In Central and Eastern Europe, the storm “Boris” caused chaos and flooding due to massive precipitation. An analysis by the Alfred Wegener Institute found that in a world without current levels of global warming, Boris would have produced nine percent less rain. This conclusion was drawn using a new modeling approach called ‘storylines’, which was recently presented in the journal Communications Earth & Environment. A freely available online tool was also released by the AWI team, allowing users to identify climate change fingerprints in extreme weather events and create comparison graphics.
The storm “Boris” led to extreme flooding in Poland, the Czech Republic, Austria, and Romania, resulting in at least 27 fatalities and numerous families being displaced. Cleanup efforts are ongoing, but concerns have already arisen about the next weather extremes in Spain. The question of whether these catastrophes are caused by global climate change is a central issue in public discourse. Dr. Marylou Athanase, lead author of the study, states that the scientific community can provide answers to this question using probabilistic attribution studies, which can determine the increased probability of an event due to climate change.
The ‘storyline’ approach developed by the AWI aims to show the influence of global climate change on local weather in a more understandable way. By comparing hypothetical scenarios with reality, scientists can clearly identify the fingerprints of climate change on extreme weather events. Using storm Boris as an example, researchers demonstrated that without global warming, the storm would have produced nine percent less rain. The storm intensified due to warmer water temperatures, resulting in more water vapor in the air and heavier rainfall.
Connecting climate model-based simulations with actual local weather involves techniques like ‘nudging’, where observed wind data is fed into climate models to accurately reproduce real weather conditions. The model used by the AWI is the CMIP6 version of their climate model, which was part of the base data for the IPCC’s Sixth Assessment Report. Daily weather analyses are run on a supercomputer at the German Climate Computing Center, and the data is transferred to an online tool that is accessible to everyone, providing real-time analyses of climate change signals in extreme and everyday weather.
The online tool allows users to track the ‘Climate Change Signal of the Day’ for temperature and precipitation changes from January 1, 2024, onwards. The goal is to promote a better understanding of the connections between climate change and extreme weather events, providing concrete and timely answers that can be used in media coverage. By utilizing the ‘storyline’ approach and modeling techniques, the AWI team hopes to enhance public awareness of climate change impacts on extreme weather events and enable more informed decision-making in response to these events.
