Articles | Volume 9, issue 2
https://doi.org/10.5194/esd-9-879-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-9-879-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
21 Jun 2018
Research article | Highlight paper |
| 21 Jun 2018
| 21 Jun 2018
Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data
Ragnhild Bieltvedt Skeie
CORRESPONDING AUTHOR
CICERO-Center for International Climate and Environmental Research – Oslo, P.O. Box 1129 Blindern, 0318 Oslo, Norway
Terje Berntsen
CICERO-Center for International Climate and Environmental Research – Oslo, P.O. Box 1129 Blindern, 0318 Oslo, Norway
Department of Geosciences, University of Oslo, P.O. Box 1047 Blindern, 0316 Oslo, Norway
Magne Aldrin
Norwegian Computing Center, P.O. Box 114 Blindern, 0314 Oslo, Norway
Marit Holden
Norwegian Computing Center, P.O. Box 114 Blindern, 0314 Oslo, Norway
Gunnar Myhre
CICERO-Center for International Climate and Environmental Research – Oslo, P.O. Box 1129 Blindern, 0318 Oslo, Norway
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Cited
21 citations as recorded by crossref.
- Negligible Unforced Historical Pattern Effect on Climate Feedback Strength Found in HadISST-Based AMIP Simulations N. Lewis & T. Mauritsen 10.1175/JCLI-D-19-0941.1
- Observational Constraint on the Climate Sensitivity to Atmospheric CO2 Concentrations Changes Derived from the 1971–2017 Global Energy Budget J. Chenal et al. 10.1175/JCLI-D-21-0565.1
- Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. 10.1029/2019RG000660
- Pacific variability reconciles observed and modelled global mean temperature increase since 1950 M. Stolpe et al. 10.1007/s00382-020-05493-y
- What We Know and Don’t Know about Climate Change, and Implications for Policy R. Pindyck 10.1086/711305
- Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate L. McBride et al. 10.5194/esd-12-545-2021
- The aerosol pathway is crucial for observationally constraining climate sensitivity and anthropogenic forcing R. Skeie et al. 10.5194/esd-15-1435-2024
- Separating internal and externally forced contributions to global temperature variability using a Bayesian stochastic energy balance framework M. Schillinger et al. 10.1063/5.0106123
- Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing L. Regayre et al. 10.5194/acp-23-8749-2023
- Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity C. Smith et al. 10.1029/2020JD033622
- How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change? J. Gregory et al. 10.1007/s00382-019-04991-y
- Assessing Global and Local Radiative Feedbacks Based on AGCM Simulations for 1980–2014/2017 R. Zhang et al. 10.1029/2020GL088063
- Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets P. Goodwin & B. Cael 10.5194/esd-12-709-2021
- The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures J. Kikstra et al. 10.5194/gmd-15-9075-2022
- Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response Z. Nicholls et al. 10.5194/gmd-13-5175-2020
- A future perspective of historical contributions to climate change R. Skeie et al. 10.1007/s10584-021-02982-9
- Origins of a Relatively Tight Lower Bound on Anthropogenic Aerosol Radiative Forcing from Bayesian Analysis of Historical Observations A. Albright et al. 10.1175/JCLI-D-21-0167.1
- Observational constraints on the effective climate sensitivity from the historical period K. Tokarska et al. 10.1088/1748-9326/ab738f
- Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections Z. Nicholls et al. 10.1029/2020EF001900
- Quantifying human contributions to past and future ocean warming and thermosteric sea level rise K. Tokarska et al. 10.1088/1748-9326/ab23c1
- CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool M. Sandstad et al. 10.5194/gmd-17-6589-2024
21 citations as recorded by crossref.
- Negligible Unforced Historical Pattern Effect on Climate Feedback Strength Found in HadISST-Based AMIP Simulations N. Lewis & T. Mauritsen 10.1175/JCLI-D-19-0941.1
- Observational Constraint on the Climate Sensitivity to Atmospheric CO2 Concentrations Changes Derived from the 1971–2017 Global Energy Budget J. Chenal et al. 10.1175/JCLI-D-21-0565.1
- Bounding Global Aerosol Radiative Forcing of Climate Change N. Bellouin et al. 10.1029/2019RG000660
- Pacific variability reconciles observed and modelled global mean temperature increase since 1950 M. Stolpe et al. 10.1007/s00382-020-05493-y
- What We Know and Don’t Know about Climate Change, and Implications for Policy R. Pindyck 10.1086/711305
- Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate L. McBride et al. 10.5194/esd-12-545-2021
- The aerosol pathway is crucial for observationally constraining climate sensitivity and anthropogenic forcing R. Skeie et al. 10.5194/esd-15-1435-2024
- Separating internal and externally forced contributions to global temperature variability using a Bayesian stochastic energy balance framework M. Schillinger et al. 10.1063/5.0106123
- Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing L. Regayre et al. 10.5194/acp-23-8749-2023
- Energy Budget Constraints on the Time History of Aerosol Forcing and Climate Sensitivity C. Smith et al. 10.1029/2020JD033622
- How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change? J. Gregory et al. 10.1007/s00382-019-04991-y
- Assessing Global and Local Radiative Feedbacks Based on AGCM Simulations for 1980–2014/2017 R. Zhang et al. 10.1029/2020GL088063
- Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets P. Goodwin & B. Cael 10.5194/esd-12-709-2021
- The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures J. Kikstra et al. 10.5194/gmd-15-9075-2022
- Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response Z. Nicholls et al. 10.5194/gmd-13-5175-2020
- A future perspective of historical contributions to climate change R. Skeie et al. 10.1007/s10584-021-02982-9
- Origins of a Relatively Tight Lower Bound on Anthropogenic Aerosol Radiative Forcing from Bayesian Analysis of Historical Observations A. Albright et al. 10.1175/JCLI-D-21-0167.1
- Observational constraints on the effective climate sensitivity from the historical period K. Tokarska et al. 10.1088/1748-9326/ab738f
- Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections Z. Nicholls et al. 10.1029/2020EF001900
- Quantifying human contributions to past and future ocean warming and thermosteric sea level rise K. Tokarska et al. 10.1088/1748-9326/ab23c1
- CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool M. Sandstad et al. 10.5194/gmd-17-6589-2024
Latest update: 14 Dec 2024
Short summary
A key question in climate science is how the global mean surface temperature responds to changes in greenhouse gases. This dependency is quantified by the climate sensitivity, which is determined by the complex feedbacks in the climate system. In this study observations of past climate change are used to estimate this sensitivity. Our estimate is consistent with values for the equilibrium climate sensitivity estimated by complex climate models but sensitive to the use of uncertain input data.
A key question in climate science is how the global mean surface temperature responds to changes...
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