Tornado tracks

Posted to Maps  |  Tags: , ,  |  Kim Rees

John Nelson of IDV Solutions put 56 years worth of tornadoes on a map. John plotted each tornado’s path and used brightness for its F-scale (level of intensity). He also added secondary charts for deaths and injuries and frequency by F-scale.

It makes a gorgeous map. I would love to see the data incorporated into the wind map.

So… practically speaking, if you live in the Midwest or Southern US, you should probably put this on your reading list.

4 Comments

  • Excellent choice with the dark background and lightness by F scale. The blue is gorgeous and the symbolization very effective.
    A few things that would make this even better – use a map projection that does not cause excessive E-W distortion in the northern part of the country. The relative density and intensity of Tornadoes is diminished in the northern section of the country making it extremely difficult to compare to the southern section. The hillshade base is also distracting. Cheers, Karen

  • are tornado tracks really that straight?

  • Are tornado tracks really that long? Are these rather the tracks of the storm systems that spawned the tornadoes?

  • We’ve recently made an interactive version of this map, where you can navigate the geography and time of this data and filter by attributes like severity, magnitude, loss, and cost -if you are so inclined.

    http://uxblog.idvsolutions.com/2012/07/interactive-tornado-tracks-map-is-live.html

Favorites

Jobs Charted by State and Salary

Jobs and pay can vary a lot depending on where you live, based on 2013 data from the Bureau of Labor Statistics. Here’s an interactive to look.

Unemployment in America, Mapped Over Time

Watch the regional changes across the country from 1990 to 2016.

Years You Have Left to Live, Probably

The individual data points of life are much less predictable than the average. Here’s a simulation that shows you how much time is left on the clock.

One Dataset, Visualized 25 Ways

“Let the data speak” they say. But what happens when the data rambles on and on?