Uncertain Climate Forecasts From Multimodel Ensembles: When to Use Them and When to Ignore Them

TL;DR

This paper explores how to decide when to rely on or ignore multimodel climate forecasts by using the Bayesian Information Criterion to assess forecast uncertainty and accuracy.

Contribution

It introduces a method applying BIC to determine the usefulness of climate forecasts based on their uncertainty levels.

Findings

BIC effectively discriminates between useful and unreliable forecasts

Uncertain forecasts can be identified and excluded to improve decision-making

The approach enhances forecast reliability by quantifying uncertainty

Abstract

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 forecasts should not be used. We investigate the use of the well-known Bayesian Information Criterion (BIC) to make the decision as to whether a forecast should be used or ignored.