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Hank Pogorzelski, IBHS Applied Statistician
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Mapping Tornado and Hail Frequency 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.
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1957
1959
1961
1963
1965
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1971
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1975
1977
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1981
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1987
1989
1991
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1995
1997
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2001
2003
2005
Number of Reported Tornadoes per Year 1957 - 2006 F2 and Greater
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 Frequency
Common Method: create a grid and count the occurrences of tornadoes within each grid cell
Small 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 Frequency
Large 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 and Quantifying Tornado Frequency
Approach 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 Close
Reported F2 and greater Tornadoes reported in the Dallas/Ft. Worth area 1957 - 2006
The Process up Close
Dallas/Ft. Worth with grid cells color coded by tornado count
The Process up Close
Average of each grid cell with its nearest neighbors: 3 cells in each direction or a 7 x 7 cell area
The Process up Close
Interpolated frequency values for the 1 mile by 1 mile grid cells delineated in to frequency ranges
10 by 10 Mile Grid Cell Frequency Values
7 by 7 Grid Cell Averages
Average Tornado Frequency per 100 Square Miles, 1957-2006
Tornado Activity by Month
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1400
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tornado Reports by Month 1957-2006 Reports, F2 or Greater
• 42% of tornado reports in this analysis occurred in April and May, 66% between March and June.
Tornado Frequency by Month
Tornado Frequency by Month
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
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1,000
2,000
3,000
4,000
5,000
6,000
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9,000
1955
1957
1959
1961
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1969
1971
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1975
1977
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1983
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2007
2009
Reports of Hail 1" or Greater by Year
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.
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2,000
4,000
6,000
8,000
10,000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Reports of Hail 1" or Greater by Year
Total Reports Consolidated Reports
Distribution of Hail Reports Over the Conterminous U.S.
Methods for Representing and Quantifying Hail Frequency
The approach of the hail map is the same as the 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.
10 x 10 Mile Grid Cell Frequencies
5 x 5 Grid Cell Averages
Average Number of Hail Reports
per 100 square miles, 2000-2009
Hail Activity by Month
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2,000
4,000
6,000
8,000
10,000
12,000
14,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Hail Reports by Month
• 45% of tornado reports in this analysis occurred in May and June, 75% between April and July.
Hail Frequency by Month
Hail Frequency by Month
Questions?
