scholarly journals Declining uncertainty in transient climate response as CO2 forcing dominates future climate change

2015 ◽  
Vol 8 (3) ◽  
pp. 181-185 ◽  
Author(s):  
Gunnar Myhre ◽  
Olivier Boucher ◽  
François-Marie Bréon ◽  
Piers Forster ◽  
Drew Shindell
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Response ◽  
Transient Climate Response ◽  
Co2 Forcing

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

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.

scholarly journals Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models

2020 ◽  
Vol 11 (3) ◽  
pp. 737-750 ◽  
Author(s):  
Femke J. M. M. Nijsse ◽  
Peter M. Cox ◽  
Mark S. Williamson
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Sensitivity ◽  
Cmip5 Models ◽  
Future Climate Change ◽  
Climate Response ◽  
Transient Climate Response ◽  
Equilibrium Climate Sensitivity ◽  
Emergent Constraint ◽  
Constraint Approach

Abstract. Climate sensitivity to CO2 remains the key uncertainty in projections of future climate change. Transient climate response (TCR) is the metric of temperature sensitivity that is most relevant to warming in the next few decades and contributes the biggest uncertainty to estimates of the carbon budgets consistent with the Paris targets. Equilibrium climate sensitivity (ECS) is vital for understanding longer-term climate change and stabilisation targets. In the IPCC 5th Assessment Report (AR5), the stated “likely” ranges (16 %–84 % confidence) of TCR (1.0–2.5 K) and ECS (1.5–4.5 K) were broadly consistent with the ensemble of CMIP5 Earth system models (ESMs) available at the time. However, many of the latest CMIP6 ESMs have larger climate sensitivities, with 5 of 34 models having TCR values above 2.5 K and an ensemble mean TCR of 2.0±0.4 K. Even starker, 12 of 34 models have an ECS value above 4.5 K. On the face of it, these latest ESM results suggest that the IPCC likely ranges may need revising upwards, which would cast further doubt on the feasibility of the Paris targets. Here we show that rather than increasing the uncertainty in climate sensitivity, the CMIP6 models help to constrain the likely range of TCR to 1.3–2.1 K, with a central estimate of 1.68 K. We reach this conclusion through an emergent constraint approach which relates the value of TCR linearly to the global warming from 1975 onwards. This is a period when the signal-to-noise ratio of the net radiative forcing increases strongly, so that uncertainties in aerosol forcing become progressively less problematic. We find a consistent emergent constraint on TCR when we apply the same method to CMIP5 models. Our constraints on TCR are in good agreement with other recent studies which analysed CMIP ensembles. The relationship between ECS and the post-1975 warming trend is less direct and also non-linear. However, we are able to derive a likely range of ECS of 1.9–3.4 K from the CMIP6 models by assuming an underlying emergent relationship based on a two-box energy balance model. Despite some methodological differences; this is consistent with a previously published ECS constraint derived from warming trends in CMIP5 models to 2005. Our results seem to be part of a growing consensus amongst studies that have applied the emergent constraint approach to different model ensembles and to different aspects of the record of global warming.

scholarly journals FAIR v1.3: a simple emissions-based impulse response and carbon cycle model

2018 ◽  
Vol 11 (6) ◽  
pp. 2273-2297 ◽  
Author(s):  
Christopher J. Smith ◽  
Piers M. Forster ◽  
Myles Allen ◽  
Nicholas Leach ◽  
Richard J. Millar ◽  
...  
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Future Climate Change ◽  
Climate Response ◽  
Transient Climate Response ◽  
Carbon Cycle Model ◽  
Future Projections

Abstract. Simple climate models can be valuable if they are able to replicate aspects of complex fully coupled earth system models. Larger ensembles can be produced, enabling a probabilistic view of future climate change. A simple emissions-based climate model, FAIR, is presented, which calculates atmospheric concentrations of greenhouse gases and effective radiative forcing (ERF) from greenhouse gases, aerosols, ozone and other agents. Model runs are constrained to observed temperature change from 1880 to 2016 and produce a range of future projections under the Representative Concentration Pathway (RCP) scenarios. The constrained estimates of equilibrium climate sensitivity (ECS), transient climate response (TCR) and transient climate response to cumulative CO2 emissions (TCRE) are 2.86 (2.01 to 4.22) K, 1.53 (1.05 to 2.41) K and 1.40 (0.96 to 2.23) K (1000 GtC)−1 (median and 5–95 % credible intervals). These are in good agreement with the likely Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) range, noting that AR5 estimates were derived from a combination of climate models, observations and expert judgement. The ranges of future projections of temperature and ranges of estimates of ECS, TCR and TCRE are somewhat sensitive to the prior distributions of ECS∕TCR parameters but less sensitive to the ERF from a doubling of CO2 or the observational temperature dataset used to constrain the ensemble. Taking these sensitivities into account, there is no evidence to suggest that the median and credible range of observationally constrained TCR or ECS differ from climate model-derived estimates. The range of temperature projections under RCP8.5 for 2081–2100 in the constrained FAIR model ensemble is lower than the emissions-based estimate reported in AR5 by half a degree, owing to differences in forcing assumptions and ECS∕TCR distributions.

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

2020 ◽  
Author(s):  
Philip Goodwin ◽  
B. B. Cael
Keyword(s):  
Climate Sensitivity ◽  
Heat Content ◽  
Future Climate ◽  
Climate Feedback ◽  
Future Climate Change ◽  
Climate Response ◽  
Ocean Heat Uptake ◽  
Transient Climate Response ◽  
Posterior Probability Distribution ◽  
Future Global Warming

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 effective climate sensitivity (ECS) and transient climate response (TCR). However, the ECS 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 ECS and TCR by using historic observations of surface warming, since the mid-19th century, and ocean heat uptake, 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 slow feedbacks (acting over decades). We extract posterior distributions by applying likelihood functions derived from different combinations of observational datasets. The resulting TCR distributions are similar when using different historic datasets: from a TCR of 1.5 (1.3 to 1.7 at 5–95 % range) °C, up to 1.7 (1.4 to 2.0) °C. However, the posterior probability distribution for ECS on a 100-year response timescale varies depending on which combinations of temperature and heat content anomaly datasets are used: from ECS of 2.2 (1.5 to 4.5) °C, for datasets with less historic warming, up to 2.8 (1.8 to 6.1) °C, for datasets with more historic warming. Our results demonstrate how differences between historic climate reconstructions imply significant differences in expected future global warming.

Responses of Irish Vegetation to Future Climate Change

2006 ◽  
Vol 106 (3) ◽  
pp. 323-334 ◽  
Author(s):  
Michael B. Jones ◽  
Alison Donnelly ◽  
Fabrizio Albanito
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change

Future climate change and its impacts over small island states

2002 ◽  
Vol 19 ◽  
pp. 179-192 ◽  
Author(s):  
M Lal ◽  
H Harasawa ◽  
K Takahashi
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change ◽  
Small Island ◽  
Island States ◽  
Small Island States

Supplemental Material to the A&WMA 2008 Critical Review "Prospects for Future Climate Change and the Reasons for Early Action"

2008 ◽  
Vol 58 (6) ◽  
Author(s):  
Sylvia Edgerton ◽  
Michael MacCracken ◽  
Meng-Dawn Cheng ◽  
Edwin Corporan ◽  
Matthew DeWitt ◽  
...  
Keyword(s):  
Climate Change ◽  
Critical Review ◽  
Future Climate ◽  
Future Climate Change ◽  
Early Action
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