Communicating probabilistic information from climate model ensembles—lessons from numerical weather prediction
Bibliographic Data
| ID | 12929078 |
|---|---|
| Authors | Elisabeth Stephens (0000-0002-5439-7563, University of Bristol, corresponding author), Tamsin Edwards (0000-0002-4760-4704, University of Bristol), David Demeritt (0000-0002-2030-0807, King's College London) |
| Year | 2012 |
| Volume | 3 |
| Issue | 5 |
| Pages | 409-426 |
| Publication date | 2012-08-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Wiley Interdisciplinary Reviews Climate Change (JOURNAL) |
| Journal identifiers | ISSN: 1757-7780 • E-ISSN: 1757-7799 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/wcc.187 |
| OpenAlex | W2099747136 |
| Language | EN |
| Citations received | 15 |
| References cited | 62 |
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. WIREs Clim Change 2012. doi: 10.1002/wcc.187 This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Perceptions, Behavior, and Communication of Climate Change > Communication
Climate change · Climate model · Climatology · Data science · Environmental resource management · Geography · Hydrometeorology · Meteorology · Precipitation · Probabilistic logic · Robustness (evolution · Climate Change Communication and Perception · Climate variability and models · Computer Science · Environmental Science · Meteorological Phenomena and Simulations · Artificial Intelligence · Ecology
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| Unique citing works | 15 |
|---|---|
| Citations per year | 1,25 |
| Citation span | 2014 - 2024 (11) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 15 |