A few weeks ago, the storm “Boris” unleashed severe rainfall that resulted in chaos and flooding across Central and Eastern Europe. Research from the Alfred Wegener Institute indicates that if global warming were not a factor, Boris would have produced about nine percent less rainfall. These insights come from an innovative modelling technique known as “storylines.” This method’s application in near-real-time analysis was just reported in the journal *Nature Communications Earth & Environment*. Additionally, the AWI team has introduced a free online tool that enables users to detect the effects of climate change on present extreme weather events and to generate their own comparative graphics.
In mid-September, storm Boris caused heavy rain and extreme flooding in Poland, the Czech Republic, Austria, and Romania. In several areas impacted, the rainfall reached some of the highest levels ever documented over a five-day period. At least 27 people have lost their lives, and many families had to evacuate their homes. The situation is improving, and clean-up operations are ongoing, but new weather disturbances in Spain are raising concerns. This recurring scenario leads to a critical question in public, political, and media discussions: Did global climate change cause this disaster?
“For several years, science has been able to provide clear responses to this very important question,” states Dr. Marylou Athanase, a physicist at the Climate Dynamics Section of the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). “Within one or two weeks post-event, probabilistic attribution studies can offer an initial analysis of how much more likely the event was because of climate change.”
However, the challenge lies in the fact that probabilities can seem abstract, especially when faced with tangible, extraordinary real-world scenarios. In terms of public communications and discussions with decision-makers, the scientific community has lacked a tool that can effectively illustrate the impact of global climate change on local weather in a compelling and comprehensible manner. “This is why we at the AWI concentrated on developing a new method—the ‘storyline’ approach,” explains Dr. Antonio Sánchez-Benítez, another physicist in the Climate Dynamics Section and co-author of the study. “We essentially apply the ‘what if?’ concept. How would a disaster appear in a world without climate change? Or in a scenario with even higher temperatures? By contrasting these hypothetical situations with actual events, we can clearly identify the effects of climate change—not only for extreme events but also for everyday weather.”
By examining storm Boris, the AWI researchers showcased the potential of this new approach in *Nature Communications Earth & Environment*. The comparative analysis reveals that, without global warming, Boris would have brought approximately nine percent less rainfall. However, as it traveled from the eastern Mediterranean and the Black Sea towards Central Europe, the storm gained strength due to water temperatures being about two degrees Celsius warmer than preindustrial levels. This resulted in a higher percentage of water vapor present in the air over the area. Nine percent may seem minor, but regarding the outcome of intense rains, it significantly impacts how much water accumulates and its subsequent distribution—whether rivers, dams, or sewage systems can manage it or if it overflows, leading to substantial destruction.
But how did the researchers bridge climate model simulations, typically designed for long-term trends, with actual local weather? “One crucial element is termed ‘nudging,’” explains Dr. Helge Gößling, a climate physicist and head of the storyline research at AWI. “Climate models usually simulate a particular, quasi-random series of weather patterns adhering to their programming’s physical laws. To identify climate differences, one must observe whether average values and distributions shift over the long term amidst numerous weather occurrences. Likewise, in weather models, conditions deviate from reality after a few weeks; actual weather predictions remain limited. With ‘nudging,’ we feed observed wind data—including phenomena like the jet stream—into the model, nudging it toward the actual observed winds. This allows us to accurately replicate real weather within the real climate. Next, we modify the model’s background climate, simulating a world unaffected by climate change by lowering greenhouse gas concentrations and adjusting other elements, then repeating the experiment.”
The model employed is the CMIP6 version of the AWI climate model, which also contributed to the foundational data for the IPCC’s Sixth Assessment Report. The wind data used comes from the ERA5 reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF). “We have automated the system to run daily analyses of current weather on the supercomputer at the German Climate Computing Center (DKRZ),” states Marylou Athanase. “This data is sent to an online tool hosted on AWI’s servers, available to everyone at https://climate-storylines.awi.de. Analyses are conducted with a three-day delay on ‘real-time,’ after which they go online. Consequently, users can access the ‘Climate Change Signal of the Day’ for extreme events and everyday weather globally and in near-real-time through interactive maps and timelines, although for now, only temperature and precipitation data from January 1, 2024, onwards is available. Our aim is to enhance understanding of the connections between climate change and extreme weather and to offer clear and timely information that can aid media coverage of these occurrences.
