
This is good news for businesses and policy-makers currently seeking predictions to aid planning for adaptation to climate change in the coming years, and for whom such improvements could present enormous economic savings: uncertainty in climate forecasts means that adaptation measures have to be designed with greater resilience, making them more expensive.
The results came after the researchers, based at the Walker Institute, University of Reading, used data from a suite of state-of-the-art climate models to identify the main causes of uncertainty in predictions of temperature change over different space and time scales. Although this type of study had previously been done on a global scale, this is the first time it has been attempted on regional scales (2000 km) across the globe.
Results showed that for all regions for the next four decades, the main uncertainties in climate predictions are dominated by: (i) differences between the climate models themselves eg in the way they represent different atmospheric processes; (ii) the natural variability of the climate (ie changes in the climate not brought about by human influences). Fortunately, both types of uncertainty are reducible through investment and progress in climate science.
An important issue for planners and funding agencies, therefore, is how climate science can best deliver improvements in such predictions, and so reduce the costs of adaptation to a changing climate…..
A traditional iron weather vane, shot by Unisouth, Wikimedia Commons, under the Creative Commons Attribution ShareAlike 3.0 License
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