities and pronounced “spikes” of an order of magnitude in which EG values (in both miles per hour and knots) end in the digits 0 or 5. Sources such as NWS employees, storm chasers, and the general public overestimate EGs, whereas trained spotters are relatively accurate. Analysis of the ratio of EG to MG and their sources also reveals an apparent warning-verification-influence bias in the climatological distribution of wind gusts imparted by EG reliance in the Southeast. Results from prior wind-tunnel testing of human subjects are applied to 1) illustrate the difference between measured and perceived winds for the database and 2) show the impact on the severe-wind dataset if EGs were bias-corrected for the human overestimation factor.
Abstract
Convective surface winds in the contiguous United States are classified as severe at 50 kt (58 mi h−1, or 26 m s−1), whether measured or estimated. In 2006, NCDC (now NCEI) Storm Data, from which analyzed data are directly derived, began explicit categorization of such reports as measured gusts (MGs) or estimated gusts (EGs). Because of the documented tendency of human observers to overestimate winds, the quality and reliability of EGs (especially in comparison with MGs) has been challenged, mostly for nonconvective winds and controlled-testing situations, but only speculatively for bulk convective data. For the 10-yr period of 2006–15, 150 423 filtered convective-wind gust magnitudes are compared and analyzed, including 15 183 MGs and 135 240 EGs, both nationally and by state. Nonmeteorological artifacts include marked geographic discontinuities and pronounced “spikes” of an order of magnitude in which EG values (in both miles per hour and knots) end in the digits 0 or 5. Sources such as NWS employees, storm chasers, and the general public overestimate EGs, whereas trained spotters are relatively accurate. Analysis of the ratio of EG to MG and their sources also reveals an apparent warning-verification-influence bias in the climatological distribution of wind gusts imparted by EG reliance in the Southeast. Results from prior wind-tunnel testing of human subjects are applied to 1) illustrate the difference between measured and perceived winds for the database and 2) show the impact on the severe-wind dataset if EGs were bias-corrected for the human overestimation factor.
Extreme Weather Records
Compilation, Adjudication, and Publication
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.
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
The accuracy, reliability, and skill of several objective supercell identification methods are evaluated using 113 simulations from an idealized cloud model with 1-km horizontal grid spacing. Horizontal cross sections of vorticity and radar reflectivity at both mid- and low levels were analyzed for the presence of a supercell, every 5 min of simulation time, to develop a “truth” database. Supercells were identified using well-known characteristics such as hook echoes, inflow notches, bounded weak-echo regions (BWERs), and the presence of significant vertical vorticity.
The three objective supercell identification techniques compared were the Pearson correlation (PC) using an analysis window centered on the midlevel storm updraft; a modified Pearson correlation (MPC), which calculates the PC at every point in the horizontal using a small 3 km × 3 km analysis window; and updraft helicity (UH). Results show that the UH method integrated from 2 to 5 km AGL, and using a threshold value of 180 m2 s−2, was equally as accurate as the MPC technique—averaged from 2 to 5 km AGL and using a minimum updraft threshold of 7 m s−1 with a detection threshold of 0.3—in discriminating between supercells and nonsupercells for 1-km horizontal grid spacing simulations. At courser resolutions, the UH technique performed best, while the MPC technique produced the largest threat scores for higher-resolution simulations. In addition, requiring that the supercell detection thresholds last at least 20 min reduced the number of false alarms.
Abstract
The accuracy, reliability, and skill of several objective supercell identification methods are evaluated using 113 simulations from an idealized cloud model with 1-km horizontal grid spacing. Horizontal cross sections of vorticity and radar reflectivity at both mid- and low levels were analyzed for the presence of a supercell, every 5 min of simulation time, to develop a “truth” database. Supercells were identified using well-known characteristics such as hook echoes, inflow notches, bounded weak-echo regions (BWERs), and the presence of significant vertical vorticity.
The three objective supercell identification techniques compared were the Pearson correlation (PC) using an analysis window centered on the midlevel storm updraft; a modified Pearson correlation (MPC), which calculates the PC at every point in the horizontal using a small 3 km × 3 km analysis window; and updraft helicity (UH). Results show that the UH method integrated from 2 to 5 km AGL, and using a threshold value of 180 m2 s−2, was equally as accurate as the MPC technique—averaged from 2 to 5 km AGL and using a minimum updraft threshold of 7 m s−1 with a detection threshold of 0.3—in discriminating between supercells and nonsupercells for 1-km horizontal grid spacing simulations. At courser resolutions, the UH technique performed best, while the MPC technique produced the largest threat scores for higher-resolution simulations. In addition, requiring that the supercell detection thresholds last at least 20 min reduced the number of false alarms.
Abstract
A sample of 413 soundings in close proximity to tornadic and nontornadic supercells is examined. The soundings were obtained from hourly analyses generated by the 40-km Rapid Update Cycle-2 (RUC-2) analysis and forecast system. A comparison of 149 observed soundings and collocated RUC-2 soundings in regional supercell environments reveals that the RUC-2 model analyses were reasonably accurate through much of the troposphere. The largest error tendencies were in temperatures and mixing ratios near the surface, primarily in 1-h forecast soundings immediately prior to the standard rawinsonde launches around 1200 and 0000 UTC. Overall, the RUC-2 analysis soundings appear to be a reasonable proxy for observed soundings in supercell environments.
Thermodynamic and vertical wind shear parameters derived from RUC-2 proximity soundings are evaluated for the following supercell and storm subsets: significantly tornadic supercells (54 soundings), weakly tornadic supercells (144 soundings), nontornadic supercells (215 soundings), and discrete nonsupercell storms (75 soundings). Findings presented herein are then compared to results from previous and ongoing proximity soundings studies. Most significantly, proximity soundings presented here reinforce the findings of previous studies in that vertical shear and moisture within 1 km of the ground can discriminate between nontornadic supercells and supercells producing tornadoes with F2 or greater damage. Parameters that combine measures of buoyancy, vertical shear, and low-level moisture show the strongest ability to discriminate between supercell classes.
Abstract
A sample of 413 soundings in close proximity to tornadic and nontornadic supercells is examined. The soundings were obtained from hourly analyses generated by the 40-km Rapid Update Cycle-2 (RUC-2) analysis and forecast system. A comparison of 149 observed soundings and collocated RUC-2 soundings in regional supercell environments reveals that the RUC-2 model analyses were reasonably accurate through much of the troposphere. The largest error tendencies were in temperatures and mixing ratios near the surface, primarily in 1-h forecast soundings immediately prior to the standard rawinsonde launches around 1200 and 0000 UTC. Overall, the RUC-2 analysis soundings appear to be a reasonable proxy for observed soundings in supercell environments.
Thermodynamic and vertical wind shear parameters derived from RUC-2 proximity soundings are evaluated for the following supercell and storm subsets: significantly tornadic supercells (54 soundings), weakly tornadic supercells (144 soundings), nontornadic supercells (215 soundings), and discrete nonsupercell storms (75 soundings). Findings presented herein are then compared to results from previous and ongoing proximity soundings studies. Most significantly, proximity soundings presented here reinforce the findings of previous studies in that vertical shear and moisture within 1 km of the ground can discriminate between nontornadic supercells and supercells producing tornadoes with F2 or greater damage. Parameters that combine measures of buoyancy, vertical shear, and low-level moisture show the strongest ability to discriminate between supercell classes.
Abstract
Over 400 vertical wind profiles in close proximity to nontornadic and tornadic supercell thunderstorms are examined. The profiles were obtained from the Rapid Update Cycle (RUC) model/analysis system. Ground-relative wind speeds throughout the lower and middle troposphere are larger, on average, in tornadic supercell environments than in nontornadic supercell environments. The average vertical profiles of storm-relative wind speed, vertical wind shear, hodograph curvature, crosswise and streamwise vorticity, and storm-relative helicity are generally similar above 1 km in the tornadic and nontornadic supercell environments, with differences that are either not statistically significant or not what most would regard as meteorologically significant. On the other hand, considerable differences are found in these average vertical profiles within 1 km of the ground, with environments associated with significantly tornadic supercells (those producing tornadoes of at least F2 intensity) having substantially larger low-level vertical wind shear, streamwise vorticity, and storm-relative helicity compared to environments associated with nontornadic supercells and weakly tornadic supercells (those producing F0 or F1 tornadoes). These findings may partly explain the extraordinary difficulty in discriminating between tornadic and nontornadic supercell environments in a forecasting setting, given the low temporal and spatial frequency of wind observations in the lowest 1 km. It is believed that it would be a worthwhile investment to augment low-level wind profiling capabilities, in addition to taking a closer look at the dynamical sensitivities of supercell storms to near-surface wind shear by way of high-resolution numerical simulations.
Abstract
Over 400 vertical wind profiles in close proximity to nontornadic and tornadic supercell thunderstorms are examined. The profiles were obtained from the Rapid Update Cycle (RUC) model/analysis system. Ground-relative wind speeds throughout the lower and middle troposphere are larger, on average, in tornadic supercell environments than in nontornadic supercell environments. The average vertical profiles of storm-relative wind speed, vertical wind shear, hodograph curvature, crosswise and streamwise vorticity, and storm-relative helicity are generally similar above 1 km in the tornadic and nontornadic supercell environments, with differences that are either not statistically significant or not what most would regard as meteorologically significant. On the other hand, considerable differences are found in these average vertical profiles within 1 km of the ground, with environments associated with significantly tornadic supercells (those producing tornadoes of at least F2 intensity) having substantially larger low-level vertical wind shear, streamwise vorticity, and storm-relative helicity compared to environments associated with nontornadic supercells and weakly tornadic supercells (those producing F0 or F1 tornadoes). These findings may partly explain the extraordinary difficulty in discriminating between tornadic and nontornadic supercell environments in a forecasting setting, given the low temporal and spatial frequency of wind observations in the lowest 1 km. It is believed that it would be a worthwhile investment to augment low-level wind profiling capabilities, in addition to taking a closer look at the dynamical sensitivities of supercell storms to near-surface wind shear by way of high-resolution numerical simulations.
Abstract
The NCAR acoustical ice nucleus counter was calibrated against a Bigg-Warner Weather Bureau type chamber modified as a mixing chamber. The mixing chamber was in turn calibrated against the CSU-NSF isothermal diffusion cloud chamber. This work was carried out using a 300-liter aluminized mylar bag into which known samples of silver iodide nuclei were introduced. Nuclei were transferred from the bag to the NCAR counter in a carrier gas, at a flow rate of 10 liters min−1. It was found that the NCAR counter measured from 16–52% of the count given by the mixing chamber. An NCAR unit was modified with a velvet liner to test the feasibility of eliminating the glycol system, and measurements were made as described above. The modified unit did not count reliably.
Abstract
The NCAR acoustical ice nucleus counter was calibrated against a Bigg-Warner Weather Bureau type chamber modified as a mixing chamber. The mixing chamber was in turn calibrated against the CSU-NSF isothermal diffusion cloud chamber. This work was carried out using a 300-liter aluminized mylar bag into which known samples of silver iodide nuclei were introduced. Nuclei were transferred from the bag to the NCAR counter in a carrier gas, at a flow rate of 10 liters min−1. It was found that the NCAR counter measured from 16–52% of the count given by the mixing chamber. An NCAR unit was modified with a velvet liner to test the feasibility of eliminating the glycol system, and measurements were made as described above. The modified unit did not count reliably.
During the early to middle 2000s, in response to demand for more detail in wind damage surveying and recordkeeping, a team of atmospheric scientists and wind engineers developed the enhanced Fujita (EF) scale. The EF scale, codified officially into National Weather Service (NWS) use in February 2007, offers wind speed estimates for a range of degrees of damage (DoDs) across each of 28 damage indicators (DIs). In practice, this has increased precision of damage surveys for tornado and thunderstorm-wind events. Still, concerns remain about both the representativeness of DoDs and the sufficiency of DIs, including the following: How dependable are the wind speed ranges for certain DoDs? What other DIs can be included? How can recent advances in mapping and documentation tools be integrated into the surveying process and the storm records? What changes should be made to the existing scale: why, how, and by whom? What alternative methods may be included or adapted for estimating tornado intensity?
To begin coordinated discussion on these and related topics, interested scientists and engineers (including some involved in EF scale development) organized a national EF Scale Stakeholders' Meeting, held on 2–3 March 2010 in Norman, Oklahoma. This article presents more detailed background information, summarizes the meeting, presents possibilities for the future of the EF scale and damage surveys, and solicits ideas from the engineering and atmospheric science communities.
During the early to middle 2000s, in response to demand for more detail in wind damage surveying and recordkeeping, a team of atmospheric scientists and wind engineers developed the enhanced Fujita (EF) scale. The EF scale, codified officially into National Weather Service (NWS) use in February 2007, offers wind speed estimates for a range of degrees of damage (DoDs) across each of 28 damage indicators (DIs). In practice, this has increased precision of damage surveys for tornado and thunderstorm-wind events. Still, concerns remain about both the representativeness of DoDs and the sufficiency of DIs, including the following: How dependable are the wind speed ranges for certain DoDs? What other DIs can be included? How can recent advances in mapping and documentation tools be integrated into the surveying process and the storm records? What changes should be made to the existing scale: why, how, and by whom? What alternative methods may be included or adapted for estimating tornado intensity?
To begin coordinated discussion on these and related topics, interested scientists and engineers (including some involved in EF scale development) organized a national EF Scale Stakeholders' Meeting, held on 2–3 March 2010 in Norman, Oklahoma. This article presents more detailed background information, summarizes the meeting, presents possibilities for the future of the EF scale and damage surveys, and solicits ideas from the engineering and atmospheric science communities.
Abstract
Tropical cyclone tornadoes pose a unique challenge to warning forecasters given their often marginal environments and radar attributes. In late August 2017 Hurricane Harvey made landfall on the Texas coast and produced 52 tornadoes over a record-breaking seven consecutive days. To improve warning efforts, this case study of Harvey’s tornadoes includes an event overview as well as a comparison of near-cell environments and radar attributes between tornadic and nontornadic warned cells. Our results suggest that significant differences existed in both the near-cell environments and radar attributes, particularly rotational velocity, between tornadic cells and false alarms. For many environmental variables and radar attributes, differences were enhanced when only tornadoes associated with a tornado debris signature were considered. Our results highlight the potential of improving warning skill further and reducing false alarms by increasing rotational velocity warning thresholds, refining the use of near-storm environment information, and focusing warning efforts on cells likely to produce the most impactful tornadoes.
Abstract
Tropical cyclone tornadoes pose a unique challenge to warning forecasters given their often marginal environments and radar attributes. In late August 2017 Hurricane Harvey made landfall on the Texas coast and produced 52 tornadoes over a record-breaking seven consecutive days. To improve warning efforts, this case study of Harvey’s tornadoes includes an event overview as well as a comparison of near-cell environments and radar attributes between tornadic and nontornadic warned cells. Our results suggest that significant differences existed in both the near-cell environments and radar attributes, particularly rotational velocity, between tornadic cells and false alarms. For many environmental variables and radar attributes, differences were enhanced when only tornadoes associated with a tornado debris signature were considered. Our results highlight the potential of improving warning skill further and reducing false alarms by increasing rotational velocity warning thresholds, refining the use of near-storm environment information, and focusing warning efforts on cells likely to produce the most impactful tornadoes.
