How reliable are climate models?

By Jouni Raäisaänen. 2007

380 citations recorded by the source corpus.

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.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/56beff179f8b5c1915da2ddc5c204e0c362be2b1

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Citations in the corpus

Description and validation of a two-step analogue/regression downscaling method (2013, background): “2005; John and Soden 2007), partly due to low spatial resolution (Räisänen 2007).”
The end of model democracy? (2010, background): “the mean state of climate (Gleckler et al. 2008; Räisänen 2007; Randall et al. 2007; Reichler and Kim 2008), or past trends (Hegerl et al.”
Climate change multi‐model projections for temperature extremes in Portugal (2014, methodology): “The use of equally weighted multi-model ensembles in this study is currently the best approach to take into account the uncertainties in climate change projections (Räisänen, 2007; Christensen et al., 2010), as is clearly depicted in Figures S3 and S4.”