Effect of ocean mixing on the transient climate response to a CO2increase: Analysis of recent model results

AbstractThe transient climate response to cumulative carbon emissions (TCRE) is a key metric in estimating the remaining carbon budget for given temperature targets. However, the TCRE has a small scenario dependence that can be non-negligible for stringent temperature targets. To investigate the parametric correlations and scenario dependence of the TCRE, the present study uses a 512-member ensemble of an Earth system model of intermediate complexity (EMIC) perturbing 11 physical and biogeochemical parameters under scenarios with steady increases of 0.25%, 0.5%, 1%, 2%, or 4% per annum (ppa) in the atmospheric CO2 concentration (pCO2), or an initial increase of 1% followed by an annual decrease of 1% thereafter. Although a small difference of 5% (on average) in the TCRE is observed between the 1-ppa and 0.5-ppa scenarios, a significant scenario dependence is found for the other scenarios, with a tendency toward large values in gradual or decline-after-a-peak scenarios and small values in rapidly increasing scenarios. For all scenarios, correlation analysis indicates a remarkably large correlation between the equilibrium climate sensitivity (ECS) and the relative change in the TCRE, which is attributed to the longer response time of the high ECS model. However, the correlations of the ECS with the TCRE and its scenario dependence for scenarios with large pCO2 increase rates are slightly smaller, and those of biogeochemical parameters such as plant respiration and the overall pCO2–carbon cycle feedback are larger, than in scenarios with gradual increases. The ratio of the TCREs under the overshooting (i.e., 1-ppa decrease after a 1-ppa increase) and 1-ppa increase only scenarios had a clear positive relation with zero-emission commitments. Considering the scenario dependence of the TCRE, the remaining carbon budget for the 1.5 °C target could be reduced by 17 or 22% (before and after considering the unrepresented Earth system feedback) for the most extreme case (i.e., the 67th percentile when using the 0.25-ppa scenario as compared to the 1-ppa increase scenario). A single ensemble EMIC is also used to indicate that, at least for high ECS (high percentile) cases, the scenario dependence of the TCRE should be considered when estimating the remaining carbon budget.

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Equilibrium Climate Sensitivity and Transient Climate Response biased low in historical simulations of CMIP6 models

10.1002/essoar.10507840.1 ◽

2021 ◽

Author(s):

Yue Dong ◽

Kyle C. Armour ◽

Cristian Proistosescu ◽

Timothy Andrews ◽

David S. Battisti ◽

...

Keyword(s):

Climate Sensitivity ◽

Climate Response ◽

Transient Climate Response ◽

Equilibrium Climate Sensitivity

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Large ensemble assessment of how the global surface warming response to cumulative carbon differs for negative and positive carbon emissions

10.5194/egusphere-egu21-12718 ◽

2021 ◽

Author(s):

Negar Vakilifard ◽

Katherine Turner ◽

Ric Williams ◽

Philip Holden ◽

Neil Edwards ◽

...

Keyword(s):

Carbon Emissions ◽

Radiative Forcing ◽

Climate Model ◽

Climate Feedback ◽

Climate Response ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Surface Warming ◽

Radiative Processes ◽

Negative Emission

The controls of the effective transient climate response (TCRE), defined in terms of the dependence of surface warming since the pre-industrial to the cumulative carbon emission, is explained in terms of climate model experiments for a scenario including positive emissions and then negative emission over a period of 400 years. We employ a pre-calibrated ensemble of GENIE, grid-enabled integrated Earth system model, consisting of 86 members to determine the process of controlling TCRE in both CO2 emissions and drawdown phases. Our results are based on the GENIE simulations with historical forcing from AD 850 including land use change, and the future forcing defined by CO2 emissions and a non-CO2 radiative forcing timeseries. We present the results for the point-source carbon capture and storage (CCS) scenario as a negative emission scenario, following the medium representative concentration pathway (RCP4.5), assuming that the rate of emission drawdown is 2 PgC/yr CO2 for the duration of 100 years. The climate response differs between the periods of positive and negative carbon emissions with a greater ensemble spread during the negative carbon emissions. The controls of the spread in ensemble responses are explained in terms of a combination of thermal processes (involving ocean heat uptake and physical climate feedback), radiative processes (saturation in radiative forcing from CO2 and non-CO2 contributions) and carbon dependences (involving terrestrial and ocean carbon uptake).&#160;&#160;

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Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets

Earth System Dynamics ◽

10.5194/esd-12-709-2021 ◽

2021 ◽

Vol 12 (2) ◽

pp. 709-723

Author(s):

Philip Goodwin ◽

B. B. Cael

Keyword(s):

Climate Sensitivity ◽

Future Climate ◽

Climate Feedback ◽

Future Climate Change ◽

Climate Projections ◽

Climate Response ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Posterior Probability Distribution ◽

The Impact

Abstract. Future climate change projections, impacts, and mitigation targets are directly affected by how sensitive Earth's global mean surface temperature is to anthropogenic forcing, expressed via the climate sensitivity (S) and transient climate response (TCR). However, the S and TCR are poorly constrained, in part because historic observations and future climate projections consider the climate system under different response timescales with potentially different climate feedback strengths. Here, we evaluate S and TCR by using historic observations of surface warming, available since the mid-19th century, and ocean heat uptake, available since the mid-20th century, to constrain a model with independent climate feedback components acting over multiple response timescales. Adopting a Bayesian approach, our prior uses a constrained distribution for the instantaneous Planck feedback combined with wide-ranging uniform distributions of the strengths of the fast feedbacks (acting over several days) and multi-decadal feedbacks. We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions when using two preferred combinations of historic datasets both find a TCR of 1.5 (1.3 to 1.8 at 5–95 % range) ∘C. We find the posterior probability distribution for S for our preferred dataset combination evolves from S of 2.0 (1.6 to 2.5) ∘C on a 20-year response timescale to S of 2.3 (1.4 to 6.4) ∘C on a 140-year response timescale, due to the impact of multi-decadal feedbacks. Our results demonstrate how multi-decadal feedbacks allow a significantly higher upper bound on S than historic observations are otherwise consistent with.

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