Regular Article

What is the effect of unresolved internal climate variability on climate sensitivity estimates?

R. Olson

Department of Geosciences, Penn State University, University Park, Pennsylvania, USA

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R. Sriver

Department of Atmospheric Sciences, University of Illinois at Urbana‒Champaign, Urbana, Illinois, USA

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W. Chang

Department of Statistics, Penn State University, University Park, Pennsylvania, USA

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M. Haran

Department of Statistics, Penn State University, University Park, Pennsylvania, USA

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N. M. Urban

Computational Physics and Methods (CCS‒2), Los Alamos National Laboratory, Los Alamos, New Mexico, USA

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K. Keller

Department of Geosciences, Penn State University, University Park, Pennsylvania, USA

Earth and Environmental Systems Institute, Penn State University, University Park, Pennsylvania, USA

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First published: 8 April 2013
Cited by: 5
Corresponding author: R. Olson, Department of Geosciences, Penn State University, University Park, PA, USA. (rzt2-wrk@psu.edu)

Abstract

[1] Many studies have attempted to estimate the equilibrium climate sensitivity (CS) to the doubling of CO2concentrations. One common methodology is to compare versions of Earth models of intermediate complexity (EMICs) to spatially and/or temporally averaged historical observations. Despite the persistent efforts, CS remains uncertain. It is, thus far, unclear what is driving this uncertainty. Moreover, the effects of the internal climate variability on the CS estimates obtained using this method have not received thorough attention in the literature. Using a statistical approximator (“emulator”) of an EMIC, we show in an observation system simulation study that unresolved internal climate variability appears to be a key driver of CS uncertainty (as measured by the 68% credible interval). We first simulate many realizations of pseudo‒observations from an emulator at a “true” prescribed CS, and then reestimate the CS using the pseudo‒observations and an inverse parameter estimation method. We demonstrate that a single realization of the internal variability can result in a sizable discrepancy between the best CS estimate and the truth. Specifically, the average discrepancy is 0.84°C, with the feasible range up to several °C. The results open the possibility that recent climate sensitivity estimates from global observations and EMICs are systematically considerably lower or higher than the truth, since they are typically based on the same realization of climate variability. This possibility should be investigated in future work. We also find that estimation uncertainties increase at higher climate sensitivities, suggesting that a high CS might be difficult to detect.

Number of times cited: 5

  • , The value of knowledge accumulation on climate sensitivity uncertainty: comparison between perfect information, single stage and act then learn decisions, Sustainability Science
  • , Predicting future uncertainty constraints on global warming projections, Scientific Reports, 6, 1
  • , Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections, Journal of Climate, 28, 2, (838)
  • , Estimating climate sensitivity and future temperature in the presence of natural climate variability, Geophysical Research Letters, 41, 6, (2086-2092), (2014).
  • , Beyond equilibrium climate sensitivity, Nature Geoscience, 10.1038/ngeo3017, 10, 10, (727-736), (2017).