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“The two most important requirements for major success are: first, being in the right place at the right time, and second, doing something about it”

-Ray Kroc

One of the most difficult pieces in The Sirens Project puzzle is being in the right place at the right time. For weather enthusiasts and researchers alike, the years of planning and preparation come down to moments and miles. The expression, “missed it by a mile” can be taken very literally when hunting severe weather.

The essence of what we are trying to do at The Sirens Project is dependent on our position and deductive forecasting during severe weather events. If we new the exact location where a tornado would form, down to the yard, this project wouldn’t exist. Instead, our efforts are put on the table in a gamble of atmospheric conditions and road networks.

However, we are not totally in the dark when it comes to forecasting large scale severe weather events. We use what is called “model guidance” to help bring the odds in our favor when chasing storms. Essentially, computers combine a series of complicated algorithms with current analysis and historical analogues to guess what the weather might do in the up coming days. They are far from perfect, but are improving with every data set that is analyzed. We use these models to help bring our chances of seeing a tornado from “picking the winning lottery ticket” to “getting nothing but net from half court”.


There are several models to chose from when forecasting severe weather (GFS, NAM, ECMWF, etc.) One model is not king over the other, and therefore, all outputs should be compared together with current analysis. As a fellow storm chaser, Chris Sanner, always warns: “Garbage in, garbage out”. Models, including current analysis, are only a tool and not the end all be all. At the end of the day, it takes a gut check and some luck to be in the right place at the right time. We hope, through our efforts and similar, we can bring the odds a little more in our favor!

Follow the links below for some of our favorite forecasting resources:

Strom Prediction Center

Mesoanalysis (Current Analysis)

Twister Data

Pivotal Weather

College of DuPage

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