Search Results
Abstract
In the United States, tornado activity of a given year is usually assessed in terms of the total number of human-reported tornadoes. Such assessments fail to account for the seldom-acknowledged fact that an active (or inactive) tornado year for the United States does not necessarily equate with activity (or inactivity) everywhere in the country. The authors illustrate this by comparing the geospatial tornado distributions from 1987, 2004, and 2011. Quantified in terms of the frequency of daily tornado occurrence (or “tornado days”), the high activity in the South Atlantic and upper Midwest regions was a major contributor to the record-setting number of tornadoes in 2004. The high activity in 2011 arose from significant tornado occurrences in the Southeast and lower Midwest. The authors also show that the uniqueness of the activity during these years can be determined by modeling the local statistical behavior of tornado days by a gamma distribution.
Abstract
In the United States, tornado activity of a given year is usually assessed in terms of the total number of human-reported tornadoes. Such assessments fail to account for the seldom-acknowledged fact that an active (or inactive) tornado year for the United States does not necessarily equate with activity (or inactivity) everywhere in the country. The authors illustrate this by comparing the geospatial tornado distributions from 1987, 2004, and 2011. Quantified in terms of the frequency of daily tornado occurrence (or “tornado days”), the high activity in the South Atlantic and upper Midwest regions was a major contributor to the record-setting number of tornadoes in 2004. The high activity in 2011 arose from significant tornado occurrences in the Southeast and lower Midwest. The authors also show that the uniqueness of the activity during these years can be determined by modeling the local statistical behavior of tornado days by a gamma distribution.
Abstract
U.S. tornado records form the basis for a variety of meteorological, climatological, and disaster-risk analyses, but how reliable are they in light of changing standards for rating, as with the 2007 transition of Fujita (F) to enhanced Fujita (EF) damage scales? To what extent are recorded tornado metrics subject to such influences that may be nonmeteorological in nature? While addressing these questions with utmost thoroughness is too large of a task for any one study, and may not be possible given the many variables and uncertainties involved, some variables that are recorded in large samples are ripe for new examination. We assess basic tornado-path characteristics—damage rating, length, width, and occurrence time, as well as some combined and derived measures—for a 24-yr period of constant path-width recording standard that also coincides with National Weather Service modernization and the WSR-88D deployment era. The middle of that period (in both time and approximate tornado counts) crosses the official switch from F to EF. At least minor shifts in all assessed path variables are associated directly with that change, contrary to the intent of EF implementation. Major and essentially stepwise expansion of tornadic path widths occurred immediately upon EF usage, and widths have expanded still farther within the EF era. We also document lesser increases in pathlengths and in tornadoes rated at least EF1 in comparison with EF0. These apparently secular changes in the tornado data can impact research dependent on bulk tornado-path characteristics and damage-assessment results.
Abstract
U.S. tornado records form the basis for a variety of meteorological, climatological, and disaster-risk analyses, but how reliable are they in light of changing standards for rating, as with the 2007 transition of Fujita (F) to enhanced Fujita (EF) damage scales? To what extent are recorded tornado metrics subject to such influences that may be nonmeteorological in nature? While addressing these questions with utmost thoroughness is too large of a task for any one study, and may not be possible given the many variables and uncertainties involved, some variables that are recorded in large samples are ripe for new examination. We assess basic tornado-path characteristics—damage rating, length, width, and occurrence time, as well as some combined and derived measures—for a 24-yr period of constant path-width recording standard that also coincides with National Weather Service modernization and the WSR-88D deployment era. The middle of that period (in both time and approximate tornado counts) crosses the official switch from F to EF. At least minor shifts in all assessed path variables are associated directly with that change, contrary to the intent of EF implementation. Major and essentially stepwise expansion of tornadic path widths occurred immediately upon EF usage, and widths have expanded still farther within the EF era. We also document lesser increases in pathlengths and in tornadoes rated at least EF1 in comparison with EF0. These apparently secular changes in the tornado data can impact research dependent on bulk tornado-path characteristics and damage-assessment results.
Abstract
This research compares reanalysis-derived proxy soundings from the North American Regional Reanalysis (NARR) with collocated observed radiosonde data across the central and eastern United States during the period 2000–11: 23 important parameters used for forecasting severe convection are examined. Kinematic variables such as 0–6-km bulk wind shear are best represented by this reanalysis, whereas thermodynamic variables such as convective available potential energy exhibit regional biases and are generally overestimated by the reanalysis. For thermodynamic parameters, parcel-ascent choice is an important consideration because of large differences in reanalysis low-level moisture fields versus observed ones. Results herein provide researchers with potential strengths and limitations of using NARR data for the purposes of depicting climatological information for hazardous convective weather and initializing model simulations. Similar studies should be considered for other reanalysis datasets.
Abstract
This research compares reanalysis-derived proxy soundings from the North American Regional Reanalysis (NARR) with collocated observed radiosonde data across the central and eastern United States during the period 2000–11: 23 important parameters used for forecasting severe convection are examined. Kinematic variables such as 0–6-km bulk wind shear are best represented by this reanalysis, whereas thermodynamic variables such as convective available potential energy exhibit regional biases and are generally overestimated by the reanalysis. For thermodynamic parameters, parcel-ascent choice is an important consideration because of large differences in reanalysis low-level moisture fields versus observed ones. Results herein provide researchers with potential strengths and limitations of using NARR data for the purposes of depicting climatological information for hazardous convective weather and initializing model simulations. Similar studies should be considered for other reanalysis datasets.
Abstract
Many tornadoes are unreported because of lack of observers or are underrated in intensity, width, or track length because of lack of damage indicators. These reporting biases substantially degrade estimates of tornado frequency and thereby undermine important endeavors such as studies of climate impacts on tornadoes and cost–benefit analyses of tornado damage mitigation. Building on previous studies, we use a Bayesian hierarchical modeling framework to estimate and correct for tornado reporting biases over the central United States during 1975–2018. The reporting biases are treated as a univariate function of population density. We assess how these biases vary with tornado intensity, width, and track length and over the analysis period. We find that the frequencies of tornadoes of all kinds, but especially stronger or wider tornadoes, have been substantially underestimated. Most strikingly, the Bayesian model estimates that there have been approximately 3 times as many tornadoes capable of (E)F2+ damage as have been recorded as (E)F2+ [(E)F indicates a rating on the (enhanced) Fujita scale]. The model estimates that total tornado frequency changed little over the analysis period. Statistically significant trends in frequency are found for tornadoes within certain ranges of intensity, pathlength, and width, but it is unclear what proportion of these trends arise from changes in damage survey practices. Simple analyses of the tornado database corroborate many of the inferences from the Bayesian model.
Significance Statement
Prior studies have shown that the probabilities of a tornado being reported and of its intensity, track length, and width being accurately estimated are strongly correlated with the local population density. We have developed a sophisticated statistical model that accounts for these population-dependent tornado reporting biases to improve estimates of tornado frequency in the central United States. The bias-corrected tornado frequency estimates differ markedly from the official tornado climatology and have important implications for tornado risk assessment, damage mitigation, and studies of climate change impacts on tornado activity.
Abstract
Many tornadoes are unreported because of lack of observers or are underrated in intensity, width, or track length because of lack of damage indicators. These reporting biases substantially degrade estimates of tornado frequency and thereby undermine important endeavors such as studies of climate impacts on tornadoes and cost–benefit analyses of tornado damage mitigation. Building on previous studies, we use a Bayesian hierarchical modeling framework to estimate and correct for tornado reporting biases over the central United States during 1975–2018. The reporting biases are treated as a univariate function of population density. We assess how these biases vary with tornado intensity, width, and track length and over the analysis period. We find that the frequencies of tornadoes of all kinds, but especially stronger or wider tornadoes, have been substantially underestimated. Most strikingly, the Bayesian model estimates that there have been approximately 3 times as many tornadoes capable of (E)F2+ damage as have been recorded as (E)F2+ [(E)F indicates a rating on the (enhanced) Fujita scale]. The model estimates that total tornado frequency changed little over the analysis period. Statistically significant trends in frequency are found for tornadoes within certain ranges of intensity, pathlength, and width, but it is unclear what proportion of these trends arise from changes in damage survey practices. Simple analyses of the tornado database corroborate many of the inferences from the Bayesian model.
Significance Statement
Prior studies have shown that the probabilities of a tornado being reported and of its intensity, track length, and width being accurately estimated are strongly correlated with the local population density. We have developed a sophisticated statistical model that accounts for these population-dependent tornado reporting biases to improve estimates of tornado frequency in the central United States. The bias-corrected tornado frequency estimates differ markedly from the official tornado climatology and have important implications for tornado risk assessment, damage mitigation, and studies of climate change impacts on tornado activity.
