scholarly journals Relating Climate Sensitivity Indices to projection uncertainty

2019 ◽  
Author(s):  
Benjamin Sanderson
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Internal Variability ◽  
Surprising Result ◽  
Mitigation Scenario ◽  
Global Response ◽  
Transient Climate Response ◽  
Sensitivity Indices ◽  
Future Warming ◽  
Single Number

Abstract. Can we summarize uncertainties in global response to greenhouse gas forcing with a single number? Here we assess the degree to which traditional metrics are related to future warming indices using an ensemble of simple climate models together with results from CMIP5 and CMIP6. We consider Effective Climate Sensitivity (EffCS), Transient Climate Response at CO2 quadrupling (T140) and a proposed simple metric of temperature change 140 years after a quadrupling of carbon dioxide (A140). In a perfectly equilibrated model, future temperatures under a non-mitigation scenario are almost perfectly described by T140, whereas in a strongly mitigated future, both ECS and T140 are found to be poor predictors of 21st century warming, and future temperatures are better correlated with A140. However, we show that T140 and EffCS calculated in full CMIP simulations are subject to errors arising from control model drift and internal variability. Simulating these factors in the simple model leads to 30 % relative error in the measured value of T140, but only a 10 % error for EffCS. As such, measured values of EffCS can be better correlated with true TCR than measured values of TCR itself. We propose that this could be an explanatory factor in the previously noted surprising result that EffCS is a better predictor than TCR of future transient warming under RCP8.5.

scholarly journals Relating climate sensitivity indices to projection uncertainty

2020 ◽  
Vol 11 (3) ◽  
pp. 721-735 ◽  
Author(s):  
Benjamin Sanderson
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Surprising Result ◽  
Transient Climate Response ◽  
Sensitivity Indices ◽  
Project Phases ◽  
Single Number ◽  
Relative Errors

Abstract. Can we summarize uncertainties in global response to greenhouse gas forcing with a single number? Here, we assess the degree to which traditional metrics are related to future warming indices using an ensemble of simple climate models together with results from the Coupled Model Intercomparison Project phases 5 and 6 (CMIP5 and CMIP6). We consider effective climate sensitivity (EffCS), transient climate response (TCR) at CO2 quadrupling (T140) and a proposed simple metric of temperature change 140 years after a quadrupling of carbon dioxide (A140). In a perfectly equilibrated model, future temperatures under RCP8.5 (Representative Concentration Pathway 8.5) are almost perfectly described by T140, whereas in a mitigation scenario such as RCP2.6, both EffCS and T140 are found to be poor predictors of 21st century warming, and future temperatures are better correlated with A140. We show further that T140 and EffCS calculated in full CMIP simulations are subject to errors arising from control model drift and internal variability, with greater relative errors in estimation for T140. As such, if starting from a non-equilibrated state, measured values of effective climate sensitivity can be better correlated with true TCR than measured values of TCR itself. We propose that this could be an explanatory factor in the previously noted surprising result that EffCS is a better predictor than TCR of future transient warming under RCP8.5.

scholarly journals On the climate sensitivity and historical warming evolution in recent coupled model ensembles

2020 ◽  
Vol 20 (13) ◽  
pp. 7829-7842 ◽  
Author(s):  
Clare Marie Flynn ◽  
Thorsten Mauritsen
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Transient Climate Response ◽  
Antarctic Sea Ice ◽  
Intercomparison Project ◽  
Future Warming ◽  
Model Treatment ◽  
Model Ensembles

Abstract. The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased to 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models, despite an increase in TCR between CMIP eras (mean TCR increased from 1.7 to 1.9 K). The evolution of the warming suggests, however, that several of the CMIP6 models apply too strong aerosol cooling, resulting in too weak mid-20th century warming compared to the instrumental record.

scholarly journals The Impact of Recent Forcing and Ocean Heat Uptake Data on Estimates of Climate Sensitivity

2018 ◽  
Vol 31 (15) ◽  
pp. 6051-6071 ◽  
Author(s):  
Nicholas Lewis ◽  
Judith Curry
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Temperature Data ◽  
Historical Period ◽  
Climate Feedbacks ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Surface Temperature Change ◽  
Aerosol Forcing ◽  
The Impact

Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived based on the best estimates and uncertainty ranges for forcing provided in the IPCC Fifth Assessment Report (AR5). Recent revisions to greenhouse gas forcing and post-1990 ozone and aerosol forcing estimates are incorporated and the forcing data extended from 2011 to 2016. Reflecting recent evidence against strong aerosol forcing, its AR5 uncertainty lower bound is increased slightly. Using an 1869–82 base period and a 2007–16 final period, which are well matched for volcanic activity and influence from internal variability, medians are derived for ECS of 1.50 K (5%–95% range: 1.05–2.45 K) and for TCR of 1.20 K (5%–95% range: 0.9–1.7 K). These estimates both have much lower upper bounds than those from a predecessor study using AR5 data ending in 2011. Using infilled, globally complete temperature data give slightly higher estimates: a median of 1.66 K for ECS (5%–95% range: 1.15–2.7 K) and 1.33 K for TCR (5%–95% range: 1.0–1.9 K). These ECS estimates reflect climate feedbacks over the historical period, assumed to be time invariant. Allowing for possible time-varying climate feedbacks increases the median ECS estimate to 1.76 K (5%–95% range: 1.2–3.1 K), using infilled temperature data. Possible biases from non–unit forcing efficacy, temperature estimation issues, and variability in sea surface temperature change patterns are examined and found to be minor when using globally complete temperature data. These results imply that high ECS and TCR values derived from a majority of CMIP5 climate models are inconsistent with observed warming during the historical period.

scholarly journals On the Climate Sensitivity and Historical Warming Evolution in Recent Coupled Model Ensembles

2020 ◽  
Author(s):  
Clare Marie Flynn ◽  
Thorsten Mauritsen
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Antarctic Sea Ice ◽  
Intercomparison Project ◽  
Future Warming ◽  
Model Treatment ◽  
Systematic Shift ◽  
Model Ensembles

Abstract. The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient 35 climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased: 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles, and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models; the evolution of the warming suggests, however, that several of the models apply too strong aerosol cooling resulting in too weak mid 20th Century warming compared to the instrumental record.

scholarly journals Estimating Remaining Carbon Budgets Using Emulators of CMIP6 Models

2021 ◽  
Author(s):  
Martin Rypdal ◽  
Niklas Boers ◽  
Hege-Beate Fredriksen ◽  
Kai-Uwe Eiselt ◽  
Andreas Johansen ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Climate Sensitivity ◽  
Carbon Budget ◽  
Climate Models ◽  
Coupled Model ◽  
High Sensitivity ◽  
Earth System ◽  
Transient Climate Response ◽  
Uncertainty Range ◽  
Intercomparison Project

Abstract A remaining carbon budget (RCB) estimates how much CO2 we can emit and still reach a specific temperature target. The RCB concept is attractive since it easily communicates to the public and policymakers, but RCBs are also subject to uncertainties. The expected warming levels for a given carbon budget has a wide uncertainty range, which we show here to increase with less ambitious targets, i.e., with higher CO2 emissions and temperatures. Leading causes of RCB uncertainty are the future non-CO2 emissions, Earth system feedbacks, and the spread in the climate sensitivity among climate models. The latter is investigated in this paper, using simple emulators of Earth System Models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble. It is shown that the transient climate response to cumulative emissions of carbon (TCRE) is approximately proportional to the effective equilibrium climate sensitivity (ECS). For temperature targets between 1.5-3.0 degrees C, the models exhibiting low ECS increase RCB by a factor two compared to those with high sensitivity, suggesting that observational constraints imposed on the ECS in the model ensemble also will reduce uncertainty in the RCB estimates.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

scholarly journals An observation-based scaling model for climate sensitivity estimates and global projections to 2100

2020 ◽  
Author(s):  
Raphaël Hébert ◽  
Shaun Lovejoy ◽  
Bruno Tremblay
Keyword(s):  
Climate Sensitivity ◽  
Coupled Model ◽  
Internal Variability ◽  
Forced Response ◽  
Scaling Exponent ◽  
Climate Response ◽  
Transient Climate Response ◽  
Rcp 8.5 ◽  
Historical Temperature ◽  
Inner Scale

AbstractWe directly exploit the stochasticity of the internal variability, and the linearity of the forced response to make global temperature projections based on historical data and a Green’s function, or Climate Response Function (CRF). To make the problem tractable, we take advantage of the temporal scaling symmetry to define a scaling CRF characterized by the scaling exponent H, which controls the long-range memory of the climate, i.e. how fast the system tends toward a steady-state, and an inner scale $$\tau \approx 2$$ τ ≈ 2   years below which the higher-frequency response is smoothed out. An aerosol scaling factor and a non-linear volcanic damping exponent were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference which allows us to analytically calculate the transient climate response and the equilibrium climate sensitivity as: $$1.7^{+0.3} _{-0.2}$$ 1 . 7 - 0.2 + 0.3   K and $$2.4^{+1.3} _{-0.6}$$ 2 . 4 - 0.6 + 1.3   K respectively (likely range). Projections to 2100 according to the RCP 2.6, 4.5 and 8.5 scenarios yield warmings with respect to 1880–1910 of: $$1.5^{+0.4}_{-0.2}K$$ 1 . 5 - 0.2 + 0.4 K , $$2.3^{+0.7}_{-0.5}$$ 2 . 3 - 0.5 + 0.7   K and $$4.2^{+1.3}_{-0.9}$$ 4 . 2 - 0.9 + 1.3   K. These projection estimates are lower than the ones based on a Coupled Model Intercomparison Project phase 5 multi-model ensemble; more importantly, their uncertainties are smaller and only depend on historical temperature and forcing series. The key uncertainty is due to aerosol forcings; we find a modern (2005) forcing value of $$[-1.0, -0.3]\, \,\,\mathrm{Wm} ^{-2}$$ [ - 1.0 , - 0.3 ] Wm - 2 (90 % confidence interval) with median at $$-0.7 \,\,\mathrm{Wm} ^{-2}$$ - 0.7 Wm - 2 . Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to RCP 2.6 for which the probability to remain under 1.5 K is 48 %. RCP 4.5 and RCP 8.5-like futures overshoot with very high probability.

Uncertainty quantification of climate sensitivity: State-dependence, extreme values and the probability of tipping

2020 ◽  
Author(s):  
Anna von der Heydt
Keyword(s):  
Climate Sensitivity ◽  
Climate Models ◽  
Extreme Values ◽  
State Dependence ◽  
Internal Variability ◽  
Relative Strength ◽  
Climate System ◽  
Ice Age ◽  
System Sensitivity ◽  
Time Scale Separation

<p>The Equilibrium Climate Sensitivity (ECS) remains not very well constrained, either by climate models, observational, historical or palaeoclimate data. In particular, large values of warming as a consequence of atmospheric greenhouse gas increase cannot be excluded. Interestingly, some of the most recent state-of-the-art climate models (CMIP6) suggest much more warming than previous generations of climate models. Next to the classical (measurement) uncertainty, the spread in ECS values is due to dynamical aspects: </p><ol><li>The climate system has strong internal variability on many timescales such that the 'equilibrium' will only be relative to fixing slow processes. This implies the assumption that time scale separation exists and ECS values from palaeoclimate time series can be compared to short model simulations. Palaeoclimate records often determine the Earth System Sensitivity, which includes the integrated effect of slow processes and boundary conditions (e.g. geography, vegetation and land ice).</li> <li>The background state dependence of fast feedback processes: Information from the late Pleistocene ice age cycles indicates that ECS varies considerably between regime because of fast feedback processes changing their relative strength over one cycle.</li> <li>Tipping elements in the climate system: Extreme values of palaeo-derived ECS suggest that the climate response is in a region where the assumption of linear response to perturbations breaks down. </li> </ol><p>Here we show for climate system models with more than one regime and occasional switches between these regimes, we can empirically determine probability of change in regime and confirm that extremes of climate sensitivity are associated with very high probabilities of tipping.</p>

scholarly journals Past warming trend constrains future warming in CMIP6 models

2020 ◽  
Author(s):  
Martin Stolpe ◽  
Katarzyna Tokarska ◽  
Sebastian Sippel ◽  
Erich Fischer ◽  
Christopher Smith ◽  
...  
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Warming Trend ◽  
Paris Agreement ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Mitigation Scenario ◽  
Future Global Warming ◽  
Intercomparison Project ◽  
Future Warming

<div>Future global warming estimates have been similar across past assessments, but several climate models of the latest Sixth Coupled Model Intercomparison Project (CMIP6) simulate much stronger warming, apparently inconsistent with past assessments. Here we show that projected future warming is correlated with the simulated warming trend during recent decades across CMIP5 and CMIP6 models, enabling us to constrain future warming based on consistency with the observed warming. These findings carry important policy-relevant implications: the observationally-constrained CMIP6 median warming in high emissions and ambitious mitigation scenarios is over 16% and 14% lower by 2050 compared to the raw CMIP6 median, respectively, and over 14% and 8% lower by 2090, relative to 1995-2014. Observationally-constrained CMIP6 warming is consistent with previous assessments based on CMIP5 models, and in an ambitious mitigation scenario, the likely range is consistent with reaching the Paris Agreement target.</div><div> </div><div>Reference: </div><div>Tokarska, K.B.<sup>†</sup>, Stolpe, M.B.<sup>†</sup>, Sippel, S., Fischer, E.M., Smith, C.J., Lehner, F., and Knutti, R. (2020). Past warming trend constrains future warming in CMIP6 models. <em>Science Advances</em>  (accepted).</div><div><sup>†</sup>equal first authors</div>

scholarly journals Estimating remaining carbon budgets using temperature responses informed by CMIP6

2021 ◽  
Author(s):  
Martin Rypdal ◽  
Niklas Boers ◽  
Hege-Beate Fredriksen ◽  
Kai-Uwe Eiselt ◽  
Andreas Johansen ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Climate Sensitivity ◽  
Carbon Budget ◽  
Climate Models ◽  
Earth System ◽  
Model Ensemble ◽  
Transient Climate Response ◽  
Carbon Cycle Model ◽  
Uncertainty Range ◽  
Temperature Responses

Abstract A remaining carbon budget (RCB) estimates how much CO2 we can emit and still reach a specific temperature target. The RCB concept is attractive since it easily communicates to the public and policymakers, but RCBs are also subject to uncertainties. The expected warming levels for a given carbon budget has a wide uncertainty range, which increases with less ambitious targets, i.e., with higher CO2 emissions and temperatures. Leading causes of RCB uncertainty are the future non-CO2 emissions, Earth system feedbacks, and the spread in the climate sensitivity among climate models. The latter is investigated in this paper, using a simple carbon cycle model and emulators of the temperature responses of the Earth System Models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble. Driving 41 CMIP6 emulators with 127 different emission scenarios for the 21st century, we find almost perfect linear relationship between maximum global surface air temperature and cumulative carbon emissions, allowing unambiguous estimates of RCB for each CMIP6 model. The range of these estimates over the model ensemble is a measure of the uncertainty in the RCB arising from the range in climate sensitivity over this ensemble, and it is suggested that observational constraints imposed on the transient climate response in the model ensemble can reduce uncertainty in RCB estimates.

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