by David Stainforth
- Climate predictions on regional scales are highly sought after by policy and decision makers. Here a new method is presented for extracting model based probabilistic information on regional and seasonal scales, utilising the world’s largest climate ensemble exploring the consequences of model uncertainty. For the first time ensemble filtering is implemented to counter problems of in-sample bias in future analyses. A probabilistic interpretation is presented of the regional scale consequences of targets to halve global GHG emissions by 2050, using a scenario with an estimated 32% probability of exceeding 2°C global warming (relative to pre-industrial levels).
Stainforth, D. (2010). "Probabilistic Regional and Seasonal Predictions of Twenty-First Century Temperature and Precipitation." Grantham Research Institute on Climate Change and the Environment Working Paper No. 23, Aug 2010.