25 citations · 255 across the 52 of their papers we have counts for
52 papers
Uncertain Climate Forecasts From Multimodel Ensembles: When to Use Them and When to Ignore Them
Stephen Jewson, Dan Rowlands
Uncertainty around multimodel ensemble forecasts of changes in future climate reduces the accuracy of those forecasts. For very uncertain forecasts this effect may mean that the fo…
Objective Climate Model Predictions Using Jeffreys' Prior: the General Multivariate Normal Case
Stephen Jewson, Dan Rowlands, Myles Allen
Objective probabilistic forecasts of future climate that include parameter uncertainty can be made by using the Bayesian prediction integral with the prior set to Jeffreys' Prior.…
Objective Probabilistic Forecasts of Future Climate Based on Jeffreys' Prior: the Case of Correlated Observables
Stephen Jewson, Dan Rowlands, Myles Allen
To include parameter uncertainty into probabilistic climate forecasts one must first specify a prior. We advocate the use of objective priors, and, in particular, the Jeffreys' Pri…
Improving Uncertain Climate Forecasts Using a New Minimum Mean Square Error Estimator for the Mean of the Normal Distribution
Stephen Jewson, Ed Hawkins
When climate forecasts are highly uncertain, the optimal mean squared error strategy is to ignore them. When climate forecasts are highly certain, the optimal mean squared error st…
Improving the expected accuracy of forecasts of future climate using a simple bias-variance tradeoff
Stephen Jewson, Ed Hawkins
We describe a simple method that utilises the standard idea of bias-variance trade-off to improve the expected accuracy of numerical model forecasts of future climate. The method c…
CMIP3 ensemble spread, model similarity, and climate prediction uncertainty
Stephen Jewson, Ed Hawkins
The CMIP3 multi-model ensemble spread most likely underestimates the real model uncertainty in future climate predictions because of the similarity, and shared defects, of the mode…