The relationship between elevation roughness and tornado activity: A spatial statistical model fit to data from the central great plains

The statistical relationship between elevation roughness and tornado activity is quantified using a spatial model that controls for the effect of population on the availability of reports. Across a large portion of the central Great Plains the model shows that areas with uniform elevation tend to have more tornadoes on average than areas with variable elevation. The effect amounts to a 2.3% [(1.6%, 3.0%) = 95% credible interval] increase in the rate of a tornado occurrence per meter of decrease in elevation roughness, defined as the highest minus the lowest elevation locally. The effect remains unchanged if the model is fit to the data starting with the year 1995. The effect strengthens for the set of intense tornadoes and is stronger using an alternative definition of roughness. The elevation-roughness effect appears to be strongest over Kansas, but it is statistically significant over a broad domain that extends from Texas to South Dakota. The research is important for developing a local climatological description of tornado occurrence rates across the tornado-prone region of the Great Plains

Adjusted Tornado Probabilities

Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, expressed as return periods, arestates, including Alabama, Mississippi, Arkansas, and Oklahoma. The expected annual number of people exposed to tornadoes is highest for Illinois followed by Alabama and Indiana. For the four states with the highest tornado rates, exposure increases since 1980 are largest for Oklahoma (24%) and Alabama (23%)

Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

Meta-analysis of genome-wide association studies for extraversion:Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

The influence of the North Atlantic oscillation on seasonal snowfall totals in the northeastern United States, 1961-2010

The North Atlantic Oscillation (NAO) is one of the main components of atmospheric circulation variability within the middle and high latitudes of the Northern Hemisphere and largely affects winter weather in northeastern United States. This study examined the most recent decadal trend of the NAO as well as its influence on snowfall totals and storm track variability in the northeast U.S. over the previous 50-year period. Previous research has indicated greater snowfall totals in the Northeast during NAO negative phases due to repeated polar outbreaks. Nonetheless, past research has also shown connections between the NAO positive phase and active winter seasons in this region. This study provides insight on how both positive and negative NAO phases can produce significant snowfall in the Northeast. Statistical and graphical analysis were completed to assess the relationship between the NAO and seasonal snowfall (NDJFM) from 1961-2010 for stations within the Northeast (Virginia to Maine). In addition, two case studies of recent winter events with differing NAO phases were evaluated to provide insight on how both NAO phases can produce significant snowfall in the Northeast. The statistical analysis revealed inverse relationships between the NAO negative phase and seasonal snowfall. The composite analysis indicated an average positive NAO pattern from 1961-2010, yet the NAO negative years produced higher frequency of snowfall in the Northeast. The case studies highlighted variations in storm track and snowfall distribution of the two winter events in differing phases. This study shows that snowfall can occur in particular regions of the Northeast regardless of the NAO phase which has important implications for forecasters. This research also provides the necessary information to complete the most recent decadal trend of the NAO and determine its average pattern. The update of this record will assist climatologists and weather forecasters in predicting future northeast U.S. winter storms.Department of GeographyThesis (M.S.

The influence of the North Atlantic oscillation on seasonal snowfall totals in the northeastern United States, 1961-2010

The North Atlantic Oscillation (NAO) is one of the main components of atmospheric circulation variability within the middle and high latitudes of the Northern Hemisphere and largely affects winter weather in northeastern United States. This study examined the most recent decadal trend of the NAO as well as its influence on snowfall totals and storm track variability in the northeast U.S. over the previous 50-year period. Previous research has indicated greater snowfall totals in the Northeast during NAO negative phases due to repeated polar outbreaks. Nonetheless, past research has also shown connections between the NAO positive phase and active winter seasons in this region. This study provides insight on how both positive and negative NAO phases can produce significant snowfall in the Northeast. Statistical and graphical analysis were completed to assess the relationship between the NAO and seasonal snowfall (NDJFM) from 1961-2010 for stations within the Northeast (Virginia to Maine). In addition, two case studies of recent winter events with differing NAO phases were evaluated to provide insight on how both NAO phases can produce significant snowfall in the Northeast. The statistical analysis revealed inverse relationships between the NAO negative phase and seasonal snowfall. The composite analysis indicated an average positive NAO pattern from 1961-2010, yet the NAO negative years produced higher frequency of snowfall in the Northeast. The case studies highlighted variations in storm track and snowfall distribution of the two winter events in differing phases. This study shows that snowfall can occur in particular regions of the Northeast regardless of the NAO phase which has important implications for forecasters. This research also provides the necessary information to complete the most recent decadal trend of the NAO and determine its average pattern. The update of this record will assist climatologists and weather forecasters in predicting future northeast U.S. winter storms.Thesis (M.S.)Department of Geograph

A Statistical Model for Regional Tornado Climate Studies.

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

Population changes between 1970 and 2012.

<p>The change is expressed as a percentage difference with 2012 as the base year.</p

Tornado report frequency by county for Kansas.

<p>Only tornadoes rated EF1 and higher are used. Lines show the tornado track. The shortest tracks are not visible at this scale. Total tornado counts over the period 1970–2013 are listed inside the county and the color scale is from few (blue) to many (red).</p