Limits...
A Statistical Model for Regional Tornado Climate Studies.

Jagger TH, Elsner JB, Widen HM - PLoS ONE (2015)

Bottom Line: The model is significantly improved by adding terrain roughness.The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation.Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, Florida State University, Tallahassee, Florida, United States of America.

ABSTRACT
Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

No MeSH data available.


Related in: MedlinePlus

Correlated random effects from the Kansas tornado model.Values are the posterior mean and are expressed as the percent difference from the state average. The model includes annual population density and calendar year as fixed effects.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4526675&req=5

pone.0131876.g006: Correlated random effects from the Kansas tornado model.Values are the posterior mean and are expressed as the percent difference from the state average. The model includes annual population density and calendar year as fixed effects.

Mentions: The random-effects term is the spatially correlated set of residuals that provides a description of tornado occurrence statewide that accounts for population changes, differences in exposure, and trend within each county. A map of this term reveals where tornadoes are more likely relative to the state average (Fig 6) after controlling for population density, county area and annual variation. Values are the posterior means and are expressed as a percent difference from the state average. Counties with significantly (at the 90% level) higher and lower rates are outlined in bold. Uncertainty on the magnitude of these values is measured by the posterior standard deviation (Fig 7). Standard deviations tend to be lower (precision higher) in counties with more neighbors (away from the state borders).


A Statistical Model for Regional Tornado Climate Studies.

Jagger TH, Elsner JB, Widen HM - PLoS ONE (2015)

Correlated random effects from the Kansas tornado model.Values are the posterior mean and are expressed as the percent difference from the state average. The model includes annual population density and calendar year as fixed effects.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526675&req=5

pone.0131876.g006: Correlated random effects from the Kansas tornado model.Values are the posterior mean and are expressed as the percent difference from the state average. The model includes annual population density and calendar year as fixed effects.
Mentions: The random-effects term is the spatially correlated set of residuals that provides a description of tornado occurrence statewide that accounts for population changes, differences in exposure, and trend within each county. A map of this term reveals where tornadoes are more likely relative to the state average (Fig 6) after controlling for population density, county area and annual variation. Values are the posterior means and are expressed as a percent difference from the state average. Counties with significantly (at the 90% level) higher and lower rates are outlined in bold. Uncertainty on the magnitude of these values is measured by the posterior standard deviation (Fig 7). Standard deviations tend to be lower (precision higher) in counties with more neighbors (away from the state borders).

Bottom Line: The model is significantly improved by adding terrain roughness.The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation.Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, Florida State University, Tallahassee, Florida, United States of America.

ABSTRACT
Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.

No MeSH data available.


Related in: MedlinePlus