Project goal

The Intergovernmental Panel on Climate Change (IPCC) recently advised in their sixth assessment report (AR6) to weight model projections of global temperature change by their ability to reproduce historical warming. While it is clear that this improves projections of global temperature change, it is unclear if this weighting scheme is useful for other projections, such as precipitation or regional temperature change. We’re analyzing the skill of the IPCC’s weighting scheme in projections of other climate variables to address this ambiguity.

Abstract

It depends. The Intergovernmental Panel on Climate Change’s (IPCC) Assessment Report Six (AR6) took a step towards ending so-called ‘model democracy’ by discounting climate models that are too warm over the historical period (i.e., models that ‘run hot’) when making projections of global temperature change. However, the IPCC did not address whether this procedure is reliable for other quantities. Here, we explore the implications of weighting climate models according to their skill in reproducing historical global-mean surface temperature using three other climate variables of interest: annual average precipitation change, regional average temperature change, and regional average precipitation change. We find that the temperature-based weighting scheme leads to an improved prediction of global average precipitation, though we show that this prediction could be overconfident. On regional scales, we find a heterogeneous pattern of error reduction in future regional precipitation. This stands in sharp contrast with the broad regional pattern of error reduction in future temperature projections, though we do find regions where error is not significantly reduced. Our results demonstrate that practitioners using weighted climate model ensembles for climate projections must take care when weighting by temperature alone, lest they produce unreliable climate projections that result from an inappropriate weighting procedure.

Full paper and citation

Link to accepted version.; this version: 9/20/2024’; published version can be found here

Citation: McDonnell, A., A. M. Bauer, C. Proistosescu. To what extent does discounting ‘hot’ climate models improve the predictive skill of climate model ensembles? Earth’s Future, 12(10), 2024.

Collaborators

Abby McDonnell and Cristi Proistosescu.

Presentations

• American Geophysical Union Fall Meeting, December 2022 (Poster, presented by Abby McDonnell).