Communicating Risk with Possibility, Not Probability

Abstract

Communicating forecast uncertainty effectively is a persistent challenge in predictive endeavours such as weather forecasting. This paper explores the application of possibility theory as a complementary approach to traditional probability in risk communication. Unlike probability, possibility theory allows for the representation of uncertain events as ranges of potential, distinguished by degrees of plausibility possibility and certainty necessity. Using a simplified fuzzy-logic inference system, we generate possibility forecasts of ozone-concentration forecasts from meteorological inputs. Observations are pre-processed as degrees of an adjective, e.g., 1 m/s wind speed may belong to the adjective "calm" at degree 0.8 (perhaps represented with an adverb as "substantially"). Aggregation of all rule activations yields a possibility distribution over the output range. As possibility is an upper bound of probability, possibilities provides most value for risk-averse stakeholders sensitive to the event of interest, especially near the event's predictability horizon when there is most uncertainty to remove. By setting the forecast challenge as the possibility of an event, we effectively extend the predictability horizon: trading some specificity for detection of fainter signals of the event's future occurrence. Possibility theory appreciates uncertainty's dual nature: inherent randomness (aleatoric) and knowledge deficiency (epistemic). While the unfamiliar nature of the theory requires more accessible language before operational use and public communication, possibility offers substantial practical benefits for assessment of uncertainty at the edge of predictability limits for vulnerable users.