The project is our approach on continuously covering and explaining climate change. At its core there is a live dashboard. It is directly embedded on spiegel.de 24/7, 365 days a year, as well as on the project’s sub-site, that shows nine of the most important indicators on our planet’s condition
- global warming
- sea level rise
- arctic sea ice
- forest loss
- renewable energies
accompanied by in-depth explainers on each topic (Example, Released as work-in-progress. Three of them have already been published, rest will follow shortly) and an extensive and completely transparent methodology article.
Our basic idea, and hopefully the effect on our audience, was to break the news cycle for climate change reporting. Climate change is probably the biggest challenge humanity is facing at the moment and in the near future. It is happening slowly (at least in the eyes of a human), often eludes individual perception and mostly makes it into the news when there are catastrophies or political talks. Yet, climate change is happening every day: our climate has already changed significantly, it already affect’s people’s lives and we are already reacting and try to adopt.
We want to inform our readers about the current situation on a daily basis. There is a section on our landing page where we always show a combination of our latest climate coverage and our continuously updating dashboard. It’s a constant reminder where we are, how climate change affects the situation in Germany and what progress we’ve already made. From the pure and simple numbers, it’s just one click to read our in-depth articles that combine latest data and dataviz/storytelling techniques in order to explain the bigger picture.
Since the initial release of the project (a first version has been published in 2020, the current, largely extended one in august 2021) at least four other major German news sites have released similar projects. Many schools, organizations, and companies have asked to reuse our live-updating dashboard and diagrams from our explainer on global warming are currently being used in lectures on arctic cruises. I have received more comments and letters from readers than ever before in my career. Some by fierce climate change deniers, but many more from interested readers.
In many ways, this project would not be possible without climate scientists and their generosity to share their data and insights with us. Data for the arctic sea ice extend and the level of drought in Germany for example is automatically retrieved several times a day from open data sets.
Some of the in-depth articles use live data as well. There are for example charts that show the energy production in Germany during the last week in 15-minutes intervals and charts and maps that show where temperatures have been exceptionally high recently (comparison for the given month). Those charts are built in Datawrapper and are updated via R and the DatawRappr-library.
Finally, we use QGIS for geospatial analysis and mapping and AI2HTML to produce static, yet responsive graphics.
What was the hardest part of this project?
Gaining editorial support for an unusual project. What kind of content do we produce as journalists? At DER SPIEGEL it’s normally articles, videos or podcasts that are of high current relevance. After publication we move on to the next article. This project is different. Its aim was to create a platform that’s here to stay for years. This meant a lot more preparation than usual and it takes a lot of sustained effort to keep everything running. In order to do this, we needed the support up to t editors and the commitment that we would be willing to permanently showcase the project on our landing page. This meant many talks, presentations, and feedback loops, but proved fruitful in the end. Regarding the content it’s not trivial to find indicators that do both: inform about climate change in a concise manner and offer information that changes on a daily basis. A good example is our metric on exceptionally high temperatures in Germany. Using raw data by the national weather service we continuously calculate the share of weather stations that have reported exceptionally high temperatures (for the given month) within the last week. By doing so, we address a time period everyone can relate with (current weather), provide a comparison to a time before climate change took hold (the resulting numbers often are astonishingly high and raise awareness to climate change regardless of the current season) and offer the results on a local level (map provided in the according background article) Keep everything up and running. The project has dependencies to six different external data sources. There’s around a dozen scripts running 24/7 and roughly as many charts that must be maintained. Lastly, we need to make changes every time there are major advances in climate change (mostly in the IPCC
What can others learn from this project?
- When dealing with topics that are of high relevance for a long period of time, it is well worth it to take a step back and rethink on how we report on the subject. This might lead to formats that are unusual, challenge the way we work but also inform our readers in a different, surprising but still fitting way.
- For the project described here, a different approach also meant different skill requirements. Beyond “ordinary reporting” we also needed technical expertise in data gathering and processing, IT infrastructure and front-end design that might not be available everywhere. If we don’t invest in this kind of resources and interdisciplinary teams, we ultimately miss out on opportunities how to best inform our audience.
- Finally, when reporting on climate change you’ll most likely face strong opposition from climate change deniers. We didn’t want to give them any leverage to doubt our coverage or the indicators we’re working with. To prevent this, we’ve published an extensive and completely transparent methodology article alongside with the project. In our choice for indicators and data sets we rated broad scientific consensus above everything. Wherever possible, we’ve tried to work with well approved, long-scale data instead of individual studies (even if they were newer). In many cases we ended up with the newest IPCC report as our primary source.