Animated spiral of changes in global temperature (1850-2025)
Professor Ed Hawkins is a leading climate scientist and communicator at the National Centre for Atmospheric Science, based at the University of Reading. Hawkins served as a Lead Author for the IPCC 6th Assessment Report. His research focuses on understanding historical climate variations, future climate projections and how these can inform decisions today on adapting to and mitigating climate risk.
In this discussion, Hawkins explores his viral climate spiral, an influential visualisation that has informed public conversations on climate change risks and solutions. He explains the motivation behind its creation, the data used, and provides insights into how you can create a similar visualisation.
What story does this visualisation tell?
"The visualisation demonstrates how global temperatures have changed over the past 170 years (see below). We have tried to tell a story with the data, rather than simply presenting it in a typical static line graph. I think one of the benefits of having the spiral animation approach is that it draws people into the visualisation."
"When we put the climate spiral online back in 2016, people watched it over and over again. One of the main reasons for this is the visual shock at the end.
"For the first part of the animation, global temperatures are gradually changing, with the increases fairly slow and steady. Suddenly, at the end, the global temperature bursts outwards, propagating to the edge of the graphic."
Why was it created?
"I was, as many scientists do, experimenting with different ways of visualizing data. I remember I'd made a graphic which the BBC had used for a piece about COP. The graphic was more traditional; it was still animated but with stacked horizontal lines illustrating global temperatures from January to December each year from 1850.
"In response to this I received an e-mail from Norwegian climate scientist Jan Fuglestvedt. It was a Friday afternoon and he emailed saying he had ‘just a slightly crazy thought’. This thought involved connecting the lines together at the ends of my graphic, joining up the months of January and December, to turn it into a circle.
"I thought this sounded quite interesting and so I spent a couple of hours developing the idea. We iterated backwards and forwards, before putting it online early the next week. Suddenly, everyone was liking it as well."
The data and methods
Tell us about the data.
"For the global temperature spiral, I used a data set called HadCRUT4 (Hadley Centre/Climatic Research Unit, version 4 - Met Office Hadley Centre observations datasets), which is collated by the Met Office and the University of East Anglia.
"The data set is publicly available and consists of estimates of global mean temperature dating back to January 1850. You can download the global average to the simple time series at one value per month and use it in any way you like.
"The data set has since been updated to HadCRUT5 and there are other sources of similar data, such as from NOAA (National Oceanic and Atmospheric Administration) and NASA in the US. You can download the data and it comes with an uncertainty estimate as well, although we chose not to use this in the climate spiral.
"We now have approximately 170 years of temperature records. In our data sets, we have around 1 billion thermometer observations, which are brought together to produce global averages. That's a large number of observations which we have distilled down to a very simple graphic."
What methods did you use to collect and analyse the data?
"We have temperature records going back to the 1600s and the 1700s in certain places, although the widespread adoption of thermometers across the world started in the early 1800s.
"Beginning in 1850, we have lots of data sets recording temperatures over land, and especially over the ocean. These observations were taken on ships, measuring both the air and sea temperature. Back in the 1850s, mariners were instructed to throw buckets over the side of ships, collect water, haul up the buckets, and use a thermometer to measure the temperature of sea water.
"Now, especially on land, we have special enclosures called Stevenson screens, which encase thermometers to ensure they measure the temperature of the air as cleanly as possible without any interference from sunlight and other sources.
"We haven't always had Stevenson screens in place, and so we have to make some corrections for observations to produce these overall data sets."
What tools did you use to create the visualisation?
"I use software called MATLAB - many people now use Python, but I’ve chosen to stick with this software for my visualisations."
Why did you choose to present the data in this way over other approaches?
"There are so many different ways of presenting the same data and I think it's very hard to know in advance which will work best for different audiences. We have to experiment and there are many scientists all over the world who are trialling different approaches.
"We need to have a range of graphics that we can use for different situations, from very simple to very complex depending on the audience. We're always trying to find new ways to spread the key message that the climate is changing and it's our fault."
The impacts
What impact has the visualisation had in research, policy and other contexts?
The visualisation’s impact has largely involved raising awareness and starting conversations. I put the spiral online in March 2016 and it was really popular at the time. Later that year was the Rio Olympics, which featured a sequence in the opening ceremony on climate risks and climate change.
One of the graphics used was the spiral in a redrawn form, showcased on the screen for nearly a billion people all over the world.
Advice for using this visualisation technique
How else might this approach or data be used?
I still update the spiral every year when new data comes in. Other people have also been inspired to take the approach, improving and adopting it in different ways.
For example, the National Visualisation Team at NASA have made a version with their own data set: NASA GISTEMP (GISS Surface Temperature Analysis - Data.GISS: GISS Surface Temperature Analysis (GISTEMP v4)), animating it and twisting it into 3 dimensions.
What steps can others take to try this visualisation technique?
So much data is now available openly. Data sets can be very local to where you are and that allows you to tell stories about what's happening locally. I think that is a very powerful way of reaching people.
You can also use the big data sets which cover the whole planet. I would recommend you go and explore, find data and just experiment.
What's your one top tip for geographers looking to visualise data in this way?
Simplify. I think it's very easy to get stuck in the complexity of the data and try to represent everything in one go. The most powerful visualisations often try to be simple with a key message.
Understanding why you are making something right from the beginning is important. You should define the intent of the graphic, writing down what you are trying to achieve very clearly.