Visualizing Climate Change Data with Python

Visualizing Climate Change Data with Python

Creating climate change graphs with the xarray and cartopy Python libraries

It is an undeniable fact that climate change poses the biggest challenge for humanity in the current era. The global mean temperature is constantly rising, and the IPCC has pointed out the increase should be limited to 1.5 °C above pre-industrial levels, to have any hope of mitigating the harmful effects of climate change. This goal was set in the Paris Agreement, which was adopted by almost every country in the world on 2015. Unfortunately though, little action is being taken to deal with the problem, highlighted by the alarming scientific research that is constantly published.

The COVID-19 pandemic led to a drop in most aspects of human activity, and the subsequent decrease of fossil fuel burning and CO2 emissions. Regardless of that, 2020 was one of the hottest years in history, with extreme weather events being recorded all over the globe. Furthermore, according to research published in the Cryosphere journal, ice sheets are melting at record rates across the planet, being in line with the worst-case scenarios of IPCC¹. Other scientists claim that climate change and biodiversity loss pose an unprecedented existential threat for humanity, on a scale that is difficult to grasp even for experts².

According to surveys conducted by the Pew Research Center, about 70% of people worldwide believe that climate change is a major threat to their country. This percentage has increased significantly compared to 2013, but it should still be considered low, as everyone must understand the magnitude of the problem. One way to inform the public about climate change, is by creating informative and aesthetically appealing visualizations of the associated data. In this article, I am going to show you how to create map charts and animations of temperature variability, using Python.

data-visualization data-science climate-change python

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