Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data

Skeie, Ragnhild Bieltvedt; Berntsen, Terje; Aldrin, Magne; Holden, Matthew T. G.; Myhre, Gunnar

doi:10.5194/esd-9-879-2018

Cited by 29 publications

(29 citation statements)

References 55 publications

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“…We cannot rule out the very high value of ECS, but we assign a low probability based on the IPCC 2013 low likelihood for the needed value of AER RF2011. Our empirically based determination of ECS is in good overall agreement with the recent empirical determinations of Lewis and Grünwald (2018) (1.87°C, range of 1.1-4.05°C) and Skeie et al (2018) (2.0°C, range of 1.2-3.1°C) and the slightly older empirically determination reported by Otto et al (2013) (2.0°C, range of 1.2-3.9°C) (all range values are for the 5 th and 95 th percent confidence interval). Nijsse et al (2020) reported a median value of ECS of 2.6°C (range of 1.52-4.05°C) based upon analysis of CMIP6 output tied to the actual climate record.…”

Section: Discussionsupporting

confidence: 88%

“…Four empirical determinations of ECS (our study plus Lewis and Grünwald (2018), Otto et al (2013), and Skeie et al (2018)) and the CMIP6-based estimate of Nijsse et al (2020) are in slight contrast with the 2.3-4.7°C range for ECS (5 th and 95 th confidence interval) published recently by Sherwood et al…”

Section: Ecscontrasting

confidence: 86%

“…CC BY 4.0 License. the range of 2.3 to 4.7°C at the 5 th to 95 th percent confidence intervals; their lower bound for ECS is quite a bit higher than the lower bound found in our analysis, as well as by Grünwald (2018), Nijsse et al (2020), Otto et al (2013), and Skeie et al (2018).…”

Section: Discussioncontrasting

confidence: 63%

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Comparison of CMIP6 Historical Climate Simulations and Future Projected Warming to an Empirical Model of Global Climate

McBride¹,

Hope²,

Canty³

et al. 2020

Preprint

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Abstract. The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is the latest modeling effort for general circulation models to simulate and project various aspects of climate change. Many of the general circulation models (GCMs) participating in CMIP6 provide archived output that can be used to calculate equilibrium climate sensitivity (ECS) and forecast future temperature change based on emissions scenarios from several Shared Socioeconomic Pathways (SSPs). Here we use our multiple linear regression energy balance model, the Empirical Model of Global Climate (EM-GC), to simulate and project changes in global mean surface temperature (GMST), calculate ECS, and compare to results from the CMIP6 multi-model ensemble. An important aspect of our study is comprehensive analysis of uncertainties due to radiative forcing of climate from tropospheric aerosols (AER RF) in the EM-GC framework. We quantify the attributable anthropogenic warming rate (AAWR) from the climate record using the EM-GC and use AAWR as a metric to determine how well CMIP6 GCMs replicate human-driven global warming over the last forty years. The CMIP6 multi-model ensemble indicates a median value of AAWR over 1975–2014 of 0.217 °C/decade (range of 0.150 to 0.294 °C/decade; all ranges given here are for 5th and 95th confidence intervals), which is notably faster warming than our best estimate for AAWR of 0.135 °C/decade (range of 0.097 to 0.195 °C/decade) inferred from analysis of the Hadley Center Climatic Research Unit data record for GMST. Estimates of ECS found using the EM-GC (best estimate 2.01 °C; range of 1.12 to 4.12 °C) are generally consistent with the range of ECS of 1.5 to 4.5 °C given by IPCC's Fifth Assessment Report. The CMIP6 multi-model ensemble exhibits considerably larger values of ECS (median 3.74 °C; range of 2.19–5.65 °C). The dominant factor in the uncertainty for our empirical determinations of AAWR and ECS is imprecise knowledge of AER RF for the contemporary atmosphere. We calculate the likelihood of achieving the Paris Agreement target (1.5 °C) and upper limit (2.0 °C) of global warming relative to pre-industrial for seven of the SSPs using both the EM-GC and the CMIP6 multi-model ensemble. In our model framework, SSP1-2.6 is the 1.5 °C pathway with a 64.8 % probability of limiting warming at this level by the end of century and SSP4-3.4 is the 2.0 °C pathway, with a 74.0 % probability of achieving the Paris upper limit. In addition, we quantify the sensitivity of future warming to the curbing of the current rapid growth of atmospheric methane and show major near-term limits on the future growth of methane are especially important for achievement of the 1.5 °C goal of future warming. Finally, we assess warming projections in terms of future anthropogenic emissions of atmospheric carbon. In our model framework, humans can emit only another 268 Gt C after 2019 to have a 66 % likelihood of limiting warming to 1.5 °C, and another 565 Gt C to have the same probability of limiting warming to 2.0 °C. Given the current emission of 11.7 Gt C per year due to combustion of fossil fuels and deforestation, our EM-GC simulations suggest the 1.5 °C warming target of the Paris Agreement will not be achieved unless carbon and methane emissions are severely curtailed in the next two decades.

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Section: Discussionsupporting

confidence: 88%

Section: Ecscontrasting

confidence: 86%

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Comparison of CMIP6 Historical Climate Simulations and Future Projected Warming to an Empirical Model of Global Climate

McBride¹,

Hope²,

Canty³

et al. 2020

Preprint

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show abstract

“…The ensemble by Smith et al (2018) has a 16-84% confidence interval for transient climate response of 1.3 to 2.0 K, which translates into a ±1 confidence interval for aerosol ERF of −1.2 to −0.6 W m −2 . Skeie et al (2018) obtain a quantitatively similar relationship between aerosol ERF and transient climate response using an energy balance model.…”

Section: 1029/2019rg000660mentioning

confidence: 99%

Bounding Global Aerosol Radiative Forcing of Climate Change

Bellouin

Quaas

Gryspeerdt

et al. 2020

Reviews of Geophysics

Self Cite

587

348

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Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol‐radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol‐driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed‐phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of ‐1.6 to ‐0.6 W m−2, or ‐2.0 to ‐0.4 W m−2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial‐era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.

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“…3.1; Hansen et al 2005). Therefore historical F is a source of systematic uncertainty in estimating , especially on account of anthropogenic tropospheric aerosol forcing (Gregory et al 2002;Myhre et al 2013;Forster 2016;Skeie et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

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Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data

Cited by 29 publications

References 55 publications

Comparison of CMIP6 Historical Climate Simulations and Future Projected Warming to an Empirical Model of Global Climate

Comparison of CMIP6 Historical Climate Simulations and Future Projected Warming to an Empirical Model of Global Climate

Bounding Global Aerosol Radiative Forcing of Climate Change

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

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