Cited by 356Climate variability and modelsMeteorological Phenomena and SimulationsClimate Change and Environmental Impact

How reliable are climate models?

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Räisänen, Jouni·2007·Tellus A: Dynamic Meteorology and Oceanography

Abstract

How much can we trust model-based projections of future anthropogenic climate change? This review attempts to give an overview of this important but difficult topic by using three main lines of evidence: the skill of models in simulating present-day climate, intermodel agreement on future climate changes, and the ability of models to simulate climate changes that have already occurred. A comparison of simulated and observed present-day climates shows good agreement for many basic variables, particularly at large horizontal scales, and a tendency for biases to vary in sign between different models, but there is a risk that these features might be partly a result of tuning. Overall, the connection between model skill in simulating present-day climate and the skill in simulating future climate changes is poorly known. An intercomparison of future climate changes between models shows a better agreement for changes in temperature than that for precipitation and sea level pressure, but some aspects of change in the latter two variables are also quite consistent between models. A comparison of simulations with observed climate changes is, in principle, a good test for the models, but there are several complications. Nonetheless, models have skilfully simulated many large-scale aspects of observed climate changes, including but not limited to the evolution of the global mean surface air temperature in the 20th century. Furthermore, although there is no detailed agreement between the simulated and observed geographical patterns of change, the grid box scale temperature, precipitation and pressure changes observed during the past half-century generally fall within the range of model results. Considering the difficulties associated with other sources of information, the variation of climate changes between different models is probably the most meaningful measure of uncertainty that is presently available. In general, however, this measure is more likely to underestimate than overestimate the actual uncertainty.

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  • A weak link between current model performance and future projections has been reported in many studies.

    “many studies have found only a weak relation between present-day model performance and future projections (Ra ¨isa ¨nen 2007; Whetton et al. 2007;Jun et al. 2008;Knutti et al. 2010;Scherrer 2010)”

    From Risks of Model Weighting in Multimodel Climate Projections (2010) · cites this paper as Ra ¨isa ¨nen 2007

    Section 3.3 finds little evidence of a relationship between simulated present-day mean temperatures and projected temperature changes outside high-latitude sea areas, and says earlier simulations support that conclusion. The paper describes the broader connection between present-day model performance and future-change skill as poorly understood, rather than establishing that many studies found a weak relationship across future projections generally. (LLM, conf=0.84)

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Authors
Räisänen, J.
Affiliations
University of Helsinki (FI)
Corresponding author
Räisänen, Jouni
Venue
Tellus A: Dynamic Meteorology and Oceanography
Published
2007-01-01
Volume
59
Issue
1
Pages
2
ISSN
  • 0280-6495 (ISSN-L)
  • 1600-0870
OpenAlex
W2075532188
Cited by
356
References
0
Citations by year
2026: 8 · 2025: 16 · 2024: 16 · 2023: 11 · 2022: 13 · 2021: 16 · 2020: 7 · 2019: 18 · 2018: 7 · 2017: 22 · 2016: 18 · 2015: 26 · 2014: 21 · 2013: 33 · 2012: 28
FWCI
10.68
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
Tellus A Dynamic Meteorology and Oceanography (publishedVersion, cc-by)
Funders
  • U.S. Department of Energy
  • Office of Science
  • Lawrence Livermore National Laboratory
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
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
Keywords
model skill, model calibration, climate change detection, model uncertainty, global mean surface air temperature, precipitation change, sea level pressure, 20th century climate change, model validation against observations

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