Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part II: Climate Sensitivity

Simon F. B. Tett*, Daniel J. Rowlands, Michael J. Mineter, Coralia Cartis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

A large number of perturbed-physics simulations of version 3 of the Hadley Centre Atmosphere Model (HadAM3) were compared with the Clouds and the Earth's Radiant Energy System (CERES) estimates of outgoing longwave radiation (OLR) and reflected shortwave radiation (RSR) as well as OLR and RSR from the earlier Earth Radiation Budget Experiment (ERBE) estimates. The model configurations were produced from several independent optimization experiments in which four parameters were adjusted. Model-observation uncertainty was estimated by combining uncertainty arising from satellite measurements, observational radiation imbalance, total solar irradiance, radiative forcing, natural aerosol, internal climate variability, and sea surface temperature and that arising from parameters that were not varied. Using an emulator built from 14 001 slab model evaluations carried out using the ensemble, the climate sensitivity for each configuration was estimated. Combining different prior probabilities for model configurations with the likelihood for each configuration and taking account of uncertainty in the emulated climate sensitivity gives, for the HadAM3 model, a 2.5%-97.5% range for climate sensitivity of 2.7-4.2 K if the CERES observations are correct. If the ERBE observations are correct, then they suggest a larger range, for HadAM3, of 2.8-5.6 K. Amplifying the CERES observational covariance estimate by a factor of 20 brings CERES and ERBE estimates into agreement. In this case the climate sensitivity range is 2.7-5.4 K. The results rule out, at the 2.5% level for HadAM3 and several different prior assumptions, climate sensitivities greater than 5.6 K.

Original languageEnglish
Pages (from-to)9367-9383
Number of pages17
JournalJournal of Climate
Issue number23
Early online date24 Jul 2013
Publication statusPublished - Dec 2013

Keywords / Materials (for Non-textual outputs)

  • Climate sensitivity
  • Bayesian methods
  • Climate models


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