How climate change intensified storm Boris’ extreme rainfall, revealed by near-real-time storylines

How climate change intensified storm Boris’ extreme rainfall, revealed by near-real-time storylines | Communications Earth & Environment

Abstract

Disentangling the impact of climate change on environmental extremes is of key importance for mitigation and adaptation. Here we present an automated system that unveils the climate change signal of the day in near-real-time, employing a set of innovative storyline simulations based on a coupled climate model. Its potential to complement probabilistic assessments is showcased for storm Boris, which brought record-breaking rainfall over Central and Eastern Europe in September 2024, leading to devastating floods. Our near-real-time storylines suggest that storm Boris deposited about 9% more rain due to human-induced warming. The area impacted by the same storm’s extreme rainfall (>100 mm) was 18% larger and would continue expanding in a future warmer climate. Results from our prototype storyline system are disseminated publicly via an online tool. The case of Storm Boris demonstrates the potential of near-real-time storylines for rapid evidence-based climate change communication.

Introduction

At present, there is hardly any weather-related extreme event with societal impact that does not spawn public and scientific discussion about the role played by climate change. In recent years, heatwaves, droughts, and extreme rainfall events have impacted human health 1, disrupted ecosystems 2, 3, caused large losses to agro-economic sectors 4, 5, and induced considerable societal costs 6. In mid-September 2024, unprecedented rainfall over Central and Eastern Europe brought by storm Boris, led to multiple casualties and infrastructure damages 7. For such an extreme flood event as for the everyday weather, two questions arise: How much of the observed conditions is attributable to climate change? And how are they projected to unfold in an even warmer future climate?

To address the attribution and projection questions posed above, the scientific community predominantly employs probabilistic methods which rely on observational data and the use of large ensembles of climate model simulations to estimate changes in the likelihood or intensity of extremes 8. This approach is the cornerstone of successful attribution efforts by the World Weather Attribution (WWA) group 9 which routinely quantifies the influence of climate change on high-profile extreme weather events, often within just 1 or 2 weeks. The method has recently been adopted routinely by national weather services (e.g., the German Meteorological Service). Rapid attribution is now also being carried out by ClimaMeter 10 based on circulation analogs found in the observed record.

However, finding good analogs of record-shattering events in previous observations, which usually span just the last few decades, is challenging because of these events’ exceptional characteristics—as acknowledged by the ClimaMeter assessment of storm Boris 11. This can also be an issue when using large ensembles of climate model simulations, particularly for record-breaking or unseen extremes such as the floods triggered by storm Boris’. Furthermore, answers from different models can differ substantially. Finally, the concept of probability can be challenging to convey to non-scientists.

Event-based storylines have been used increasingly to complement the probabilistic approach 12, 13, 14, 15, 16, 17, 18. The approach followed here employs a technique called nudging 19, 20, 21 and offers relatable “what if” scenarios: First, real contemporary extreme events are reproduced in a global climate model by imposing the observed evolution of the large-scale winds in the free troposphere (i.e., the jet stream). Second, the same winds are imposed using different background climates, thereby simulating how the same events would unfold if they occurred in a colder preindustrial climate (attribution), or in a possible future warmer world (projection). By setting aside uncertain changes associated with the circulation 22, 23, 24, the approach provides climate change information with a high signal-to-noise ratio and thereby unveils how thermodynamic aspects of global warming affect the daily weather, be it extreme or not.

So far, event-based storyline studies focused on past individual weather extremes, often a few months if not years behind real-time 22. Here we present the prototype of an automated system that continuously provides storyline attribution and projection of the weather for any place on Earth, and only 3 days behind real-time—when events like storm Boris that just caused devastating floods in Europe are still salient.

Results

Storyline attribution and projection of storm Boris’ rainfall

Our storyline simulations are based on the Alfred Wegener Institute Climate Model 25, 26, 27(AWI-CM-1-1-MR). This model has contributed to the Coupled Model Intercomparison Project 28 and thereby to the latest IPCC Assessment Report 8—and was shown to be one of the most realistic models 29, 30. The storyline simulations are generated by constraining (i.e., nudging) the observed large-scale free-troposphere atmospheric circulation (that is, horizontal scales larger than ~1000 km) in the climate model, in colder preindustrial, present-day, and future +4 °C warmer climates. The nudged simulations comprise 5 ensemble members for each climate storyline, shown here as ensemble mean (“Methods”). This approach has been successfully used to analyze past heatwaves on land 20 and in the ocean 21. We now brought the storyline approach to near-real-time. As detailed in the “Methods”, the storyline simulations are automatically extended every day and disseminated via an online tool. The tool is freely accessible at https://climate-storylines.awi.de and allows both scientific and non-scientific users to explore the climate change signal of the day.

The simulated version of storm Boris in present-day conditions accurately replicates the spatial extent and exceptional nature of the event. The simulated peak value near 200 mm of rain, accumulated over 12–16 September 2024, much better resembles the observed 225 mm (Fig. 1a,b) compared to that obtained from past circulation analogs 11. A simulated area of about 150,000 km2 experienced accumulated precipitation exceeding 100 mm.

Total precipitation accumulated over 12–16 September 2024 (in mm), as (a) observed (using ERA5 reanalysis data 45 as a surrogate for observations) and (b) simulated in present-day conditions. c Simulated changes in total accumulated precipitation between the present-day event and the same extreme in a preindustrial world. This change addresses the attribution question: how much has climate change contributed to the event? d Simulated changes between the same extreme if it unfolded in a future 4 °C warmer world and the present-day event. This change addresses the projection question: how may future climate change impact the event? Panels are generated with the webtool https://climate-storylines.awi.de.

Comparing our storyline simulations of the event in present-day and preindustrial climates reveals the thermodynamic contribution of climate change to this extreme rainfall (Fig. 1c). While rainfall is marginally reduced in the western part of the event, up to 50 mm more rain can be attributed to climate change towards the east. The area experiencing more than 100 mm of accumulated rainfall is 18% larger than in a world without climate change, with the peak intensity increasing by 8% (changes significant at the 95% confidence level, see “Methods”). Integrated over the broad event region defined in the “Methods”, 9% more rain is deposited, consistent with the 7% combined estimate of the WWA assessment 31(99% confidence level). Anthropogenic climate change has therefore substantially contributed to the intensification of this extreme precipitation event. Preliminary analysis of the factors driving this intensification reveals a large increase of about 15% in vertically integrated water vapor (Supplementary Fig. S1), which is ~10% per degree Celsius of local surface warming and thus exceeds the 7% per °C rate expected from Clausius-Clapeyron scaling 32. This rise in available water vapor may be explained by the amplified warming by about 2 °C in the Eastern Mediterranean and Black Sea, which are important moisture source regions for Boris 31(Supplementary Fig. S2). Finally, increases in vertical air ascent may have also contributed to the intensification of the event, indicating a positive dynamical feedback (Supplementary Fig. S3).

Projected future changes in the event’s rainfall in a globally 4 °C warmer climate (2.7 °C warmer than today) are less clear-cut (Fig. 1d). We find that a future analog of the event would be partially shifted slightly to the northeast. A 14% larger area would receive over 100 mm of rain (99% confidence level), affecting regions at the event’s core and eastern periphery. Future climate change may thus continue exacerbating such an extreme rainfall event, although possibly at a more moderate rate (+2% over the broader event, statistically not significant). Large increases in water vapor (Supplementary Fig. S1), amplified sea surface warming in moisture source regions (Supplementary Fig. S2), and conversion of snow to rain likely contribute to future increased rainfall and flood risks. However, projected changes in vertical air ascent (Supplementary Fig. S3) exhibit a significant dipole pattern similar to the precipitation changes.

The shift in rainfall and air ascent likely results from a complex interplay between dynamics and thermodynamics 33, given that dynamic adjustments remain partially possible in our simulations in which only large-scale horizontal winds above 700 hPa are constrained (“Methods”). While such an interplay is challenging to disentangle and can depend on regional specificities S4). Increased convective available potential energy over the Eastern Mediterranean and Black Sea, important moisture source regions of this event, may also cause more upstream rainfall deposition along the advection path toward Central Europe (Supplementary Fig. S5).

Accessible and relatable climate change information

Our near-real-time storylines are disseminated through a prototype webtool ( https://climate-storylines.awi.de) hosted on servers of the Alfred Wegener Institute and fed with data generated and stored at the German Climate Computing Center (DKRZ). The webtool allows the visualization of our climate storylines from 1 January 2024 and is updated every day 3 days behind real time, following the workflow detailed in Supplementary Fig. S6. Details on the data are in the “Methods”. The webtool features a simple interface in which users can choose the parameter, the background climate (preindustrial, present-day, or +4 °C world), the region of interest, and the type of map or time series to visualize. The first subset of parameters available for visualization includes daily mean, minimum, and maximum 2-m air temperature, sea surface temperature, and total precipitation. Other aspects of the visualization can be adjusted by users to fit their targeted applications and analyses.

Storylines in near-real-time come with great potential for climate change communication. For example, in July 2023 the German broad-readership magazine Zeit Online featured our storyline view on the hottest day of the year in Germany, including an interactive location search to foster personal relatability, just 4 days after the event 34.

Discussion

Revealing the climate change signal of the day with global storyline simulations in near-real-time can add scientific evidence to the public debate unfolding during and right after extreme events—not only for storm Boris, but for any climate-related event happening anywhere at any time on the planet. Our prototype relies on a single coupled climate model, implying that some of our results may be model-specific. Given the growing number of groups applying wind nudging and producing climate storylines 14, 20, 21, 35, 36, 37 we envisage an expansion to a multi-model approach also in near-real-time. Even if carried to a multi-model footing, storyline simulations do not address potential changes in the frequency of occurrence of circulation patterns. Therefore, the approach cannot replace existing probabilistic methods but rather complements those. Even if some (currently largely unknown) dynamical changes are possible, there is no evidence that existing weather patterns will completely vanish or entirely new ones will emerge 38.

Our current storylines are also limited by the coarse (~100 km) atmospheric resolution of the climate model. Km-scale storyline simulations already exist regionally without near-real-time capabilities 39, and are in development at the global scale within the Climate Adaptation Digital Twin of the Destination Earth (DestinE) Initiative 40. They can offer local granularity, important to capture orographic effects and finer structures of precipitation patterns in particular. Km-scale simulations might also shed light on the complex interactions between thermodynamical effects and dynamic adjustments affecting precipitation extremes. Such an interplay is expected to be highly event-specific 33, implying that rainfall changes and mechanisms identified here for storm Boris may not necessarily be generalizable.

Ongoing work to include impact modeling for agricultural 41, hydrological 42 or urban storylines promises to provide further adaptation-relevant information needed to enhance societal resilience, ultimately also in near-real-time. Finally, providing simple access to storyline simulation data, such as planned in the form of data lakes and their operationalization within DestinE, will enable a broad range of applications, including those expected from the recent boost of artificial intelligence in weather and climate science 43.

Here we have showcased how a near-real-time storyline system can provide rapid, relatable climate change information for a broad-impact extreme such as the devastating European rainfall in September 2024. We envisage that this approach will become a useful tool for scientific research and an important piece of the future dissemination portfolio of climate change information.

Methods

Near-real-time storyline simulations

Our 5-member storyline simulations are performed using the global coupled climate model developed at the Alfred Wegener Institute (Germany), AWI-CM-1-1-MR 25, 26, 27. The storyline simulations are carried out following the method first described in ref. 20, and successfully used for analyses several years behind real-time 21. The observed atmospheric circulation (vorticity and divergence) is constrained (i.e., nudged) at large synoptic and planetary scales, that is, horizontal scales larger than ~1000 km. Only vertical levels between 700 hPa and 100 hPa are nudged, to leave the atmospheric planetary boundary to evolve freely. In the tropics, the performance of the approach is thus limited by the larger role of convective processes compared to horizontal large-scale advection and the presence of thermally more direct circulations such as the Walker circulation.

Here we present a prototype system for near-real-time storyline attribution and projection of the weather for any place on Earth at any time, following the workflow illustrated in Supplementary Fig. S6. Storylines are first initialized using states from our AWI-CM-1-1-MR historical and Shared Socio-economic Pathway scenario ssp370 free-running simulations to produce the different background climate conditions. Preindustrial, present-day and +4 °C conditions are obtained by branching 4-year nudged simulations off the free runs respectively on the 1st January 1851, 2017 and 2093, the latter corresponding to a +4 °C global mean surface air temperature increase compared to preindustrial in the model. Storyline simulations are then extended from these different initial states, and nudged to the global atmospheric vorticity and divergence from ERA5 starting on the 1st January 2017 until the 31st December 2023.

From the 1st January onwards, the storylines are extended daily, and utilize atmospheric vorticity and divergence from the ERA5 reanalysis initial release (ERA5T) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) 3 days behind real-time. This daily extension workflow is illustrated by the dashed box in Supplementary Fig. S6. Storylines each comprise five ensemble members spawned from the five respective AWI-CM-1-1-MR free-running simulation ensemble members and thus starting from different initial conditions. Figures show ensemble means for each five-member storyline ensemble. All storyline simulations are generated and stored on the German Climate Computing Center (DKRZ), using 1600 node-hours (3071 cores) for a throughput of 1680 GB per simulated year.

Prototype visualization webtool

The prototype webtool disseminating our near-real-time storylines is accessible to everyone at: https://climate-storylines.awi.de. The webtool features a simple interface in which users can choose the data source (storyline simulations or ERA5 climate reanalysis data), the parameter, the background climate (preindustrial, present-day, or +4 °C world), and the type of map or time series to visualize. ERA5 reanalysis data and the simulated SST fields are interpolated to the grid of the model’s atmospheric component to facilitate comparisons. The storyline data has daily resolution and is averaged over five ensemble members for each climate storyline—that is, five versions of the storyline simulation differing slightly from one another. Visualizing the ensemble average ensures that the signal of climate change of the day that may arise from our storylines is robust.

Calculating anomalies

SST anomalies shown in Supplementary Fig. S2 are derived with respect to the reference period 1985–2014. Anomalies for the ERA5 reanalysis fields are produced with respect to the ERA5 climatology. For the present-day storyline simulations, we derive the simulated climatology from the 5-member ensemble mean of our AWI-CM-1 model’s free-running simulations with historical scenario, from which the storylines are branched off.

Thermodynamical changes

Changes in precipitation, air and sea surface temperature, and vertical wind velocity, are calculated as the difference between the 5-member ensemble mean storyline simulations (in preindustrial, present-day, or 4 °C warmer climates). Relative changes, given in %, are all with respect to absolute values from present-day simulations. Changes in precipitation are additionally scaled with the local 2-m air temperature changes, to compare to the expected Clausius-Clapeyron precipitation scaling.

Spatially-integrated quantities

We define a broad event region enclosed within 11–25°E, 46–54°N to quantify large-scale changes in the event’s intensity. Geographic boundaries for the region are derived from the observed distribution of precipitation, following a similar approach to the WWA 31. We additionally use a 100 mm threshold for total precipitation as an indicator of areas undergoing severe rainfall in each storyline simulation (in preindustrial, present-day, or 4 °C warmer climates). The total area experiencing more than 100 mm of rain is calculated at the sum of the grid area for each grid cell identified over the threshold. The relative changes, given in %, are all with respect to the area from present-day simulations.

Confidence level

We calculate the statistical significance of changes in our simulations with a two-sided Wilcoxon test. The test is applied to the two 5-member storyline ensembles being compared (i.e., present-day against preindustrial storylines or +4 °C against present-day storylines). For reference, a complete separation of 5-member ensembles between two climates corresponds to a p value of 0.008, i.e., a confidence level above 99%, and is therefore highly significant.

Data availability

Data from the AWI-CM-1-1-MR free runs are available in the Earth System Grid Federation (ESGF) data nodes ( https://esgf-data.dkrz.de/search/cmip6-dkrz/). The nudged storyline simulations are stored in the supercomputer Levante from DKRZ and are available on Zenodo ( https://doi.org/10.5281/zenodo.14034062). ERA5 reanalysis data used in this study can be accessed from the European Centre for Medium-Range Weather Forecasts (ECMWF; https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5).

Code availability

The source code for the coupled FESOM v.1.4 model that is used in AWI-CM-1-1-MR is the same as in ref. 20, 21, and available online (Zenodo, https://doi.org/10.5281/zenodo.10401309). For the source code of ECHAM6, registration on the MPI-ESM user page is required ( http://www.mpimet.mpg.de/en/science/models/license/).

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Acknowledgements

This work was supported by the Helmholtz Research Field Earth & Environment for the Innovation Pool Project SCENIC. All simulations were performed at the German Climate Computing Center (DKRZ) using ESM Tools 44 and resources from the ba1264 and bk1099 projects. We thank Stefan Pinkernell for the assistance with the webtool ( https://climate-storylines.awi.de), and Angelika Heil for making the ERA5 initial release data available at DKRZ.

Funding

Open Access funding enabled and organized by Projekt DEAL.

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Communications Earth & Environment thanks Damián Insua-Costa and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Heike Langenberg. A peer review file is available.

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Athanase, M., Sánchez-Benítez, A., Monfort, E. et al. How climate change intensified storm Boris’ extreme rainfall, revealed by near-real-time storylines. Commun Earth Environ 5, 676 (2024). https://doi.org/10.1038/s43247-024-01847-0

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DOI: https://doi.org/10.1038/s43247-024-01847-0