How Spatial Uncertainty in Probabilistic Weather Forecasts Shapes Risk Perception

As climate change intensifies extreme weather events, reliable forecast information is increasingly important for deciding when and how to prepare for hazardous conditions. But even with advances in forecast accuracy, effective risk communication still depends on whether people interpret and use information appropriately, especially for low-probability, high-impact events. A central challenge is the fundamental trade-off between forecast probabilities and spatial uncertainty: Finer spatial resolutions provide more localized predictions but often imply lower event probabilities, whereas coarser spatial resolutions produce higher probabilities but with considerable uncertainty around where in the region the event will occur. We investigated how people map region-level forecast probabilities into perceived personal risk of being affected at their own location. Stimuli were sampled from issued severe wind gust warnings, reflecting operational forecast products with realistic spatial patterns and probability ranges. We tested a representative sample of the German population ($N=1,179$) and a sample of experts ($N=77$). In the public sample, perceived personal risk decreased as spatial resolution became coarser, but only when probabilities were communicated numerically. When the same forecasts were accompanied by probability maps, inferred risk was largely independent of spatial resolution. Experts showed decreasing risk estimates with coarser resolution across all formats. Both groups rated higher-resolution forecasts as more useful, but only the public sample rated them as more trustworthy. These results show that inferring location-specific risks from forecast probabilities under spatial uncertainty depends on both communication format and expertise---a finding that offers practical guidance for designing risk-communication tools that foster appropriate use of spatial information.