What might the climate be in 2053?
A typical display from the climateprediction.net model showing the temperature of the Earth.
Dr Jamie Kettleborough, Rutherford Appleton Laboratory.
Professor Bob Spicer, The Open University.
Dr Myles Allen, Dr Sylvia Knight, Mr David Stainforth, Dr Dave Frame and Dr Mark New,
University of Oxford.
Dr Eleanor Highwood, University of Reading.
Dr Mat Collins, The Met Office.
Early results from climateprediction.net suggest that the climate could be a lot more sensitive to greenhouse gases and could warm a lot more than the Intergovernmental Panel on Climate Change (IPCC) has previously suggested. These and future results will form part of the UK's contribution to the fourth report of the IPCC due in 2007. 'Better assessment of the uncertainties in climate forecasts is a priority for the Met Office and the Government. The climateprediction.net experiment should give policy-makers a better scientific basis for addressing one of the biggest potential global problems of the twenty-first century', says Mat Collins of the Met Office.
Climate change and our response to it are issues of global importance, affecting food production, water resources, ecosystems, energy demand and insurance costs. There is a broad scientific consensus that the Earth will warm over the coming century, but the key question is by how much? Climateprediction.net should, for the first time, allow scientists to give a much more complete answer to this question.
Best estimates of future climate change come from general circulation models (GCMs), which are the same models used to make everyday weather forecasts. GCMs simulate as much as possible about the climate system: the incoming and outgoing radiation, the way the air moves, the way the ice sheets grow or shrink and how all these different parts of the climate system interact and affect each other. A limiting factor in developing accurate models has been the time that even the most powerful computers take to repeatedly run models with slight variations in all these interacting factors.