Mapping Tornado and HailFrequency in the Lower 48 A Spatial Analysis of Tornado and Hail Reports from the National Climatic Data Center
Tornado Report Data• The original source of the data is the Storm Prediction Center’s (SPC) Storm Data.• Through the SVRGIS project at Ball State University, the SPC data set was converted into a shapefile format compatible with the mapping software ArcGIS.• This also involved concatenating multiple path segments and removing reports with no liftoff coordinates.
Tornado Report Data• Date Range: 50 year period 1957 – 2006• Includes tornadoes of F2 or greater strength• 5,884 reports fit this criteria with no pattern of increasing activity over the reporting period. Number of Reported Tornadoes per Year 1957 - 2006 F2 and Greater250200150100 50 0 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
Tornado Report Data• Tornado reports are represented spatially by a pair of coordinates representing touchdown and liftoff.• This implies a straight line path for all tornado reports.
The Dataset Plotted:1957 – 2006 Reports, F2 or Greater
Methods for Representing and Quantifying Tornado FrequencyCommon Method: create a grid and count theoccurrences of tornadoes within each grid cellSmall Grid Cells:• Though some regions are more tornado prone than others, precise touchdown and liftoff locations are random.• Using small grid cells can result in cells within tornado prone areas with few or no reported tornadoes.
Methods for Representing and Quantifying Tornado FrequencyLarge Grid Cells• Large grid cells in effect cast a wider net and therefore are less likely to end up with “donut holes” of low or no activity within larger areas that are tornado prone.• However, the use of large cells may over generalize frequency, and result in a more coarsely pixilated depiction of tornado frequency.• Large cells are less sensitive to path length than small grid cells.
Methods for Representing andQuantifying Tornado FrequencyApproach of the current map:• Begin with small grid cell: 10 x 10 mile, or 100 sq. miles.• The tornado count is taken for each cell.• These counts are used to calculate the average of each cell and it’s nearest neighboring cells.• An interpolation technique is used to smooth the transitions between cell values.
The Process up CloseReported F2 and greater Tornadoes reported in theDallas/Ft. Worth area 1957 - 2006
The Process up CloseDallas/Ft. Worth with grid cells color coded bytornado count
The Process up CloseAverage of each grid cell with its nearestneighbors: 3 cells in each direction or a 7 x 7 cellarea
The Process up CloseInterpolated frequency values for the 1 mile by 1mile grid cells delineated in to frequency ranges
Average Tornado Frequency per 100 Square Miles, 1957-2006
Tornado Activity by Month• 42% of tornado reports in this analysis occurred in April and May, 66% between March and June. Tornado Reports by Month 1957-2006 Reports, F2 or Greater140012001000 800 600 400 200 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Hail Report Data• The hail data also comes from the SVRGIS project which converted reports from the SPC hail database into shapefiles.• The entire SVRGIS data set includes reports from 1955 through 2009.
Hail Reports Have Increased Dramatically Over Time Reports of Hail 1" or Greater by Year 9,000 8,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
Possible Explanations for the Increase• Population growth in areas that previously had few or no people present to observe an event, and more trained observers.• Improved radar technology that can identify weather conditions likely to produce hail with increasing certainty.• Increasing use of multiple reports to describe what may have been contained in one report in prior periods.
Consequences for Spatial Analysis• To the extent it exists, population bias will deemphasize the threat of hail in rural areas relative to urban areas of similar risk.• The presence of multiple reports, if not distributed evenly, will result in similar distortions.
Remedies• Since some of the increase in the total number of reports is attributed to improved reporting in rural or previously rural areas, only the most recent 10 years of data is used in the current analysis (2000-2009).• Any reports with coordinates that were within 0.2 degrees of each other, and within 30 minutes of each other were combined into 1 report.
Hail Report Data• There are 65,591 reports of hail 1” or larger in the data set between 2000 and 2009.• After consolidating multiple reports that were very close to each other with respect to time and space, 53,028 hail reports remained. Reports of Hail 1" or Greater by 10,000 Year 8,000 6,000 4,000 2,000 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Total Reports Consolidated Reports
Distribution of Hail Reports Over the Conterminous U.S.
Methods for Representing and Quantifying Hail FrequencyThe approach of the hail map is the same asthe tornado map:• Begin with small grid cells: 10 x 10 mile, or 100 sq. miles.• Calculate the average of each cell and it’s nearest neighboring cells.• Use an interpolation technique to smooth the transitions between cell values.
Average Number of Hail Reportsper 100 square miles, 2000-2009
Hail Activity by Month• 45% of tornado reports in this analysis occurred in May and June, 75% between April and July. Hail Reports by Month14,00012,00010,000 8,000 6,000 4,000 2,000 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec