Abstract
Throughout the past ten years, the global climate has seen several considerable changes,
with many key causes being chosen as culprits for the change. The main questions surrounding
this topic include what is affecting the climate and by how much, how much global temperatures
are changing compared to previous years, and what are the implications of the rapidly changing
climate. Extensive research has already been performed by professionals who have dedicated their
jobs to answering those very questions, and there are databases containing raw data for every
measurable aspect of the globe that could be linked to climate change. News articles and blog
posts then use that data to create visualizations to spread that data to a wider audience.
The goal of this project is similar to those sites, which is to visualize the number of causes
and effects that are linked to climate change and how they are linked. To accomplish this,
we created the visualizations using Heatmaps - Figure 1 ,
choropleth maps Figure 2., small multiples Figure 3 a, and correlation mappings Figure 4.
to solve two major tasks.
Introduction
There are numerous causes and effects that have been attributed to climate change. So much so that including all of them would stretch the scope of this project far too thin to sufficiently focus on them all. For that reason, we decided to focus on the attributes that we determined to be the most important. The three effects that we chose are carbon dioxide emissions, which is a number corresponding to the amount of carbon dioxide emitted by each country, temperature anomaly, which is measured as the deviation from the mean temperature of a specific time period, and sea level, which is measured as the change in sea level from one time period to the next.
In order to reach as many people as possible, the main intended users for these visualizations would be the general public. Because the effects of climate change are not limited to a single area, having our visualizations be easily accessible and understandable by highlighting the most important information is a top priority. While the goal is to be as wide-reaching as possible, it does require that the user has a basic understanding of the topic of climate change. For example, users would need to understand what carbon dioxide emissions are and the consequences of releasing large amounts of carbon dioxide are. However, users are not required to know how carbon dioxide is being emitted, nor do they need to know what company or household is emitting the most.
While there are numerous online visualizations surrounding the topic of climate change, they frequently have flaws that hinder their effectiveness. For example, many lack user interaction, use color poorly, or have inconsistent scaling. Our visualizations aim to avoid those common problems that many online visualizations contain by implementing user interaction such as zooming and panning, facets such as small multiples and juxtaposition, and color that is culturally significant and that emphasizes important points in the data.
To drive the creation of our visualizations, we determined two potential tasks that users may want to solve. The first task is to identify correlations between carbon dioxide emissions and temperature anomalies by region. The second task is that users should be able to identify outliers in sea level rise between bodies of water.