Communicating probabilistic information from climate model ensembles-lessons from numerical weather prediction

E M Stephens, Tamsin L Edwards, David Demeritt

Research output: Contribution to journalArticle (Academic Journal)peer-review

52 Citations (Scopus)

Abstract

Climate model ensembles are widely heralded for their potential to quantify uncertainties and generate probabilistic climate projections. However, such technical improvements to modeling science will do little to deliver on their ultimate promise of improving climate policymaking and adaptation unless the insights they generate can be effectively communicated to decision makers. While some of these communicative challenges are unique to climate ensembles, others are common to hydrometeorological modeling more generally, and to the tensions arising between the imperatives for saliency, robustness, and richness in risk communication. The paper reviews emerging approaches to visualizing and communicating climate ensembles and compares them to the more established and thoroughly evaluated communication methods used in the numerical weather prediction domains of day-to-day weather forecasting (in particular probabilities of precipitation), hurricane and flood warning, and seasonal forecasting. This comparative analysis informs recommendations on best practice for climate modelers, as well as prompting some further thoughts on key research challenges to improve the future communication of climate change uncertainties.
Original languageEnglish
Pages (from-to)409-426
JournalWiley Interdisciplinary Reviews: Climate Change
Volume3
Issue number5
DOIs
Publication statusPublished - Sep 2012

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