February Tornadoes
Since I forgot to post a “Question of the Week” this week due to continued winter weather and because the snow battered center of the United States has begun its long awaited warm-up, I thought I’d go ahead and share the statistics and figures relating to February tornadoes. The plots and statistics are similar to those I computed for January that can be found in posts here and here.
February Averages (based on data from 1950 – 2009)
- 24.5 tornadoes
- 128.3 injuries
- 10 fatalities
Above is a figure depicting the number of February tornadoes per county for the years 1950 to 2009. Most tornadoes tend to occur in the southeast United States, however tornadoes have been reported as far west as California and Hawaii, and as far north as Oregon and western New York!
If we sum up the number of unique tornadoes from the country data and turn it into the number of tornadoes by state, it would look like this:
Florida and Mississippi lead the way with over 180 tornadoes, followed by Texas and then the rest of the southeastern states. Breaking down each states numbers, the tallies look like this:
Now, the number of injuries per state break down as follows (please note the order of the states listed on the left is in descending order of number of tornadoes per state):
The number of fatalities per state break down as follows (please note the order of the states listed on the left is in descending order of number of tornadoes per state):
And putting everything into a single, cluttered figure, we have this:
SPC Slight Risk Climatology
Next up in the list of Storm Prediction Center (SPC) outlook climatologies is the yearly climatology of slight risks. Between 1990 and 2008 there were 24,455 slight risk polygons issued. This does not mean there were 24,455 slight risk outlooks issued as it is possible to have more than one slight risk polygon drawn on a given outlook. Furthermore, note that each day consists of multiple outlooks and so it is possible for a grid point to receive multiple “hits” for being located in a slight risk outlook on the same day. In other words, if a location was located within 2 slight risk outlooks, this does not guarantee that two days of slight risks. The location might simply be contained within a slight risk from two separate outlooks issued for the same day.
Below is the slight risk climatology that employs the Kernel Density Estimation technique. Notice how it is smoother along the edges than the raw outlook which is located at the end of this post. The black solid lines are contour intervals of outlooks per year in steps of 25. The color fill contours are in increments of 1 outlook per year. As you can see, the central United States is once again the leader in the number of slight risks to expect per year. This has to do with the repeatability and predictability of the ingredients necessary for severe thunderstorm development. In other words, ingredients come together more frequently and more reliability across “Tornado Alley” than anywhere else in the world. This doesn’t mean that other areas aren’t prone to severe thunderstorms. Some of the largest tornado outbreaks in history have actually occurred well east of traditional Tornado Alley (e.g., 21 January 1999 and 3-4 April 1974).
Below is the raw graphic, with now Kernel Density Estimation applied. Because the edges are not smooth line, rather they are intersections from thousands of polygons, I did not plot any black line contours.
All SPC Moderate and High Risk Climatologies
After posting the climatology of where the first moderate and high risks occur, I’ve received a couple of requests for additional graphics. One that was extremely easy to produce, and also one most frequently requested, is a climatology of moderate and high risks. Using the same Kernel Density Estimation technique described in the original post, I’ve calculated the number of moderate and high risk outlooks an area might expect during a given year, based on data from 1990 through 2008.
Please note that each day consists of multiple outlooks and so it is possible for a grid point to receive multiple “hits” for being located in a Moderate or High risk outlook on the same day. In other words, if your location is located within 2 high risk outlooks, this does not guarantee that you will have two days of high risks. The location might simply be contained within a high risk from two separate outlooks issued for the same day.
For moderate risks, central Oklahoma appears to be the clear winner with nearly 30 moderate risks averaged per year. Increase probabilities extend both north and east from here.
As expected, the average number of high risks per years is considerably less than the average number of moderate risks. (In fact, I had to change the color scale!) Northeast Kansas, northern Missouri, and west-central Illinois are the most likely areas to experience a high risk in a given year with slightly more than 2 expected. A minor axis of increased probability extends southward from the eastern edges of this highest probability band, reaching portions of eastern Arkansas and far northern Mississippi.
Notice how in both of these climatologies, the maximum probabilities are centered in the central United States — east of the Rocky Mountains and west of the Appalachian Mountains. We’ll leave discussion as to why this is for another blog post.
AOTW: Storm Prediction Center Moderate & High Risks
Although most of the country is still digging out and cleaning up from a historic winter storm, commonly referred to as the “Groundhog’s Day Storm”, I decided to go ahead and answer the Question of the Week regarding Storm Prediction Center (SPC) Moderate and High Risks.
Before I answer the questions, first let me explain how I arrived at the answers…
I took the polygon outlining the first Moderate [High] risk during a given year, regardless of time of issuance. This means I treated a 12 UTC issuance the same as a 1630 UTC issuance and 2000 UTC issuance. I took the risk polygon, placed it on a 4km grid (specifically grid number 240), and activate all grid points that fell inside the risk polygon. This left me with a grid of 1′s (inside outlook) and 0′s (outside outlook). I created a grid for each year and then summed all the grids together. This gave me a grid containing the number of times each grid point was within the first Moderate [High] risk of the year. I then divided each grid point by the number of years I was examining. This left me with the probability that a grid point would be contained in the first Moderate [High] risk of the year.
The resulting plots were extremely blocky because of the straight edges of the outlook polygons and the relatively small size of the resulting sample size (19 years for Moderate risks and 18 years* for High risks). In an attempt to better retrieve the underlying probability distribution, I employed a technique called Kernel Density Estimation. I used a gaussian kernel with a bandwidth of 120 kilometers (per Brooks et al. 1998), and extended the resulting distributions out to 5 standard deviations.
To determine when the first Moderate [High] risk is typically issued, I converted the day and month of the first Moderate [High] risk into the corresponding day of year (e.g., 1 July is the 182 day of the year). I then took the mean day of the year and converted it back to day and month. This means that the average first issuance of a Moderate [High] risk may not fall on a day that actually had a Moderate [High] risk issued.
For this analysis I only evaluated the years between 1990 and 2008. This is because in the early years of the National Severe Storms Forecast Center (NSSFC) / Storm Prediction Center categorical risks had a different meaning than they do now. Thus, I tried to limit the analysis to relatively current definitions.
So, here are this week’s answers:
In the graphics below, the colored contour intervals are every 1% and the thin black contours are every 5%.
- Climatologically, where is the most likely location to experience the first SPC Moderate Risk of a given year?
- What about High Risk?
- There are actually two areas when using the raw probabilities: southwest Arkansas and southern Alabama. However, when applying the kernel density estimator, the area in southern Alabama has a slightly higher probability. As for when this first Moderate risk is issued, the average first issuance is 28 January.
- There is actually more variability (both spatially and temporally) in the issuance of the first High risk than the first Moderate risk. This is most likely the result of the greater variability in time of year, and thus greater variability of the large scale pattern. High risks have been issued as early as 21 January (1999) and as late as 1 July (1997). [Technically it has been issued as late as never, because 2000 did not have a single High risk issued.] For early High risks, the favored location is in the southeast United States where the ingredients that favor severe thunderstorms is more often confined to the Gulf Coast areas. Later in the year, more northern locations are favored as the cyclone track, and ingredients for severe thunderstorms, lifts northward. With this said, the first High Risk is typically issued across portions of southeast Arkansas and northern Mississippi between 27-28 March.
First Moderate Risk of Year
(1990 – 2008)
- 1990: Jan 18 (1200 UTC)
- 1991: Feb 18 (1200 UTC)
- 1992: Jan 13 (1200 UTC)
- 1993: Jan 15 (1500 UTC)
- 1994: Jan 26 (1200 UTC)
- 1995: Jan 06 (2000 UTC)
- 1996: Jan 17 (2000 UTC)
- 1997: Jan 24 (1500 UTC)
- 1998: Jan 15 (1500 UTC)
- 1999: Jan 22 (1200 UTC)
- 2000: Jan 03 (1200 UTC)
- 2001: Feb 08 (1630 UTC)
- 2002: Jan 23 (1630 UTC)
- 2003: Feb 21 (1200 UTC)
- 2004: Mar 04 (1200 UTC)
- 2005: Mar 21 (1200 UTC)
- 2006: Jan 02 (1200 UTC)
- 2007: Feb 23 (1200 UTC)
- 2008: Jan 10 (1630 UTC)
First High Risk of Year
(1990 – 2008)
- 1990: Feb 01 (1200 UTC)
- 1991: Mar 22 (1200 UTC)
- 1992: Apr 19 (1200 UTC)
- 1993: Apr 19 (1500 UTC)
- 1994: Apr 25 (1200 UTC)
- 1995: Apr 17 (2000 UTC)
- 1996: Mar 18 (1200 UTC)
- 1997: Jul 01 (1500 UTC)
- 1998: Apr 08 (1200 UTC)
- 1999: Jan 21 (1200 UTC)
- 2000: [ None ]
- 2001: Apr 06 (1200 UTC)
- 2002: Apr 16 (1200 UTC)
- 2003: Apr 06 (1630 UTC)
- 2004: Mar 04 (1630 UTC)
- 2005: Apr 11 (1630 UTC)
- 2006: Mar 12 (1200 UTC)
- 2007: Mar 01 (1200 UTC)
- 2008: Feb 05 (1300 UTC)

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