This study presents a novel method of tornado track identification in forested regions in Europe based on remote sensing data. The method enables an objective estimate (i.e. independent of population ...density and observational networks) of tornado climatology in forested regions. The method is based on the identification of narrow and elongated areas as forest disturbances obtained using Landsat satellite images and Landsat-based Global Forest Change (GFC) data. These areas were subsequently verified with high-resolution satellite images for verification of a tornadic cause of forest damage. Landsat and MODIS satellite images, weather station observations and reanalysis data were additionally involved in order to determine tornado dates. A minimum F-scale tornado intensity was estimated by a Weibull distribution model using information on tornado path lengths and widths. The method is applied to the forested regions of northeast Europe, where 110 tornado tracks were identified between the 2000 and 2014years, 105 of which were previously unreported and discovered for the first time. For some regions, tornado density estimates using the new method is 2–3 times higher than other previously published estimates. The largest number of tornadoes occurred in 2009, and June is the most favourable month for tornado formation (including strong tornadoes and tornado outbreaks). Most identified tornadoes have path length <10km with maximum and mean widths of approximately 200–300m and 100–200m, respectively. A few tornadoes with long and wide paths were found; four of them likely had F3 minimal intensity.
•A novel method for tornado track identification is proposed.•The method allows robust identification of relatively strong tornadoes in forested areas.•The method was implemented for forested regions of northeast Europe for 2000–2014years.•110 tornado tracks were found, 105 of them were reported for the first time.•Estimated tornado density is 2–3 times higher than previously published.
•Effects of swirl ratio and translation speed (tornado features) on tornado loading.•Effect of building’s distance to tornado mean path on tornado loading.•Effect of building’s orientation on tornado ...loading.•Maximum peak wind load coefficients for a low-rise building.
Significant parameters that influence tornado-induced wind loads on low-rise buildings are yet to be fully explored. In the current study, the influence of tornado parameters such as swirl ratio and translation speed and building’s spatial parameters such as its distance from the tornado mean path and its orientation with respect to the tornado’s translation direction on tornado-induced wind loads are investigated. A low-rise gable roof building with a roof angle of 35 degrees and a square plan area is chosen for this study. Laboratory simulated tornadoes with two swirl ratios with different ground-surface pressure characteristics, and three translation speeds were used. The 1:200-scaled building model that was used for this study was located on both sides of the simulated tornado’s mean path at several locations up to the distance of several tornado-core radii. At locations where maximum loadings occurred, orientation of the building was changed to explore its effect on peak loads. Results show significantly larger peak load coefficients for the tornado with lower swirl ratio which were comparable to its peak ground surface pressure drop. Peak roof uplift on the building located at the tornado’s mean path is smaller by 6–19% for the lower-swirl tornado case and up to 16% for the higher-swirl tornado case, compared to the other locations, for the three translation speeds investigated. For simulated tornado with lower swirl ratio, measurements showed that peak roof uplift increases with increase in translation speed when building is located on tornado mean path, whereas peak roof uplift decreases with increase in translation speed at locations other than tornado mean path. For tornado with higher swirl ratio, increase in translation speed does not change the maximum peak uplift load. Building experiences maximum horizontal and uplift loads at building orientation angle of −45° and 0° for lower swirl tornado case and −45° and −30° for higher swirl tornado case, respectively, with respect to the translation direction of the tornado.
A Tornado is a strong wind or it can also be called a big, very strong storm with a whirlwind at a certain speed. Disasters cannot be predicted at any time and can occur. The need for disaster ...preparedness to prevent the risk of human casualties, material losses, environmental damage and psychological impacts that threaten and disrupt people's lives and livelihoods. Elderly is a group that is very at risk before, during and after a disaster occurs, because the elderly have many chronic diseases, functional decline, cognitive impairment, dementia, and physical limitations. Preparedness is an action taken in anticipation of a disaster to ensure that the actions taken can be. This research is a quantitative study using the research design "cross sectional". This research was conducted to determine the preparedness and factors related to the preparedness of the elderly in facing the tornado disaster in Sitinjo Village, Sitinjo District, Dairi Regency in 2021. The population in this study were 70 elderly people in the work area of Sitinjo District, the sampling technique was stratified random sampling and met the inclusion criteria. The results of the study obtained the majority of respondents in the elderly, low education, female gender, lack of knowledge, have a positive attitude toward disaster preparedness of the Tornado wind, have experienced the Tornado disaster, are not prepared for the Tornado wind disaster. The results of chi square statistical test showed that there is no relationship between age, gender and the preparedness of the elderly in the face of Tornado disaster. There is a relationship between education p-value 0.022, knowledge p-value 0.01, attitude p-value 0.002, and experience p-value 0.021 with the preparedness for the cyclone disaster. It is hoped that the elderly can increase the knowledge and preparedness for the putting wind disaster by participating in socialization, training and conducting disaster simulations and it is necessary to coordinate with the relevant Dairi Regency BPBD to conduct socialization and mitigation of Tornado wind disaster preparedness
Numerical simulation of tornado-like vortices, like those produced in experimental facilities, poses many challenges. This is attributed to the complexity of vortical flow-field and the common ...practice of directly using the geometric dimensions and configuration of physical elements like guide vane angle, ceiling height, etc. of experimental simulators as a measure of parameters needed to characterize the generated vortices. The inherent differences in geometric dimensions and vortex generation mechanisms of the existing experimental tornado simulators makes such vortex characterization very ad-hoc in nature and hinders direct comparison and validation of results. Therefore, to facilitate a common interpretation of experimental simulators, a simplified numerical tornado model, representing the three types of existing experimental tornado simulators, is developed in this study. The three experimental simulators in consideration are VorTECH at Texas Tech University, Tornado Simulator at Iowa State University and WindEEE Dome at Western University as representatives of “Ward” type, “top-down” type and “3-D wind chamber” type designs, respectively. First, the numerically generated flow-field for each simulator obtained by modelling full experimental system is validated with experimental results. Then the simplification of these full laboratory models into a cylindrical computational domain is carried out by extracting vortex characterizing parameters strictly from the flow-field for various configurations. The dimensions and inlet boundary condition of the cylindrical model vary from one configuration to other and are dictated by vortex characterizing parameters like inflow depth, radius of updraft, swirl ratio etc. The result of this study is a simplified generic numerical tornado model that (i) can reproduce the flow-field of the original experimental systems, (ii) shows a direct dependence of the vortex flow-structure on parameters obtained from flow-field (as opposed to extracting them directly from the physical dimensions of experimental simulators).
•A generic numerical tornado model is developed that can replicate flow-field generated in experimental facilities.•The parameters required to characterize tornado-like vortices are strictly extracted from the flow-field.•These parameters are then utilized in the development and calibration of a simplified numerical model.•Tornado flow-fields from the simplified and full CFD models replicating the experimental facilities are compared.•The numerical tornado model developed in this study can be further used for preliminary tornadic wind load evaluation.
Abstract
This study examines the possibility that supercell tornado forecasts could be improved by utilizing the storm-relative helicity (SRH) in the lowest few hundred meters of the atmosphere ...(instead of much deeper layers). This hypothesis emerges from a growing body of literature linking the near-ground wind profile to the organization of the low-level mesocyclone and thus the probability of tornadogenesis. This study further addresses the ramifications of near-ground SRH to the skill of the significant tornado parameter (STP), which is probably the most commonly used environmental indicator for tornadic thunderstorms. Using a sample of 20 194 severe, right-moving supercells spanning a 13-yr period, sounding-derived parameters were compared using forecast verification metrics, emphasizing a high probability of detection for tornadic supercells while minimizing false alarms. This climatology reveals that the kinematic components of environmental profiles are more skillful at discriminating significantly tornadic supercells from severe, nontornadic supercells than the thermodynamic components. The effective-layer SRH has by far the greatest forecast skill among the components of the STP, as it is currently defined. However, using progressively shallower layers for the SRH calculation leads to increasing forecast skill. Replacing the effective-layer SRH with the 0–500 m AGL SRH in the formulation of STP increases the number of correctly predicted events by 8% and decreases the number of missed events and false alarms by 18%. These results provide promising evidence that forecast parameters can still be improved through increased understanding of the environmental controls on the processes that govern tornado formation.
This review and analysis illustrates that the spatial distribution and temporal clustering of tornadoes in the United States are changing. Tornado activity is increasing throughout the Southeast and ...in the southern portion of the Midwest and is decreasing throughout the southern and northwestern portions of the Great Plains and in the northern Midwest. This eastward shift is seen in tornado density maps, regional and gridded trends, and in an eastward shift of the mean center of tornadoes at the annual scale and in summer. The mean centers of tornado activity in other seasons are rather insensitive to these changes. Tornadoes are also clustering on fewer days in the year, and days with few tornadoes are becoming less common whereas days with many tornadoes are becoming more common. These concurrent and opposing trends are subsequently altering the frequency distribution of tornado days. The seasonality of these big tornado days also appears to be changing, as their increase in frequency is greatest in the fall and winter. Lastly, the increasing frequency of these big tornado days, which are most common in the Southeast and southern Midwest, contributes to the documented eastward shift in tornado activity.
Tornadoes are one of the most pressing research topics in wind engineering due to the extensive damages they impact on infrastructure and the environment. The proper scaling of experimentally ...produced tornado-like vortices (TLVs) against actual tornadoes is, therefore, a quintessential part of assessing tornadic damages on the built environment. The Wind Engineering, Energy and Environment (WindEEE) Dome at Western University has already demonstrated its capacity to generate TLVs characterized by length scales in the range between 1:300 and 1:150 by using only a part of the full potential of this simulator. This paper introduces a new experimental mode of the WindEEE Dome operation intending to create larger-scale TLVs in the geometric scaling approximately 1:50. In addition to the six upper fans (source of suction) and the peripheral louvers (source of swirl) that were used in the previous TLV simulations, the new tornado mode of the WindEEE Dome also utilizes the peripheral fans situated along the periphery of the testing chamber as an additional source of angular momentum in the inflow. The simulated TLV is scaled up and compared against published Doppler-radar data of an actual tornado in the United States. Our analyses show that the WindEEE Dome large-scale TLV corresponds to EF0 to EF2-rated twisters in nature. The geometric scale of the produced TLV is ~1:50. This large geometric scale of the TLVs facilitates the experimental investigation of tornadic actions on structures, including aeroelastic testing of wind-structure interactions.
•A new experimental mode of the WindEEE Dome to create larger-scale TLVs in the geometric scaling approximately 1:50.•Facilitating the experimental investigation of tornadic actions on structures, including aeroelastic testing.•Analyzing both surface pressure and velocity field measurements and also comparing to full-scale data.•Distribution of vortex centers in the 1-, 2-, and 3-cell structures of Mode B TLVs.•Characterizing of the turbulent velocity field.
Satellite‐based post‐tornado assessments have been widely used for the detection of tornado tracks, which heavily relies on the identification of vegetation changes through observations at visible ...and near‐infrared channels. During the deadly 10–11 December 2021 tornado outbreak, a series of violent tornadoes first touched down over northeastern Arkansas, an area dominated by cropland with rare vegetation coverage in winter. Through the examination of Moderate Resolution Imaging Spectroradiometer multi‐spectral observations, this study reveals significant scars on shortwave infrared channels over this region, but none are captured by visible and near‐infrared channels. The dominant soil type is aquert (one of vertisols), whose high clay content well preserves the severe changes in soil structure during the tornado passage, when the topmost soil layer was removed and underlying soil with higher moisture content was exposed to the air. This study suggests a quick post‐tornado assessment method over less vegetated area by using shortwave infrared channels.
Plain Language Summary
This study showcases an application of using Moderate Resolution Imaging Spectroradiometer (MODIS) data to detect tornado damage tracks over northeastern Arkansas after the deadly 10–11 December 2021 tornado outbreak. The special soil type with rich clay content well retains the tornado scars, whose moisture content is higher than the surrounding area, causing significant signals on MODIS shortwave infrared channels. Although coarse in spatial resolution, MODIS’s rapid revisit cycle and minimal latency in data availability make it an ideal platform for the post‐tornado assessment over the winter farmland, when the vegetation coverage is low, thus the conventional vegetation‐based tornado track detection does not work well.
Key Points
The 2021 winter tornado outbreak left significant linear scars on Arkansas aquert farmland observed from Moderate Resolution Imaging Spectroradiometer (MODIS) shortwave infrared (SWIR) channels
The scars are unrecognizable on MODIS visible and near‐infrared channels due to the coarse resolution and rare vegetation cover in winter
SWIR provides a fast assessment of tornado track as topmost layer is removed by suction vortices and wetter underlying soil is exposed
Tornadoes cause damage to buildings and infrastructure. Providing the spatially varying tornado activities or tornado occurrence rate alone does not facilitate the tasks of checking and evaluating ...structures subjected to the tornado wind velocity hazard. In the present study, the estimation of the quantile of the tornado wind velocity hazard along the height for southern Ontario – a tornado-prone region in Canada – is carried out. For the assessment, a tornado occurrence rate model is developed by considering the reporting bias due to population density and by using the cloud-to-ground lightning flash density and thunderstorm days per year as the explanatory variables. Also, a simple equivalent along height tornado design wind profile for a vertical line-like structure is proposed by considering the bending moment and shear force along the height of the structure. Moreover, the concept of disaggregation analysis is employed to identify the scenario tornado wind profiles. The results indicate that the identified scenario wind profiles could be crudely bounded by using the rectangular wind profile and the power-law wind profile for synoptic winds, which are all hinged at the return period value of the tornado wind velocity at 10 m height.
•A systematic modeling of tornado occurrence for southern Ontario is presented.•The cloud-to-ground lightning flash density and thunderstorm days are used as explanatory variables.•Tornado wind profile based on quantiles of tornado wind speed is presented.•Simple equivalent tornado design wind profiles are developed or point-like and line like structures.
ABSTRACT
Previous tornado climatology research has relied primarily upon a mean value of tornadoes or tornado days fixed on one period to define regions of elevated tornado risk. However, a more ...comprehensive understanding of the climatological distribution of tornadoes is achieved by analysing the spatial and temporal variability of tornado days. Two methods of analysing tornado days for predefined areas across the continental United States using a refined version of the Storm Prediction Center's tornado data set for 1950–2011 are considered in this study. Statistical analyses of averages and return periods reveal the variability in the record, while consecutive tornado days present an alternative method to assess the seasonal repeatability and risk for historic, multi‐day tornado outbreaks. The results of this research better define the climatological variability of tornado events in addition to offering insight regarding the spatial patterns of locations with the greatest tornado risks, especially those with higher interannual variability.
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