This session invites presentations by individuals and teams on communicating scientific uncertainty to non-expert audiences, addressing topics such as:
(1) Innovative and practical tools (e.g. from social or statistical research) for communicating uncertainty
(2) Pitfalls, challenges and solutions to communicating uncertainty with non-experts
(3) Communicating uncertainty in risk and crisis situations (e.g., natural hazards, climate change, public health crises)
Examples of research fitting into the categories above include a) new, creative ways to visualize different aspects of uncertainty, b) new frameworks to communicate the level of confidence associated with research, c) testing the effectiveness of existing tools and frameworks, such as the categories of “confidence” used in expert reports (e.g., IPCC), or d) research addressing the challenges of communicating high-uncertainty high-impact events.
This session encourages you to share your work and join a community of practice to inform and advance the effective communication of uncertainty in earth and space science.
Uncertainty is an inherent part of geoscience research and arises at multiple stages of the scientific process, from data collection and modelling to analysis and interpretation. In recent years, growing attention has been devoted to uncertainty quantification and assessment, alongside increasing recognition of the importance of uncertainty communication. These aspects are closely linked, as robust characterization of uncertainty provides an essential basis for transparent communication within the scientific community and beyond it.
Communicating uncertainty not only plays a key role in improving the understanding of how scientific knowledge is produced, but can also help to foster trust by increasing transparency and contextualizing results. Nevertheless, reluctance to explicitly assess and communicate uncertainty persists, particularly when addressing non-expert audiences. This challenge is especially relevant in the context of natural hazard risk assessment and management: Here, adequate communication of uncertainties can add particularly valuable information for decision-making, risk governance, and a better understanding of the risks at hand among public audiences.
This contribution presents an exploratory, database-driven overview of the scientific literature on uncertainty communication in geoscience, with a particular focus on natural hazards. Using structured queries in the Web of Science database, we examine publication trends over time, disciplinary distributions, thematic emphases, and possible blind spots. Keyword combinations range from general terms such as “uncertainty communication” and “multi-hazard communication” to more specific queries combining uncertainty, communication, and individual natural hazards (e.g., floods, earthquakes, droughts).
Preliminary results indicate that uncertainty communication spans a broad range of scientific categories, while the level of attention varies substantially across hazard types, with flood-related studies being more prominent than others. Initial findings also suggest that multi-hazard uncertainty communication remains comparatively underrepresented, despite the increasing emphasis on multi-hazard and multi-risk assessments in recent research and policy frameworks. The growing volume of publications further highlights the need for systematic approaches to literature mapping, as well as the potential role of data-driven and AI-assisted tools in supporting such analyses.
This research was partially funded by the European Civil Protection and Humanitarian Aid Operations (ECHO) of the European Commission (EC) through the VOLCAN project (ref. 101193100) and by the 2024 Research Prize of the Dr. K. H. Eberle Foundation to Mohadjer, Pelzer and Dietrich.
How to cite: Schneider-Pérez, I., López-Saavedra, M., Martí, J., Castellà, J., Mohadjer, S., Pelzer, M., and Dietrich, P.: An overview of the scientific literature on uncertainty communication in geoscience , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11747, https://doi.org/10.5194/egusphere-egu26-11747, 2026.
It is well known that scientific data have uncertainties and that it is crucial to take these uncertainties into account in any decision making process. Nevertheless, despite data producer’s best efforts to provide complete and rigorous uncertainty estimates alongside their data, users commonly struggle to make sense of uncertainty information. This is because uncertainties are usually expressed as the statistical spread in the observations (for example, as random error standard deviation), which does not relate to the intended use of the data.
Put simply, data and their uncertainty are usually expressed as something like “x plus/minus y”, which does not answer the really important question: How much can I trust “x”, or any use of or decision based upon “x”? Consequently, uncertainties are often either ignored altogether and the data taken at face value, or interpreted by experts (or non-experts) heuristically to arrive at rather subjective, qualitative judgements of the confidence they can have in the data.
In line with existing practices (e.g., the communication of uncertianties in the IPCC reports), we conjecture that the key to enabling users to make sense of uncertainties is to represent them as the confidence one can have in whatever event one is interested in, given the available data and their uncertainty.
To that end, we propose a novel, generic framework that transforms common uncertaintiy representations (i.e., estimates of stochastic data properties, such as “the state of this variable is “x plus/minus y”) into more meaningful, actionable information that actually relate to their intended use, (i.e., statements such as “the data and their uncertainties suggest that we can be “z” % confident that…”). This is done by first formulating a meaningful question that links the available data to some events of interest, and then deriving quantiative estimates for the confidence in the occurrence of these events using Bayes theorem.
We demonstrate this framework using two case examples: (i) using satellte soil moisture retrievals and their uncertainty to derive how confident one can be in the presence and severity of a drought; and (ii) how ocean temperature analyses and their uncertainty can be used to determine how confident one can be that prevailing conditions are likely to cause coral bleaching.
How to cite: Gruber, A., Bulgin, C., Dorigo, W., Emburry, O., Formanek, M., Merchant, C., Mittaz, J., Muñoz-Sabater, J., Pöppl, F., Povey, A., and Wagner, W.: Making Sense of Uncertainties: Ask the Right Question, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7755, https://doi.org/10.5194/egusphere-egu26-7755, 2026.
Uncertainty is a defining feature of the nature of science; besides driving curiosity in research, its acknowledgement and reporting are expected to ensure transparency and credibility. However, when science is communicated to a non-expert audience, uncertainty often gets oversimplified or omitted. This practice can lead to misconceptions about science (e.g., science leads to absolute knowledge) or erode confidence when uncertainties inevitably surface. In this session, we will explore how uncertainty is framed within the Nature of Science framework of science education, and which educational strategies might be of interest for science communication. Drawing on examples from communicating planetary science, we will discuss approaches that can make uncertainty relatable and constructive, helping audiences appreciate science as a dynamic, evidence-based process rather than a collection of fixed facts.
How to cite: Stepanovic, J., Claes, S., and Sermeus, J.: Communicating the Uncertain Nature of Science Through the Lens of Science Education, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17550, https://doi.org/10.5194/egusphere-egu26-17550, 2026.
Climate change is an ongoing environmental and societal challenge. Communicating its ramifications and related uncertainties clearly to stakeholders and the public is an imperative task for time-critical decision-making. Public communication about climate change often includes maps, aimed at facilitating the understanding of complex scientific findings and making these more accessible to non-specialist audiences. This is especially important when difficult concepts such as inherent uncertainties related to climate predictions are involved.
While climate change communication may appear abstract and distant to non-experts, climate change discourse often involves strong emotional responses from the public. Engaging visual storytelling with climate change maps may be a useful strategy to reduce the psychological distance of the public. However, elicited emotions may influence how people perceive the presented information and thus their willingness to trust the maps.
We aimed to investigate the effect of emotional narratives on map readers’ trust in visualized (un)certainty information in static climate change forecast maps. We applied a 3x2 mixed factorial, map-based study design, including electrodermal activity measurements and eye-tracking. We designed three versions of climate change prediction map stimuli, inspired by the Swiss Climate Scenarios CH2018. Uncertainty was operationalized as a within-subjects independent variable such that participants viewed 18 map stimuli in total, showing different climate variables in randomized order, equally distributed across three conditions: (1) without uncertainty information, (2) uncertainty visualized as black gridded dots, or (3) uncertainty visualized as black randomly distributed dots. Following prior research, we used the term ‘certainty’ in our map stimuli, as it is better understood by the audience than ‘uncertainty’. We used narrative instructions as the between-subjects independent variable, with participants randomly assigned and matched across groups to one of the two conditions: (1) emotion or (2) control. In the emotion condition, each map stimulus was accompanied by an emotion-inducing verbal narrative and a human cartoon character. In the control condition, participants viewed the same map stimuli accompanied only by a factual verbal narrative.
We recruited 61 participants (30 females, 31 males, average age = 30 years) from the Department of Geography at the University of Zurich to participate in the study. After viewing each map stimulus, participants were asked (without any time restriction) to select one of the six predefined locations shown in the maps that they predicted to be most/least affected by climate change. Finally, they indicated their trust in each stimulus type using a standardized questionnaire.
Preliminary results suggest no significant differences in participants’ overall average trust ratings across the two narrative conditions. However, participants significantly trust climate change prediction maps more when certainty information is also included, regardless of the narrative condition they were assigned to. Conversely, we found no significant difference in trust ratings between the map stimuli that contain certainty information visualized as gridded or randomly distributed dots.
These novel empirical findings stress the need to visually communicate (un)certainty information to support people’s trust in climate science and climate change forecast maps. The use of cartoon characters to emotionally engage the public in climate change communication remains to be further empirically investigated.
How to cite: Bazzurri, S. F., Kapaj, A., and Fabrikant, S. I.: Effects of emotional narratives and uncertainty visualization on non-experts’ trust in climate change forecast maps, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2979, https://doi.org/10.5194/egusphere-egu26-2979, 2026.
Heatwaves are among the most impactful climate extremes in Europe, driving acute health risks and socio-economic disruption. They are a challenge for early warning and public understanding due to uncertainties in event onset, severity, and human response. Building on the interdisciplinary Strengthening the Research Capacities for Extreme Weather Events in Romania (SCEWERO) project funded by the European Union, this study investigates how scientific evidence, perception data, and communication strategies interact within Romania’s heatwave Early Warning System operated by Meteo-Romania. We analyse both empirical perception data — collected through structured surveys and focus groups to quantify how different communities interpret heat warnings, risk levels, and confidence intervals — and observational heatwave metrics to map divergences between communicated risk and public understanding. This research highlights specific sources of uncertainty faced by forecasters (e.g., variable heat exposure, model forecast spreads), and documents how these uncertainties are interpreted or misinterpreted by non-expert audiences. By tracing how uncertainty in forecast signals propagates through institutional warning messages and into public perception, we identify communication gaps that can lead to maladaptive responses or reduced trust in warnings during heat events. Framing uncertainty, contextualised risk information, and tailored communication strategies improve both public comprehension and behavioural intent during heatwave alerts. We propose evidence-based recommendations for operational Early Warning Systems that move beyond fixed deterministic thresholds, instead incorporating probabilistic messaging where appropriate and grounding risk communication in locally derived perception data. This work illustrates how harmonising scientific uncertainty communication with Early Warning practices can strengthen societal resilience to heatwaves, offering a transferable framework for climate risk communication in other European regions.
How to cite: Santin, S., Croitoru, A.-E., Petrovici, N., Pop, C., Petre, M.-J., Scoccimarro, E., and Xoplaki, E.: Heatwaves and Early Warning Systems: Perception Data and the Role of Science Communication – A Case Study from Romania, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11821, https://doi.org/10.5194/egusphere-egu26-11821, 2026.
Climate information is increasingly being produced and shared as governments, businesses and individuals need to adapt to the changing climate. Yet, communicating uncertain climate change information to non-experts remains a challenge. The information that is currently made available to non-climate science specialists is too complex for them to understand and use. A key challenge in climate science is that estimating future change comes with uncertainties which are highly technical to non-climate specialists. Nevertheless, it is paramount that when climate information is shared and used, the limitations and uncertainties attached are well understood. This is particularly important amongst audiences that lack technical familiarity with climate science. Additionally, scientists and climate service providers do not have a common approach to represent the range of future change. Some scientists place an emphasis on probabilistic projections, meanwhile others focus on the full range of plausible futures.
There has been a limited effort to assess whether the audience understands what the producer of the climate information intended. Testing or evaluating different methods and visualisations of communicating future climate information, and its related uncertainties, can provide insight into what is most effective. Isolating what is (mis)understood can shed light on how to effectively communicate future climate information. This study investigates the interpretation of different presentations of future climate information using a survey and discussion with 45 participants working within weather and disaster agencies in Madagascar. Icon arrays, climate risk narratives, key statements and verbal probability language was tested to provide insight into how practitioners understand different ways of communicating future climate information. Both probabilistic and plausible framings of uncertainty are considered to explore how participants interpret each.
The percentage of participants that selected the correct answers across comprehension questions ranged from 24-82%. For the interpretation of verbal and numeric probabilities which was communicated as “virtually certain [99-100%]”, the correct numerical probability was selected by 24% of participants, highlighting the systematic misinterpretation of verbal and numerical probabilities. The climate risk narrative provided 3 plausible narratives, however, over a third of participants incorrectly believed there were 3 narratives to allow decision makers to select a narrative that is sector relevant. Some reasons for misinterpretation were provided by the participants such as confusing legends and icons, using their prior knowledge instead of the information document or experiencing cognitive dissonance. Meanwhile some expressed difficulty understanding due to lots of information while others requested additional insights, demonstrating the need for flexibility in design.
This study has highlighted new ways of communicating climate risk as well as ineffective current practises. Recommendations suggest that climate scientists and climate communicators should; include an explicit explanation of why there are multiple climate risk narratives; reconsider the use of numeric and verbal probability expression given they are commonly misinterpreted and consider that an individuals’ prior knowledge influences their interpretation of new information.
How to cite: Craig, A., James, R., Kennedy-Asser, A., Stephens, E., Vincent, K., Jones, R., Taylor, A., Jack, C., McClure, A., and Shaw, C.: Communicating uncertain future climate risk: Lessons learned from adaptation and disaster risk practitioners in Madagascar, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20429, https://doi.org/10.5194/egusphere-egu26-20429, 2026.
Informing robust decisions on flood risk and water resource management necessitates, among other factors, clearer communication of hydrological model uncertainty to non-specialist audiences. In this presentation, we demonstrate that simplified toy models, which abstract away systemic complexity, can serve as an accessible and effective tool for this purpose. As a specific case study, we illustrate how the choice of calibration scoring function shapes model behavior and associated uncertainty estimates. This foundational approach helps build the core intuition needed to effectively engage with more complex, real-world systems. Overall, we present a practical framework that supports experts articulate, and non-experts comprehend, the essential "why" and "how" of uncertainty in hydrological predictions.
Acknowledgements: This work was funded by the Research Center on Climate Change Impacts - University of Padova, Rovigo Campus - supported by Fondazione Cassa di Risparmio di Padova e Rovigo.
How to cite: Papacharalampous, G., Marra, F., Dallan, E., and Borga, M.: Communicating hydrological model calibration with toy examples, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5507, https://doi.org/10.5194/egusphere-egu26-5507, 2026.
Flood risk uncertainty is a growing problem in New Zealand and the rest of the world. Decision-makers are facing increasing uncertainty in planning for future events. Growing population centres, increased cost of living and the resulting increased exposure to these natural hazards are just some of factors they need to consider in planning and mitigating future events. Climate change predictions represent a large part of the uncertainty present in these future flood risk assessments. Variables such as rainfall intensity and duration are likely to change significantly with increased temperatures which would result in potentially larger and more frequent flood events. To better understand how these different uncertainties could influence decision-making, a series of flood model and risk assessment output representations containing uncertainty were generated from a Monte Carlo framework. These representations were tested using an online survey and focus groups across regional councils, national response agencies and private companies that work with flood information. The results showed that traditional flood outputs such as depth and extent were still rated more useful than uncertain outputs such as confidence and exceedance probabilities. Larger AEPs (annual exceedance probabilities) such as 0.5% and 0.1% were seen as useful for long-term development planning but lower AEPs such as 1% and 5% were better suited for mitigation and emergency response plans. Across all the uncertainty outputs, respondents stressed the need for additional contextual information such as socio-economic overlays, area specific information such as land use and building types that would work in tandem with rebuild cost estimates and building damage data. From this feedback, a series of recommendations for presenting flood uncertainty information to decision-makers were created.
How to cite: Ash, C., Wilson, M., Hultquist, C., and White, I.: Communicating Flood Risk Uncertainty for Decision-Making in Aotearoa-New Zealand, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15153, https://doi.org/10.5194/egusphere-egu26-15153, 2026.
Aquifer thermal energy storage (ATES) is a way to use the groundwater to heat and cool buildings, with very low CO2 emissions. It classifies as a shallow geothermal technology, and it is gaining popularity worldwide because of its sustainability, efficiency and cost-effectiveness. While its potential has been extensively proven in traditional homogenous, productive sandy groundwater layers, investing in more complex subsurface settings has greater financial risk. This is related to uncertainty about the (hydraulic) project feasibility and (thermal) efficiency of the system. Basically, we cannot directly look underground, so it is uncertain to what extent our subsurface model correctly represents reality. Even though this subsurface uncertainty leads to a great globally untapped potential for thermal energy storage, it is often neglected in feasibility studies. To move new ATES developments forward in complex subsurface settings, we present an uncertainty-driven sound scientific method to make investment decisions. Uncertainty in subsurface models is recognized by using a stochastic approach. The model predictions are then processed with clustering and global sensitivity analysis. This allowed to define criteria on critical subsurface properties that guarantee project (in)feasibility. For edge-cases, uncertainty is quantified to determine the probability of project feasibility from a risk-taking or risk-averse decision-maker perspective. Additionally, this approach quantified the potential of changing operational parameters (flow rate, well spacing, design injection temperature) to enhance project feasibility. All results are summarized in an easy-to-interpret decision tree that guides go/no-go decisions for new ATES projects. Importantly, the decision-tree can be followed prior to carrying out costly field tests. To illustrate, the uncertainty-driven decision tree approach is applied to a low-transmissivity aquifer for ATES, which represents a subsurface setting at the limit of ATES suitability. In conclusion, our approach effectively handles uncertainty while also focusing on improving clear communication to investors about the probability of project feasibility. As such, it could be an example study on how to handle model uncertainty for predictions of aquifer thermal energy storage systems in the future.
How to cite: Tas, L., Caers, J., and Hermans, T.: An Uncertainty-Driven Decision Tree Approach Guiding Feasibility Decisions of Shallow Geothermal Systems in Complex Subsurface Settings, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14276, https://doi.org/10.5194/egusphere-egu26-14276, 2026.
