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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.


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Tornado report frequency by county for Illinois, Mississippi, South Dakota, and Ohio.
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pone.0131876.g010: Tornado report frequency by county for Illinois, Mississippi, South Dakota, and Ohio.

Mentions: Flexibility of the model is demonstrated by fitting it to tornado and environmental data from four additional states including Illinois, Mississippi, South Dakota, and Ohio. The choice of states is based on a representative sample of other tornado-prone areas in the United States. The summary and model statistics discussed below are listed by state in Table 1. Maps of raw tornado counts by county for the four states are shown in Fig 10. The procedures for preparing the data at the county level are the same as before. An exception occurs for South Dakota where an additional raster of elevations is needed for counties north of 45° N latitude. Like across Kansas, tornado counts are significantly correlated with county size in Illinois, Mississippi, and Ohio. South Dakota is the exception where the larger counties in the western half of the state tend to have fewer tornadoes compared to the smaller counties in the southeast corner.


A Statistical Model for Regional Tornado Climate Studies.

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

Tornado report frequency by county for Illinois, Mississippi, South Dakota, and Ohio.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0131876.g010: Tornado report frequency by county for Illinois, Mississippi, South Dakota, and Ohio.
Mentions: Flexibility of the model is demonstrated by fitting it to tornado and environmental data from four additional states including Illinois, Mississippi, South Dakota, and Ohio. The choice of states is based on a representative sample of other tornado-prone areas in the United States. The summary and model statistics discussed below are listed by state in Table 1. Maps of raw tornado counts by county for the four states are shown in Fig 10. The procedures for preparing the data at the county level are the same as before. An exception occurs for South Dakota where an additional raster of elevations is needed for counties north of 45° N latitude. Like across Kansas, tornado counts are significantly correlated with county size in Illinois, Mississippi, and Ohio. South Dakota is the exception where the larger counties in the western half of the state tend to have fewer tornadoes compared to the smaller counties in the southeast corner.

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