Steve Easterbrook: How good are predictions from climate models?
The whole post is worth a read. Here are his summary points:
• We can be very confident that the climate is changing due to anthropogenic carbon emissions (observational studies, paleoclimate analysis and climate models all agree on this). But the more it changes, the less confident we are about what happens next.
• The most important function of climate models is to explore ‘what if’ questions, to improve our understanding of climate processes.
• Climate models have steadily improved in their ability to simulate observed climate, and the range of errors across models is decreasing.
• The models do an excellent job of reproducing temperatures, but are less good at other variables, such as precipitation.
• Getting good simulations of 20th Century climate provides a way of falsifying models, but not of proving them correct.
• The more the climate changes in the future, the less we can be sure that current climate models give us good predictions (because of the probability that different kinds of physical processes kick in).
• Probabilistic forecasts are important, but easily misunderstood. In particular, the chances of temperatures exceeding the 99% confidence line are likely to be much higher than 1%!
• Deterministic forecasts (i.e. from a single run) are useless.
• Choice of a good model depends on the purpose – e.g. for regional predictions, the choice depends on both the region and the variables we are interested in (e.g. temperature, seasonal variation, precipitation, etc).
• Climate modelers tend to be very nervous about use of their models for future predictions, but people outside this community often over-sell the ability of the models.
Also: one can hardly mention the AGU meeting without recommending this video of the keynote talk by Richard Alley.