Effects of Population Density and Storm Reports in Minnesota from
1985-2005
Michael M. Stanga
St. Cloud State University
Department of Earth and Atmospheric Sciences
Department of Geography
Final Revision
16 April 2009
Faculty Reader Committee Members
_____________________________________
Lewis G. Wixon (GEOG 432 Advisor)
_____________________________________
Anthony R. Hansen (EAS Department Advisor)
_____________________________________
Mikhail S. Blinnikov
Effects of Population Density and Storm Reports in Minnesota from
1985-2005
Michael Stanga
St. Cloud State University
Department of Earth and Atmospheric Sciences
Department of Geography
ABSTRACT
The primary objective of this study was to determine whether population density has
played a role in the severe weather reports in Minnesota from 1985-2005. A secondary
objective of the study was to determine if the mean node of all reports on a yearly basis was
near the mean node of the population density. The data for the time period was analyzed using
geospatial, statistical and spatial analysis tools in ESRI ArcMap 9.3. Interpretations of the data
suggest that population density is directly related to severe weather reports in the State of
Minnesota during the study time period. Evidence also suggests that the mean node for all
reports is close to the mean node of the populated places.
______________________________________________
1.0 INTRODUCTION
Since 1950 the National Weather Service, formerly the U.S. Weather Bureau, has
aggregated reports from severe weather events for the purpose of documenting, analyzing, and
predicting future weather events. This study is an analysis of severe weather events from the
Storm Prediction Center (SPC) event database in conjunction with the National Climatic Data
Center (NCDC) in the State of Minnesota from 1985-2005. The variables selected for
examination include Tornadoes, Hail, and High Wind reports. These reports included 766
Tornado reports, 5624 Hail reports and 4546 High Wind reports when combined include 10,936
total reports (Fig. 1). These reports will be aggregated and analyzed against a predicted
population density data in the 1990s for spatial patterns and correlations between the data
sets.
Minnesota is an appropriate state for the study due to its contiguous higher population
density areas located directly adjacent to areas of lower population densities. To achieve a
time period of significant length, the years 1985 to 2005 were selected for this study. Other
studies have examined broad tornado trends from 1950 to 2001 in Minnesota and Iowa
(Turcotte 2002); although no known studies have explored the variables in Minnesota during
the time period. It is essential that these data are analyzed to help predict and further
understand future weather events.
Figure 1.
This graphic is an illustration of all Tornado, Hail, and High Wind reports from the
SPC database in Minnesota from 1985-2005.
2.0 HYPOTHESIS
It is hypothesized in this study that the spatial patterns of the reports reflect the
population density in Minnesota in the years 1985-2005. However, it was concluded in a
previous similar study that “…correlation between tornado frequency and population density is
not evident when combining all Minnesota and Iowa counties [between 1950 and 2001].”
(Turcotte 2002). It was also hypothesized that the average node of the reports may be closely
located to average node of populated places using Department of Natural Resources
“Populated Places” (Interactive Data 2009) data, and as determined by the software program
ESRI ArcMap 9.3. If the reports are more concentrated in higher population density areas
and/or near Population Places average node, then it can be concluded that population density
has a direct effect on storm reports during the time period.
3.0 METHODOLOGY
To test the hypothesis, ESRI ArcMap 9.3 was used for the initial statistical and spatial
analysis for all of the data. After the primary data aggregation, a qualitative analysis was
performed on the data maps. Years included in the study were from January 1st to December
31st. The data was compiled from the Storm Prediction Center Storm reports archival database.
In order to interpolate population density, an Inverse Distance Weighting (IDW) algorithm (Fig.
2) was used to create the population map used in this study.
Where:
Figure 2
Simple Inverse Distance Weighting Algorithm
Source: (Shepard 1968)
This study also uses basic visual reference data including a county line image of the
State of Minnesota. The image was added to the analysis for perspective with sensitivity to
known political boundaries, although this study was not limited to using political boundaries
other than those which outline Minnesota (Fig. 3). Tornado reports in this study were used
only at their reported start location. This method however did not distinguish whether the
tornadoes were “long track”, which is one tornado on the ground continuously or if “successive
tornadoes”, which occurs when a tornado formed, dissipates and reforms on a same general
path, and in theory could create multiple tornado start points for one tornado event. In this
study it is of importance to note that the start location matters of all tornadoes reported and
will be correlated to population density in that fashion, regardless of the type of tornado family
that was observed during the event. Maps that were generated for the study included a
nearest neighbor density map for 1985-2005 for all reports in the 20 year time period, a density
map of all reports for individual years, an average node map for all reports for all years, and an
IDW population density map. The visual qualitative analysis performed were based on report
Figure 3.
All Reports and Populated Places as shown in ArcMap 9.3. Populated Places are
shown as purple dots. All other dots are Storm Reports are from 1985-2005. Tornado reports
are red triangles, Hail reports are green dots, and High Wind reports are blue squares.
density against population density, and mean node for the storm reports against the mean
node for the populated places.
4.0 RESULTS
All results are shown in figures 4 through 14 below. Images are shown in order from
population and reports density analysis to storm report node analysis. In general the darker
the shade of a color the more densely populated (population or total density) an area is
considered. For determining whether a relationship exists between population density and
storm report density a qualitative analysis was performed on the images below.
After the images are put side by side, a subjective analysis of population density against total
report densities for all storm reports and all report categories was performed. This was done in
order to create the best possible subjective and qualitative analysis of the data. This method
will best show the correlations of the data for this study.
For the nodal analysis of population center against storm report average center, the
population center was superimposed on the yearly average storm report nodes (fig. 12 – 14)
and qualitatively analyzed. This allowed for the best subjective analysis of the data to be
performed. The symbology for the maps include: yellow circle identifies the population node,
and each type of storm report is broken down into average center node of reports per year,
which are the red triangles for Tornadoes, green circles for Hail and blue squares for High Wind
reports.
Figure 4.
IDW Population Density
Figure 5.
Populated Places
Figure 6.
1985-2005 Tornado Reports
Figure 7.
1985-2005 Tornado Reports Density
Figure 8.
1985-2005 Hail Reports
Figure 9.
1985-2005 Hail Reports Density
Figure 10.
1985-2005 High Wind Reports
Figure 11.
1985-2005 High Wind Reports Density
Figure 12.
Average population node with average Tornado Reports node
Figure 13.
Average population node with average Hail Reports node
Figure 14.
Average population node with average High Wind Reports node
5.0 INTERPRETATIONS
When determining whether a relationship exists between the population density and
storm reports, a qualitative analysis was performed when placing two maps side by side. In
general, these maps showed that overall, populated places with larger population densities did
have more reports in those areas. Although these conclusions can be considered subjective, it
is inferred to be mostly unbiased due to the same population density map being used for all
interpretations. Evidence obtained from the mean node of the yearly reports qualitatively
analyzed against the mean node of the populated places suggests that on average population
has played a factor in the average nodes of the storm reports on a yearly basis.
6.0 CONCLUSIONS
Evidence from the study suggests that the population density for the state of Minnesota
from 1985-2005 has had a direct influence on the density of storm reports in the same time
frame. Evidence also suggests that the population center node for the state of Minnesota also
had a direct correlation with the average storm reports node on a yearly basis for the same
time period.
Further investigation for this study could include surrounding states using the same type
of analysis. Also, should the data be quantified it could be numerically and statistically
analyzed, which could further confirm the results of this study.
REFERENCES
"Interactive Data Download." MnDNR Data Deli. 28 Jan. 2009
<http://deli.dnr.state.mn.us/data_search.html>.
Shepard, Donald (1968). "A two-dimensional interpolation function for irregularly-spaced data".
Proceedings of the 1968 ACM National Conference: 517–524. doi:10.1145/800186.810616
Turcotte, Justin T. Tornado Trends in Minnesota and Iowa from 1950-2001.
DATA
"WCM Page." Storm Prediction Center. 21 Jan. 2009 <http://www.spc.noaa.gov/wcm/index.html#data>.