Abstract
Today's ensemble weather prediction systems provide reliable and sharp probabilistic forecasts—yet they are still rarely communicated to outside users because of two main worries: the difficulty of communicating probabilities to lay audiences and their presumed reluctance to use probabilistic forecasts. To bridge the gap between the forecasts available and their use in day‐to‐day decision making, we encourage scientists, developers, and end‐users to engage in interdisciplinary collaborations. Here, we discuss our experience with three different approaches of introducing probabilistic forecasts to different user groups and the theoretical and practical challenges that emerged. The approaches range from quantitative analyses of users' revealed preferences online to a participatory developer–user dialogue based on trial cases and interactive demonstration tools. The examples illustrate three key points. First, to make informed decisions, users need access to probabilistic forecasts. Second, forecast uncertainty can be understood if its visual representations follow validated best practices from risk communication and information design; we highlight five important recommendations from that literature for communicating probabilistic forecasts. Third, to appreciate the value of probabilistic forecasts for their decisions, users need the opportunity to experience them in their everyday practice. With these insights and practical pointers, we hope to support future efforts to integrate probabilistic forecasts into everyday decision making.
Highlights
Probabilistic forecasts have been available for many years within weather services
With the exception of standardised weather forecasts for airports and several flood forecasting offices (Frick and Hegg, 2011), probabilistic forecasts are rarely communicated to outside users
To test which information emergency managers might find useful, we developed and implemented five different representations of probabilistic forecasts for the most relevant weather conditions for emergency managers in Germany: wind, precipitation, and thunderstorms
Summary
Probabilistic forecasts have been available for many years within weather services (e.g., probabilities for exceeding precipitation thresholds or for the occurrence of thunderstorms). With the exception of standardised weather forecasts for airports and several flood forecasting offices (Frick and Hegg, 2011), probabilistic forecasts are rarely communicated to outside users. More than 150 years later, the advent of numerical weather prediction models heralded a new era and transformed these initial ideas into operational probabilistic forecast products. While the early probability forecasts were based on subjective and statistical interpretations of the intrinsic uncertainty in single numerical forecasts, the estimation of uncertainty later relied on the combination of several forecast runs of one numerical weather model (a “time-lagged ensemble”; Brankovicet al., 1990) or of numerical forecasts from different operational centres (a “poor-man’s ensemble”; Ebert, 2001).
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