Articles | Volume 11, issue 2
https://doi.org/10.5194/esd-11-347-2020
https://doi.org/10.5194/esd-11-347-2020
Research article
 | 
21 Apr 2020
Research article |  | 21 Apr 2020

Bayesian deconstruction of climate sensitivity estimates using simple models: implicit priors and the confusion of the inverse

James D. Annan and Julia C. Hargreaves

Related authors

Can we reliably reconstruct the mid-Pliocene Warm Period with sparse data and uncertain models?
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, Erin McClymont, and Sze Ling Ho
Clim. Past, 20, 1989–1999, https://doi.org/10.5194/cp-20-1989-2024,https://doi.org/10.5194/cp-20-1989-2024, 2024
Short summary
A new global surface temperature reconstruction for the Last Glacial Maximum
James D. Annan, Julia C. Hargreaves, and Thorsten Mauritsen
Clim. Past, 18, 1883–1896, https://doi.org/10.5194/cp-18-1883-2022,https://doi.org/10.5194/cp-18-1883-2022, 2022
Short summary
Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020,https://doi.org/10.5194/cp-16-1847-2020, 2020
Short summary
A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020,https://doi.org/10.5194/cp-16-1715-2020, 2020
Short summary
What could we learn about climate sensitivity from variability in the surface temperature record?
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
Earth Syst. Dynam., 11, 709–719, https://doi.org/10.5194/esd-11-709-2020,https://doi.org/10.5194/esd-11-709-2020, 2020
Short summary

Related subject area

Earth system change: climate prediction
Past and future response of the North Atlantic warming hole to anthropogenic forcing
Saïd Qasmi
Earth Syst. Dynam., 14, 685–695, https://doi.org/10.5194/esd-14-685-2023,https://doi.org/10.5194/esd-14-685-2023, 2023
Short summary
Performance-based sub-selection of CMIP6 models for impact assessments in Europe
Tamzin E. Palmer, Carol F. McSweeney, Ben B. B. Booth, Matthew D. K. Priestley, Paolo Davini, Lukas Brunner, Leonard Borchert, and Matthew B. Menary
Earth Syst. Dynam., 14, 457–483, https://doi.org/10.5194/esd-14-457-2023,https://doi.org/10.5194/esd-14-457-2023, 2023
Short summary
Emergent constraints for the climate system as effective parameters of bulk differential equations
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023,https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Ensemble forecast of an index of the Madden–Julian Oscillation using a stochastic weather generator based on circulation analogs
Meriem Krouma, Riccardo Silini, and Pascal Yiou
Earth Syst. Dynam., 14, 273–290, https://doi.org/10.5194/esd-14-273-2023,https://doi.org/10.5194/esd-14-273-2023, 2023
Short summary
Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model
Hongmei Li, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz
Earth Syst. Dynam., 14, 101–119, https://doi.org/10.5194/esd-14-101-2023,https://doi.org/10.5194/esd-14-101-2023, 2023
Short summary

Cited articles

Aldrin, M., Holden, M., Guttorp, P., Skeie, R. B., Myhre, G., and Berntsen, T. K.: Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content, Environmetrics, 23, 253–271, https://doi.org/10.1002/env.2140, 2012. a, b
Annan, J. D. and Hargreaves, J. C.: Using multiple observationally-based constraints to estimate climate sensitivity, Geophys. Res. Lett., 33, L06704, https://doi.org/10.1029/2005GL025259, 2006. a, b, c, d, e, f
Annan, J. D. and Hargreaves, J. C.: On the generation and interpretation of probabilistic estimates of climate sensitivity, Climatic Change, 104, 423–436, https://doi.org/10.1007/s10584-009-9715-y, 2011. a, b, c
Annan, J. D. and Hargreaves, J. C.: A new global reconstruction of temperature changes at the Last Glacial Maximum, Clim.e Past, 9, 367–376, https://doi.org/10.5194/cp-9-367-2013, 2013. a, b
Bernardo, J. and Smith, A.: Bayesian Theory, Wiley, Chichester, UK, 1994. a
Download
Short summary
We explore the implicit assumptions that underlie many published probabilistic estimates of the equilibrium climate sensitivity – that is, the amount the climate will warm under a doubling of the atmospheric CO2 concentration. We demonstrate that many such estimates have made assumptions that would be difficult to justify and show how the calculations can be repeated in a more defensible manner. Our results show some significant differences from previous calculations.
Altmetrics
Final-revised paper
Preprint