scholarly journals Climate sensitivity in the Anthropocene

2011 ◽  
Vol 2 (2) ◽  
pp. 531-550 ◽  
Author(s):  
M. Previdi ◽  
B. G. Liepert ◽  
D. T Peteet ◽  
J. Hansen ◽  
D. J Beerling ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Vegetation Change ◽  
Surface Albedo ◽  
Climate Feedbacks ◽  
Surface Warming ◽  
Ocean Carbon ◽  
Dangerous Anthropogenic Interference ◽  
Earth’S Climate ◽  
Global Surface ◽  
Higher Sensitivity

Abstract. Understanding the sensitivity of Earth's climate to an imposed external forcing is one of the great challenges in science and a critical component of efforts to avoid dangerous anthropogenic interference with the climate system. Climate sensitivity (or equilibrium global surface warming) to a doubling of atmospheric CO2 has long been estimated to be about 3 °C, considering only fast climate feedbacks associated with increases in water vapor, decreases in sea ice, and changes in clouds. However, evidence from Earth's history suggests that slower surface albedo feedbacks due to vegetation change and melting of Greenland and Antarctica can come into play on the timescales of interest to humans, which could increase the sensitivity to significantly higher values, as much as 6 °C. Even higher sensitivity may result as present-day land and ocean carbon sinks begin to lose their ability to sequester anthropogenic CO2 in the coming decades. The evolving view of climate sensitivity in the Anthropocene is therefore one in which a wider array of Earth system feedbacks are recognized as important. Since these feedbacks are overwhelmingly positive, the sensitivity is likely to be higher than has traditionally been assumed.

Drivers of (non-)linear Eocene surface warming in the DeepMIP ensemble

2021 ◽  
Author(s):  
Sebastian Steinig ◽  
Jiang Zhu ◽  
Ran Feng ◽  
Keyword(s):  
Temperature Gradient ◽  
Heat Transport ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Large Scale ◽  
Surface Albedo ◽  
Early Eocene ◽  
Meridional Heat Transport ◽  
Surface Warming ◽  
Global Mean

<p>The early Eocene greenhouse represents the warmest interval of the Cenozoic and therefore provides a unique opportunity to understand how the climate system operates under elevated atmospheric CO<sub>2</sub> levels similar to those projected for the end of the 21st century. Early Eocene geological records indicate a large increase in global mean surface temperatures compared to present day (by ~14°C) and a greatly reduced meridional temperature gradient (by ~30% in SST). However, reproducing these large-scale climate features at reasonable CO<sub>2</sub> levels still poses a challenge for current climate models. Recent modelling studies indicate an important role for shortwave (SW) cloud feedbacks to drive increases in climate sensitivity with global warming, which helps to close the gap between simulated and reconstructed Eocene global warmth and temperature gradient. Nevertheless, the presence of such state-dependent feedbacks and their relative strengths in other models remain unclear.</p><p>In this study, we perform a systematic investigation of the simulated surface warming and the underlying mechanisms in the recently published DeepMIP ensemble. The DeepMIP early Eocene simulations use identical paleogeographic boundary conditions and include six models with suitable output: CESM1.2_CAM5, GFDL_CM2.1, HadCM3B_M2.1aN, IPSLCM5A2, MIROC4m and NorESM1_F. We advance previous energy balance analysis by applying the approximate partial radiative perturbation (APRP) technique to quantify the individual contributions of surface albedo, cloud and non-cloud atmospheric changes to the simulated Eocene top-of-the-atmosphere SW flux anomalies. We further compare the strength of these planetary albedo feedbacks to changes in the longwave atmospheric emissivity and meridional heat transport in the warm Eocene climate. Particular focus lies in the sensitivity of the feedback strengths to increasing global mean temperatures in experiments at a range of atmospheric CO<sub>2</sub> concentrations between x1 to x9 preindustrial levels.</p><p>Preliminary results indicate that all models that provide data for at least 3 different CO<sub>2</sub> levels show an increase of the equilibrium climate sensitivity at higher global mean temperatures. This is associated with an increase of the overall strength of the positive SW cloud feedback with warming in those models. This nonlinear behavior seems to be related to both a reduction and optical thinning of low-level clouds, albeit with intermodel differences in the relative importance of the two mechanisms. We further show that our new APRP results can differ significantly from previous estimates based on cloud radiative forcing alone, especially in high-latitude areas with large surface albedo changes. We also find large intermodel variability and state-dependence in meridional heat transport modulated by changes in the atmospheric latent heat transport. Ongoing work focuses on the spatial patterns of the climate feedbacks and the implications for the simulated meridional temperature gradients.</p>

scholarly journals Time-Varying Climate Sensitivity from Regional Feedbacks

2013 ◽  
Vol 26 (13) ◽  
pp. 4518-4534 ◽  
Author(s):  
Kyle C. Armour ◽  
Cecilia M. Bitz ◽  
Gerard H. Roe
Keyword(s):  
Surface Temperature ◽  
Climate Sensitivity ◽  
Time Variation ◽  
Radiative Forcing ◽  
Global Climate ◽  
Regional Climate ◽  
Climate Feedback ◽  
Climate Feedbacks ◽  
Geographic Pattern ◽  
Surface Warming

Abstract The sensitivity of global climate with respect to forcing is generally described in terms of the global climate feedback—the global radiative response per degree of global annual mean surface temperature change. While the global climate feedback is often assumed to be constant, its value—diagnosed from global climate models—shows substantial time variation under transient warming. Here a reformulation of the global climate feedback in terms of its contributions from regional climate feedbacks is proposed, providing a clear physical insight into this behavior. Using (i) a state-of-the-art global climate model and (ii) a low-order energy balance model, it is shown that the global climate feedback is fundamentally linked to the geographic pattern of regional climate feedbacks and the geographic pattern of surface warming at any given time. Time variation of the global climate feedback arises naturally when the pattern of surface warming evolves, actuating feedbacks of different strengths in different regions. This result has substantial implications for the ability to constrain future climate changes from observations of past and present climate states. The regional climate feedbacks formulation also reveals fundamental biases in a widely used method for diagnosing climate sensitivity, feedbacks, and radiative forcing—the regression of the global top-of-atmosphere radiation flux on global surface temperature. Further, it suggests a clear mechanism for the “efficacies” of both ocean heat uptake and radiative forcing.

Evaluating parametric sensitivity of climate feedbacks in CNRM-CM6

2021 ◽  
Author(s):  
Saloua Peatier ◽  
Benjamin Sanderson ◽  
Laurent Terray
Keyword(s):  
Climate Sensitivity ◽  
General Circulation ◽  
Temperature Response ◽  
Coupled Model ◽  
General Circulation Models ◽  
Future Climate Change ◽  
Climate Feedbacks ◽  
Geophysical Research ◽  
Physics Ensemble ◽  
Earth’S Climate

<p>The global surface temperature response to CO2 doubling (Equilibrium Climate Sensitivity or ECS) is a key uncertain parameter determining the extent of future climate change. Sherwood et al. (2020) estimated the ECS to be within [2.6K - 4.5K], but in the Coupled Model Intercomparison Project phase 6 (CMIP6), 1/3 of the General Circulation Models (GCMs) show ECS exceeding 4.5K (Zelinka et al., 2020). CNRM-CM6-1 is one of these models, with an ECS of 4.9K. In this paper, we sampled 30 atmospheric parameters of CNRM-CM6-1 and produced a Perturbed Physics Ensemble (PPE) of atmospheric-only simulations to explore the feedback parameters diversity and the climatological plausibility of the members. This PPE showed a comparable  range of feedback parameters to the multi-model archive, from 0.8 W.m-2/K to 1.8 W.m-2/K. Emulators of climatological performance and feedback parameters were used together with  observational datasets to search for optimal model configurations conditional on different net climate feedbacks. The climatological constraints considered here did not themselves rule out the higher end ECS values of 5K and above. An optimal subset of parameter configurations were chosen to sample the range of ECS allowing the assessment of feedback constraints in future fully coupled experiments.</p><p> </p><p><strong>References :</strong></p><p>Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., ... & Zelinka, M. D. (2020). An assessment of Earth's climate sensitivity using multiple lines of evidence. Reviews of Geophysics, 58(4), e2019RG000678.</p><p>Zelinka, M. D., Myers, T. A., McCoy, D. T., Po‐Chedley, S., Caldwell, P. M., Ceppi, P., ... & Taylor, K. E. (2020). Causes of higher climate sensitivity in CMIP6 models. Geophysical Research Letters, 47(1), e2019GL085782.</p><p><br><br></p>

scholarly journals Local and Global Climate Feedbacks in Models with Differing Climate Sensitivities

2006 ◽  
Vol 19 (2) ◽  
pp. 193-209 ◽  
Author(s):  
Markus Stowasser ◽  
Kevin Hamilton ◽  
George J. Boer
Keyword(s):  
Climate Sensitivity ◽  
Positive Feedback ◽  
General Circulation ◽  
Global Climate ◽  
Tropical Pacific ◽  
Climate Feedbacks ◽  
Climate System Model ◽  
Surface Warming ◽  
Model Version ◽  
Global Mean

Abstract The climatic response to a 5% increase in solar constant is analyzed in three coupled global ocean–atmosphere general circulation models, the NCAR Climate System Model version 1 (CSM1), the Community Climate System Model version 2 (CCSM2), and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model version 3 (CGCM3). For this simple perturbation the quantitative values of the radiative climate forcing at the top of the atmosphere can be determined very accurately simply from a knowledge of the shortwave fluxes in the control run. The climate sensitivity and the geographical pattern of climate feedbacks, and of the shortwave, longwave, clear-sky, and cloud components in each model, are diagnosed as the climate evolves. After a period of adjustment of a few years, both the magnitude and pattern of the feedbacks become reasonably stable with time, implying that they may be accurately determined from relatively short integrations. The global-mean forcing at the top of the atmosphere due to the solar constant change is almost identical in the three models. The exact value of the forcing in each case is compared with that inferred by regressing annual-mean top-of-the-atmosphere radiative imbalance against mean surface temperature change. This regression approach yields a value close to the directly diagnosed forcing for the CCCma model, but a value only within about 25% of the directly diagnosed forcing for the two NCAR models. These results indicate that this regression approach may have some practical limitation in its application, at least for some models. The global climate sensitivities differ among the models by almost a factor of 2, and, despite an overall apparent similarity, the spatial patterns of the climate feedbacks are only modestly correlated among the three models. An exception is the clear-sky shortwave feedback, which agrees well in both magnitude and spatial pattern among the models. The biggest discrepancies are in the shortwave cloud feedback, particularly in the tropical and subtropical regions where it is strongly negative in the NCAR models but weakly positive in the CCCma model. Almost all of the difference in the global-mean total feedback (and climate sensitivity) among the models is attributable to the shortwave cloud feedback component. All three models exhibit a region of positive feedback in the equatorial Pacific, which is surrounded by broad areas of negative feedback. These positive feedback regions appear to be associated with a local maximum of the surface warming. However, the models differ in the zonal structure of this surface warming, which ranges from a mean El Niño–like warming in the eastern Pacific in the CCCma model to a far-western Pacific maximum of warming in the NCAR CCSM2 model. A separate simulation with the CCSM2 model, in which these tropical Pacific zonal gradients of surface warming are artificially suppressed, shows no region of positive radiative feedback in the tropical Pacific. However, the global-mean feedback is only modestly changed in this constrained run, suggesting that the processes that produce the positive feedback in the tropical Pacific region may not contribute importantly to global-mean feedback and climate sensitivity.

Controls of the TCRE in Earth system models

2021 ◽  
Author(s):  
Ric Williams ◽  
Paulo Ceppi ◽  
Anna Katavouta
Keyword(s):  
Radiative Forcing ◽  
Thermal Response ◽  
Earth System ◽  
Climate Feedbacks ◽  
Ocean Heat Uptake ◽  
Surface Warming ◽  
System Models ◽  
Heat Uptake ◽  
Ocean Carbon ◽  
Earth System Models

<p>The controls of a climate metric, the Transient Climate Response to cumulative carbon Emissions (TCRE), are assessed using a suite of Earth system models, 9 CMIP6 and 7 CMIP5, following an annual 1% rise in atmospheric CO2 over 140 years. The TCRE is interpreted in terms of a product of three dependences: (i) a thermal response involving the surface warming dependence on radiative forcing (including the effects of physical climate feedbacks and planetary heat uptake), (ii) a radiative response involving the radiative forcing dependence on changes in atmospheric carbon and (iii) a carbon response involving the airborne fraction (involving terrestrial and ocean carbon uptake). The near constancy of the TCRE is found to result primarily from a compensation between two factors: (i) the thermal response strengthens  in time from more surface warming per radiative forcing due to a strengthening in surface warming from short-wave cloud feedbacks and a declining effectiveness of ocean heat uptake, while  (ii) the radiative response weakens in time due to a saturation in the radiative forcing with increasing atmospheric carbon. This near constancy of the TCRE at least in complex Earth system models appears to be rather fortuitous given the competing effects of physical climate feedbacks, saturation in radiative forcing, changes in ocean heat uptake and changes in terrestrial and ocean carbon uptake.</p><p>Intermodel differences in the TCRE are mainly controlled by the thermal response, which arise through large differences in physical climate feedbacks that are only partly compensated by smaller differences in ocean heat uptake. The other contributions to the TCRE from the radiative and carbon responses are of comparable importance to the contribution from the thermal response on timescales of 50 years and longer for our subset of CMIP5 models, and 100 years and longer for our subset of CMIP6 models.</p><p> </p>

scholarly journals Sensitivity of Global Warming to Carbon Emissions: Effects of Heat and Carbon Uptake in a Suite of Earth System Models

2017 ◽  
Vol 30 (23) ◽  
pp. 9343-9363 ◽  
Author(s):  
Richard G. Williams ◽  
Vassil Roussenov ◽  
Philip Goodwin ◽  
Laure Resplandy ◽  
Laurent Bopp
Keyword(s):  
Climate Sensitivity ◽  
Carbon Emissions ◽  
Radiative Forcing ◽  
Carbon Uptake ◽  
Earth System ◽  
Ocean Heat Uptake ◽  
Surface Warming ◽  
System Models ◽  
Heat Uptake ◽  
Earth System Models

Climate projections reveal global-mean surface warming increasing nearly linearly with cumulative carbon emissions. The sensitivity of surface warming to carbon emissions is interpreted in terms of a product of three terms: the dependence of surface warming on radiative forcing, the fractional radiative forcing from CO2, and the dependence of radiative forcing from CO2 on carbon emissions. Mechanistically each term varies, respectively, with climate sensitivity and ocean heat uptake, radiative forcing contributions, and ocean and terrestrial carbon uptake. The sensitivity of surface warming to fossil-fuel carbon emissions is examined using an ensemble of Earth system models, forced either by an annual increase in atmospheric CO2 or by RCPs until year 2100. The sensitivity of surface warming to carbon emissions is controlled by a temporal decrease in the dependence of radiative forcing from CO2 on carbon emissions, which is partly offset by a temporal increase in the dependence of surface warming on radiative forcing. The decrease in the dependence of radiative forcing from CO2 is due to a decline in the ratio of the global ocean carbon undersaturation to carbon emissions, while the increase in the dependence of surface warming is due to a decline in the ratio of ocean heat uptake to radiative forcing. At the present time, there are large intermodel differences in the sensitivity in surface warming to carbon emissions, which are mainly due to uncertainties in the climate sensitivity and ocean heat uptake. These uncertainties undermine the ability to predict how much carbon may be emitted before reaching a warming target.

Does CMIP6 better constrain projections of 21st century Antarctic sea ice loss?

2021 ◽  
Author(s):  
Caroline Holmes ◽  
Tom Bracegirdle ◽  
Paul Holland
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Sensitivity ◽  
Linear Constraint ◽  
Antarctic Sea Ice ◽  
Historical Climatology ◽  
Regression Techniques ◽  
The Mean ◽  
Global Surface ◽  
Global Mean

<p>Results from CMIP5 have previously suggested that ensemble regression techniques or model selection may provide solutions to the challenge of making projections of future Antarctic sea ice area (SIA) in the presence of large historical biases. Here, we revisit and extend such analysis incorporating the CMIP6 ensemble, which shows modest improvements in some aspects of sea ice simulation and in particular a reduction of inter-model spread in historical SIA. We focus on the strongest forcing scenarios analysed, CMIP5 RCP85 and CMIP6 SSP5.85.</p><p>In summer (February) the historical climatology of SIA is a strong linear constraint on projections of SIA in both generations. This is because the strong forcing leads to the loss of the majority of summer SIA in each model, so that the models that start with greater SIA exhibit greater reductions. Differences between CMIP5 and CMIP6 are largely explained by the fact that, compared to CMIP6, CMIP5 contains many more models that have very large positive biases in historical SIA and do not lose the majority of ice.</p><p>In winter (September), a much smaller proportion of SIA is lost, but inter-model spread in SIA climatology still explains just under half the variance in projections of SIA change, in both CMIP5 and CMIP6. The mean historical winter climatology is similar between generations, as is the regression slope of SIA change against SIA climatology.  However, there is a greater reduction of SIA in CMIP6 than CMIP5. We find this to be statistically related to greater global mean warming in CMIP6 than CMIP5, and therefore potentially to the larger climate sensitivity in the CMIP6 ensemble.</p><p>These findings imply that, depending on season, a different balance of local (SIA climatology) and global (GMST change) drivers can be used to explain the inter-model and inter-generation spread in projections of SIA loss. They also firmly tie our ability to project Antarctic SIA loss to our understanding of the fidelity of higher CMIP6 climate sensitivity. Questions remain about whether models are correct in their simulation of Antarctic SIA sensitivity to global surface temperature.</p>

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