How accurately can the climate sensitivity to $$\hbox {CO}_{2}$$ be estimated from historical climate change?

Abstract

The equilibrium climate sensitivity (ECS, in K) to CO 2 doubling is a large source of uncertainty in projections of future anthropogenic climate change. Estimates of ECS made from non-equilibrium states or in response to radiative forcings other than 2 × CO 2 are called "effective climate sensitivity" (EffCS, in K). Taking a "perfect-model" approach, using coupled atmosphere-ocean general circulation model (AOGCM) experiments, we evaluate the accuracy with which CO 2 EffCS can be estimated from climate change in the "historical" period (since about 1860). We find that (1) for statistical reasons, unforced variability makes the estimate of historical EffCS both uncertain and biased; it is overestimated by about 10% if the energy balance is applied to the entire historical period, 20% for 30-year periods, and larger factors for interannual variability, (2) systematic uncertainty in historical radiative forcing translates into an uncertainty of ± 30 to 45% (standard deviation) in historical EffCS, (3) the response to the changing relative importance of the forcing agents, principally CO 2 and volcanic aerosol, causes historical EffCS to vary over multidecadal timescales by a factor of two. In recent decades it reached its maximum in the AOGCM historical experiment (similar to the multimodel-mean CO 2 EffCS of 3.6 K from idealised experiments), but its minimum in the real world (1.6 K for an observational estimate for 1985-2011, similar to the multimodel-mean value for volcanic forcing). The real-world variations mean that historical EffCS underestimates CO 2 EffCS by 30% when considering the entire historical period. The difference for recent decades implies that either unforced variability or the response to volcanic forcing causes a much stronger regional pattern of sea surface temperature change in the real world than in AOGCMs. We speculate that this could be explained by a deficiency in simulated coupled atmosphere-ocean feedbacks which reinforce the pattern (resembling the Interdecadal Pacific Oscillation in some respects) that causes the low EffCS. We conclude that energy-balance estimates of CO 2 EffCS are most accurate from periods unaffected by volcanic forcing. Atmosphere GCMs provided with observed sea surface temperature for the 1920s to the 1950s, which was such a period, give a range of about 2.0-4.5 K, agreeing with idealised CO 2 AOGCM experiments; the consistency is a reason for confidence in this range as an estimate of CO 2 EffCS. Unless another explosive volcanic eruption occurs, the first 30 years of the present century may give a more accurate energy-balance historical estimate of this quantity.

Observational constraints on the effective climate sensitivity from the historical period

“…The increased greenhouse gas scaling factors, and with it the increase in estimated effective climate sensitivity calculated from the recent period could reflect feedbacks associated with a rapid increase in greenhouse gas forcing. Gregory et al (2019) also find that the effective climate sensitivity is higher since the year 1975 when greenhouse gas forcing has rapidly increased. Alternative approaches have been also suggested to this simple energy balance model (equation (2)) that account for stratospheric adjustments, which are related to the changing feedback parameters (Ceppi and Gregory 2019).…”

Energy budget constraints on historical radiative forcing

“…However they showed their estimate of model radiative forcing was largely robust to this in a single model. Gregory et al 45 estimated the CMIP5 AOGCM-mean hist to be 1.27 Wm -2 K -1 , which is slightly larger than the mean 4x of CMIP5 AOGCMs given by Forster et al 3 ( 4x =1.13 Wm -2 K -1 ). If this difference is representative of the 'pattern effect' between historical and abrupt-4xCO 2 simulations in AOGCMs it suggests the forcing estimates of Forster et al 3 may be biased low by ~0.14 Wm -2 in the multi-model mean, given their AOGCM-mean historical dT of ~1.0 K. Future participation by modelling centres in RFMIP 5 will address this bias uncertainty across the model ensemble in a more definitive way.…”

Heat stored in the Earth system: where does the energy go?

“…In addition, detected instrumental biases in MBTs, XBTs and other instruments pose a further challenge for the global scale OHC estimate (Abraham et al, 2013;Ciais et al, 2013;Rhein et al, 2013), but significant progress has been made recently to correct biases and provide high-quality data for climate research (Boyer et al, 2016;Cheng et al, 2016;Goni et al, 2019;Gouretski and Cheng, 2020). Satellite altimeter measurements of sea surface height began in 1992 and are used to complement in situ-derived OHC estimates, either for validation purposes (Cabanes et al, 2013) or to complement the development of global gridded ocean temperature fields (Guinehut et al, 2012;Willis et al, 2004). Indirect estimates of OHC from remote sensing through the global sea-level budget became possible with satellite-derived ocean mass information in 2002 (Dieng et al, 2017;Llovel et al, 2014;Loeb et al, 2012;Meyssignac et al, 2019;von Schuckmann et al, 2014).…”

“…However, this conceptual picture is complicated by the presence of unforced internal variability in the climate system, which adds substantial noise to the real-world expression of this equation (Gregory et al, 2020;Marvel et al, 2018;Palmer and McNeall, 2014). For example, at timescales from interannual to decadal periods, the phase of the El Niño-Southern Oscillation contributes to both positive or negative variations in EEI (Cheng et al, 2019a;Loeb et al, 2018;Johnson and Birnbaum, 2017;Loeb et al, 2012).…”