The traditional approach to extreme event analysis treats the occurrence of a flood, storm, or drought as a random variable described by a probability distribution fitted to historical observations. Design values for infrastructure are extrapolated from the tail of that distribution, often corresponding to magnitudes that have never actually been recorded. A 100-year event, for instance, is expected on average to occur once every 100 years, carrying an annual exceedance probability of 0.01. But as the authors emphasize, this framework rests on the natural variability of the climate and on assumptions of stationarity that are increasingly strained in a warming world, where hazards such as flooding, storms, and droughts are becoming more frequent and severe while urban exposure continues to grow.

The core of the new analysis is a simple but powerful reframing. In engineering, reliability is defined as the probability that a system remains in a satisfactory state over its lifetime. For a system designed around a T-year event over a lifespan of N years, the reliability is calculated as the probability that the design event never occurs during that period. The authors invert this familiar formula: instead of asking whether a structure will survive, they ask whether the T-year event itself is likely to appear in a dataset of observations or simulations spanning N years. The complement of the engineering reliability—the probability of observing the event of interest at least once—becomes a quantitative measure of confidence in the data itself.

Expressed as a function of the ratio between the return period T and the dataset length N, this observation probability converges, as the dataset grows large, to a Poisson distribution. The elegance of the Poisson approximation is that it is independent of the underlying distribution used to model the phenomenon, making it a broadly applicable yardstick. The authors caution, however, that the approximation breaks down for very small datasets, those shorter than roughly 30 years, and for return periods vastly exceeding the record length. Within its valid range, the metric delivers strikingly counterintuitive results that challenge how the rarity of extremes is commonly interpreted.

The most arresting finding concerns the case where the return period equals the length of the record. When N equals T, the probability of having observed the event of interest is always 0.63, regardless of the absolute magnitudes involved. The chance of seeing a 30-year event in 30 years of data is identical to the chance of seeing a 1000-year event in 1000 years of data. This invariance means that the extreme character of an event should be judged not in absolute terms but relative to the length of the observations or simulations used to derive it. A 100-year event estimated from 50 years of observations carries only about a 0.40 probability of having been captured in the record at all, and that figure drops to 0.26 when only 30 years of data are available—precisely the range of most instrumental records worldwide.

These numbers matter because recorded observations typically span only 30 to 50 years, meaning that inferences about 100-year or rarer events almost always lie outside the range of the data and depend heavily on the chosen statistical model. History shows how unprepared societies can be for events beyond their records: the 1953 storm surge flood in the Netherlands reshaped that country’s entire flood management system precisely because it exceeded what past experience had suggested was possible. The authors argue that preparedness must go beyond historical events, accepting that the past may not be a reliable guide to the future in a nonstationary climate, and that unexpected events are intrinsic to nonlinear, dynamic systems.

One promising response to the scarcity of observations is the use of large ensembles—many climate model simulations run under identical forcing conditions, each producing a different physically plausible realization of weather. Large ensembles allow researchers to sample internal climate variability far beyond what the observational record permits, and they have already demonstrated their value. Ensemble boosting techniques generated plausible storylines of a heatwave hotter than the unprecedented Pacific Northwest event of late June 2021, an event that was essentially unpredictable from observations alone. Conditional probability approaches have since shown promise in assigning return periods to such extreme simulated events, and studies using large ensembles have flagged high risks of unprecedented rainfall in the current climate.

Yet the authors issue a clear warning against overconfidence in these tools. Ensemble members are generated by climate models validated against observations, meaning their credibility derives from matching the statistical properties of the very records whose limitations the ensembles are meant to overcome. The apparent reduction in uncertainty comes simply from having more events to count, not necessarily from better estimates. Capturing internal variability in climate models is harder than capturing their response to external forcings, the computational demands of large ensembles are substantial, and validating their representativeness is not always feasible. Crucially, the reliability framework shows that the probability of simulating an event whose return period equals the dataset length remains 0.63 no matter how large the ensemble grows—more data does not dissolve this fundamental constraint.

The authors also dismantle the hope that large ensembles could eliminate statistical extrapolation altogether. Because the severity of an event is defined by its frequency of exceedance, some form of extrapolation—parametric or nonparametric—is unavoidable. Nonparametric plotting positions involve empirical interpolation whose results vary depending on the method chosen, while order statistics reveal that the return period of the single largest event in a dataset is formally undefined, tending to infinity. The link between event frequency and the definition of an extreme cannot be severed. Under nonstationarity, the classical formulas no longer hold because exceedance probabilities change from year to year; some researchers have proposed time-varying return periods, while others recommend abandoning return periods in favor of reliability-based design, fixing a desired reliability level within a project horizon and deriving design values numerically.

The broader message is one of calibrated humility. Return periods are often perceived as certain estimates, but attaching a reliability level to every inferred extreme would give decision-makers an honest measure of confidence and encourage critical use of available resources, whether observational or model-based. Large ensembles remain extremely valuable for compensating for limited observations, but they should be deployed with caution to avoid a false sense of security rooted in modeling assumptions and biases. As climate extremes intensify and exposure grows, the study suggests that the most dangerous illusion in disaster risk science may be the belief that our numbers about rare events are more solid than the data behind them.

Subject of Research: Reliability of estimated return periods for climate extremes based on observational and simulated dataset length

Article Title: On the Reliability of Estimated Return Periods for Climate Extremes

Article References: Ragno, E., & AghaKouchak, A. (2026). On the Reliability of Estimated Return Periods for Climate Extremes. International Journal of Disaster Risk Science. https://doi.org/10.1007/s13753-026-00764-4

Image Credits: AI Generated

DOI: 10.1007/s13753-026-00764-4

Keywords: return period, climate extremes, reliability, large ensembles, Poisson distribution, nonstationarity, risk assessment, statistical extrapolation, climate adaptation, disaster risk science, Estimated, Return

The underlying topic is important because returning to paid employment after a stroke is not determined solely by whether a person can walk, speak or perform a standard clinical task. Stroke can affect attention, information processing, movement, communication, mood and the ability to sustain effort over time. Fatigue adds another layer of difficulty. Post-stroke fatigue is commonly understood as a persistent or disproportionate feeling of exhaustion that can reduce physical, cognitive or emotional capacity, sometimes without an obvious increase in workload. It may fluctuate during the day and can become more apparent when a survivor resumes activities that require prolonged concentration or multitasking. In a workplace, that distinction matters. A person may appear able to complete a task briefly yet struggle to maintain the same performance across a full shift, recover between shifts or manage unexpected demands. The article’s title frames this return not as a simple recovery milestone but as an occupational adaptation process, in which people and workplaces must adjust activities, routines and expectations to accommodate changing capacity.

Occupational adaptation is a technical concept used in rehabilitation and occupational therapy to describe how people respond to demands in their everyday environments. “Occupation” in this context does not mean only a job; it includes meaningful activities and roles, such as household responsibilities, social participation and employment. After a stroke, adaptation can involve changing how a task is performed, modifying the environment, redistributing responsibilities or developing strategies that reduce the impact of impaired stamina. At work, examples might include taking planned recovery periods, reducing interruptions, simplifying sequences of actions, using written prompts or gradually increasing hours. These examples are general rehabilitation approaches, not results reported by the correction itself. The central point is that work capacity is relational: it emerges from the interaction between an individual’s abilities and the demands, pace, predictability and supportiveness of a particular job. Two people with similar clinical impairments may therefore experience very different barriers when attempting to return to employment.

Fatigue is especially difficult to assess because it is partly subjective and does not always correspond neatly to visible impairment. Conventional neurological examinations can document strength, coordination or language, but they may not capture the effort required to maintain attention, suppress distractions or switch between tasks. A worker may compensate effectively during a brief assessment while using substantial mental energy to do so. Later, that hidden cost can appear as slowed performance, mistakes, reduced communication or a need for extended recovery. Fatigue can also interact with sleep disturbance, pain, depression, anxiety, medication effects and the neurological consequences of the stroke. These factors can reinforce one another, making it challenging to identify a single cause or a universal remedy. For occupational rehabilitation, the practical implication is that assessment should consider patterns over time and in real activities, not only performance at one moment. A return-to-work plan may need to account for both what a worker can do and how long that ability can be sustained safely and consistently.

The corrected publication does not provide a new set of clinical recommendations, and it does not report a new analysis of stroke-related fatigue. Its purpose is narrower but still consequential: to repair the public research record. Funding disclosures are part of that record because they allow readers to understand how a study was supported and whether sponsors had a role in decisions that could influence the work. In this case, the corrected statement explicitly separates financial support from scientific control. The listed organizations provided funding, while the notice says they had no involvement in design, data collection, analysis, publication decisions or writing. That distinction does not prove that a study is correct, nor does a funding declaration replace independent scrutiny. It does, however, give readers a clearer basis for assessing the article alongside its methods, evidence and limitations. Corrections of this kind are therefore not merely administrative updates; they help preserve the accuracy and transparency on which cumulative science depends.

The article was authored by Jessica Vollertsen, Mathilda Björk, Anna-Karin Norlin and Elin Ekbladh, with affiliations at Linköping University in Sweden. Vollertsen is associated with the university’s Department of Rehabilitation and Department of Health, Medicine and Caring Sciences in Motala. Björk and Norlin are affiliated with the Pain and Rehabilitation Center and the Department of Health, Medicine and Caring Sciences in Linköping, while Ekbladh is affiliated with the Department of Health, Medicine and Caring Sciences. The study’s placement in an occupational therapy journal reflects the need to connect neurological recovery with the practical realities of daily work. Clinical rehabilitation can improve movement, communication or cognitive function, but employment also depends on workplace schedules, task design, social expectations and the availability of adjustments. A person may need coordination among stroke specialists, occupational therapists, employers, human-resources staff and the worker themselves. Such coordination is most effective when fatigue is treated as a legitimate functional issue rather than as a lack of motivation or evidence that recovery has failed.

For employers, the subject raises questions about how work is organized and how performance is evaluated. A gradual return may involve fewer hours, lighter workloads or a staged increase in complexity, but the appropriate arrangement depends on the job and the person’s recovery. Flexibility can be particularly important when fatigue varies unpredictably or when cognitive tasks are more demanding than physical ones. A quiet workspace, reduced multitasking, predictable scheduling or additional time for complex instructions may change the energy cost of work without removing the essential role. These adjustments should be developed collaboratively and reviewed as circumstances change. They should also be distinguished from assumptions that every stroke survivor has the same limitations. Some people return to their previous work, some change roles, and some cannot return to paid employment. The corrected study record cannot establish how common any particular outcome is, because the correction reports no new outcome data. What it does is keep attention on a problem that can be overlooked when recovery is judged only by visible physical function.

The correction also points to a broader lesson for research on long-term disability: accurate scientific communication includes both substantive findings and the administrative details surrounding them. The original article remains identified by its own publication DOI, 10.1080/11038128.2026.2613621, while the correction has a separate canonical DOI, 10.1007/s44474-026-00005-3. The notice makes clear that the funding statement was the element that required amendment. Readers consulting the article should therefore distinguish the correction from a new investigation and avoid treating the updated notice as evidence of a newly discovered medical effect. The research question remains focused on fatigue and the complex process of adapting work after stroke. By correcting the disclosure, the journal provides a more complete account of the study’s provenance while leaving interpretation to the evidence reported in the original article. For survivors and clinicians, the enduring message is that a successful return to work may require attention to invisible fatigue, task demands and workplace adaptation alongside conventional measures of neurological recovery.

Publication corrections serve an important role in maintaining a reliable scientific record because they distinguish an error in the published article from a change in the underlying research. In this case, the journal’s notice identifies the funding statement as the specific element requiring amendment. That narrow scope matters when readers interpret the correction: the notice should be read as an update to the article’s disclosure information, not as a report of additional participants, revised measurements or a new clinical conclusion. The corrected record also preserves the connection between the notice and the earlier study by naming the original article and its authors.

The funding information places the work within a Swedish rehabilitation and occupational-health research setting. Support came from organizations with interests spanning insurance, regional health services, stroke advocacy and occupational or social concerns, while the statement explicitly records that the funders did not participate in the scientific or editorial stages listed by the authors. Such disclosures help readers separate a study’s financial provenance from its operational independence. They are also useful for indexing and archiving: future readers who encounter the original publication can identify why a later notice exists and which portion of the record has been amended.

The correction is openly accessible under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence. This permits non-commercial reuse with appropriate credit, but it does not authorize distribution of adapted material derived from the article. The notice also cautions that some images or other third-party material may have separate rights if they are excluded from the article’s licence. These conditions are relevant when research findings are shared in educational, clinical or public settings, where reproducing the text or figures may involve permissions beyond simply linking to the publication.

The author affiliations further show the interdisciplinary setting in which the work was produced, combining rehabilitation, health and caring sciences with a pain and rehabilitation centre at Linköping University. That institutional context is consistent with a research focus on how health changes affect participation in everyday roles. It also underscores why a correction about funding, although administrative in form, belongs alongside the scholarly record: transparent reporting helps readers evaluate the provenance of research that may inform rehabilitation practice, workplace discussions and future studies of employment after stroke.

Subject of Research: Workplace adaptation and fatigue after stroke

Article Title: Correction to: Return to Work with Fatigue After Stroke: A Complex Occupational Adaptation Process

Article References: Vollertsen, J., Björk, M., Norlin, A.-K., & Ekbladh, E. (2026). Correction to: Return to Work with Fatigue After Stroke: A Complex Occupational Adaptation Process. Scandinavian Journal of Occupational Therapy, 33(1), Article 4. https://doi.org/10.1007/s44474-026-00005-3

Image Credits: AI Generated

DOI: 10.1007/s44474-026-00005-3

Keywords: stroke recovery, post-stroke fatigue, return to work, occupational therapy, occupational adaptation, rehabilitation, workplace accommodations, research transparency, Correction, Return, Work, Fatigue