Approaches for Using CMIP Projections in Climate Model Ensembles to Address the ‘Hot Model’ Problem

Open-File Report 2024-1008
Prepared in cooperation with the University of Colorado and the University of Oklahoma
By: , and 

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Abstract

Several recent generation global-climate models were found to have anomalously high climate sensitivities and may not be useful for certain applications. Four approaches for developing ensembles of climate projections for applications that address this issue are:

  1. Using an “all models” approach;
  2. Screening using equilibrium climate sensitivity and (or) transient climate response;
  3. Bayesian model averaging; and
  4. Using global warming levels.

Advantages and disadvantages of each approach are described by using example applications to study the effects of climate change on an imaginary at-risk species. Choosing the right approach is dependent on the location, goals, and system focus of each application and the risk-tolerance and resource-management context.

Suggested Citation

Boyles, R., Nikiel, C.A., Miller, B.W., Littell, J., Terando, A.J., Rangwala, I., Alder, J.R., Rosendahl, D.H., and Wootten, A.M., 2024, Approaches for using CMIP projections in climate model ensembles to address the ‘hot model’ problem: U.S. Geological Survey Open-File Report 2024–1008, 14 p., https://doi.org/10.3133/ofr20241008

ISSN: 2331-1258 (online)

Table of Contents

  • Acknowledgements
  • Abstract
  • Introduction
  • Approaches for GCM Selection and Weighting
  • Example: The Golden-billed Raptor
  • Conclusion
  • References Cited
  • Glossary
  • Appendix 1
Publication type Report
Publication Subtype USGS Numbered Series
Title Approaches for using CMIP projections in climate model ensembles to address the ‘hot model’ problem
Series title Open-File Report
Series number 2024-1008
DOI 10.3133/ofr20241008
Year Published 2024
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Alaska Science Center, Southeast Climate Science Center, National Climate Adaptation Science Center, South Central Climate Adaptation Science Center
Description v, 14 p.
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details