Enhanced Fujita Research Articles

An Approach for Assessing Misclassification of Tornado Characteristics Using Damage

Abstract Tornado characteristics (e.g., frequency and intensity) are challenging to capture. Assessment of tornado characteristics typically requires damage as a proxy. The lack of validation in the enhanced Fujita (EF) scale and the likelihood of rural tornadoes suggests that tornado characteristics are not accurately captured. This paper presents an approach to quantify the potential misclassification of tornado characteristics using Monte Carlo simulation for residential structures in rural areas. An analytical tornado wind field model coupled with fragility curves generates degrees of damage (i.e., DOD) from the EF scale in a wind speed–to-damage approach. The simulated DODs are then used to derive damage-to–wind speed relationships built from the National Weather Service Damage Assessment Toolkit (NWS DAT). Comparisons are then made between the simulated tornado characteristics and those derived from damage. Results from the simulations show a substantial proportion of tornadoes were “missed” and path width and pathlength on average are underestimated. An EF4 rating based on damage is favored for EF3–EF5 simulated tornadoes. A linear regression was utilized and determined damage-based wind speeds of different percentiles, damage length, damage width, and the number of structures rated at a particular DOD were important for prediction. The distribution of DODs was also used to predict wind speed and the associated intensity rating. These methods were tested on actual tornado cases. Tornadoes that have the same damage-based peak wind speed can be objectively assessed to determine differences in overall intensity. The results also raise questions about the level of confidence when assessing wind speed based on damage.

Assessment of wind speeds along the damage path of the Alonsa, Manitoba EF4 tornado on 3 August 2018

Given the impracticality of attempting to directly measure wind speeds in tornadoes, wind speed estimation typically relies on the assessment of damage to structures and vegetation using classifications described in the Enhanced Fujita (EF) Scale. The advent of technology enabling the collection of large amounts of data, including detailed ground, drone, and aerial imagery, has led to a growth in research on non-conventional approaches for estimating tornado wind speeds. Research methods focused on defining the tornadic wind field based on forensic analysis of damage observations have shown promise for improving tornado assessments in a quantitative manner. In this study, novel methods for collecting forensic data following tornadoes are presented. Data from the Alonsa, MB tornado are applied to estimating the wind field along the damage path using treefall pattern analysis and threshold debris flight speed calculations. Comparison of the resulting wind speed estimates show reasonable agreement, with maximum speeds from both methods in the EF5 range. These research methods yield higher wind speeds than the maximum value obtained from the conventional EF-Scale assessment, which is in the low-end of the EF4 range based on a wood-frame house with sub-standard construction that was swept entirely from its foundation. Further work is still needed to make these methods operational for routine tornado intensity estimates.

Application of Random Forest Algorithm on Tornado Detection

Tornadoes are highly destructive small-scale extreme weather processes in the troposphere. The weather radar is one of the most effective remote sensing devices for the monitoring and early warning of tornadoes. The existing tornado detection algorithms based on radar data are unsupervised and have strict multi-altitude constraints, such as the tornado detection algorithm based on tornado vortex signatures (TDA-TVS), which may lead to high false alarm rates, and the performance of the detection algorithm is greatly affected by the radar data quality control algorithm. A novel TDA-RF algorithm based on the random forest (RF) classification algorithm is proposed for real-time tornado identification of the S-band China new generation of Doppler weather radar (CINRAD-SA). The TDA-RF algorithm uses velocity features to identify tornadoes and adds features related to reflectivity and velocity spectrum width in radar level-II data. Historical CINRAD-SA tornado data from 2006–2015 are used to construct the tornado dataset and train the TDA-RF model. The performance of TDA-RF is evaluated using CINRAD-SA data from five tornadoes of 2016–2020 with enhanced Fujita(EF) scale ratings ranging from EF0 to EF4 and distances from 10 to 130 km to the radar. TDA-RF performs well overall with the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of 71%, 29%, and 55%, respectively. Moreover, the TDA-RF improves POD and CSI, and reduces FAR compared to the TDA-TVS. The maximum tornado early-warning time of TDA-RF is 17 min, and the average is 6 min; TDA-RF can provide classification probability according to the tornado generation and development process to facilitate tracking ability.

Determination of Individual Building Performance Targets to Achieve Community-Level Social and Economic Resilience Metrics

The retrofit of wood-frame residential buildings is a relatively effective strategy to mitigate damage caused by windstorms. However, little is known about the effect of modifying building performance for intense events such as a tornado and the subsequent social and economic impacts that result at the community level following an event. This paper presents a method that enables a community to select residential building performance levels representative of either retrofitting or adopting a new design code that computes target community metrics for the effects on the economy and population. Although not a full risk analysis, a series of generic tornado scenarios for different Enhanced Fujita (EF) ratings are simulated, and five resilience metrics are assigned to represent community goals based on economic and population stability. To accomplish this, the functionality of the buildings following the simulated tornado is used as input to a computable general equilibrium (CGE) economics model that predicts household income, employment, and domestic supply at the community level. Population dislocation as a function of building damage and detailed sociodemographic US census-based data is also predicted and serves as a core community resilience metric. Finally, this proposed methodology demonstrates how the metrics can help meet community-level resilience objectives for decision support based on a level of design code improvement or retrofit level. The method is demonstrated for Joplin, Missouri. All analyses and data have been developed and made available on the open-source IN-CORE modeling environment. The proposed multidisciplinary methodology requires continued research to characterize the uncertainty in the decision support results.

A Multi-Platform Reanalysis of the Kankakee Valley Tornado Cluster on 30 June 2014

Two derecho-producing quasi-linear convective systems moved across northeast Illinois and northwest Indiana on the evening of 30 June 2014. Both produced damage across a large area, including a concentrated cluster in the Kankakee River Valley associated with two long-lived and adjacent mesovortices in the second derecho. Post-event surveys of this region revealed a widespread, complex damage pattern and initially documented 14 tornadoes of EF1 rating on the Enhanced Fujita (EF) Scale, along with a swath of damaging nontornadic winds. Later, a number of uncertainties from the original surveys were examined in conjunction with high-resolution satellite imagery not available immediately after the event. Inconsistencies noted during this process led to an intensive reanalysis of the entire cluster using radar data, the original ground and aerial surveys, and the newly available satellite imagery. This new analysis concluded that at least 18 tornadoes impacted the Kankakee Valley, most with a path orientation different from the initial results. This paper details the reassessment process from initial motivation to final results, addresses potential sources of error, and discusses operational considerations stemming from such a prolifically tornadic event.

Verification and Analysis of Impact-Based Tornado Warnings in the Central Region of the National Weather Service

The Joplin, Missouri EF5 tornado event on 22 May 2011 prompted the Central Region of the National Weather Service (NWS) to re-evaluate the current tornado warning format and implement the impact-based tornado warning (IBTW) experiment. IBTWs consist of tiers including damage tags and impact wording that convey increasing levels of damage. The damage wording within an IBTW is shown to relate to the Enhanced Fujita (EF) scale. Wording included in non-tagged IBTWs corresponds to EF0-EF2 tornado damage, while the damage wording for tagged IBTWs corresponds to EF3-EF5 tornado damage. This study investigates the accuracy of IBTWs by examining if a tornado occurs during the warning time frame, and whether the resulting damage matches the damage wording in the IBTW. All IBTWs from 1 April 2013 through 30 November 2013 were collected, as well as tornado survey information. Using these survey data, IBTWs were verified by the intensity of the tornado, if one occurred. Probability of detection (POD) and false alarm ratio (FAR) statistics are calculated through 2×2 contingency tables for both non-tagged and tagged IBTWs. Results indicate that the majority of both non-tagged and tagged IBTWs are false alarms, and tagged IBTWs have a very low POD. Other studies have shown that limitations in current technology and scientific knowledge may contribute to false alarms and missed detections. Case studies are examined to analyze whether these limitations play role in the use of IBTWs.

Changes in Tornado Climatology Accompanying the Enhanced Fujita Scale

AbstractUnited States tornado records form the basis for a variety of meteorological, climatological and disaster-risk analyses, but how reliable are they in light of changing standards for rating, as with the 2007 transition of Fujita (F) to Enhanced Fujita (EF) damage scales? To what extent are recorded tornado metrics subject to such influences that may be nonmeteorological in nature? While addressing these questions with utmost thoroughness is too large of a task for any one study, and may not be possible given the many variables and uncertainties involved, some variables that are recorded in large samples are ripe for new examination. We assess basic tornado-path characteristics—damage rating, length, width, and occurrence time, as well as some combined and derived measures—for a 24-yr period of constant path-width recording standard that also coincides with National Weather Service modernization and the WSR-88D deployment era. The middle of that period (in both time and approximate tornado counts) crosses the official switch from F to EF. At least minor shifts in all assessed path variables are associated directly with that change, contrary to the intent of EF implementation. Major and essentially stepwise expansion of tornadic path widths occurred immediately upon EF usage, and widths have expanded still further within the EF era. We also document lesser increases in path lengths, and in tornadoes rated at least EF1 compared to EF0. These apparently secular changes in the tornado data can impact research dependent on bulk tornado-path characteristics and damage-assessment results.

Environmental Controls on the Climatological Scaling of Tornado Frequency with Intensity

AbstractThe scaling of U.S. tornado frequency with enhanced Fujita (EF)-rated intensity is examined for the range EF1–EF3. Previous work has found that tornado frequency decreases exponentially with increasing EF rating and that many regions around the world show the same exponential rate of decrease despite having quite different overall tornado frequencies. This scaling is important because it relates the frequency of the most intense tornadoes to the overall tornado frequency. Here we find that U.S. tornado frequency decreases more sharply with increasing intensity during summer than during other times of the year. One implication of this finding is that, despite their rarity, when tornadoes do occur during the cool season, the relative likelihood of more intense tornadoes is higher than during summer. The environmental driver of this scaling variability is explored through new EF-dependent tornado environmental indices (TEI-EF) that are fitted to each EF class. We find that the sensitivity of TEI-EF to storm relative helicity (SRH) increases with increasing EF class. This increasing sensitivity to SRH means that TEI-EF predicts a slower decrease in frequency with increasing intensity for larger values of SRH (e.g., cool season) and a sharper decrease in tornado frequency in summer when wind shear plays a less dominant role. This explanation is also consistent with the fact that the fraction of supercell tornadoes is smaller during summer.

Tornadic environments in the Iberian Peninsula and the Balearic Islands based on ERA5 reanalysis

AbstractA dataset of 907 tornado and waterspout events recorded from 1980 to 2018 was built to study convective environments in the Iberian Peninsula and Balearic Islands (western Mediterranean). The events were grouped into different categories, distinguishing waterspouts and tornadoes that were stratified by intensity according to the Fujita (F) scale and the Enhanced Fujita (EF) scale. The analysis separated the north‐east (NE) and south‐west (SW) subareas in the region of study, which present different seasonal cycles. For each event, atmospheric profiles from the ERA5 reanalysis data were used to determine convective available potential energy (CAPE), storm‐relative helicity (SRH), vertical wind‐shear (WS), the Universal Tornadic Index (UTI), and the product of wind‐shear and the square root of two times CAPE (WMAXSHEAR). Results showed that the NE events are mostly associated with higher CAPE and lower helicity and wind‐shear than the SW events. Thus, a significant number of SW tornadoes are associated with high‐shear, low‐CAPE environments. Moreover, the low‐shear, high‐LCL tornado environment, which is common inland during warm‐season, is more usual in the NE subarea. Composite parameters such as the UTI and WMAXSHEAR06 are good discriminators between significant and weak tornado events, although WMAXSHEAR06 presents some limitations for the SW events due to low CAPE and weak differences in the WS (0–6 km) between the (E)F1 and (E)F2+ events. This weakness was resolved by using the 0–3 km WS instead of the 0–6 km WS when calculating the WMAXSHEAR. A new threshold for WMAXSHEAR03 is proposed (500 m2⋅s−2) to distinguish between significant and non‐significant tornado environments. Finally, the Szilagyi Waterspout Nomogram, originally developed for the Great Lakes of North America, was successfully tested in the forecasting of waterspout formation for the first time in the western Mediterranean area, although the technique should be adapted to correctly detect cool‐season mid‐latitude waterspouts.

Simulated Performance of Cross-Laminated Timber Residential Structures Subject to Tornadoes

Tornadoes are some of the most severe and devastating natural events and cause significant damage to structures in the United States. Light-frame wood residential structures have shown vulnerabilities to these events, but they are not explicitly addressed in the design requirements due to their infrequent occurrence, relatively small impact area (compared to hurricanes), and complex wind profile. This paper explores the potential of Cross-Laminated Timber (CLT) to serve as a residential building material, specifically with regards to its performance in tornado events. CLT is an engineered wood product made when orthogonal layers of dimensioned lumber are glued to create panels. To compare the tornado performance of CLT buildings, six archetype residential buildings were each designed using CLT and light-frame wood in accordance to the appropriate US building code provisions and engineering principles. The capacity of each of the structural components was simulated using Monte Carlo Simulation based on the panel spans and connections of the panel boundaries. In addition, the resistance to structure sliding and combined uplift and overturning was simulated using engineering principles based on the load path of a CLT residential structure. Analysis of tornado induced wind loading was performed using recommendations from the 2016 ASCE-7 commentary and applicable literature that attempts to account for the wind-induced pressures caused by tornadoes. Fragility analysis was performed to determine the probability of failure for a given estimated tornado wind-speed. When compared to the wind speeds of the Enhanced Fujita (EF) scale, the CLT residential archetypes showed wind speeds resulting in 10% probability of failure were in the range of EF-4 level events. Factors such as the connection spacing, and roof panel spans had the most significant effect on the simulated performance of the residential archetypes. Thicker panels, more robust connections, or tighter connection spacing could also lead to residential CLT structures that withstand EF-5 level events.

Evidence of Tornadoes and Microbursts in São Paulo State, Brazil: A Synoptic and Mesoscale Analysis

Synoptic and mesoscale analyses indicate environmental conditions favorable to the development of tornados and downbursts in Eastern Sao Paulo State, Brazil, between 16 May and 06 June 2016 under El Nino Sothern Oscillation (ENSO) condition. A subtropical jet stream strengthened by the 2015/2016 El Nino event over southeast Brazil and low-level moisture advection from the Amazon induced mid-level mesoscale vorticity and strong updrafts, respectively. These synoptic summer-like conditions yielded high dynamic and thermodynamic instability, producing deep convection and supercells with high lightning and precipitation rates with golf ball-sized hail stones and high winds at the surface, causing damages to trees, houses, towers and other structures with debris features associated with tornadoes and microbursts. Cellular phone photos and movies of severe weather events in Campinas and Janiru cities on 05 and 06 June 2016 suggest wind damage features caused by tornadoes ranked in the enhanced Fujita (EF) wind scale as EF1 (38–49 m s−1) and EF2 (49–60 m s−1), respectively. Similarly, cellular phone movies of Embu-Guacu City severe weather event on 16 May 2016 suggest a microburst case. The present study is based on quantitative and qualitative records of three high-impact rainfall, hail, lightning and wind gust episodes in the extra tropics during late fall 2016.

Performance of structures and infrastructure facilities during an EF4 Tornado in Yancheng

Heavy damages to properties with attendant losses were frequently caused by tornadoes in recent years. This natural hazard is one of the most destructive wind events that must be fully studied and well understood in order to keep the safety of structures and infrastructure facilities. On June 23, 2016, a severe tornado, which is an Enhanced Fujita (EF) 4 storm, occurred in the rim of a coastal city named as Yancheng in China. Numerous low-rise buildings as well as facilities (e.g., transmission towers) were destroyed or damaged. In this paper, damages to structures and infrastructure facilities by the severe tornado are reviewed. The collapses of residential buildings, industrial structures and other infrastructure facilities are described. With an overview of the damages, various possible mechanisms of the collapse are then discussed and utilized to reveal the initiation of the damage to various facilities. It is hoped that this paper can provide a concise but comprehensive reference for the researchers and engineers to help understand the tornado effects on structures and expose the vulnerabilities that need to be improved in current wind-resistant design practices.

Pattern and spectrum of tornado injury and its geographical information system distribution in Yancheng, China: a cross-sectional study

ObjectivesFew studies of tornado injuries have considered differences related to damage levels and Enhanced-Fujita (EF) scale ratings. This study aimed to evaluate the pattern, spectrum and geographical distribution of injuries...

Tornado identification and forewarning with very high frequency windprofiler radars

The ability of very high frequency (VHF) (~50 MHz) windprofilers to measure backscatter, winds and turbulence in the troposphere and the lower stratosphere gives them a unique perspective not available with many other remote sounding radar techniques. This capability has been utilized to study the environment of 31 tornadoes generated in the provinces of Ontario and Quebec in Canada over an 11‐year period. Tornadoes were mostly of Enhanced Fujita (EF) types EF0 to EF2, with one being EF3. Focus is on events which produced visible damage. Signals detected show characteristics demonstrating new informative—and potentially predictive—capabilities. A large enhancement in backscattered power immediately above the common volume of the radar and the tornadic supercell, reaching to the tropopause and beyond, when coupled with radar measurements of strong turbulence and wind speeds, provides good radar evidence of tornadic activity.

Sounding‐derived parameters associated with tornadic storms in Catalonia

ABSTRACTCatalonia, a southern Europe coastal region in the western Mediterranean basin, is regularly affected by severe local storms which every year produce an average of 5 tornadoes and 12 waterspouts, based on data recorded from 2000 to 2016. Despite these tornadoes mostly being weak – not exceeding EF1 on the enhanced Fujita (EF) damage intensity scale – they occasionally reach stronger intensities, posing an evident threat to population and socio‐economic activity, particularly in densely populated coastal conurbations such as Tarragona or Barcelona. This study provides analysis of upper air conditions that favour the formation of tornadic storms in the region, considering five different stations in Spain and France to build a database of 333 soundings which included 49 tornadic soundings, 104 waterspout soundings (WAT) as well as non‐tornadic thunderstorms and dry period soundings. For each one, 12 different parameters were calculated and analysed to test their potential capacity to discriminate non‐tornadic from tornadic environments and also to assess the feasibility of stratifying tornado intensity (EF0, and EF1 or stronger, on the EF scale). The results indicate that storm‐relative helicity for the layer 0–3 km, with a threshold value of 150 m2 s−2, wind shear for the same layer, with a threshold of 15 m s−1, and composite parameters such as the supercell composite parameter with a threshold of 1.2 and universal tornadic index with a threshold of 0.3 are all useful to distinguish between non‐tornadic thunderstorms and EF1 or stronger tornadic events. These results contribute to a better description of the climatology of upper air conditions that favour tornadic storms in the region and can also help operational weather forecasting and surveillance tasks, thus increasing situational awareness in severe convective weather events.

Sensitivities of 1-km Forecasts of 24 May 2011 Tornadic Supercells to Microphysics Parameterizations

On 24 May 2011, Oklahoma experienced an outbreak of tornadoes, including one rated EF5 on the enhanced Fujita (EF) scale and two rated EF4. The extensive observation network in this area makes this an ideal case to examine the impact of using five different microphysics parameterization schemes, including single-, double-, and triple-moment microphysics, in an efficient high-resolution data assimilation system suitable for nowcasting and short-term forecasting with low latencies. Additionally, the real-time configuration of the 1-km ARPS, which assimilated increments produced by 3DVAR with cloud analysis using incremental analysis updating (IAU), had success providing a good baseline forecast. ARPS forecasts of 0–2 h are verified using observation-point, neighborhood, and object-based verification techniques. The object-based verification technique uses updraft helicity fields to represent mesocyclone centers, which are verified against tornado locations from three supercells of interest. Varying levels of success in the forecasts are found and appear to be dependent on the complexity of the storm interaction, with early forecasts of isolated storms exhibiting the most success. Verification scores indicate that the multimoment microphysics schemes tend to produce better forecasts of tornadic supercells. However, some of the forecasts from the single-moment microphysics schemes perform as well as or better than the forecasts from the multimoment microphysics schemes.

Empirical Approach to Evaluating the Tornado Fragility of Residential Structures

Tornado-induced wind load modeling has advanced significantly in recent years, but comparison of the experimental or numerical models to observed tornado damage is limited. This paper describes the development of empirically derived tornado fragility functions for residential structures following the 22 May 2011 Joplin, Missouri tornado. The fragility functions were created by combining a residential structure damage assessment of the Joplin tornado using the enhanced Fujita (EF) scale and a tornado wind field model conditioned to tree-fall patterns. The damage states for the fragility functions used the degrees of damage (DOD) for one- and two-story residential structures from the EF scale. The empirical tornado fragility functions were compared to analytically derived fragility functions for straightline winds from the FEMA Hazus hurricane model to provide a first attempt at ascertaining how different or similar failure wind speeds are for residential structures under tornado-induced and straightline wind loads. Median failure wind speeds from the empirical tornado fragility functions increased monotonically with DOD, from 33.4 m/s for DOD1 to 85.6 m/s for DOD9. Median failure wind speeds of the empirical tornado fragility functions and Hazus hurricane straightline wind fragility functions differed by 5% or less when suburban terrain was assumed throughout the damage path, and 25% or less when open terrain was assumed. The results suggest that tornado load amplification factors are at worst no more than 55% for residential structures, and may be lower than 10%.

Using High-Resolution Simulations to Quantify Underestimates of Tornado Intensity from In Situ Observations

Abstract Large-eddy simulations are used to produce realistic, high-resolution depictions of near-surface winds in translating tornadoes. The translation speed, swirl ratio, and vertical forcing are varied to provide a range of vortex intensities and structural types. Observation experiments are then performed in which the tornadoes are passed over groups of simulated sensors. Some of the experiments use indestructible, error-free anemometers while others limit the range of observable wind speeds to mimic the characteristics of damage indicators specified in the enhanced Fujita (EF) scale. Also, in some of the experiments the sensors are randomly placed while in others they are positioned in regularly spaced columns perpendicular to the vortex tracks to mimic field project deployments. Statistical analysis of the results provides quantitative insight into the limitations of tornado intensity estimates based on damage surveys or in situ measurements in rural or semirural areas. The mean negative bias relative to the “true” global maximum 3-s gust at 10 m AGL (the standard for EF ratings) exceeds 10 m s−1 in all cases and 45 m s−1 in some cases. A small number of sensors are generally sufficient to provide a good approximation of the running time-mean maximum during the period of observation, although the required spatial resolution of the sensor group is still substantially higher than that previously attained by any field program. Because of model limitations and simplifying assumptions, these results are regarded as a lower bound for tornado intensity underestimates in rural and semirural areas and provide a baseline for further inquiry.

Diagnosing the Conditional Probability of Tornado Damage Rating Using Environmental and Radar Attributes

Abstract Radar-identified convective modes, peak low-level rotational velocities, and near-storm environmental data were assigned to a sample of tornadoes reported in the contiguous United States during 2009–13. The tornado segment data were filtered by the maximum enhanced Fujita (EF)-scale tornado event per hour using a 40-km horizontal grid. Convective mode was assigned to each tornado event by examining full volumetric Weather Surveillance Radar-1988 Doppler data at the beginning time of each event, and 0.5° peak rotational velocity (Vrot) data were identified manually during the life span of each tornado event. Environmental information accompanied each grid-hour event, consisting primarily of supercell-related convective parameters from the hourly objective mesoscale analyses calculated and archived at the Storm Prediction Center. Results from examining environmental and radar attributes, featuring the significant tornado parameter (STP) and 0.5° peak Vrot data, suggest an increasing conditional probability for greater EF-scale damage as both STP and 0.5° peak Vrot increase, especially with supercells. Possible applications of these findings include using the conditional probability of tornado intensity as a real-time situational awareness tool.

Reconstruction of a near-surface tornado wind field from observed building damage

In this study, residential building damage states observed from a post-tornado damage survey in Joplin after a 2011 EF 5 tornado were used to reconstruct the near-surface wind field. It was based on well-studied relationships between Degrees of Damage (DOD) of building and wind speeds in the Enhanced Fujita (EF) scale. A total of 4,166 one- or two-family residences (FR12) located in the study area were selected and their DODs were recorded. Then, the wind speeds were estimated with the EF scale. The peak wind speed profile estimated from damage of buildings was used to fit a translating analytical vortex model. Agreement between simulated peak wind speeds and observed damages confirms the feasibility of using post-tornado damage surveys for reconstructing the near-surface wind field. In addition to peak wind speeds, the model can create the time history of wind speed and direction at any given point, offering opportunity to better understand tornado parameters and wind field structures. Future work could extend the method to tornadoes of different characteristics and therefore improve model's generalizability.