My flatmates and I have been tending to a small garden plot over the last few years and every year we have the same discussion: When can we safely transplant all of the fragile plants we’ve reared on our windowsills to the garden? I’m usually in favor of transplanting as soon as possible, while my roommates usually want to be a bit more careful.
An argument that always comes up is some form of he sentence: “We can’t plant them yet Eisheiligen hasn’t passed yet!” Where I live in southern Germany, the concept of Eisheiligen or Ice Saints is a rule of thumb when the last cold days of ground frost can occur. Wikipedia writes:

In parts of the Northern Hemisphere, the period from May 12 to May 15 is often believed to bring a brief spell of colder weather in many years, including the last nightly frosts of the spring.

Wikipedia – Ice Saints

This year, during the discussion I decided to look at the data to see whether I can disprove the statistical significance of the Ice Saints and subsequently have an edge in this year’s discussion.

The Setup

The German weather agency provides historical weather data from hundreds of weather stations, reaching back up to 1950. The data comes as a “.csv” file containing day-wise measurements which I will be analyzing with python’s pandas library. The interesting column according to the manual provided by the data source is “TMK”, the mean temperature over the course of a day.

I took the temperature for each day and determined a mean as well as a standard deviation for each day of the year. Interestingly to say, this requires some interpolation due to leap years. What is plotted below is the mean temperature for a day of the year along with the 1-sigma percentiles for depending on the temperature distribution of the given day.

Temperature by day of year. Upper and lower confidence intervals are given by the standard deviation. The region where the Ice Saints phenomenon is expected according to Wikipedia is marked with a dashed line.

If the Ice Saints were a statistically significant rule, I’d expect to see some sort of dip in the trend at the expected date. Looking at our data, there does not seem to be a visible systematic dip in the mean of temperatures. I’ll try to see if we can see the phenomenon directly by checking the individual years. To do this, I check every day of each year and count the percentage of years in which that day had a minimum Temperature below freezing. The result is shown below, again, the expected date of the phenomenon is marked with a dotted line.

In this analysis a small peak in probability for cold days shows up exactly when it would be expected. Also, after this date, none of the days up to autumn went below freezing. In summary we can see:

  • For all years in our sample, transplanting would have been safe to transplant after Ice Saints
  • There was a non-zero chance of sub-zero temperatures for ost days earlier than Ice Saints

So after all, waiting on the Ice Saints is clearly the safest bet you can make. But there are also arguments to be made for planting earlier with a very small chance of freezing temperatures and the added benefits of giving your plants more advantage over weeds and other such considerations.
Whether my analysis helps me in discussing with my roommates, with roommates who don’t really care for data remains to be seen 😉

It might be interesting to see whether a trend in when the last freezing temperature of the year occurs exists due to climate change, but that will be left for another post. Thanks for reading!


Ice Saints, do they exist?

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