Context can be a powerful tool, especially in data visualisation. In this post I will discuss one powerful example of a chart where its context and minimalist design led to its popularity. The chart in question is known colloquially as a 'warming stripe' and is often used to show long-term temperature trends in the context of climate change and global warming. They were first conceptualised by British climatologist Ed Hawkins. You have almost certainly come across them, but they look something like this...
The Power of Context
There is a key reason why this chart is so impactful and that is the context in which it is most commonly used - temperature increase and climate change. Blue tones denote cooler temperatures and red tones denote warmer temperatures, with the bars arranged in chronological order. As humans we usually associate these colours with cold and warmth and so can almost instantly associate a shift from blue to red in the chart with a temperature increase. This is an example of a pre-attentive attribute which is something which conveys information instantly to the brain without needing to be processed (colour, size, length are some examples). Obviously a line chart could be used to show temperature increase over time but the association between colour and temperature is not present which makes it far less impactful. This chart actually went viral which has only cemented its importance within the world of climate change in a way no line chart ever really could.
Warming Stripes in Action
I used these stripes extensively during both of my initial application and final viz for The Data School; both within the context of temperature change and other scenarios as well. Take a look at these from my initial application viz on the climate of Svalbard...
The chart on the left is the classic 'warming stripe' design and uses that characteristic diverging colour scheme. It is important to highlight the value at which the colours diverge (change from blue to red). This is given in the tooltip. The other two charts show changes in precipitation and annual frost days respectively and use sequential colour schemes instead. The darker the tone, the higher the value of the measure.
How To Make A Warming Stripe in Tableau
Tableau makes it very easy to create a warming stripe plot so lets take a look at how it can be done.
Step 1:
Import your data into Tableau and ensure one of the fields is a measure of time and the other is a number. In this example we will look at the minimum surface air temperature in Svalbard between 1901 and 2024. Then go to a new sheet to make it.
Step 2:
Drag your measure of a time field (which will be a green pill) to the columns section of the worksheet and your other measure to colours which is in the marks card. Finally set the marks type to bar. You should get something like this...
Step 3:
If you wish to change the colour palette of your stripes then do so by selecting colour and then 'edit colour' in the marks card like so...
Step 4:
Change the worksheet view from 'Standard' to 'Entire View', which should leave something like this...
Hopefully you should now have a warming stripe chart! In my opinion they can be a great way to show long term trends instead of a line chart but do be careful not to overuse them. Also be mindful of your context to make the most of them.
That is it for this blog so happy visualising!