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Using Infographics to Make Climate Change More Visible to the Public

Climate change may not be a directly observable phenomenon, but its impacts are currently threatening the lives of all living organisms. Although the majority of scientists believe that human actions are significantly affecting the global climate, many people still do not take climate change seriously. Even among individuals who are convinced that climate change is real, many believe that it is a spatially- or temporally-distant issue. For example, many people who live in developed countries perceive climate change solely as a threat to developing countries on the other side of the world, or as a threat to future generations. Social scientists have identified this thinking as the “psychological distance of climate change.” Individuals who have experienced the consequences of climate change firsthand (for example, those affected by extreme flooding) are not only concerned about climate change, but they are also more likely to take action to mitigate its effects.

Visualizations, in the form of charts, graphs, or pictures, can help communicate abstract or complex ideas to the public in a simple form. Visualizations can be leveraged to provide direct links between people’s daily lives and climate change. This may help to motivate the public to take action towards more sustainable behavior. Research has demonstrated that using past events, we can help pre-experience possible future events. We can leverage visualizations to provide examples of past climate change and help reconstruct what the climate will look in the future. A hands-on approach where people can build visualizations themselves, or interact with them, may help convince them to take climate change mitigation more seriously. In this article, I will demonstrate potential visualizations that may help to shrink the psychological distance of climate change. 

Carbon dioxide concentrations

Carbon dioxide is the major greenhouse gas responsible for increasing the average temperature of the Earth. Its concentration has continued to increase since the pre-industrial era, thanks to the burning of fossil fuels. One climate-change visualization that is widely popular among the public is the Keeling Curve, which depicts the increase of carbon-dioxide concentrations in the atmosphere from 1958 to the present day. The curve is named after the famous scientist Charles David Keeling, who began the monitoring program on which it is based. The Keeling Curve has often been hailed as one of the most important scientific works of the 20th century. The curve depicts daily atmospheric carbon-dioxide concentration data collected by Hawaii’s Mauna Loa Observatory. This data is available as a public service to those who are interested in climate change. I was able to make use of this data to create my own version of the Keeling Curve in R. Click here to learn how to create the Keeling Curve in R.

 

The Keeling Curve that depict the rise in concentration of carbon dioxide in atmosphere.

Evidence of climate change in glaciers

There is much evidence of climate change, but its effects are most prominently seen in glaciers. Glaciers are huge masses of ice that move slowly due to the influence of their weight and gravity. Because of climate change, many glaciers around the globe are retreating (reduction of size by melting) at an unprecedented rate, which leads to sea-level rise. The United States Geological Survey (USGS) estimates that the sea level would rise by approximately 70 meters if all the glaciers of the globe were to melt. Thanks to satellites such as Landsat, which is operated by the National Aeronautics and Space Administration (NASA) of the United States, it is possible to compare changes in the size and volume of individual glaciers over time. Almost all of the glaciers in the United States’ Glacier National Park have lost a significant portion of their surface area, with some having lost close to 80 percent of their area. Using publicly-available spatial data from the USGS, I created an application where users can manipulate a slide bar to see the changes in individual glaciers at Glacier National Park between 1966 and 2015. Click here to interact with the application.

Glaciers in Glacier National Park of the United States. Click here to interact with the visualization.

Land-use and land-cover change

There are many actions that lead to emissions of greenhouse gases into the atmosphere, and one of the most prominent of these is land-use and land-cover change. The IPCC’s 2014 report estimated that land-use change is responsible for about a quarter of human-induced greenhouse gas emissions. Forests, grasslands, and peatlands sequester a massive amount of carbon from the atmosphere, and cutting or clearing them for human development releases trapped greenhouse gases into the atmosphere. Over the progression of time, forest land has been cleared at an alarming rate to make room for more human settlement and agriculture. While many imagine land-use clearing as taking place in developing countries with dense rainforests, this effect is also pronounced in developed countries such as the United States. Using ArcGIS online and a publicly-available dataset, I created an application that shows the change in land cover around the globe. The map is zoomed in to the city of Phoenix in Arizona, one of the fastest-growing cities in North America, but you can pan anywhere in the world to see how land cover has changed historically. Click here to interact with the visualization.

Changing land cover of Phoenix, AZ, United States. Raster data can be utilized to visualize the land-cover change through time. Click here to interact with the visualization.

Projected future increase in temperature

The Intergovernmental Panel on Climate Change (IPCC) report (2018) mentioned with high confidence that global warming is likely to reach more than 1.5° C between 2030 and 2052. The IPCC recommended limiting global warming to 1.5° C and stressed the importance of taking unprecedented actions in all aspects of society to do so. While global warming means that the average temperature of the Earth is increasing, not all places will bear this rise in temperature equally. This is due to many factors including the diverse geography (oceans, mountains, and polar regions) of the earth. Climate scientists use Representative Concentration Pathways (RCP) in their models, to estimate future increases in global temperature. RCP is the ratio of energy absorbed by the Earth’s atmosphere over energy reflected back into the atmosphere. Increases or decreases in greenhouse gases in the atmosphere cause fluctuations in RCP. Climate scientists use different scenarios of greenhouse-gas emissions to estimate the future change in the Earth’s temperature. Using an available raster dataset from ESRI, I created an application that shows projected increases in the temperature of the Earth at different locations. Users can search their address in the address bar and learn about projected temperature increases in that place. Click here to interact with the visualization.

Projected future increase in temperature using Intergovernmental Panel on Climate Change. Source of data: Living Atlas of ArcGIS. Click here to interact with the visualization.

Natural calamities

The impacts caused by extreme global warming will be long-lasting and could be irreversible, causing the loss of many important ecosystems around the world. Natural disasters have already claimed the lives of thousands of people and destroyed billions of dollars’ worth of property. Scientists are worried that the frequency and intensity of natural disasters will increase in the future due to climate change, and that this will severely impact human life and property. Using the publicly-available dataset from the National Oceanic and Atmospheric Administration website, I created a dashboard in Tableau that depicts the estimated total number of deaths, injuries, and total costs of natural disasters from 2011 to 2020 in the United States. Users can filter out the data by State, Year, or both. Dashboards like this one can help the general public understand how much is lost because of natural calamities and encourage more action to mitigate climate change. To interact with the dashboard, click here.

Dashboard that depicts the impacts of Natural disasters in the United States from 2011 to 2020. Click here to interact with the dashboard. 

Conclusion

Climate change is a global issue that needs to be addressed as soon as possible. Carbon dioxide is the main greenhouse gas responsible for climate change and its emissions should be reduced drastically to mitigate climate damage. Many people, however, are not concerned about climate change. This lack of concern may be caused either by a bogus understanding, or a lack of concern about the potential consequences of its effects. Even among those individuals who believe in climate change, there are many who do not perceive it as an immediate threat. To address this issue, I experimented with a range of data visualization approaches to illustrate and personalize the impacts of climate change.

I used the Keeling Curve to illustrate the consistent upward climb of carbon dioxide concentrations in the atmosphere. Similarly, I applied a slider in an application to demonstrate glacier retreat in a much-beloved national park where users can compare the past and the present status of glaciers. This will help in educating themselves about the consequences of climate change. I personalized a time-series application of land cover change to allow users to “see” prospective impacts on geographies of importance to them. I also quantified the cost of lost lives and property in financial terms in a Tableau dashboard. These interactive and personalized visualizations attempt to make climate change individually meaningful — more “real” — and motivate planet-saving action.


Author profile

Rajesh Sigdel (Raj) is a Ph.D. Candidate in the Department of Geography, Environment, and Sustainability at the University of North Carolina at Greensboro. Raj enjoys wrangling and visualizing various spatial and non-spatial data. For more posts like this, you can follow him on Twitter (@GeoStudentRaj) or LinkedIn (https://www.linkedin.com/in/rajeshsig/).