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Title: Evaluating Emergent Constraints for Equilibrium Climate Sensitivity

Abstract

Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. Here, this study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO2 doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owingmore » to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. Lastly, the fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles.« less

Authors:
 [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1438763
Report Number(s):
LLNL-JRNL-738384
Journal ID: ISSN 0894-8755
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 31; Journal Issue: 10; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; Climate change; Climate sensitivity; Feedback; Statistics; Climate models

Citation Formats

Caldwell, Peter M., Zelinka, Mark D., and Klein, Stephen A. Evaluating Emergent Constraints for Equilibrium Climate Sensitivity. United States: N. p., 2018. Web. doi:10.1175/JCLI-D-17-0631.s1.
Caldwell, Peter M., Zelinka, Mark D., & Klein, Stephen A. Evaluating Emergent Constraints for Equilibrium Climate Sensitivity. United States. doi:10.1175/JCLI-D-17-0631.s1.
Caldwell, Peter M., Zelinka, Mark D., and Klein, Stephen A. Mon . "Evaluating Emergent Constraints for Equilibrium Climate Sensitivity". United States. doi:10.1175/JCLI-D-17-0631.s1. https://www.osti.gov/servlets/purl/1438763.
@article{osti_1438763,
title = {Evaluating Emergent Constraints for Equilibrium Climate Sensitivity},
author = {Caldwell, Peter M. and Zelinka, Mark D. and Klein, Stephen A.},
abstractNote = {Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. Here, this study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO2 doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owing to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. Lastly, the fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles.},
doi = {10.1175/JCLI-D-17-0631.s1},
journal = {Journal of Climate},
number = 10,
volume = 31,
place = {United States},
year = {2018},
month = {4}
}

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