Increasingly Powerful Tornadoes in the United States

Elsner, James B.; Fricker, Tyler; Schroder, Zoe

doi:10.1029/2018gl080819

Cited by 44 publications

(28 citation statements)

References 24 publications

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“…Signs on the fixed-effect coefficients (Table 3) are consistent with expectations based on physical reasoning derived from the current understanding of how environmental factors influence tornado activity (Smith et al, 2012;Thompson et al, 2017). The coefficient on cluster year is positive indicating a trend toward higher rated tornadoes as discussed in Elsner et al (2018). The coefficient on distance-to-nearest-city/town is negative as expected.…”

Section: Resultssupporting

confidence: 81%

“…Coefficients on the environmental variables are consistent with expectations based on physical reasoning derived from the current understanding of how environmental factors influence tornado activity. There is a trend toward higher rated tornadoes with time as inferred in Elsner et al (2018). The closer a tornado occurs to a city/town, the greater the chance it will get rated at the next higher EF rating.…”

Section: Discussionmentioning

confidence: 71%

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Tornado damage ratings estimated with cumulative logistic regression

Elsner¹,

Schroder²

2019

Preprint

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Empirical studies have led to improvements in evaluating and quantifying the tornado threat. However more work is needed to put the research onto a solid statistical foundation. Here the authors begin to build this foundation by introducing and then demonstrating a statistical model to estimate damage rating probabilities. A goal is to alert researchers to available statistical technology for improving severe weather warnings. The model is cumulative logistic regression and the parameters are determined using Bayesian inference. The model is demonstrated by estimating damage rating probabilities from values of known environmental factors on days with many tornadoes in the United States. Controlling for distance-to-nearest town/city, which serves as a proxy variable for damage target density, the model quantifies the chance that a particular tornado will be assigned any damage rating given specific environmental conditions. Under otherwise average conditions the model estimates a 65% chance that a tornado occurring in a city or town will be rated EF0 when bulk shear is weak (10 m/s). This probability drops to 38% when the bulk shear is strong (40 m/s). The model quantifies the corresponding increases in the chance of the same tornado receiving higher damage ratings. Quantifying changes to the probability distribution on the ordered damage rating categories is a natural application of cumulative logistic regression.

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Section: Resultssupporting

confidence: 81%

Section: Discussionmentioning

confidence: 71%

Tornado damage ratings estimated with cumulative logistic regression

Elsner¹,

Schroder²

2019

Preprint

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“…densities and are highly susceptible to wind flow in extreme wind events 51 . In addition, as the climate changes, high wind storm events such as hurricanes and tornadoes will increase in strength and/or frequency, outside of the system's historic norms 5,[52][53][54] .…”

mentioning

confidence: 99%

The impact of Hurricane Michael on longleaf pine habitats in Florida

Zampieri

Pau

Okamoto

2020

Sci Rep

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Global biodiversity hotspots (GBHs) are increasingly vulnerable to human stressors such as anthropogenic climate change, which will alter the ecology of these habitats, even where protected. the longleaf pine (Pinus palustris) ecosystem (Lpe) of the north American coastal plain is a GBH where disturbances are integral for ecosystem maintenance. However, stronger storms due to climate change may be outside their historical norm. in this study, we estimate the extent of florida Lpe that was directly affected by Hurricane Michael in 2018, an unprecedented Category 5 storm. We then leveraged a unique data set in a Before-After study of four sites within this region. We used variable-area transects and generalized linear mixed-effects models to estimate tree densities and logistic regression to estimate mortality by size class. We found at least 28% of the global total remaining extent of LPE was affected in Florida alone. Mortality was highest in medium sized trees (30-45 cm dbh) and ranged from 4.6-15.4% at sites further from the storm center, but increased to 87.8% near the storm center. As the frequency and intensity of extreme events increases, management plans to mitigate climate change need to account for large-scale stochastic mortality events to preserve critical habitats. Ecological disturbances play an integral role in maintaining ecosystem structure and functioning 1-3. Many ecological disturbances are expected to change with anthropogenic climate change 4 , altering the frequency, intensity, duration, and timing of events 5. Shifting disturbance regimes due to climate change pose a threat to the conservation of biodiversity as species experience conditions outside their historical norms 6-8. In savanna systems, which are characterized by a grassy or herbaceous understory and low tree densities, changing disturbance regimes can trigger demographic transitions altering the density of trees 9-11 , upon which biodiversity depends. Longleaf pine (Pinus palustris Mill.) habitats located within the North American Coastal Plain (NACP) are a global biodiversity hotspot 12,13. These savanna-type systems provide critical habitat for numerous endangered plant and animal species, which are dependent on the presence of sparse but critically important mature longleaf pine trees 14-17. The canopy of longleaf pine habitats is generally monotypic, with a range of tree densities (from <100 to 300+ tree/ha), a largely open canopy, and an herbaceous, grass dominated understory 18-20. Frequent seasonal fire is an integral part of this ecosystem and is the most important process for maintaining ecosystem structure and function 12,21-24. The highest quality stands are dominated by mature trees with a sufficiently frequent fire interval (1-5 year return) to promote regeneration and maintain a highly biodiverse understory-containing as many as >40 species per m 2,17,25-28. Canopy gaps are critical in promoting this biodiverse understory 29 and allow for recruitment and regeneration of longleaf pine 30,31. Gaps allow for greater li...

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“…Recent studies find upward trends in the interannual variability and clustering of tornadoes over the past few decades (Brooks et al, 2014;Elsner et al, 2015;Tippett et al, 2015). They also find a shift in the areal extent of tornado occurrence (Agee et al, 2016;Moore, 2017), and increasing tornado power (Elsner et al, 2018b). Other research argues that an increase in total population and dispersal of the built environment will lead to an increase in the amount of tornado destruction (Strader et al, 2017).…”

Section: Discussionmentioning

confidence: 98%

Evaluating tornado casualty rates in the United States

Fricker

2020

International Journal of Disaster Risk Reduction

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Tornadoes account for nearly one fifth of all natural hazard fatalities in the United States, yet there exist no general estimates of casualty rates across the country. Here tornado casualty rates are estimated for all casualty-producing tornadoes over the period 1995-2016 using tornado level information related to the population and total housing units within each damage path. The 22-year United States per-capita casualty rate is 2.3%, while the 22-year United States per-housing unit casualty rate is 5.4%. Injury and fatality rates are also estimated over the same period. The 22-year United States per-capita fatality rate is .15% and the per-capita injury rate is 2.1%. The per-housing unit fatality rate is .36% and the per-housing unit injury rate is 5.1%. Casualty rates are further examined through subsets of Enhanced Fujita rating, state boundaries, and county boundaries. When used in conjunction with estimates of future changes in tornado behavior and population growth, these casualty rates can help predict tornado casualty events in communities throughout the United States.

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Increasingly Powerful Tornadoes in the United States

Cited by 44 publications

References 24 publications

Tornado damage ratings estimated with cumulative logistic regression

Tornado damage ratings estimated with cumulative logistic regression

The impact of Hurricane Michael on longleaf pine habitats in Florida

Evaluating tornado casualty rates in the United States

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