This week is the anniversary of one of the worst tornado outbreaks in U.S. history. On April 3-4, 1974, at least 148 tornadoes roared across the United States. Since then, this has been eclipsed by only the May 21-26, 2011 tornado outbreak. A tornado is generally the result of cold air diving south into warm moist air while a strong jet stream streaks across the convergence. This “setup” is unique to the U.S. and, therefore, we are the tornado capital of the world.
I’ve always been fascinated by tornadoes. They take on many different shapes and sizes and can be quite beautiful. But tornadoes are serious business. Researchers and chasers study them relentlessly. They have their own reality television shows. The art and science of predicting where and when a tornado will strike has improved greatly since 1974, but there is still much we don’t know about tornadoes.
I’m sure at one time you’ve seen a traditional “Tornado Alley” map or maybe you’ve seen a map of the U.S. counties most likely to get hit with a tornado. I wanted to create a map that was more detailed than something at the county level. I wanted to zero in on precise locations where tornadoes have historically occurred because the past is likely to predict the future.
To start, I located some data provided by the National Weather Service (NWS). They had a GIS file of tornado tracks from 1950-2006. Information on the intensity (EF scale), the length and width of the track, property and crop loss estimates, as well as fatalities and injuries were included in the file’s attributes. In order to quantify the impact of a tornado without including biased data, I chose two variables – the number of tornadoes and the intensity of each tornado. Next, I simply laid out an imaginary 10 square mile grid across the U.S. as a geography for aggregating my data. I chose a 10 square mile grid because it is usually much smaller than a county (on average you can fit 4-5 grid cells within an average sized county). I counted each tornado that crossed into a grid cell and summed up the EF scale intensity of each tornado (actually, I added a value of 1 to each storm’s EF number to account for storms with an intensity of EF 0 ). Each of the data values were normalized before computing a final value for each between 0 and 1.
The results of the exercise can be found here in this interactive map. Based on our methodology, the part of the country most likely to experience a tornado is located on the Oklahoma and Kansas border – specifically, the the northwest corner of Kay County, OK and the southeast corner of Sumner County, KS:
Luckily, this is not a densely populated area. In fact, less than 500 people live in this particular cell. However, the Top Ten Tornado Hot Spots include several areas where the population is high:
|Primary County Area||State||2011 Population|
|NW Kay County, OK/SE Sumner County, KS||OK||466|
|NE Cullman County, AL||AL||13,407|
|WC Bossier Parish LA/EC Caddo Parish, LA/E Harrison County, TX||LA||138,159|
|SC Pulaski County, AR/WC Lonoke County, AR||AR||111,338|
|EC Simpson County, MS||MS||13,837|
|EC Hinds County, MS||MS||72,116|
|SE Thayer County, NE||NE||231|
|SW Oklahoma County, OK||OK||275,475|
|EC Cass County, TX||TX||11,230|
|NE Marlboro County, SC||TX||16,166|
As you can see, there are several heavily populated corridors that are historically most likely to experience a tornado. Oklahoma City (OK), Shreveport (LA), Little Rock (AR), and Jackson (MS) are the most heavily populated cities within our computed danger zone.
If we assume that small changes in the climate over time will not result in dramatic shifts of tornadic activity, then we can safely predict that the areas of high tornadic activity in the past will continue to experience intense, long-track tornadoes into the future. This knowledge should affect things like building design and cityurban design, disaster preparedness, and insurance rates.
We’ll be posting various maps related to this exercise on our Pinterest site over the next couple of weeks. Check back from time to time to see what we’ve come up with.