Climate projections: Past performance no guarantee of future skill?
Abstract
The principle of selecting climate models based on their agreement with observations has been tested for surface temperature using 17 of the IPCC AR4 models. Those models simulating global mean, Siberian and European 20th Century surface temperature with a lower error than the total ensemble for one period on average do not do so for a subsequent period. Error in the ensemble mean decreases systematically with ensemble size, N, and for a random selection as approximately 1/Nα, where α lies between 0.6 and 1. This is larger than the exponent of a random sample (α = 0.5) and appears to be an indicator of systematic bias in the model simulations. There is no evidence that any subset of models delivers significant improvement in prediction accuracy compared to the total ensemble.
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Model skill persisted only slightly over the past century.
“and only a slight persistence of model skill during the past century (Reifen and Toumi 2009).”
From Risks of Model Weighting in Multimodel Climate Projections (2010) · cites this paper as Reifen and Toumi 2009
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Pastén-Zapata, E., Eberhart, T., Jensen, K. H., Refsgaard, J. C., & Sonnenborg, T. O. (2022) · Water Resources Management · doi:10.1007/s11269-022-03212-2 · Cited by 11 · see citing works
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A comparison of absolute and relative changes in precipitation in multimodel climate projection
Baker, N. C., & Huang, H. (2012) · Atmospheric Science Letters · doi:10.1002/asl.388 · Cited by 11 · see citing works
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- Authors
- Reifen, C., & Toumi, R.
- Affiliations
- Imperial College London (GB)
- ORCID
- Toumi, R.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-07
- Volume
- 36
- Issue
- 13
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2064730812
- Cited by
- 144
- References
- 12
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 3 · 2022: 5 · 2021: 5 · 2020: 9 · 2019: 6 · 2018: 11 · 2017: 10 · 2016: 11 · 2015: 14 · 2014: 8 · 2013: 11 · 2012: 12
- FWCI
- 10.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Geophysical Research Letters (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Keywords
- climate model selection, model skill, surface temperature, ensemble size, model bias, climate change projections
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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