The authors, led by Jeffery R. L. Pendleton of the Department of Psychology at Cambridge, together with Paul W. Pritchard, David Wilkinson, Clive Wilkins, and Nicola S. Clayton, contend that climate futures gain practical force only when they become mentally constructible, narratively scaffolded, socially stabilized, and culturally legitimated. In other words, a model may describe a future in precise technical terms, but action still depends on whether an institution can think with it, rehearse it, challenge it, and connect it to decisions. The paper, a Perspective article in the journal’s Reason and Decision-Making section, does not dismiss probability; rather, it treats plausibility as a distinct layer of the decision process encompassing the cognitive and institutional conditions under which a possible future becomes available for coordinated judgement.

Deep uncertainty unsettles the comfortable assumption that better data and more elaborate models will, by themselves, improve climate-risk judgement. Nonlinear change, path dependence, tipping dynamics, spatial unevenness, and decades-long horizons make future outcomes hard to picture concretely and harder still to hold within shared institutional understanding. Climate-related financial risk illustrates the point starkly. Disclosure-led approaches remain constrained by radical uncertainty, and conventional risk-management frameworks confront model uncertainty and broader systemic uncertainty in settings where stable historical analogs are absent. A growing body of finance and risk literature indicates that increasing model complexity can create false precision and narrow the recognized range of futures, leaving plausible harms underappreciated precisely when severe uncertainty demands the widest possible field of view.

The Bank for International Settlements’ Green Swan report argues that climate change is creating an epistemological break for financial stability analysis, because nonlinear dynamics and endogenous feedbacks strain widely used methods, especially in analyses of catastrophic tail events. Research on euro area banks and carbon-price sensitivity makes a related point. Historical data retain value, but their regularities now provide a weaker guide than conventional risk architectures tend to assume. The authors argue that scenario design is therefore a question of epistemic discipline as well as technical sophistication: its aim should be to widen the space of plausible futures for structured testing under an explicit account of deep uncertainty, not to compress uncertainty into a single spurious estimate.

At the heart of the framework lies a striking claim about the architecture of future thought. Remembering the past and imagining the future engage overlapping constructive and reconstructive processes, recruiting the hippocampus, medial prefrontal cortex, posterior cingulate cortex, and related regions of the default mode network, through which stored experience, semantic knowledge, current goals, and situational demands are recombined into possible events and trajectories. From this perspective, memory serves as a resource for simulation, evaluation, anticipation, and preparation. The concept of mental time travel, introduced to mark the continuity between recollection and prospection, suggests that episodic memory evolved with the future in mind. Human future thought combines computation with a phenomenological experience resembling the remembering of prospective events, with fragments of prior experience furnishing the structure of scenes available for advance inspection.

Crucially, constructive simulation can remain useful even when historical experience lacks a close analog, because its generative process recombines episodic elements with semantic knowledge, model outputs, current goals, and externally represented causal constraints to form novel event wholes. The epistemological break described in climate-risk analysis weakens straightforward extrapolation from the past, yet memory retains its relevance through the components and organizing structures supplied by past experience. Climate science and scenario narratives extend the available relations and constraints, and durable external records keep this material available for recombination through what the authors call transpersonal extended mental time travel, through which individual future thinking is extended across people and generations by cultural and technological artifacts, shared narratives, communication, and durable external records. Source monitoring supplies one safeguard by keeping the origins of a simulation’s components inspectable, helping preserve the distinction between coherence and evidential support.

The framework identifies four interacting conditions that may support the transition from probabilistic abstraction to usable anticipation. Constructive simulation integrates abstract information into event-based mental representations that decision-makers can inspect and pre-experience. Narrative scaffolding provides the temporal sequences and causal structure needed to navigate thresholds, nonlinear changes, and cascading effects. Social stabilization, through repeated collective rehearsal and strategic conversation, may move individual prospection into shared representations. Cultural legitimation influences whether scenarios remain legible within the identities, values, mandates, and local knowledge of the receiving institution. Across these stages, the authors propose simulational fluency — the experienced ease with which an individual constructs and maintains a possible future as an ordered event representation — as one candidate individual-level pathway through which scenario form may influence judged plausibility.

The psychology of magic provides a mechanistically informative illustration of how prediction, attention, expectation, inference, and reconstructive memory interact under controlled violations of expectation. An audience can miss a sleight-of-hand effect because perception follows the expected sequence, a well-studied result in the field. In the framework proposed here, this work supplies an analogy and a testable hypothesis for climate governance, where familiar scenario architectures may direct attention away from discontinuities. Coherent priors can preserve an incorrect interpretation by suppressing anomalous information, and illusions are useful precisely because they make cognitive blind spots visible. The same mechanisms that allow scenario work to sharpen judgement also carry an epistemic risk, because vividness and truth are different properties: transportation into narrative can influence belief, and ease of processing can influence perceived truth, meaning that repetition and fluent imagining can confer a separate sense of coherence distinct from evidential support.

On quantification, the authors are equally precise. An IFRS Foundation staff paper reproducing TCFD guidance identifies a clear narrative of drivers, pathways, constraints, and outcomes as a prerequisite for effective quantification, warning that a rush to quantification may serve only to put an ever-finer point on an ineffective tool. Numbers attached to a weak scenario can create the appearance of control and leave understanding unchanged; numbers attached to an intelligible pathway can deepen analysis and make comparison more rigorous. Formal methods still have an important role: belief-function approaches such as Dempster–Shafer theory preserve distinctions among belief, plausibility, and uncertainty when evidence is incomplete, while robust Bayesian and imprecise Bayesian approaches can support disciplined updating while keeping uncertainty about priors, utilities, and model structure in view. The central issue concerns sequencing, with scenario narrative and quantification working best when they develop together in a mutually constraining way.

The framework also extends from persons to institutions through distributed coordination of prospective representations across people, artifacts, routines, and decision rights. Institutions set the bounds of what futures can be discussed and what uncertainties can be recognized, and those bounds determine which pathways gain enough shared recognition to guide coordinated action. Because social stabilization can reproduce blind spots established by professional norms and reinforced by political culture, the authors recommend that scenario governance record which pathways, assumptions, stakeholders, and forms of evidence are excluded; preserve reasoned dissent and minority scenarios; broaden or rotate participation; and periodically subject scenario sets and decision rules to independent challenge. Pierre Wack, reflecting on early Shell scenario work, argued that the task was to influence the microcosms through which decision-makers pictured reality, since a scenario package alone would be like water on a stone without that shift in mental image. That observation anticipates the challenge developed in this article: scenario work succeeds when it changes how futures are imagined and discussed inside institutions, and adding another report to the archive seldom achieves that shift.

Several design principles follow from the framework. Scenario exercises should build causal pathways before intensive quantification; make thresholds, feedbacks, and transmission mechanisms explicit; include enough contextual detail for decision-makers to mentally navigate the pathway; test whether neglected futures remain cognitively available during later deliberation; involve users early so scenarios become socially shared; and preserve multiple plausible futures together with the uncertainty they represent. Future research can manipulate causal sequencing and contextual detail within scenario exercises, then examine how collective rehearsal and evidential safeguards alter later access and use, with simulational fluency assessed through reported construction ease and construction latency. By bridging cognitive psychology, comparative cognition, scenario planning, and climate-risk governance, the framework offers a structured approach grounded in the fundamental evolutionary premise that memory evolved with the future in mind. Navigating the radical uncertainty of climate change depends on precise calculation and the capacity of minds and institutions to inhabit possible futures cognitively — keeping uncertainty explicit and judgement both revisable and answerable to evidence.

Subject of Research: From probability to plausibility in climate-risk scenarios: a cognitive framework for decision-making under deep uncertainty

Article Title: From probability to plausibility in climate-risk scenarios: a cognitive framework for decision-making under deep uncertainty

Article References: Pendleton, J. R. L., Pritchard, P. W., Wilkinson, D., Wilkins, C., & Clayton, N. S. (2026). From probability to plausibility in climate-risk scenarios: a cognitive framework for decision-making under deep uncertainty. Frontiers in Cognition, 5, Article 1928401. https://doi.org/10.3389/fcogn.2026.1928401

Image Credits: AI Generated

DOI: 10.3389/fcogn.2026.1928401

Keywords: probability, plausibility, climate-risk, scenarios, cognitive, framework, decision-making, under, deep, uncertainty, scientific research