Abstract
Abstract. To inform the way probabilistic forecasts would be displayed on their website, the UK Met Office ran an online game as a mass participation experiment to highlight the best methods of communicating uncertainty in rainfall and temperature forecasts, and to widen public engagement in uncertainty in weather forecasting. The game used a hypothetical “ice-cream seller” scenario and a randomized structure to test decision-making ability using different methods of representing uncertainty and to enable participants to experience being “lucky” or “unlucky” when the most likely forecast scenario did not occur. Data were collected on participant age, gender, educational attainment, and previous experience of environmental modelling. The large number of participants (n>8000) that played the game has led to the collation of a unique large dataset with which to compare the impact on the decision-making ability of different weather forecast presentation formats. This analysis demonstrates that within the game the provision of information regarding forecast uncertainty greatly improved decision-making ability and did not cause confusion in situations where providing the uncertainty added no further information.
Highlights
Small errors in observations of the current state of the atmosphere as well as the simplifications required to make a model of the real world lead to uncertainty in the weather forecast
For this study we focused on two aspects of the weather forecast: precipitation, as Lazo et al (2009) found this to be of the most interest to users and probability of precipitation (PoP) has been presented for a number of years, and temperature, since a part of the UK Met Office website at that time included an indication of predicted temperature uncertainty (“Invent”)
We estimate that approximately 15 % of participants had this misconception, this figure might vary for different demographic groups: it is difficult to specify the exact figure since errors in understanding of probability would exhibit a similar footprint in the results
Summary
Small errors in observations of the current state of the atmosphere as well as the simplifications required to make a model of the real world lead to uncertainty in the weather forecast. In a statistically reliable ensemble, if 60 % of the ensemble members forecast rain, there is a 60 % chance of rain. This ensemble modelling approach has become common place within operational weather forecasting (Roulston et al, 2006), the information is more typically used by forecasters to infer and express the level of uncertainty rather than directly communicate it quantitatively to the public. The probability of precipitation (PoP) is perhaps the only exception, with PoP being directly presented to the US public since 1965 (NRC, 2006), originally derived using statistical techniques rather than ensemble modelling. This study aimed to build on prior studies that have addressed public understanding of the “reference class” of PoP (e.g. Gigerenzer et al, 2005; Morss et al, 2008) and decision-making ability using probabilistic forecasts (e.g. Roulston and Kaplan, 2009; Roulston et al, 2006), and to dig deeper into the conclusions that suggest that there
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