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

Smith, Bryan T.; Thompson, Richard L.; Dean, Andrew R.; Marsh, Patrick T.

doi:10.1175/waf-d-14-00122.1

Cited by 53 publications

(50 citation statements)

References 40 publications

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“…In addition, the results of the Mann-Whitney test indicated the STP associated with violent tornadoes was greater than the STP associated with significant tornadoes. These results are similar to the findings from Smith et al (2015).…”

Section: A Previously Researched Parameterssupporting

confidence: 92%

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Relationship of Low-Level Instability and Tornado Damage Rating Based on Observed Soundings

Hampshire¹,

Mosier²,

Ryan³

et al. 2018

J. Operational Meteor.

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A database of upper-air soundings was collected for weak (EF0/EF1), significant (EF2/EF3), and violent (EF4/ EF5) tornadoes that occurred within 100 km and 6 h of the rawindsonde observation. After case filtering and quality control, a total of 50 proximity soundings for violent tornadoes and randomized samples of 100 proximity soundings for significant tornadoes and 102 for weak tornadoes were obtained. Key convective parameters were analyzed between the tornado datasets. Low-level instability parameters (0-3-km lapse rates and 0-3-km mixed-layer convective available potential energy) were noteworthy predictors of the highest tornado damage rating, whereas mixed-layer lifted condensation level, wind shear, and effective storm relative helicity displayed little predictive skill distinguishing significant and violent tornado environments. The ability of the significant tornado parameter (STP) to discriminate between significant and violent tornadoes also was analyzed. This analysis found that STP does statistically discriminate between violent and significant tornadoes, with mixedlayer convective available potential energy the best discriminator of its variables. Because of the skill in the lowlevel instability parameters, this study also offers a new violent tornado parameter that includes the low-level instability fields in order to better differentiate between significant and violent tornado environments. ABSTRACT (Manuscript

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Section: A Previously Researched Parameterssupporting

confidence: 92%

“…The specific effects of low-level instability were not presented. Smith et al (2015) did address violent tornadoes independently in terms of the STP and found values about two quartiles larger than the EF2 tornadoes. However, STP was the only parameter studied when investigating the violent tornado environments.…”

Section: Introductionmentioning

confidence: 97%

Relationship of Low-Level Instability and Tornado Damage Rating Based on Observed Soundings

Hampshire¹,

Mosier²,

Ryan³

et al. 2018

J. Operational Meteor.

View full text Add to dashboard Cite

show abstract

“…To contextualize these observations, the vortex strength can also be expressed as a rotational wind (half the shear) and thereby compared with NEXRAD observations from a large sample of ordinary tornadic storms compiled in Smith et al (2015). The maximum FGV rotational winds (18.5 m/s) fall in the interquartile range of EF1-2 tornadoes linked to quasi-linear convective systems and EF0-1 tornadoes spawned from supercells (see Figure 7 in Smith et al, 2015). The estimated EF-3 surface winds in the Carr fire vortex exceed these intensity classifications, which may reflect contributions of fire processes to vortex intensification, uncertainties in the wind estimates due to fire damage, or other unknown factors.…”

Section: Vortex Evolutionmentioning

confidence: 99%

The Carr Fire Vortex: A Case of Pyrotornadogenesis?

Lareau

Nauslar²,

Abatzoglou

2018

Geophysical Research Letters

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Radar and satellite observations document the evolution of a destructive fire‐generated vortex during the Carr fire on 26 July 2018 near Redding, California. The National Weather Service estimated that surface wind speeds in the vortex were in excess of 64 m/s, equivalent to an EF‐3 tornado. Radar data show that the vortex formed within an antecedent region of cyclonic wind shear along the fire perimeter and immediately following rapid vertical development of the convective plume, which grew from 6 to 12 km aloft in just 15 min. The rapid plume development was linked to the release of moist instability in a pyrocumulonimbus (pyroCb). As the cloud grew, the vortex intensified and ascended, eventually reaching an altitude of 5,200 m. The role of the pyroCb in concentrating near‐surface vorticity distinguishes this event from other fire‐generated vortices and suggests dynamical similarities to nonmesocyclonic tornadoes.

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“…The TorMC model represents an important step in the simulation of the dynamic relationship between tornado risk, severity and vulnerability over time and space by assessing tornado impacts on an annual time scale. However, from an operational standpoint, it would be useful to have a model capable of simulating tornado impacts on shorter time scales (Karstens et al, 2015;Smith et al, 2015). A daily impacts model would allow a user to determine how the impact of an observed tornado footprint compares with the potential impacts that could have occurred under the same atmospheric environment (i.e.…”

Section: Introductionmentioning

confidence: 99%

A tornado daily impacts simulator for the central and southern United States

Hatzis

Koch

Brooks

2020

Meteorological Applications

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In an average year (1979–2016), the United States experiences nearly 1,100 tornadoes, which cause a total of 68 fatalities. Annual fatality rates have decreased since the peak in the 1920s, but there is a concern that they could start to rise again with increases in vulnerable populations and the impacts of climate change. It is possible to assess the risk of tornado fatalities using the historical record. However, the rarity of tornadoes and the short period of record may not capture the true risk. One way around this problem is to simulate thousands of years’ worth of tornadoes to obtain a broader picture of risk. Previous tornado risk models have distributed tornadoes randomly or used climatology to generate realistic tornado patterns on an annual (or longer) time scale. From an operational standpoint, it would be useful to have a model that distributes tornadoes on a daily time step to enable the forecasting of potential tornado impacts on a given day. The present study introduces one such model that distributes tornadoes using information about the favourability of the atmospheric environment for tornado development: The Tornado Daily Impacts Simulator (TorDIS). The paper demonstrates model utility through 1,000 year simulations over several metropolitan areas and with a comparison between modelled and observed impacts for several high‐impact tornado days. Forecasting potential tornado impacts on a daily time step could allow emergency managers to plan ahead for high‐risk days to prioritize their resources and save lives.

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

Cited by 53 publications

References 40 publications

Relationship of Low-Level Instability and Tornado Damage Rating Based on Observed Soundings

Relationship of Low-Level Instability and Tornado Damage Rating Based on Observed Soundings

The Carr Fire Vortex: A Case of Pyrotornadogenesis?

A tornado daily impacts simulator for the central and southern United States

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