How Data Visualization Helps Us See the Effects of Climate Change

Mapping techniques highlight how quickly the glacier margins in Glacier National Park are receding

The importance of maps

I’ve always considered maps to be powerful visuals because of how universal they are. They’re a pretty standardized encoding system, as we learn about maps and what the legends mean all the way back in school, and then we keep seeing them throughout our lives, everywhere from the weather channel to planning our commutes.

When using maps for data visualization, we build on all those lessons taught about maps throughout the years. If we choose to visualize a metric by country on a world map, we can introduce characteristics that that can capture the interest for a wider audience. Let’s take life expectancy as an example. This may not be something you’ve considered in the past, but if you were shown a map of average life expectancy, I’m fairly certain you’d look to see how your country compared to others.

(Romania, where I was born, averages 74 years, and I’m pretty confident you also checked your home country.)

Methods for visualizing data on maps have become more advanced to meet the needs of our global landscape. The Tableau-Mapbox integration has made exploring map data increasingly easy, leading to some interesting visuals such as how Africa would look like without forests or what the military presence looks like in Syria.

Maps and climate change

Inspired by the many compelling visuals, I set out to explore the effects of climate change using maps. Climate change is a complex topic that first came under the name of “global warming.” That term caused people to associate climate change with weather, which is the shorter-term manifestation of overall climate trends. This, in turn, led to questions like “How can the Earth be getting warmer if we just had a really cold winter?”

Climate is a longer-term trend than seasons and can be harder to understand intuitively, because singular weather events can skew perception of what the overall climate trend looks like. This is where visualizing data can help us look past our own experience of the weather and instead focus on long-term patterns and trends that exist on a scale we otherwise would have trouble noticing. A good proxy to understand climate change is to look at geographical units that would otherwise be stable and see how they evolved over the years. The most straightforward example for this is glaciers.

Why is the melting of glaciers always mentioned in climate change debates?

The most commonly known consequence of melting glaciers is rising sea levels, but it’s just one of many. According to the WWF, the melting process increases coastal erosion, creates more frequent coastal storms and affects the habitat of wildlife such as walruses and polar bears. Through continual melt, glaciers are a source of water throughout the year for many animals, and help regulate the stream temperatures for animals that need cold water to survive. When a glacier shrinks, that cyclical source of water disappears.

It’s difficult to remember what a glacier looked like 10 years ago compared to now. While pictures of glacier valleys before and after melting can provide an interesting visual, they can be seen as anecdotal, and lack a certain quantitative element to them. We know glaciers are melting, but how fast and by how much? What do the glaciers look like now, and what are the implications? I decided to see if I could use Tableau and map data to visualize how the glaciers are shrinking over time, to see if I could help answer some of those questions.

Choosing Glacier National Park

2.9% of the Earth is covered with glaciers, so representing all the glaciers in the world in one visualization is tricky. Not only that, but there is no universal, consistent dataset of all glacier margins that is detailed enough to derive meaningful visualizations from. As a result, I chose to narrow down my analysis to Glacier National Park, a forest preserve that spans over 1 million acres (4,000 square kilometers) between Canada and the US state of Montana. It’s home to more than 1,000 different species of plants and animals. Currently, it’s home to 37 named glaciers that have been evolving over time.

The USGS (US Geological Survey) has collected a time series spanning 49 years of the 37 named glaciers and their margins based on aerial imagery. The dataset consists of shape files that can be overlayed to produce a comparison of what the park looked like 50 years ago versus now.

Full visualization can be found here.

Looking at some of the glaciers with the most recession (as percentage of their initial span in square meters), we can compare the 1966 margins (dark blue) with the 2015 margins (very light blue).

These comparisons tell a story that is less than ideal. Taking Herbst Glacier and Two Ocean Glacier as examples, we can see that over 80% of the main glacier body area has disappeared. Summing up the losses, we find that over 7.6 million square meters of glacier area has receded. That’s over 1,000 football fields lost just out of this one national park in Montana. Below are sevenof the glaciers visualized:

What can we do next?

There is a wealth of resources that address how to slow down the effects of climate change, so access to information is clearly not the problem. From a data perspective, what we can do is help understand it better by providing the information in an accessible way. One of my favorite Tableau vizzes presents the topic of ocean plastic in a way that made me look at it closely, even after scrolling past multiple articles with the same theme throughout the years. The method in which data in presented has a great impact on whether the information is consumed.

So I invite you to dig into the data, visualize it yourself, find key insights, and share with others. In doing so, we have the ability to make others see the issues more clearly and in turn, work to address those issues.