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Title: On the Emergent Constraints of Climate Sensitivity [On proposed 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 CO2) 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 linksmore » with that feedback should be investigated to verify that the constraint is real. Additionally, 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.« less

Authors:
 [1];  [1];  [1];  [2];  [2];  [3];  [3];  [3]
  1. Univ. of California, Los Angeles, CA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. California Inst. of Technology (CalTech), Pasadena, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1418937
Report Number(s):
LLNL-JRNL-729272
Journal ID: ISSN 0894-8755
Grant/Contract Number:
AC52-07NA27344
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Climate
Additional Journal Information:
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 [On proposed emergent constraints of climate sensitivity]. United States: N. p., 2018. Web. doi:10.1175/JCLI-D-17-0482.1.
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 [On proposed emergent constraints of climate sensitivity]. United States. doi:10.1175/JCLI-D-17-0482.1.
Qu, Xin, Hall, Alex, DeAngelis, Anthony M., Zelinka, Mark D., Klein, Stephen A., Su, Hui, Tian, Baijun, and Zhai, Chengxing. 2018. "On the Emergent Constraints of Climate Sensitivity [On proposed emergent constraints of climate sensitivity]". United States. doi:10.1175/JCLI-D-17-0482.1.
@article{osti_1418937,
title = {On the Emergent Constraints of Climate Sensitivity [On proposed 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 CO2) 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. Additionally, 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 = 2018,
month = 1
}

Journal Article:
Free Publicly Available Full Text
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  • Emergent constraints are physically explainable empirical relationships between characteristics of the current climate and long-term climate prediction that emerge in collections of climate model simulations. With the prospect of constraining long-term climate prediction, scientists have recently uncovered several emergent constraints related to long-term cloud feedbacks. We review these proposed emergent constraints, many of which involve the behavior of low-level clouds, and discuss criteria to assess their credibility. With further research, some of the cases we review may eventually become confirmed emergent constraints, provided they are accompanied by credible physical explanations. Because confirmed emergent constraints identify a source of model errormore » that projects onto climate predictions, they deserve extra attention from those developing climate models and climate observations. While a systematic bias cannot be ruled out, it is noteworthy that the promising emergent constraints suggest larger cloud feedback and hence climate sensitivity.« less
  • Global climate model (GCM) estimates of the equilibrium global mean surface temperature response to a doubling of atmospheric CO2, measured by the equilibrium climate sensitivity (ECS), range from 2.0° to 4.6°C. Clouds are among the leading causes of this uncertainty. Here we show that the ECS can be up to 1.3°C higher in simulations where mixed-phase clouds consisting of ice crystals and supercooled liquid droplets are constrained by global satellite observations. The higher ECS estimates are directly linked to a weakened cloud-phase feedback arising from a decreased cloud glaciation rate in a warmer climate. We point out the need formore » realistic representations of the supercooled liquid fraction in mixed-phase clouds in GCMs, given the sensitivity of the ECS to the cloud-phase feedback.« less
  • Companies face much uncertainty about the competitive effects of the recently adopted Kyoto Protocol on global climate change and the current and future regulations that may emerge from it. Companies have considerable discretion to explore different market strategies to address global warming and reduce greenhouse gas emissions. This article examines these strategic options by reviewing the market-oriented actions that are currently being taken by 136 large companies that are part of the Global 500. There are six different market strategies that companies use to address climate change and that consist of different combinations of the market components available to managers.more » Managers can choose between more emphasis on improvements in their business activities through innovation or employ compensatory approaches such as emissions trading. They can either act by themselves or work with other companies, NGOs, or (local) governments.« less