Edited Version For Ithaca

An Informal Groundhog's Day Evaluation

Every year, for a single day, the nation puts aside all scientific reasoning and turns to the almighty groundhog for its weather wisdom. For some this tradition is rooted in fun and amusement, for others it is a cultural thorn in the delicately woven fabric of meteorological knowledge. But just how accurate are Groundhog's Day forecasts?

To answer this question, let's first determine when winter traditionally ends. According to the saying, if the groundhog sees its shadow, there will be "six more weeks of winter". If no shadow is seen, then spring will come early. Based on this, winter should traditionally end six weeks after February 2nd, ie. March 16th. We can say that a winter that ends before March 16th represents an early spring; a long winter goes until at least March 16th. Now that we know when spring and winter should be, let's determine what conditions qualify as spring and winter. To do this we'll use both snowfall and temperature.

Snowfall: Let's assume that during the winter we receive a regular series of snowfall events, and that as we move into spring, they become further and further apart. Looking at snow histories from various local cities, we can say that once we get into March, snowfalls tend to become less representative of winter when the time between snow events increases to approximately two weeks. So, once we get to the end of winter, and it stops snowing for more than two weeks, we can consider the last snowfall to have been the end of winter in terms of snow.

Temperature: The average March temperature is 32.6 degrees. Because March 16th -our traditional end to winter- is exactly in the middle of the month, we can assume the average March temperature to represent the winter/spring threshold temperature. So, once the temperature begins to get above 32.6 degrees, we can assume it is becoming spring.

Yay! We can now assign spring or winter designations to both the snow and temperature categories. So obviously, if we scored a spring in the snow category, and a spring in the temperature category, then it was spring. If we got winter in both categories, then it was winter.
But what if we get spring in one category and winter in the other? Let's say it's a very cold, but dry winter and it doesn't snow. Our snow category will be indicative of spring via the parameters we established, but the temperatures will fall short of the 32.6 degree parameter we set, indicating winter. In this case, because the March average is below normal, we can compare it to an average between the normal March and February temperatures to see how characteristic the cold March temperatures are of the beginning of March- and therefore then end of winter.

In the opposite case we could have temperatures that rise to very warm levels during the day, but at night we get a lot of light nuisance snowfalls that just stick to the grass. The categories would then reflect snowfall = winter, temperatures = spring. We can treat this the same as the previous scenario, but instead of incorporating the average February temperature, we can use the average April temperature to see how characteristic the warm March temperatures are of the end of March- and therefore the beginning of spring.

Ultimately we end up with the following table for Ithaca:
groundd.png

And applying it to the past decade yields:
Early spring: 2012, 2010, 2009, 2006
Long winter: 2015, 2014, 2013, 2011, 2008, 2007

Now we return to our original question of "how accurate are Groundhog's Day forecasts?" Over the past decade, we get the following accuracy ratings for our furry friends:
ground.png
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