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- Author or Editor: Christopher J. Nowotarski x
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Abstract
This study investigates the changes that simulated supercell thunderstorms impart on their surroundings. Supercells are simulated in a strongly sheared convective boundary layer comprising horizontal roll vortices. In sensitivity tests, the effects of cloud shading on the near-storm environment are explored through the removal of cloud ice, water, and hydrometeor effects on parameterized radiation. All of the simulated supercells increase the low-level shear in their proximal environment; however, this effect is more pronounced when cloud shading is included. Shading stabilizes the boundary layer beneath the cirrus anvil, diminishes boundary layer rolls and their attendant thermodynamic perturbations, and reduces the intensity of resolved turbulent mixing in the convective boundary layer. Anvil shading also acts to reduce the buoyancy of inflow air and the horizontal buoyancy gradient along the forward-flank outflow boundary.
Abstract
This study investigates the changes that simulated supercell thunderstorms impart on their surroundings. Supercells are simulated in a strongly sheared convective boundary layer comprising horizontal roll vortices. In sensitivity tests, the effects of cloud shading on the near-storm environment are explored through the removal of cloud ice, water, and hydrometeor effects on parameterized radiation. All of the simulated supercells increase the low-level shear in their proximal environment; however, this effect is more pronounced when cloud shading is included. Shading stabilizes the boundary layer beneath the cirrus anvil, diminishes boundary layer rolls and their attendant thermodynamic perturbations, and reduces the intensity of resolved turbulent mixing in the convective boundary layer. Anvil shading also acts to reduce the buoyancy of inflow air and the horizontal buoyancy gradient along the forward-flank outflow boundary.
Abstract
This paper reports on results of idealized numerical simulations testing the influence of low-level humidity, and thus lifting condensation level (LCL), on the morphology and evolution of low-level rotation in supercell thunderstorms. Previous studies have shown that the LCL can influence outflow buoyancy, which can in turn affect generation and stretching of near-surface vertical vorticity. A less explored hypothesis is tested: that the LCL affects the relative positioning of near-surface circulation and the overlying mesocyclone, thus influencing the dynamic lifting and intensification of near-surface vertical vorticity. To test this hypothesis, a set of three base-state thermodynamic profiles with varying LCLs are implemented and compared over a variety of low-level wind profiles. The thermodynamic properties of the simulations are sensitive to variations in the LCL, with higher LCLs contributing to more negatively buoyant cold pools. These outflow characteristics allow for a more forward propagation of near-surface circulation relative to the midlevel mesocyclone. When the mid- and low-level mesocyclones become aligned with appreciable near-surface circulation, favorable dynamic updraft forcing is able to stretch and intensify this rotation. The strength of the vertical vorticity generated ultimately depends on other interrelated factors, including the amount of near-surface circulation generated within the cold pool and the buoyancy of storm outflow. However, these simulations suggest that mesocyclone alignment with near-surface circulation is modulated by the ambient LCL, and is a necessary condition for the strengthening of near-surface vertical vorticity. This alignment is also sensitive to the low-level wind profile, meaning that the LCL most favorable for the formation of intense vorticity may change based on ambient low-level shear properties.
Abstract
This paper reports on results of idealized numerical simulations testing the influence of low-level humidity, and thus lifting condensation level (LCL), on the morphology and evolution of low-level rotation in supercell thunderstorms. Previous studies have shown that the LCL can influence outflow buoyancy, which can in turn affect generation and stretching of near-surface vertical vorticity. A less explored hypothesis is tested: that the LCL affects the relative positioning of near-surface circulation and the overlying mesocyclone, thus influencing the dynamic lifting and intensification of near-surface vertical vorticity. To test this hypothesis, a set of three base-state thermodynamic profiles with varying LCLs are implemented and compared over a variety of low-level wind profiles. The thermodynamic properties of the simulations are sensitive to variations in the LCL, with higher LCLs contributing to more negatively buoyant cold pools. These outflow characteristics allow for a more forward propagation of near-surface circulation relative to the midlevel mesocyclone. When the mid- and low-level mesocyclones become aligned with appreciable near-surface circulation, favorable dynamic updraft forcing is able to stretch and intensify this rotation. The strength of the vertical vorticity generated ultimately depends on other interrelated factors, including the amount of near-surface circulation generated within the cold pool and the buoyancy of storm outflow. However, these simulations suggest that mesocyclone alignment with near-surface circulation is modulated by the ambient LCL, and is a necessary condition for the strengthening of near-surface vertical vorticity. This alignment is also sensitive to the low-level wind profile, meaning that the LCL most favorable for the formation of intense vorticity may change based on ambient low-level shear properties.
Abstract
This study investigates relationships between climate-scale patterns and seasonal tornado outbreaks across the southeastern United States. Time series of several daily climate indices—including Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific–North American (PNA) pattern, east/west Pacific Oscillation (EPO/WPO), and both raw and detrended Gulf of Mexico SST anomalies (SSTA/SSTAD)—are collected in advance of Southeast severe convective days and grouped using self-organizing maps (SOMs). Spatiotemporal distributions of storm reports within nodes are compared to seasonal climatology, and the evolution of the regional environment for nodes associated with outbreaks is analyzed to provide physical justification for such associations. This study confirms findings from several tornado-related climate studies in the literature, while also identifying a number of new patterns associated with Southeast tornado outbreaks. Both the AO and NAO are relevant across all seasons, especially on lead time scales of 1–2 months, while SSTA/SSTADs are relevant on smaller time scales. The physical connection between these patterns and the regional storm environment is largely related to alterations of upper-level circulation and jet stream patterns, which in turn influence deep- and low-level shear, inland transport of moisture and instability, and other regional characteristics pertinent to tornado outbreaks. These results suggest that climate-scale variability can modulate and potentially be used to predict regional storm environments and their likelihood to produce tornado outbreaks across the Southeast.
Abstract
This study investigates relationships between climate-scale patterns and seasonal tornado outbreaks across the southeastern United States. Time series of several daily climate indices—including Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Pacific–North American (PNA) pattern, east/west Pacific Oscillation (EPO/WPO), and both raw and detrended Gulf of Mexico SST anomalies (SSTA/SSTAD)—are collected in advance of Southeast severe convective days and grouped using self-organizing maps (SOMs). Spatiotemporal distributions of storm reports within nodes are compared to seasonal climatology, and the evolution of the regional environment for nodes associated with outbreaks is analyzed to provide physical justification for such associations. This study confirms findings from several tornado-related climate studies in the literature, while also identifying a number of new patterns associated with Southeast tornado outbreaks. Both the AO and NAO are relevant across all seasons, especially on lead time scales of 1–2 months, while SSTA/SSTADs are relevant on smaller time scales. The physical connection between these patterns and the regional storm environment is largely related to alterations of upper-level circulation and jet stream patterns, which in turn influence deep- and low-level shear, inland transport of moisture and instability, and other regional characteristics pertinent to tornado outbreaks. These results suggest that climate-scale variability can modulate and potentially be used to predict regional storm environments and their likelihood to produce tornado outbreaks across the Southeast.
Abstract
Tropical cyclone tornadoes (TCTORs) are a hazard to life and property during landfalling tropical cyclones (TCs). The threat is often spread over a wide area within the TC envelope and must be continually evaluated as the TC moves inland and dissipates. To anticipate the risk of TCTORs, forecasters may use high-resolution, rapidly updating model analyses and short-range forecasts such as the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR), and an ingredients-based approach similar to that used for forecasting continental midlatitude tornadoes. Though RAP and HRRR errors have been identified in typical midlatitude convective environments, this study evaluates the performance of the RAP and the HRRR within the TC envelope, with particular attention given to sounding-derived parameters previously identified as useful for TCTOR forecasting. A sample of 1730 observed upper-air soundings is sourced from 13 TCs that made landfall along the U.S. coastline between 2017 and 2019. The observed soundings are paired with their corresponding model gridpoint soundings from the RAP analysis, RAP 12-h forecast, and HRRR 12-h forecast. Model errors are calculated for both the raw sounding variables of temperature, dewpoint, and wind speed, as well as for the selected sounding-derived parameters. Results show a moist bias that worsens with height across all model runs. There are also statistically significant underpredictions in stability-related parameters such as convective available potential energy (CAPE) and kinematic parameters such as vertical wind shear.
Abstract
Tropical cyclone tornadoes (TCTORs) are a hazard to life and property during landfalling tropical cyclones (TCs). The threat is often spread over a wide area within the TC envelope and must be continually evaluated as the TC moves inland and dissipates. To anticipate the risk of TCTORs, forecasters may use high-resolution, rapidly updating model analyses and short-range forecasts such as the Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR), and an ingredients-based approach similar to that used for forecasting continental midlatitude tornadoes. Though RAP and HRRR errors have been identified in typical midlatitude convective environments, this study evaluates the performance of the RAP and the HRRR within the TC envelope, with particular attention given to sounding-derived parameters previously identified as useful for TCTOR forecasting. A sample of 1730 observed upper-air soundings is sourced from 13 TCs that made landfall along the U.S. coastline between 2017 and 2019. The observed soundings are paired with their corresponding model gridpoint soundings from the RAP analysis, RAP 12-h forecast, and HRRR 12-h forecast. Model errors are calculated for both the raw sounding variables of temperature, dewpoint, and wind speed, as well as for the selected sounding-derived parameters. Results show a moist bias that worsens with height across all model runs. There are also statistically significant underpredictions in stability-related parameters such as convective available potential energy (CAPE) and kinematic parameters such as vertical wind shear.
Abstract
The self-organizing map (SOM) statistical technique is applied to vertical profiles of thermodynamic and kinematic parameters from a Rapid Update Cycle-2 (RUC-2) proximity sounding dataset with the goal of better distinguishing and predicting supercell and tornadic environments. An SOM is a topologically ordered mapping of input data onto a two-dimensional array of nodes that can be used to classify large datasets into meaningful clusters. The relative ability of SOMs derived from each parameter to separate soundings in a way that is useful in discriminating between storm type, location, and time of year is discussed. Sensitivity to SOM configuration is also explored. Simple skill scores are computed for each SOM to evaluate the relative potential of each variable for future development as a method of probabilistic forecasting. It is found that variance in SOM nodes is reduced compared to the overall dataset, indicating that this is a viable classification method. SOMs of profiles of wind-derived variables are more effective in discriminating between storm type than thermodynamic variables. The SOM method also identifies meteorological, geographic, and temporal regimes within the dataset. In general, conditional probabilities of storm-type occurrence generated using SOMs have higher skill when wind-derived variables are considered and when forecasting nonsupercell events. Storm-relative wind variables tend to have better skill than ground-relative wind variables when forecasting nonsupercells, whereas ground-relative variables become more important when forecasting tornadoes.
Abstract
The self-organizing map (SOM) statistical technique is applied to vertical profiles of thermodynamic and kinematic parameters from a Rapid Update Cycle-2 (RUC-2) proximity sounding dataset with the goal of better distinguishing and predicting supercell and tornadic environments. An SOM is a topologically ordered mapping of input data onto a two-dimensional array of nodes that can be used to classify large datasets into meaningful clusters. The relative ability of SOMs derived from each parameter to separate soundings in a way that is useful in discriminating between storm type, location, and time of year is discussed. Sensitivity to SOM configuration is also explored. Simple skill scores are computed for each SOM to evaluate the relative potential of each variable for future development as a method of probabilistic forecasting. It is found that variance in SOM nodes is reduced compared to the overall dataset, indicating that this is a viable classification method. SOMs of profiles of wind-derived variables are more effective in discriminating between storm type than thermodynamic variables. The SOM method also identifies meteorological, geographic, and temporal regimes within the dataset. In general, conditional probabilities of storm-type occurrence generated using SOMs have higher skill when wind-derived variables are considered and when forecasting nonsupercell events. Storm-relative wind variables tend to have better skill than ground-relative wind variables when forecasting nonsupercells, whereas ground-relative variables become more important when forecasting tornadoes.
Abstract
Self-organizing maps (SOMs) have been shown to be a useful tool in classifying meteorological data. This paper builds on earlier work employing SOMs to classify model analysis proximity soundings from the near-storm environments of tornadic and nontornadic supercell thunderstorms. A series of multivariate SOMs is produced wherein the input variables, height, dimensions, and number of SOM nodes are varied. SOMs including information regarding the near-storm wind profile are more effective in discriminating between tornadic and nontornadic storms than those limited to thermodynamic information. For the best-performing SOMs, probabilistic forecasts derived from matching near-storm environments to a SOM node may provide modest improvements in forecast skill relative to existing methods for probabilistic forecasts.
Abstract
Self-organizing maps (SOMs) have been shown to be a useful tool in classifying meteorological data. This paper builds on earlier work employing SOMs to classify model analysis proximity soundings from the near-storm environments of tornadic and nontornadic supercell thunderstorms. A series of multivariate SOMs is produced wherein the input variables, height, dimensions, and number of SOM nodes are varied. SOMs including information regarding the near-storm wind profile are more effective in discriminating between tornadic and nontornadic storms than those limited to thermodynamic information. For the best-performing SOMs, probabilistic forecasts derived from matching near-storm environments to a SOM node may provide modest improvements in forecast skill relative to existing methods for probabilistic forecasts.
Abstract
Proper prediction of the inflow layer of deep convective storms is critical for understanding their potential updraft properties and likelihood of producing severe weather. In this study, an existing forecast metric known as the effective inflow layer (EIL) is evaluated with an emphasis on its performance for supercell thunderstorms, where both buoyancy and dynamic pressure accelerations are common. A total of 15 idealized simulations with a range of realistic base states are performed. Using an array of passive fluid tracers initialized at various vertical levels, the proportion of simulated updraft core air originating from the EIL is determined. Results suggest that the EIL metric performs well in forecasting peak updraft origin height, particularly for supercell updrafts. Moreover, the EIL metric displays consistent skill across a range of updraft core definitions. The EIL has a tendency to perform better as convective available potential energy, deep-layer shear, and EIL depth are increased in the near-storm environment. Modifications to further constrain the EIL based on the most-unstable parcel height or storm-relative flow may lead to marginal improvements for the most stringent updraft core definitions. Finally, effects of the near-storm environment on low-level and peak updraft forcing and intensity are discussed.
Abstract
Proper prediction of the inflow layer of deep convective storms is critical for understanding their potential updraft properties and likelihood of producing severe weather. In this study, an existing forecast metric known as the effective inflow layer (EIL) is evaluated with an emphasis on its performance for supercell thunderstorms, where both buoyancy and dynamic pressure accelerations are common. A total of 15 idealized simulations with a range of realistic base states are performed. Using an array of passive fluid tracers initialized at various vertical levels, the proportion of simulated updraft core air originating from the EIL is determined. Results suggest that the EIL metric performs well in forecasting peak updraft origin height, particularly for supercell updrafts. Moreover, the EIL metric displays consistent skill across a range of updraft core definitions. The EIL has a tendency to perform better as convective available potential energy, deep-layer shear, and EIL depth are increased in the near-storm environment. Modifications to further constrain the EIL based on the most-unstable parcel height or storm-relative flow may lead to marginal improvements for the most stringent updraft core definitions. Finally, effects of the near-storm environment on low-level and peak updraft forcing and intensity are discussed.
Abstract
This paper uses idealized numerical simulations to investigate the dynamical influences of stable boundary layers on the morphology of supercell thunderstorms, especially the development of low-level rotation. Simulations are initialized in a horizontally homogeneous environment with a surface-based stable layer similar to that found within a nocturnal boundary layer or a mesoscale cold pool. The depth and lapse rate of the imposed stable boundary layer, which together control the convective inhibition (CIN), are varied in a suite of experiments.
When compared with a control simulation having little surface-based CIN, each supercell simulated in an environment having a stable boundary layer develops weaker rotation, updrafts, and downdrafts at low levels; in general, low-level vertical vorticity and vertical velocity magnitude decrease as initial CIN increases (changes in CIN are due only to variations in the imposed stable boundary layer). Though the presence of a stable boundary layer decreases low-level updraft strength, all supercells except those initiated over the most stable boundary layers had at least some updraft parcels with near-surface origins. Furthermore, the existence of a stable boundary layer only prohibits downdraft parcels from reaching the lowest grid level in the most stable cases. Trajectory and circulation analyses indicate that weaker near-surface rotation in the stable-layer scenarios is a result of the decreased generation of circulation coupled with decreased convergence of the near-surface circulation by weaker low-level updrafts. These results may also suggest a reason why tornadogenesis is less likely to occur in so-called elevated supercell thunderstorms than in surface-based supercells.
Abstract
This paper uses idealized numerical simulations to investigate the dynamical influences of stable boundary layers on the morphology of supercell thunderstorms, especially the development of low-level rotation. Simulations are initialized in a horizontally homogeneous environment with a surface-based stable layer similar to that found within a nocturnal boundary layer or a mesoscale cold pool. The depth and lapse rate of the imposed stable boundary layer, which together control the convective inhibition (CIN), are varied in a suite of experiments.
When compared with a control simulation having little surface-based CIN, each supercell simulated in an environment having a stable boundary layer develops weaker rotation, updrafts, and downdrafts at low levels; in general, low-level vertical vorticity and vertical velocity magnitude decrease as initial CIN increases (changes in CIN are due only to variations in the imposed stable boundary layer). Though the presence of a stable boundary layer decreases low-level updraft strength, all supercells except those initiated over the most stable boundary layers had at least some updraft parcels with near-surface origins. Furthermore, the existence of a stable boundary layer only prohibits downdraft parcels from reaching the lowest grid level in the most stable cases. Trajectory and circulation analyses indicate that weaker near-surface rotation in the stable-layer scenarios is a result of the decreased generation of circulation coupled with decreased convergence of the near-surface circulation by weaker low-level updrafts. These results may also suggest a reason why tornadogenesis is less likely to occur in so-called elevated supercell thunderstorms than in surface-based supercells.
Abstract
Supercell thunderstorms are simulated using an idealized numerical model to analyze the effects of modifications to the environmental low-level wind profile on near-surface rotation. Specifically, the orientation, magnitude, and depth of the low-level vertical wind shear are modified in several suites of experiments and compared to control simulations with no vertical wind shear in the prescribed layer.
The overall morphology of the simulated supercells is highly sensitive to even shallow changes in the low-level wind profile. Moreover, maximum near-surface vertical vorticity varies as the low-level wind profile is modified. The results suggest this is principally a consequence of the degree to which favorable dynamic forcing of negatively buoyant outflow is superimposed upon the near-surface circulation maximum. Simulations with easterly shear and weaker storm-relative winds over the depth of the gust front promote forward-surging outflow and smaller separation between the near-surface circulation maximum and the mesocyclone aloft compared with other hodograph shapes. This promotes near-surface vertical vorticity intensification in these simulations. Similar trends in near-surface vertical vorticity as a function of low-level shear orientation are observed for varying shear-layer depths and bulk-shear magnitudes over the shear layer. The degree to which specific hodograph shapes promote strong near-surface rotation may vary with different deep-layer wind profiles or thermodynamic environments from those simulated here; however, this study concludes that favorable positioning of the near-surface circulation maximum and mesocyclone aloft are a necessary condition for supercell tornadogenesis and this positioning may be modulated by the low-level wind profile.
Abstract
Supercell thunderstorms are simulated using an idealized numerical model to analyze the effects of modifications to the environmental low-level wind profile on near-surface rotation. Specifically, the orientation, magnitude, and depth of the low-level vertical wind shear are modified in several suites of experiments and compared to control simulations with no vertical wind shear in the prescribed layer.
The overall morphology of the simulated supercells is highly sensitive to even shallow changes in the low-level wind profile. Moreover, maximum near-surface vertical vorticity varies as the low-level wind profile is modified. The results suggest this is principally a consequence of the degree to which favorable dynamic forcing of negatively buoyant outflow is superimposed upon the near-surface circulation maximum. Simulations with easterly shear and weaker storm-relative winds over the depth of the gust front promote forward-surging outflow and smaller separation between the near-surface circulation maximum and the mesocyclone aloft compared with other hodograph shapes. This promotes near-surface vertical vorticity intensification in these simulations. Similar trends in near-surface vertical vorticity as a function of low-level shear orientation are observed for varying shear-layer depths and bulk-shear magnitudes over the shear layer. The degree to which specific hodograph shapes promote strong near-surface rotation may vary with different deep-layer wind profiles or thermodynamic environments from those simulated here; however, this study concludes that favorable positioning of the near-surface circulation maximum and mesocyclone aloft are a necessary condition for supercell tornadogenesis and this positioning may be modulated by the low-level wind profile.
Abstract
Observed supercell updrafts consistently produce the fastest mid- to upper-tropospheric vertical velocities among all modes of convection. Two hypotheses for this feature are investigated. In the dynamic hypothesis, upward, largely rotationally driven pressure gradient accelerations enhance supercell updrafts relative to other forms of convection. In the thermodynamic hypothesis, supercell updrafts have more low-level inflow than ordinary updrafts because of the large vertical wind shear in supercell environments. This large inflow makes supercell updrafts wider than that of ordinary convection and less susceptible to the deleterious effects of entrainment-driven updraft core dilution on buoyancy. These hypotheses are tested using a large suite of idealized supercell simulations, wherein vertical shear, CAPE, and moisture are systematically varied. Consistent with the thermodynamic hypothesis, storms with the largest storm-relative flow have larger inflow, are wider, have larger buoyancy, and have faster updrafts. Analyses of the vertical momentum forcing along trajectories shows that maximum vertical velocities are often enhanced by dynamic pressure accelerations, but this enhancement is accompanied by larger downward buoyant pressure accelerations than in ordinary convection. Integrated buoyancy along parcel paths is therefore a strong constraint on maximum updraft speeds. Thus, through a combination of processes consistent with the dynamic and thermodynamic hypotheses, supercell updrafts are able to realize a larger percentage of CAPE than ordinary updrafts.
Abstract
Observed supercell updrafts consistently produce the fastest mid- to upper-tropospheric vertical velocities among all modes of convection. Two hypotheses for this feature are investigated. In the dynamic hypothesis, upward, largely rotationally driven pressure gradient accelerations enhance supercell updrafts relative to other forms of convection. In the thermodynamic hypothesis, supercell updrafts have more low-level inflow than ordinary updrafts because of the large vertical wind shear in supercell environments. This large inflow makes supercell updrafts wider than that of ordinary convection and less susceptible to the deleterious effects of entrainment-driven updraft core dilution on buoyancy. These hypotheses are tested using a large suite of idealized supercell simulations, wherein vertical shear, CAPE, and moisture are systematically varied. Consistent with the thermodynamic hypothesis, storms with the largest storm-relative flow have larger inflow, are wider, have larger buoyancy, and have faster updrafts. Analyses of the vertical momentum forcing along trajectories shows that maximum vertical velocities are often enhanced by dynamic pressure accelerations, but this enhancement is accompanied by larger downward buoyant pressure accelerations than in ordinary convection. Integrated buoyancy along parcel paths is therefore a strong constraint on maximum updraft speeds. Thus, through a combination of processes consistent with the dynamic and thermodynamic hypotheses, supercell updrafts are able to realize a larger percentage of CAPE than ordinary updrafts.
