Roger's current research includes developing methods for calibrating a reduced complexity climate model against historical observations using a Bayesian statistical approach in order to obtain probabilistic projections for future global-mean temperature change.
The new emission scenarios for the IPCC's fifth assessment scenario are being investigated, as well as approaches to setting temperature change targets and carbon budgets.