Emergent constraint on equilibrium climate sensitivity from global temperature variability

Abstract

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

STAGE 2.0: Sensitivity Transfer Analysis of Greenhouse Emissions

“…In their search of an emergent constraint on ECS, Cox et al (2018) use the simple Hasselmann model (Hasselmann, 1976), relating the variation in global mean temperature ΔT in response to a change in radiative forcing ΔQ (see Appendix A for a 5 transfer-function description of this model). The principle parameter of interest to their analysis is the 'radiative damping coefficient' in their study called the 'climate feedback factor', which with respect to terminology used is somewhat confusing in relation to the feedback factor f and gain g as introduced in Section 3.…”

“…In the following, both scaling models will be contrasted to each 25 other, to demonstrate the sensitivity of long-term effects to short-term 'deviations' from this default value. Of specific interest are the new constraints put on ECS by Cox et al (2018) by analyzing the ability of coupled ocean-atmosphere climate models in the CMIP5 archive to simulate observed variations in climate.…”

“…Recently, estimates of the fast-feedback (Charney) climate sensitivity have been 'narrowed down' by constraining climate models by their ability to simulate observed variations in climate (Nature, Cox et al, 2018). It was concluded that the Charney sensitivity, in their study referred to as the 'Equilibrium climate sensitivity' (ECS), has a central estimate of 2.8 °C for 2×CO2, and a 'likely range' of 2.2-3.4 °C which sits towards the middle to lower end of the current estimate of 1.…”

A mathematical approach to understanding emergent constraints

“…The observable variable is called the predictor, while the variable that is to be constrained is called the predictand (Klein and Hall, 2015). In recent years, emergent 15 constraints have been found for Arctic warming, snow albedo feedback, tropical carbon, the global precipitation among other variables (Allen and Ingram, 2002;Bracegirdle and Stephenson, 2013;Hall and Qu, 2006;Wenzel et al, 2014) and more recently, climate sensitivity (Cox et al, 2018).…”

“…For instance, in Tian (2015) the asymmetry bias in ITCZ is linked to climate sensitivity. An example of a dynamical indirect emergent constraint is provided by Cox et al (2018), who relate a function of autocorrelation of global surface temperature to ECS.…”