z-logo
open-access-imgOpen Access
Odds Ratio Forecasts Increase Precautionary Action for Extreme Weather Events
Author(s) -
Jared E. LeClerc,
Susan Joslyn
Publication year - 2012
Publication title -
weather, climate, and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.014
H-Index - 35
eISSN - 1948-8335
pISSN - 1948-8327
DOI - 10.1175/wcas-d-12-00013.1
Subject(s) - probabilistic logic , odds , extreme weather , action (physics) , precautionary principle , extreme value theory , rare events , event (particle physics) , computer science , actuarial science , econometrics , climate change , economics , statistics , mathematics , logistic regression , artificial intelligence , machine learning , ecology , physics , quantum mechanics , biology
What is the best way to communicate the risk of rare but extreme weather to the public? One suggestion is to communicate the relative risk of extreme weather in the form of odds ratios; but, to the authors’ knowledge, this suggestion has never been tested systematically. The experiment reported here provides an empirical test of this hypothesis. Participants performed a realistic computer simulation task in which they assumed the role of the manager of a road maintenance company and used forecast information to decide whether to take precautionary action to prevent icy conditions on a town’s roads. Participants with forecasts expressed as odds ratios were more likely to take appropriate precautionary action on a single target trial with an extreme low temperature forecast than participants using deterministic or probabilistic forecasts. However, participants using probabilistic forecasts performed better on trials involving weather within the normal range than participants with only deterministic forecast information. These results may provide insight into how best to communicate extreme weather risk. This paper offers clear evidence that people given relative risk information are more inclined to take precautionary action when threatened with an extreme weather event with a low probability than people given only single-value or probabilistic forecasts.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here