Measuring growth: How GDD supports smarter turf decisions

There is, it has to be said, a lot of discussions about data nowadays and its application to turfgrass management. Data doesn’t replace the practical nous, observations and thinking from greenkeepers and groundsman/women. Used correctly, it complements it.

I really started looking at applying data to turfgrass management back in 2010. That year we had a very hard winter and the following spring was late. A course manager rang me and said his club were moaning about the state of the greens and he wanted data to go back to the club to say “Because of the weather we are ‘x’ weeks behind last year, growth-wise”.

It got me thinking.

So, I turned to Growth-Degree-Days (GDD). I knew about its use in horticulture and decided to look at applying it to turf. I chose 6°C air temperature as my base temperature, because that’s when I observed above-ground, grass growth and pulled in the minimum and maximum, daily air temperature from a weather station to calculate GDD (pictured below). 

It is a simple calculation; you add the minimum and maximum air temperature for a given day together, divide by 2 to get an average and subtract the base temperature. If the result is a negative, it is dealt with as zero GDD.

I used January 1st as a reset point and then calculated the cumulative GDD for one specific year vs. another and graphed them out.

The results were illuminating.

For me, it was the first example of applying data to a turfgrass management problem in order to provide a solution that could be easily understood.

Here’s an example.

Which start to the year was colder; the cool and humid 2024 or the warm and dry 2025?

Let’s crunch the GDD numbers from Jan 1st to the end of April and compare them for the years in question. To make it easier, I graphed them using cumulative GDD as my parameter; the results are pictured below.

We can see that 2024 followed a pretty consistent curve from mid-January, with a steady progression right up to the end of April. Turf managers like this sort of graph because there aren’t any flat points with no incremental GDD, indicating no growth.

2025 was a different story. The graph is flat right through to the 19th of February, indicating low incremental GDD, no growth. It isn’t until mid-March that GDD begins to increase consistently.

Selecting a default marker (in this case 200 cumulative GDD), we can see that 2025 hit this mark 21 days later than it did in 2024.

So, which was the warmest spring? 2024!

This is an example of applying data to a practical turfgrass management scenario in a positive and hopefully useful manner. That in my mind is where data is both useful and relevant.