Playing with Data

Personal Views Expressed in Data

A Fork in the Road

Another turning point, a fork stuck in the road
Time grabs you by the wrist, directs you where to go
So make the best of this test, and don’t ask why
It’s not a question, but a lesson learned in time
It’s something unpredictable, but in the end is right,
I hope you had the time of your life.

—- Green Day’s “Good Riddance”

Today I accepted a "Techniques Development Meteorologist" position with the Storm Prediction Center in Norman, Oklahoma. For all practical purposes this is an ideal job for someone like me. I get to develop cool stuff for use in Storm Prediction Center operations, I get to play around with data (!), and I'll occasionally get to work forecast shifts alongside some of the best meteorologists in the world. As you can imagine, I'm pretty excited right now. As excited as I am, I still like to remember how I got to where I am. In some ways this keeps me grounded in reality, or as close to reality as my life seems to allow. I'll spare you the stories of all the people who took me under their wing and invested in me. But in full disclosure it is these people — and I hope they know who they are — and their investments that have put me on the course I travel. Without them, each and every single one of them, who knows where I would be.

Instead, I want to tell the story of a fateful day back in May of 2009. I was downstairs in the National Weather Center having lunch when my current advisor came in. He had previously left the University and so our communications were fairly limited. This is important because I had not told him that I had agreed to work on the VORTEX2 project in the VORTEX2 Operations Center. See, my research at the time was on climate and climate change related things and not directly tied to a field experiment dedicated to observing and documenting tornadoes. My advisor at the time was paying me out of his own research funds, not through a dedicated grant, and if I wasn't helping and advancing his research needs he was essentially losing money on the deal. As such he informed me that he could not justify funding me for the summer if I was going to work with VORTEX2, and not on the project(s) I was supposed to — which is totally understandable.

I felt I could not back out of working with VORTEX2 as the project started in days, and so I thought I would be without funding for the summer. Fortunately for me, Lou Wicker (NSSL) and Mike Biggerstaff (OU) came through and found money in their grants to fund me for the summer. This allowed me to work on VORTEX2 and still be able to pay the bills. At the end of the summer I had to decide what I wanted to do. I could either chart a new course for my dissertation or return to working with my old advisor and promise to give up the other activities. Since I had not found any funding other funding, I felt I had to go back and work for my old advisor on topics that only interested me in passing, which was less than idea for both of us. Shortly before I was to have my decision to my old advisor, Jack Kain (NSSL), whom I had only met in passing, suggested that before I agree to go back that I first have a meeting with some people from NSSL and discuss with them some ways forward. He felt that if I wasn't passionate about what I was doing that I would not finish. I agreed to have this meeting.

This meeting consisted of Mike Coniglio (NSSL), Lou Wicker, Harold Brooks (NSSL), and Jack Kain. (There may have been others, and if I left someone out, I sincerely apologize!) At this meeting it was decided that I should spend the fall trying to figure out what I wanted to do and to secure funding for that project. In the meantime, Harold had some money set aside for emergencies and was willing to fund me for the semester.

When December rolled around I still had not found a project I was interested in that had funding. I was running out of options and had no idea what was going to happen. It was mid-month that I was told that Jack Kain, whom I still only knew in passing, had been working with Mike Coniglio and David Stensrud (NSSL) to create a Liaison position for the Hazardous Weather Testbed. They thought that I had a skill set that would be very valuable for the HWT and since I spent all my time in their anyways, by tying the two together I might actually be motivated to finish my PhD. The funding for this position came through in early January — ironically it was held up for a few weeks as the result of continuing resolution budget issues — and the rest is sort of history.

Later I asked Jack why he was willing to work so hard for someone he didn't really know and had no real ties to. He told me that he was impressed with my passion for working with the operational community and had generally heard good things about what I was capable of. He didn't want someone he believed could do good things to fall through the cracks if he could do something to help. He also pointed out that it wasn't just him, that it was actually a collection of people who were willing to take a chance on me and that I should be very thankful — which I am.

On this side of things I can look back and recognize that day in May of 2009 as a huge fork in the road of my life. If my former advisor had not pulled my funding — something he had every right to do and ultimately had a responsiblity to do!!! — I most likely am not accepting the position with the Storm Prediction Center today. For you see, the opportunity I have today is a direct result of the skills I developed in the HWT over the last 3 years.

Life is full of these painful moments that seem unfair and don't make any sense at the time. Times in which you have to make painful choices, to take chances, and you never know if you made the right decision. It's times like these I think back to the advice of my departed Grandfather. "No matter what decision you make, after you make one, it becomes the right one." The advice here: Don't look back; Don't second guess; Don't fall into the what-if trap.

You never know the opportunities that await you…until you get there.

Population Affected by Tornadoes and Tornado Warnings

I have been curious as to the number of people warned for tornado warnings during the Storm Based Warning Era for awhile. Today I needed a mental break from my dissertation so I spent 20 minutes and calculated the numbers. Then, as it typically happens, I started to ask additional questions, such as "What's the number of people impacted?" I decided to do that as well. Below are the results.

To compute the total population that was warned, I took each warning, gridded it on to the 5-km population grid I have, and then counted the number of people inside that polygon. The population grid is taken from the 2010 census, so the number of people warned is an approximation and is also normalized to 2010 numbers. To calculate the number of people impacted, I gridded each tornado track, using the data from the Storm Prediction Center's WCM Data Page, onto the population grid. This resulted in a tornado track that was 5-km wide. Assuming a tornado width of 1km (which is a large tornado!) this gives me the number of people who were approximately within 2-km of the tornado track. I repeated the process with 3 grid point line-width (+/- 7-km) and with a 5 grid point line width (+/- 12-km). I then summed the population totals for each of these scenarios. Lastly, I calculated the percentage of people warned that were impacted for each of the radii thresholds (+/- 2-km, +/- 7-km, +/- 12-km). This is presented in the tables below as the percentage in parentheses.

CAVEATS

Please note these are approximations. The population counts are based on census data and are only as good as the census data. It does not account for transients (i.e., people who were just passing through the area). Furthermore, if an area was warned twice, those people were counted twice. The number of people warned (presented here) is not the same as the number of unique people warned.

One last, important caveat. A tornado that occurred, but was not warned, will still count toward the population impacted. The population impacted by tornadoes is exactly what it says it is. It is not a conditional count requiring a warning to have been issued.

In any event, here's the results. I'm interested in what you guys think. Feel free to leave suggestions as well, but just know that I'm headed back to working on my dissertation so it might be a week or so before I can act on any of these suggestions!

Number of People Warned For
Tornado Warnings

  • 2008: 134,180,576
  • 2009: 99,676,144
  • 2010: 133,951,616
  • 2011: 144,896,400
  • 2012: 90,455,328

Number of People Impacted By
Tornadoes (+/- 2 kilometers)

  • 2008: 5,772,576 (4.3 %)
  • 2009: 3,120,432 (3.1 %)
  • 2010: 4,935,376 (3.6 %)
  • 2011: 7,068,976 (4.8 %)
  • 2012: Official Tornado Data Unavailable At This Time

Number of People Impacted By
Tornadoes (+/- 7 kilometers)

  • 2008: 15,949,392 (11.8 %)
  • 2009: 8,370,304 (8.3 %)
  • 2010: 15,872,896 (11.8 %)
  • 2011: 22,155,984 (15.2 %)
  • 2012: Official Tornado Data Unavailable At This Time

Number of People Impacted By
Tornadoes (+/- 12 kilometers)

  • 2008: 23,074,960 (17.2 %)
  • 2009: 12,152,944 (12.2 %)
  • 2010: 22,187,520 (16.5 %)
  • 2011: 33,982,416 (23.5 %)
  • 2012: Official Tornado Data Unavailable At This Time

Radar Animation of a Heavy Snow Band

Anyone who looked at radar animation of this past weekend's nor'easter would have quickly noticed an intense precipitation band that stretched from Long Island northward into Connecticut. This band, at times, had dBZ values that were higher than 55 dBZ, and predominantly produced snow. (There are some reports that in southern Connecticut sleet or maybe small hail were also reported.) Beneath this band snowfall accumulations were upwards of 6" per hour!

For those who did not witness this band in person, I have put together an animated gif depicting the evolution of this band. The animation begins near 23 UTC on 08 Feburary 2013 and ends 06 UTC on 09 Feburary 2013. The four panels are:

  • Upper Left: Lowest Tilt Base Reflectivity
  • Upper Right: Lowest Tilt Correlation Coefficient
  • Lower Left: Lowest Tilt Base Velocity
  • Lower Right: Lowest Tilt ZDR

You may recognize the background. It's the black and white version of the GRx Population Backgrounds, which were announced in this post.

For a larger image animation, click on the image above to get the full resolution. Warning, it's about a 22MB animation!

Population Density Background Maps for GRx Radar Viewers

Tonight I created a couple of Gibson Ridge Radar Viewer backgrounds that display the 2010 population data on a 5km grid. You can see a color and black and white version below. Since the background images are actually displaying interesting data, I’ve also provided a colorbar for both of these images. The color curve is logarithmic.

and

You can see what they look like in GR by looking at this and this. If you would like to download these background images, you can get the color version here and the black and white version here.

To install, you will need to:

  1. Start GR
  2. Click on “GIS” in the menu across the top
  3. Click on “Setting” in the resulting drop-down menu
  4. Click on “Backgrounds…” in the resulting drop-down menu
  5. Select the file you downloaded. (You will need to unzip the zip file if you haven’t already.)
  6. Enter the longitude and latitude values for the various corners. These are:
    • Left Lon: -125.
    • Right Lon: -63.
    • Bottom Lat: 22.5
    • Top Lat: 50.
  7. Select “OK”

If you like these, please let me know!

Climatological Estimates and Evolution of Local Daily Severe Weather Probabilities: Part 3

For the final post (at least for now) in this sequence of estimating the climatological probability of an occurrence of some sort of severe weather phenomena, I turn my attention to day 1 severe weather outlooks from the Storm Prediction Center.

I used a similar method as with the previous graphics, however, because the severe weather outlooks are larger in size than severe weather reports, I used a smaller spatial smoother. (In fact, you can do the analysis without using a spatial smoother, but the probability edges are jagged.) The spatial smoother is 80km, and affects the resulting probability magnitudes by less than 1% for slight risks.

For more animations, check out the original post, the “non-significant” severe first post in this series, or the "significant severe" second post! As with the previous graphics, the raw images should become available on the Storm Prediction Center’s website in the coming weeks.

Because the image quality is a bit degraded in the animations, the color scales for each animation are listed below.

Slight Risk (or greater): 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40+%
Moderate Risk (or greater): 1.00%, 2.00%, 3.00%, 4.00%, 5.00%, 6.00%, 7.00%, 8.00+%
High Risk: 0.05%, 0.1%, 0.25%, 0.40%, 0.55%, 0.70%, 0.85%, 1.00+%