Simulation of severe storms of tornadic intensity over Indo-Bangla region

Many severe thunderstorms of tornadic intensity were reported in the northwestern parts of Bangladesh during 30 August to 14 September, 2008. Two among them occurred at Nilphamari and Kurigram districts on 30th August, and at Nilphamari district on 3rd September. The tornadic storms are studied based on a field survey, surface data, radar and satellite observations and model simulations. Low level moisture influx by southerly flow from the Bay of Bengal coupled with an upper level westerly jet stream causing intense instability and shear in the wind fields triggered a series of storms for two weeks. The exact time and locations of the storms are investigated by using the hourly precipitation data retrieved from a S-band radar of Bangladesh Meteorological Department (BMD) located at Dhaka. Subsequently, the storms are simulated by using the WRF-ARW model on double nested domains at 9 and 3 km horizontal resolutions based on 6 hourly FNL analyses and boundary conditions of NCEP. Among the typical characteristics of the storms, the CAPE, Storm-Relative Environment Helicity (SREH), Bulk Richardson Number Shear (BRNSHR), dew point depression, and potential vorticity are studied. Results show that while there are differences of 2-3 hours between the observed and simulated time of the storms, the distances between observed and simulated locations of the storms are several tens of kilometers. The maximum CAPE is generally above 2400 J kg-1. The maximum amount of vorticity transferred by directional shear in the storm updraft (helicity) due to convective motion simulated by the model is 766 m2 sec-2, and the highest value of BRNSHR that define the region in which low-level mesocyclogenesis is more likely is 168 m2 sec-2 among the 2 cases, which is generally supposed to produce rotating storms according to the prescribed range.

Anthropogenic Influences on Tornadic Storms

The impact of climate change on severe storms and tornadoes remains uncertain, largely owing to inconsistencies in observational data and limitations of climate models. We performed ensembles of convection-permitting climate model simulations to examine how three tornadic storms would change if similar events were to occur in pre-industrial and future climates. The choice of events includes winter, nocturnal, and spring tornadic storms to provide insight into how the timing and seasonality of storms may affect their response to climate change. Updraft helicity (UH), convective available potential energy (CAPE), storm relative helicity (SRH), and convective inhibition (CIN) were used to determine the favorability for the three tornadic storm events in the different climate states. We found that from the pre-industrial to present, the potential for tornadic storms decreased in the winter event and increased in the nocturnal and spring events. With future climate change, the potential for tornadic storms increased in the winter and nocturnal events in association with increased CAPE, and decreased in the spring event despite greater CAPE.

Study of strong tornadoes in Central Europe: Various aspects of Forecasting and Nowcasting

<p>Tornados pose a significant threat to life, property, and economy. Thus, an analysis of tornadoes is of high relevance. An understanding of historical events, e.g. regarding the characteristics of tornadic storms compared to multi-year storm statistics, may help to improve the situational awareness of future tornado events.</p><p>In this study, tornadic storms with a tornado intensity of F2 or stronger on the Fujita scale that occurred in recent years (2016 – 2020) in Germany were analyzed in detail. The four F3 tornadoes (Bützow, Affing, Bonndorf and Roetgen) and sixteen F2 tornadoes, which developed on 17 different days occurred in various parts of Germany. Most of the analysed tornadoes occurred from May to early September. The other three cases are typical winter cases that differ significantly from the summer cases in some aspects that are discussed where applicable. One case which happened in the third decade of September has characteristics form both, summer and winter, and is thus the only hybrid case. The great majority of all cases occurred during the second half of the day, most of them between 12 and 18 UTC. The most active hour was 16 to 17 UTC.</p><p>Regarding forecasting, similarities and differences of the prevailing synoptic and mesoscale conditions are assessed in addition to the convective environment of the events. Furthermore, the type of convection is analysed. The goal is to anticipate typical characteristics that enhance the threat of a potentially dangerous tornado situation. Using these findings may then help to strengthen the awareness of the forecaster. Two situations in mid- and upper-level flow are typical for the occurrence of strong tornadoes. On the majority of the analysed tornadic days, the event happened on the forward flank of a long wave trough that was slowly propagating eastward. The other typical situation is a vivid short wave trough passing rather fast over the area of interest from West to East.</p><p>Regarding nowcasting, a multi-source approach was applied to best analyse the events. For this purpose, radar reflectivity and rotation data were combined with lightning detection in order to analyse the tornadic storms with respect to storm mode and storm evolution as well as lightning and rotation characteristics. In many cases, radar radial wind data showed a persistent rotation track. The automatically detected mesocyclones had a vertical depth between 2.5 and 11 km at the time of the tornado, the diameter was above 8 km. The base of the rotation was low compared to multi-year statistics of all mesocyclonic storms. The lighting activity of the tornadic storms was high. In many cases, a lightning jump occurred between 5 and 120 minutes before the event.</p>

Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

Distinguishing Characteristics of Tornadic and Nontornadic Supercell Storms from Composite Mean Analyses of Radar Observations

An improved understanding of common differences between tornadic and nontornadic supercells is sought using a large set of observations from the operational NEXRAD WSR-88D polarimetric radar network in the contiguous United States. In particular, data from 478 nontornadic and 294 tornadic supercells during a 7-yr period (2011–17) are used to produce probability-matched composite means of microphysical and kinematic variables. Means, which are centered on echo-top maxima and in a horizontal coordinate system rotated such that storm motion points in the positive x dimension, are created in altitude relative to ground level at times of peak echo-top altitude and peak midlevel rotation for nontornadic supercells and times at and prior to the first tornado in tornadic supercells. Robust differences between supercell types are found, with consistent characteristics at and preceding tornadogenesis in tornadic storms. In particular, the mesocyclone is found to be vertically aligned in tornadic supercells and misaligned in nontornadic supercells. Microphysical differences found include a low-level radar reflectivity hook echo aligned with and ~10 km right of storm center in tornadic supercells and displaced 5–10 km down-motion in nontornadic supercells, a low-to-midlevel differential radar reflectivity dipole that is oriented more parallel to storm motion in tornadic supercells and more perpendicular in nontornadic supercells, and a separation between enhanced differential radar reflectivity and specific differential phase (with unique displacement-relative correlation coefficient reductions) at low levels that is more perpendicular to storm motion in tornadic supercells and more parallel in nontornadic supercells.

Evaluating the Ability of Remote Sensing Observations to Identify Significantly Severe and Potentially Tornadic Storms

Remote sensing observations, especially those from ground-based radars, have been used extensively to discriminate between severe and nonsevere storms. Recent upgrades to operational remote sensing networks in the United States have provided unprecedented spatial and temporal sampling to study such storms. These networks help forecasters subjectively identify storms capable of producing severe weather at the ground; however, uncertainties remain in how to objectively identify severe thunderstorms using the same data. Here, three large-area datasets (geostationary satellite, ground-based radar, and ground-based lightning detection) are used over 28 recent events in an attempt to objectively discriminate between severe and nonsevere storms, with an additional focus on severe storms that produce tornadoes. Among these datasets, radar observations, specifically those at mid- and upper levels (altitudes at and above 4 km), are shown to provide the greatest objective discrimination. Physical and kinematic storm characteristics from all analyzed datasets imply that significantly severe [≥2-in. (5.08 cm) hail and/or ≥65-kt (33.4 m s−1) straight-line winds] and tornadic storms have stronger upward motion and rotation than nonsevere and less severe storms. In addition, these metrics are greatest in tornadic storms during the time in which tornadoes occur.

A Background Investigation of Tornado Activity across the Southern Cumberland Plateau Terrain System of Northeastern Alabama

The effects of terrain on tornadoes are poorly understood. Efforts to understand terrain effects on tornadoes have been limited in scope, typically examining a small number of cases with limited observations or idealized numerical simulations. This study evaluates an apparent tornado activity maximum across the Sand Mountain and Lookout Mountain plateaus of northeastern Alabama. These plateaus, separated by the narrow Wills Valley, span ~5000 km2 and were impacted by 79 tornadoes from 1992 to 2016. This area represents a relative regional statistical maximum in tornadogenesis, with a particular tendency for tornadogenesis on the northwestern side of Sand Mountain. This exploratory paper investigates storm behavior and possible physical explanations for this density of tornadogenesis events and tornadoes. Long-term surface observation datasets indicate that surface winds tend to be stronger and more backed atop Sand Mountain than over the adjacent Tennessee Valley, potentially indicative of changes in the low-level wind profile supportive to storm rotation. The surface data additionally indicate potentially lower lifting condensation levels over the plateaus versus the adjacent valleys, an attribute previously shown to be favorable for tornadogenesis. Rapid Update Cycle and Rapid Refresh model output indicate that Froude numbers for the plateaus in tornadic environments are likely supportive of enhanced low-level flow over the plateaus, which further indicates the potential for favorable wind profile changes for tornado production. Examples of tornadic storms rapidly acquiring increased low-level rotation while reaching the plateaus of northeast Alabama are presented. The use of this background to inform the VORTEX-SE 2017 field campaign is discussed.

Quantifying the Separation of Enhanced ZDR and KDP Regions in Nonsupercell Tornadic Storms

Tornadoes associated with nonsupercell storms present unique challenges for forecasters. These tornadic storms, although often not as violent or deadly as supercells, occur disproportionately during the overnight hours and the cool season—times when the public is more vulnerable. Additionally, there is significantly lower warning skill for these nonsupercell tornadoes compared to supercell tornadoes. This study utilizes dual-polarization Weather Surveillance Radar-1988 Doppler (WSR-88D) data to analyze nonsupercell tornadic storms over a three-and-a-half-year period focused on the mid-Atlantic and southeastern United States. A signature found in a large number of cases is the separation of low-level specific differential phase KDP and differential reflectivity ZDR enhancement regions, thought to arise owing to size sorting. This study employs a new method to define the “separation vector,” which comprises the distance separating the enhancement regions and the direction from the KDP enhancement region to the ZDR enhancement region, measured relative to storm motion. While there is some variation between cases, preliminary results show that the distribution of separation distance between the enhancement regions is centered around 3–4 km and tends to maximize around the time of tornadogenesis. A preferred quadrant for separation direction is found between parallel and 90° to the right of storm motion and is most orthogonal near the time of tornadogenesis. Further, it is shown that, for a given separation distance, separation direction increasing from 0° toward 90° is associated with increased storm-relative helicity.

Is There a “Tipping Point” between Simulated Nontornadic and Tornadic Supercells in VORTEX2 Environments?

Previous work has suggested that the lower-tropospheric wind profile may partly determine whether supercells become tornadic. If tornadogenesis within the VORTEX2 composite environments is more sensitive to the lower-tropospheric winds than to either the upper-tropospheric winds or the thermodynamic profile, then systematically varying the lower-tropospheric wind profile might reveal a “tipping point” between nontornadic and tornadic supercells. As a test, simulated supercells are initiated in environments that have been gradually interpolated between the low-level wind profiles of the nontornadic and tornadic VORTEX2 supercell composites while also interchanging the upper-tropospheric winds and thermodynamic profile. Simulated supercells become tornadic when the low-level wind profile incorporates at least 40% of the structure from the tornadic VORTEX2 composite environment. Both the nontornadic and tornadic storms have similar outflow temperatures and availability of surface vertical vorticity near their updrafts. Most distinctly, a robust low-level mesocyclone and updraft immediately overlie the intensifying near-surface circulation in each of the tornadic supercells. The nontornadic supercells have low-level updrafts that are disorganized, with pockets of descent throughout the region where surface vertical vorticity resides. The lower-tropospheric wind profile drives these distinct configurations of the low-level mesocyclone and updraft, regardless of the VORTEX2 composite upper-tropospheric wind profile or thermodynamic profile. This study therefore supports a potentially useful, robust link between the probability of supercell tornadogenesis and the lower-tropospheric wind profile, with tornadogenesis more (less) likely when the orientation of horizontal vorticity in the lowest few hundred meters is streamwise (crosswise).