Uncertainty: Climate models at their limit?
Mark Maslin and Patrick Austin predict a public image problem for climate change scientists.
Prediction stability: Estimates of climate sensitivity (numbered - the rise of global temperature caused by a doubling of atmospheric carbon dioxide levels) have remained fairly steady for decades.
In the run-up to the Rio+20 Earth Summit later this month, Professor Mark Maslin and Dr Patrick Austin write in the 14th June issue of Nature, predicting a serious public-image problem for climate-change scientists in the coming year. The next round of the Intergovernmental Panel on Climate Change’s science assessment, due to be released next year, is likely to produce wider rather than smaller ranges of uncertainty in its predictions of climate change. To the public and policymakers this will look as though scientific understanding is becoming less, rather than more, clear.
Many recent climate models include interactive carbon cycles, better representations of aerosols and atmospheric chemistry, and increases in spatial resolution, but this means that more ‘known unknowns’ have been included. Add to this the difficulties in predicting the economy and estimating costs to society, and the result it a blurry picture.
None of this means that climate models are useless - in fact they have proved to be remarkably stable in their core predictions. One way to tackle the public-perception problem, the authors argue, is to rephrase conclusions, emphasizing when change might happen, rather than whether it will happen at all.
The weight of scientific evidence is enough to tell us what we need to know, argue Maslin and Austin. “We need governments to just go ahead and take action, as both the United Kingdom and Mexico have done. We do not need to demand impossible levels of certainty from the models to envisage a better, safer future.”
Click here to read the PDF.
Published on-line, 13 Jun 2012: