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:
-
[1];
[2];
[3];
[1]
- NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States); Columbia Univ., New York, NY (United States)
- Univ. of Colorado, Boulder, CO (United States); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.
- 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. https://doi.org/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. https://doi.org/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 = {Mon Jan 29 00:00:00 EST 2018},
month = {Mon Jan 29 00:00:00 EST 2018}
}
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