The research addresses a fundamental blind spot in climate science. Climate models can simulate unprecedented extremes, and techniques such as ensemble boosting can efficiently generate large samples of record-shattering events. But because such events have no historical analogue, it has been unclear whether the simulations are physically credible or merely artefacts of model quirks. The 2021 Pacific Northwest heatwave, which broke previous records by almost 5 K, demonstrated that the real world can deliver events that models and records suggested were nearly impossible. Roemer and his team set out to test whether simulated month-long Western European heatwaves of comparable severity pass the credibility test.

To do this, the researchers built their assessment on three criteria: conformity with physical principles, internal consistency, and historical precedent. Rather than relying solely on statistical tests such as extreme value theory, they took a process-based approach, examining the actual physical machinery behind each simulated heatwave. Their benchmark events came from ensemble boosting simulations with the CESM2 climate model, in which a run is re-initialised a few weeks before an extreme event and restarted hundreds of times with tiny perturbations, generating thousands of alternative versions of the same weather situation. From these simulations they identified twenty unprecedented heatwaves whose 30-day mean temperature anomalies over Western Europe exceeded the most extreme event in the reanalysis record, the legendary heatwave of June and July 1976.

A central methodological innovation was the use of standardised anomalies relative to a time-evolving climatology. Because the simulated heatwaves occur in a warmer future climate while the historical comparison events occurred decades ago, comparing raw temperatures would be meaningless. Instead, the team expressed every variable, from temperature and geopotential height to soil moisture and surface heat fluxes, as an anomaly measured against the mean and variability of the background climate in which the event unfolds, using a centred 31-year window. This allowed a like-for-like comparison of the physical drivers of unprecedented simulated heatwaves with those of historical events in the ERA5 reanalysis.

The results are striking in their overall consistency. The unprecedented heatwaves are driven by the same well-known culprits as historical ones: strong blocking anticyclones over Central Europe, weak zonal winds, abundant surface solar radiation, and parched soils. The anomalies of these drivers are more intense in magnitude, but their spatial patterns and their relationships with one another closely mirror those seen in historical heatwaves. In the authors’ framing, these events are caused by extreme anomalies of common drivers rather than by any exotic new mechanism, a finding that strongly supports their physical plausibility.

The team went further, testing whether the temperature anomalies of the unprecedented heatwaves could be inferred from a simple multilinear statistical model using five predictors: geopotential height, zonal and meridional winds, soil moisture, and surface solar radiation. Remarkably, models trained on both the climate model’s own large ensemble and on historical heatwaves in the reanalysis could explain most of the variance in temperature anomalies, and they inferred the magnitudes of the unprecedented events with accuracies similar to those achieved for training data. Even the anomalies of daily minimum temperatures, which lie far beyond anything in the observational record, were reasonably captured. This suggests that the linear combination of familiar drivers holds together even deep in the tail of the distribution, an important internal consistency check that many had feared would fail.

Yet the study is not a clean bill of health. Digging into the temporal substructure of the events, the researchers uncovered substantial discrepancies between the simulated unprecedented heatwaves and their historical counterparts. CESM2 systematically underestimates the frequency and persistence of atmospheric blocking, the stubborn high-pressure systems that park over Europe and bake it for weeks. At the same time, it overestimates the drying of soils and the persistence of soil moisture deficits, amplifying land-atmosphere feedbacks. A temperature budget analysis at the 850 hPa level confirmed the pattern: simulated unprecedented heatwaves rely more on diabatic heating and less on adiabatic warming from subsiding air than historical events do. In the authors’ blunt assessment, the simulated heatwaves occur for partly the wrong reasons.

Counterintuitively, these biases may actually make the study’s conclusion more alarming rather than less. Because CESM2 underestimates the persistence of blocking, the fact that it still produces month-long heatwaves exceeding records by more than 5 K suggests that the simulated events may be a conservative estimate of what the real world could deliver. The return periods of the simulated heatwaves range from roughly 300 years to more than 6000 years, finite but far beyond a human lifetime, placing them firmly in the category of events that are statistically possible but not probable. Plausibility, the authors emphasise, sits between possibility and probability, and it is plausibility that should guide disaster preparedness, since preparing for credible worst cases is what stress-testing infrastructure is all about.

The researchers are careful about the limits of their findings. Their assessment refers primarily to standardised anomalies rather than absolute temperatures, meaning that impact studies, which typically depend on absolute thresholds such as hospital-triggering temperature limits, still require bias correction of raw model output. Surface variables such as soil moisture and heat fluxes carry substantial uncertainties in both climate models and reanalysis, and reanalysis values of the surface energy budget should not be treated as ground truth. The analysis also rests on a single climate model, and the authors call for similar evaluations with other models to test how dependent the conclusions are on CESM2’s particular strengths and weaknesses.

Western Europe is arguably the most urgent test case for this kind of work. Mean summer temperatures and extreme heat there are rising faster than in almost any other region, driven by anthropogenic warming, declining aerosol emissions, and circulation changes, and the region has been hammered by record-breaking heat in 2003, 2006, 2015, 2018, 2019, 2022, 2025, and 2026. Long-lasting heatwaves are especially deadly, as the excess mortality of the 2003 and 2010 European events demonstrated. The new framework, which the authors argue can be adapted to other extremes such as cold spells and droughts, offers decision-makers a way to distinguish between model-generated scare stories and credible worst-case scenarios. On the evidence of this study, a month-long, record-shattering European heatwave belongs firmly in the second category, and adaptation planners would be wise to plan for it.

Subject of Research: Process-based plausibility assessment of unprecedented month-long heatwaves in Western Europe using climate model storylines

Article Title: Assessing the plausibility of unprecedented events: a process-based approach applied to month-long heatwaves in Western Europe

Article References: Roemer, F. E., Fischer, E. M., Noyelle, R., & Knutti, R. (2026). Assessing the plausibility of unprecedented events: a process-based approach applied to month-long heatwaves in Western Europe. Weather and Climate Dynamics, 7(3), 1919-1949. https://doi.org/10.5194/wcd-7-1919-2026

Image Credits: AI Generated

DOI: 10.5194/wcd-7-1919-2026

Keywords: heatwaves, Western Europe, climate models, ensemble boosting, atmospheric blocking, soil moisture, land-atmosphere feedback, plausibility, climate storylines, extreme events, CESM2, adaptation planning