On the Emergent Constraints of Climate Sensitivity

Qu, Xin; Hall, Alex; DeAngelis, Anthony M.; Zelinka, Mark D.; Klein, Stephen A.; Su, Hui; Tian, Baijun; Zhai, Chengxing

doi:10.1175/JCLI-D-17-0482.1

Title: On the Emergent Constraints of Climate Sensitivity

Abstract

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO ₂ ) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable to a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, andmore »« less

Authors:

Qu, Xin ^[1]; Hall, Alex ^[1]; DeAngelis, Anthony M. ^[1]; Zelinka, Mark D. ^[2]; Klein, Stephen A. ^[2]; Su, Hui ^[3]; Tian, Baijun ^[3]; Zhai, Chengxing ^[3]

Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California
Cloud Processes Research Group, Lawrence Livermore National Laboratory, Livermore, California
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

Publication Date:: Mon Jan 01 00:00:00 EST 2018

Research Org.:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1416651

Alternate Identifier(s):: OSTI ID: 1418937

Report Number(s):: LLNL-JRNL-729272
Journal ID: ISSN 0894-8755

Grant/Contract Number:: AC52-07NA27344

Resource Type:: Published Article

Journal Name:: Journal of Climate

Additional Journal Information:: Journal Name: Journal of Climate Journal Volume: 31 Journal Issue: 2; Journal ID: ISSN 0894-8755

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 58 GEOSCIENCES; Climate change; Climate sensitivity; Clouds; Feedback; Climate models

Citation Formats


                    Qu, Xin, Hall, Alex, DeAngelis, Anthony M., Zelinka, Mark D., Klein, Stephen A., Su, Hui, Tian, Baijun, and Zhai, Chengxing. On the Emergent Constraints of Climate Sensitivity.  United States: N. p., 2018. 
Web.  doi:10.1175/JCLI-D-17-0482.1.

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                    Qu, Xin, Hall, Alex, DeAngelis, Anthony M., Zelinka, Mark D., Klein, Stephen A., Su, Hui, Tian, Baijun, & Zhai, Chengxing. On the Emergent Constraints of Climate Sensitivity.  United States.  https://doi.org/10.1175/JCLI-D-17-0482.1

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                    Qu, Xin, Hall, Alex, DeAngelis, Anthony M., Zelinka, Mark D., Klein, Stephen A., Su, Hui, Tian, Baijun, and Zhai, Chengxing. Mon .  
"On the Emergent Constraints of Climate Sensitivity".  United States.  https://doi.org/10.1175/JCLI-D-17-0482.1.

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@article{osti_1416651,

  title        = {On the Emergent Constraints of Climate Sensitivity},

  author       = {Qu, Xin and Hall, Alex and DeAngelis, Anthony M. and Zelinka, Mark D. and Klein, Stephen A. and Su, Hui and Tian, Baijun and Zhai, Chengxing},

  abstractNote = {Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO 2 ) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable to a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. In addition, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.},

  doi          = {10.1175/JCLI-D-17-0482.1},

  journal      = {Journal of Climate},

  number       = 2,

  volume       = 31,

  place        = {United States},

  year         = {Mon Jan 01 00:00:00 EST 2018},

  month        = {Mon Jan 01 00:00:00 EST 2018}

}

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Works referencing / citing this record:

Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects
journal, December 2019

Brient, Florent
Advances in Atmospheric Sciences, Vol. 37, Issue 1
DOI: 10.1007/s00376-019-9140-8

Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects
journal, December 2019

Brient, Florent
Advances in Atmospheric Sciences, Vol. 37, Issue 1
DOI: 10.1007/s00376-019-9140-8

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Title: On the Emergent Constraints of Climate Sensitivity

Abstract

Citation Formats

Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects journal, December 2019

Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects journal, December 2019

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journal, December 2019

Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects
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