A lower and more constrained estimate of climate sensitivity using updated observations and detailed radiative forcing time series

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Abstract

Equilibrium climate sensitivity (ECS) is constrained based on observed near-surface temperature change, changes in ocean heat content (OHC) and detailed radiative forcing (RF) time series from pre-industrial times to 2010 for all main anthropogenic and natural forcing mechanism. The RF time series are linked to the observations of OHC and temperature change through an energy balance model (EBM) and a stochastic model, using a Bayesian approach to estimate the ECS and other unknown parameters from the data. For the net anthropogenic RF the posterior mean in 2010 is 2.0 Wm-2, with a 90% credible interval (C.I.) of 1.3 to 2.8 Wm-2, excluding present-day total aerosol effects (direct + indirect) stronger than-1.7 Wm2. The posterior mean of the ECS is 1.8° C, with 90% C.I. ranging from 0.9 to 3.2 °C, which is tighter than most previously published estimates. We find that using three OHC data sets simultaneously and data for global mean temperature and OHC up to 2010 substantially narrows the range in ECS compared to using less updated data and only one OHC data set. Using only one OHC set and data up to 2000 can produce comparable results as previously published estimates using observations in the 20th century, including the heavy tail in the probability function. The analyses show a significant contribution of internal variability on a multi-decadal scale to the global mean temperature change. If we do not explicitly account for long-term internal variability, the 90% C.I. is 40% narrower than in the main analysis and the mean ECS becomes slightly lower, which demonstrates that the uncertainty in ECS may be severely underestimated if the method is too simple. In addition to the uncertainties represented through the estimated probability density functions, there may be uncertainties due to limitations in the treatment of the temporal development in RF and structural uncertainties in the EBM. © 2014 Author (s).

Figures

  • Fig. 1. Prior and posterior distribution of the RF time series and PDF of RF in 2010 for total RF (upper panel), anthropogenic RF (middle panel) and total aerosol effect (direct effect, cloud albedo effect, cloud lifetime effect and semi-direct effect) (lower panel) from the main analysis. Red colour for the posterior distributions and black lines and grey shadings for the prior distribution.
  • Fig. 2. Posterior distributions for the ECS for different analyses. In (a) the main analysis, (b) with NorESM data to estimate nlivt , (c) sensitivity test using HadCRUT4 instead of HadCRUT3 data, (d) sensitivity test using data for OHC change below 700 m, (e) sensitivity test allowing different ECSs in each hemisphere, (f) updating the model with data only up to 2000, (g) updating the model with data only up to 2000 and using only one OHC data series and (h) sensitivity test without the long-term internal variability (without the nlivt term). The estimated mean of ECS, the 90 % C.I. and the probability of ECS being larger than 4.5 ◦C are given in the text box of each panel. The 90 % C.I. (the error bar) and estimated posterior mean (triangle) and median (black dot) are also indicated in each panel.
  • Fig. 3. Observed and fitted (posterior mean) values for the temperature series and the ocean heat content for the main analysis. The shaded areas show the 90 % C.I. for the sum of the two first terms (mt (x1750:t , ECS, θ )+β1 et ) on the right side of Eq. (1).
  • Fig. 4. Posterior estimates of the long-term internal variability term (nlivt , left column), the ENSO term (β1 et , middle column) and the model errors (nmt , right column) for the temperature and ocean heat content.
  • Fig. 5. Posterior means (triangles), medians (dots), modes (crosses), and 90 % credible intervals for estimates of ECS using various data sets updated between 2000 and 2010 (2 yr intervals). The relative uncertainty measure R90, defined as the width of the 90 % C.I. divided by the posterior mean, is also shown.
  • Table 1. The RF mechanisms included with information on the prior distribution assumed and the prior mean value and the 90 % confidence interval in the year 2010. The RF values are relative to 1750.

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CITATION STYLE

APA

Skeie, R. B., Berntsen, T., Aldrin, M., Holden, M., & Myhre, G. (2014). A lower and more constrained estimate of climate sensitivity using updated observations and detailed radiative forcing time series. Earth System Dynamics, 5(1), 139–175. https://doi.org/10.5194/esd-5-139-2014

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