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- Author or Editor: Ariel E. Cohen x
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Abstract
Southeast U.S. cold season severe weather events can be difficult to predict because of the marginality of the supporting thermodynamic instability in this regime. The sensitivity of this environment to prognoses of instability encourages additional research on ways in which mesoscale models represent turbulent processes within the lower atmosphere that directly influence thermodynamic profiles and forecasts of instability. This work summarizes characteristics of the southeast U.S. cold season severe weather environment and planetary boundary layer (PBL) parameterization schemes used in mesoscale modeling and proceeds with a focused investigation of the performance of nine different representations of the PBL in this environment by comparing simulated thermodynamic and kinematic profiles to observationally influenced ones. It is demonstrated that simultaneous representation of both nonlocal and local mixing in the Asymmetric Convective Model, version 2 (ACM2), scheme has the lowest overall errors for the southeast U.S. cold season tornado regime. For storm-relative helicity, strictly nonlocal schemes provide the largest overall differences from observationally influenced datasets (underforecast). Meanwhile, strictly local schemes yield the most extreme differences from these observationally influenced datasets (underforecast) in a mean sense for the low-level lapse rate and depth of the PBL, on average. A hybrid local–nonlocal scheme is found to mitigate these mean difference extremes. These findings are traced to a tendency for local schemes to incompletely mix the PBL while nonlocal schemes overmix the PBL, whereas the hybrid schemes represent more intermediate mixing in a regime where vertical shear enhances mixing and limited instability suppresses mixing.
Abstract
Southeast U.S. cold season severe weather events can be difficult to predict because of the marginality of the supporting thermodynamic instability in this regime. The sensitivity of this environment to prognoses of instability encourages additional research on ways in which mesoscale models represent turbulent processes within the lower atmosphere that directly influence thermodynamic profiles and forecasts of instability. This work summarizes characteristics of the southeast U.S. cold season severe weather environment and planetary boundary layer (PBL) parameterization schemes used in mesoscale modeling and proceeds with a focused investigation of the performance of nine different representations of the PBL in this environment by comparing simulated thermodynamic and kinematic profiles to observationally influenced ones. It is demonstrated that simultaneous representation of both nonlocal and local mixing in the Asymmetric Convective Model, version 2 (ACM2), scheme has the lowest overall errors for the southeast U.S. cold season tornado regime. For storm-relative helicity, strictly nonlocal schemes provide the largest overall differences from observationally influenced datasets (underforecast). Meanwhile, strictly local schemes yield the most extreme differences from these observationally influenced datasets (underforecast) in a mean sense for the low-level lapse rate and depth of the PBL, on average. A hybrid local–nonlocal scheme is found to mitigate these mean difference extremes. These findings are traced to a tendency for local schemes to incompletely mix the PBL while nonlocal schemes overmix the PBL, whereas the hybrid schemes represent more intermediate mixing in a regime where vertical shear enhances mixing and limited instability suppresses mixing.
Abstract
The goal of this study is to document differences in the convective structure and motion of long-track, severe-wind-producing MCSs from short-track severe-wind-producing MCSs in relation to the mean wind. An ancillary goal is to determine if these differences are large enough that some criterion for MCS motion relative to the mean wind could be used in future definitions of “derechos.” Results confirm past investigations that well-organized MCSs, including those that produce derechos, tend to move faster than the mean wind, exhibiting a significantly larger degree of propagation (component of MCS motion in addition to the component contributed by the mean flow). Furthermore, well-organized systems that produce shorter-track swaths of damaging winds likewise tend to move faster than the mean wind with a significant propagation component along the mean wind. Therefore, propagation in the direction of the mean wind is not necessarily a characteristic that can be used to distinguish derechos from nonderechos. However, there is some indication that long-track damaging wind events that occur without large-scale or persistent bow echoes and mesoscale convective vortices (MCVs) require a strong propagation component along the mean wind direction to become long lived. Overall, however, there does not appear to be enough separation in the motion characteristics among the MCS types to warrant the inclusion of a mean-wind criterion into the definition of a derecho at this time.
Abstract
The goal of this study is to document differences in the convective structure and motion of long-track, severe-wind-producing MCSs from short-track severe-wind-producing MCSs in relation to the mean wind. An ancillary goal is to determine if these differences are large enough that some criterion for MCS motion relative to the mean wind could be used in future definitions of “derechos.” Results confirm past investigations that well-organized MCSs, including those that produce derechos, tend to move faster than the mean wind, exhibiting a significantly larger degree of propagation (component of MCS motion in addition to the component contributed by the mean flow). Furthermore, well-organized systems that produce shorter-track swaths of damaging winds likewise tend to move faster than the mean wind with a significant propagation component along the mean wind. Therefore, propagation in the direction of the mean wind is not necessarily a characteristic that can be used to distinguish derechos from nonderechos. However, there is some indication that long-track damaging wind events that occur without large-scale or persistent bow echoes and mesoscale convective vortices (MCVs) require a strong propagation component along the mean wind direction to become long lived. Overall, however, there does not appear to be enough separation in the motion characteristics among the MCS types to warrant the inclusion of a mean-wind criterion into the definition of a derecho at this time.
Abstract
Previous work with observations from the NEXRAD (WSR-88D) network in the United States has shown that the probability of damage from a tornado, as represented by EF-scale ratings, increases as low-level rotational velocity increases. This work expands on previous studies by including reported tornadoes from 2014 to 2015, as well as a robust sample of nontornadic severe thunderstorms [≥1-in.- (2.54 cm) diameter hail, thunderstorm wind gusts ≥ 50 kt (25 m s−1), or reported wind damage] with low-level cyclonic rotation. The addition of the nontornadic sample allows the computation of tornado damage rating probabilities across a spectrum of organized severe thunderstorms represented by right-moving supercells and quasi-linear convective systems. Dual-polarization variables are used to ensure proper use of velocity data in the identification of tornadic and nontornadic cases. Tornado damage rating probabilities increase as low-level rotational velocity V rot increases and circulation diameter decreases. The influence of height above radar level (or range from radar) is less obvious, with a muted tendency for tornado damage rating probabilities to increase as rotation (of the same V rot magnitude) is observed closer to the ground. Consistent with previous work on gate-to-gate shear signatures such as the tornadic vortex signature, easily identifiable rotation poses a greater tornado risk compared to more nebulous areas of cyclonic azimuthal shear. Additionally, tornado probability distributions vary substantially (for similar sample sizes) when comparing the southeast United States, which has a high density of damage indicators, to the Great Plains, where damage indicators are more sparse.
Abstract
Previous work with observations from the NEXRAD (WSR-88D) network in the United States has shown that the probability of damage from a tornado, as represented by EF-scale ratings, increases as low-level rotational velocity increases. This work expands on previous studies by including reported tornadoes from 2014 to 2015, as well as a robust sample of nontornadic severe thunderstorms [≥1-in.- (2.54 cm) diameter hail, thunderstorm wind gusts ≥ 50 kt (25 m s−1), or reported wind damage] with low-level cyclonic rotation. The addition of the nontornadic sample allows the computation of tornado damage rating probabilities across a spectrum of organized severe thunderstorms represented by right-moving supercells and quasi-linear convective systems. Dual-polarization variables are used to ensure proper use of velocity data in the identification of tornadic and nontornadic cases. Tornado damage rating probabilities increase as low-level rotational velocity V rot increases and circulation diameter decreases. The influence of height above radar level (or range from radar) is less obvious, with a muted tendency for tornado damage rating probabilities to increase as rotation (of the same V rot magnitude) is observed closer to the ground. Consistent with previous work on gate-to-gate shear signatures such as the tornadic vortex signature, easily identifiable rotation poses a greater tornado risk compared to more nebulous areas of cyclonic azimuthal shear. Additionally, tornado probability distributions vary substantially (for similar sample sizes) when comparing the southeast United States, which has a high density of damage indicators, to the Great Plains, where damage indicators are more sparse.
