There are different kinds of uncertainty. I outline some of the various ways that uncertainty enters science, focusing on uncertainty in climate science and weather prediction. I then show how we cope with some of these sources of error through sophisticated modelling techniques. I show how we...

Operational seasonal forecasting centres employ simulation models to make probability forecasts of future conditions on seasonal to annual lead times. Skill in such forecasts is reflected in the information they add to purely empirical statistical models, or to earlier versions of simulation...

Pattern scaling methods are being widely applied to generate scenarios of climate change for quantification of their impacts on different systems. While generic limitations of this approach are welldocumented, the implications of the use of pattern scaling to inform adaptation decisions are not...

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Parameter estimation in nonlinear models is a common task, and one for which there is no general solution at present. In the case of linear models, the distribution of forecast errors provides a reliable guide to parameter estimation, but in nonlinear models the facts that predictability may...

International carbon markets have grown quickly in recent years, but have also experienced serious problems and faced harsh criticism. This paper looks at the history of climate science, at how the economics of emissions trading developed, and at the formation of international institutions to...