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Title: Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations

Abstract

An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979–2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [1]
  1. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Columbia Univ., New York, NY (United States)
  2. Univ. of Colorado, Boulder, CO (United States); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.
  3. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
Publication Date:
Research Org.:
Univ. of Colorado, Boulder, CO (United States); Columbia Univ., New York, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1537310
Grant/Contract Number:  
SC0012549; SC0014423
Resource Type:
Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 45; Journal Issue: 3; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Geology

Citation Formats

Marvel, Kate, Pincus, Robert, Schmidt, Gavin A., and Miller, Ron L. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations. United States: N. p., 2018. Web. doi:10.1002/2017gl076468.
Marvel, Kate, Pincus, Robert, Schmidt, Gavin A., & Miller, Ron L. Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations. United States. doi:10.1002/2017gl076468.
Marvel, Kate, Pincus, Robert, Schmidt, Gavin A., and Miller, Ron L. Mon . "Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations". United States. doi:10.1002/2017gl076468. https://www.osti.gov/servlets/purl/1537310.
@article{osti_1537310,
title = {Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations},
author = {Marvel, Kate and Pincus, Robert and Schmidt, Gavin A. and Miller, Ron L.},
abstractNote = {An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979–2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.},
doi = {10.1002/2017gl076468},
journal = {Geophysical Research Letters},
number = 3,
volume = 45,
place = {United States},
year = {2018},
month = {1}
}

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