@article{c7df24507e68432ca7a5cef055001309,
title = "To What Extent Does Discounting {\textquoteleft}Hot{\textquoteright} Climate Models Improve the Predictive Skill of Climate Model Ensembles?",
abstract = "It depends. The Intergovernmental Panel on Climate Change's (IPCC) Assessment Report Six (AR6) took a step toward ending so-called {\textquoteleft}model democracy{\textquoteright} by discounting climate models that are too warm over the historical period (i.e., models that {\textquoteleft}run hot{\textquoteright}) 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: global 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.",
keywords = "climate change, climate projections, CMIP6, model democracy",
author = "Abigail McDonnell and Bauer, {Adam Michael} and Cristian Proistosescu",
note = "The authors would like to thank Ryan Sriver, three anonymous reviewers, and the attendees of the fall meeting of the American Geophysical Union 2,022 for providing useful feedback and discussions. AM and CP acknowledges support from a National Oceanic and Atmospheric Sciences Grant OAR MAPP UWSC12184. AM acknowledges support from the National Oceanic and Atmospheric Sciences Hollings Scholarship Program. AMB acknowledges support from a National Science Foundation Graduate Research Fellowship Grant DGE 21-46756 and the Climate Support Facility of the World Bank Group. Computations were performed on the Keeling computing cluster, a computing resource operated by the School of Earth, Society and Environment (SESE) at the University of Illinois Urbana-Champaign. We would also like to thank Ryan Abernathey's writings for providing a template for using CMIP6 data via a Google Cloud repository and the Pangeo Stack (Abernathey,\u00A02024). The authors would like to thank Ryan Sriver, three anonymous reviewers, and the attendees of the fall meeting of the American Geophysical Union 2,022 for providing useful feedback and discussions. AM and CP acknowledges support from a National Oceanic and Atmospheric Sciences Grant OAR MAPP UWSC12184. AM acknowledges support from the National Oceanic and Atmospheric Sciences Hollings Scholarship Program. AMB acknowledges support from a National Science Foundation Graduate Research Fellowship Grant DGE 21\u201046756 and the Climate Support Facility of the World Bank Group. Computations were performed on the Keeling computing cluster, a computing resource operated by the School of Earth, Society and Environment (SESE) at the University of Illinois Urbana\u2010Champaign. We would also like to thank Ryan Abernathey's writings for providing a template for using CMIP6 data via a Google Cloud repository and the Pangeo Stack (Abernathey, 2024 ).",
year = "2024",
month = oct,
doi = "10.1029/2024EF004844",
language = "English (US)",
volume = "12",
journal = "Earth's Future",
issn = "2328-4277",
publisher = "John Wiley & Sons, Ltd.",
number = "10",
}