Climate Feedback Variance and the Interaction of Aerosol Forcing and Feedbacks

Abstract Aerosols can influence cloud radiative effects and, thus, may alter interpretation of how Earth’s radiative budget responds to climate forcing. Three different ensemble experiments from the same climate model with different greenhouse gas and aerosol scenarios are used to analyze the role of aerosols in climate feedbacks and their spread across initial condition ensembles of transient climate simulations. The standard deviation of global feedback parameters across ensemble members is low, typically 0.02 W m−2 K−1. Feedbacks from high (8.5 W m−2) and moderate (4.5 W m−2) year 2100 forcing cases are nearly identical. An aerosol kernel is introduced to remove effects of aerosol cloud interactions that alias into cloud feedbacks. Adjusted cloud feedbacks indicate an “aerosol feedback” resulting from changes to climate that increase sea-salt emissions, mostly in the Southern Ocean. Ensemble simulations also indicate higher tropical cloud feedbacks with higher aerosol loading. These effects contribute to a difference in cloud feedbacks of nearly 50% between ensembles of the same model. These two effects are also seen in aquaplanet simulations with varying fixed drop number. Thus aerosols can be a significant modifier of cloud feedbacks, and different representations of aerosols and their interactions with clouds may contribute to multimodel spread in climate feedbacks and climate sensitivity in multimodel archives.

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Evaluating Simulated Fraction of Attributable Risk Using Climate Observations

Journal of Climate ◽

10.1175/jcli-d-15-0566.1 ◽

2016 ◽

Vol 29 (12) ◽

pp. 4565-4575 ◽

Cited By ~ 13

Author(s):

Fraser C. Lott ◽

Peter A. Stott

Keyword(s):

Climate Model ◽

Natural World ◽

Attributable Risk ◽

Climate Forcing ◽

Brier Score ◽

Strongly Correlated ◽

Model Framework ◽

Modeling Framework ◽

Probabilistic Forecasts ◽

Climate Simulations

Abstract Although it is critical to assess the accuracy of attribution studies, the fraction of attributable risk (FAR) cannot be directly assessed from observations since it involves the probability of an event in a world that did not happen, the “natural” world where there was no human influence on climate. Instead, reliability diagrams (usually used to compare probabilistic forecasts to the observed frequencies of events) have been used to assess climate simulations employed for attribution and by inference to evaluate the attribution study itself. The Brier score summarizes this assessment of a model by the reliability diagram. By constructing a modeling framework where the true FAR is already known, this paper shows that Brier scores are correlated to the accuracy of a climate model ensemble’s calculation of FAR, although only weakly. This weakness exists because the diagram does not account for accuracy of simulations of the natural world. This is better represented by two reliability diagrams from early and late in the period of study, which would have, respectively, less and greater anthropogenic climate forcing. Two new methods are therefore proposed for assessing the accuracy of FAR, based on using the earlier observational period as a proxy for observations of the natural world. It is found that errors from model-based estimates of these observable quantities are strongly correlated with errors in the FAR estimated in the model framework. These methods thereby provide new observational estimates of the accuracy in FAR.

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The value of remote marine aerosol measurements for constraining radiative forcing uncertainty

10.5194/acp-2019-1085 ◽

2019 ◽

Author(s):

Leighton A. Regayre ◽

Julia Schmale ◽

Jill S. Johnson ◽

Christian Tatzelt ◽

Andrea Baccarini ◽

...

Keyword(s):

Southern Ocean ◽

Northern Hemisphere ◽

Radiative Forcing ◽

Climate Model ◽

Model Parameters ◽

Marine Aerosol ◽

Aerosol Cloud ◽

Aerosol Forcing ◽

Model Aerosol ◽

Aerosol Cloud Interactions

Abstract. Aerosol measurements over the Southern Ocean are used to constrain aerosol-cloud interaction radiative forcing uncertainty in a global climate model. Aerosol forcing uncertainty is quantified using one million climate model variants that sample the uncertainty in nearly 30 model parameters. Ship-based measurements of cloud condensation nuclei, particle number concentrations and sulfate mass concentrations from the Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and Their Climate Effects (ACE-SPACE) are used to identify observationally implausible variants and thereby reduce the spread in the simulated forcing. Southern Ocean measurements strongly constrain natural aerosol emissions: default sea spray emissions in the model need to be increased by around a factor of 3 to be consistent with measurements. Aerosol forcing uncertainty is reduced by around 7 % using these measurements, which is comparable to the 8 % reduction achieved using an extensive set of over 9000 predominantly Northern Hemisphere measurements. The radiative forcing due to aerosol–cloud interactions (RFaci) is constrained to −2.61 to −1.10 W m−2 (95 % confidence) and the effective radiative forcing from aerosol-cloud interactions (ERFaci) is constrained to −2.43 to −0.54 W m−2. When Southern Ocean and Northern Hemisphere measurements are combined, the uncertainty in RFaci is reduced by 21 % and the strongest 20 % of forcing values are ruled out as implausible. In this combined constraint the observationally plausible RFaci is around 0.17 W m−2 weaker (less negative) with credible values ranging from −2.51 to −1.17 W m−2 and from −2.18 to −1.46 W m−2 when using one standard deviation to quantify the uncertainty. The Southern Ocean and Northern Hemisphere measurement datasets are complementary because they constrain different processes. These results highlight the value of remote marine aerosol measurements.

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Emergent constraints on climate—carbon cycle feedbacks from tropical atmospheric aridity

10.21203/rs.3.rs-132691/v1 ◽

2021 ◽

Author(s):

Armineh Barkhordarian ◽

Kevin Bowman ◽

Noel Cressie ◽

Jeffrey Jewell ◽

Junjie Liu

Keyword(s):

Carbon Cycle ◽

Carbon Balance ◽

Climate Model ◽

Substantial Reduction ◽

Climate Feedback ◽

Climate Projections ◽

Climate Feedbacks ◽

Intercomparison Project ◽

Emergent Constraint ◽

Global Carbon

Abstract The vulnerability of the terrestrial tropical carbon cycle to changes in climate, especially temperature and moisture, remains one of the largest sources of uncertainty in future climate projections. Harnessing new satellite-driven global carbon reanalysis, we show here that tropical atmospheric aridity, which is directly related to the atmospheric vapor pressure deficit (VPD), is a causal driver of the interannual variability of the tropical net carbon balance and consequently the CO2 growth rate with observed present-day sensitivities of -3.2 ± 0.62 GtC mb-1 yr-1. Our results provide evidence that a large part of tropical net biome exchange variability is indirectly driven by land-atmospheric coupling via VPD variations that cannot be explained by tropical temperatures alone. Furthermore, we find that there is an emergent relationship between the sensitivity of the tropical carbon balance to VPD and the long-term response of tropical-land carbon storage to increase in VPD across an ensemble of Earth System Models used in the Climate Model Intercomparison Project 6 (CMIP6). Employing a hierarchical emergent constraint, the global carbon—climate feedback from aridity is -22±11 GtC mb-1 which represents a substantial reduction in uncertainty relative to the CMIP6 ensemble. Our findings show that atmospheric aridity is an important proxy for the combined effects of both water and temperature on the terrestrial carbon balance and a key predictor of carbon—climate feedbacks.

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Cloud Feedbacks in the Climate System: A Critical Review

Journal of Climate ◽

10.1175/jcli-3243.1 ◽

2005 ◽

Vol 18 (2) ◽

pp. 237-273 ◽

Cited By ~ 660

Author(s):

Graeme L. Stephens

Keyword(s):

Critical Review ◽

Hydrological Cycle ◽

Cloud Feedback ◽

Climate System ◽

Climate Forcing ◽

Alternative Methods ◽

Radiation Budget ◽

Climate Feedback ◽

Theoretical Argument ◽

Cloud Feedbacks

Abstract This paper offers a critical review of the topic of cloud–climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet’s hydrological cycle to climate radiative forcings. The paper provides a brief overview of the effects of clouds on the radiation budget of the earth–atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative–convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global–time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis. It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model’s credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress. Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

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Past, present and future aerosol forcing derived from CMIP6

10.5194/egusphere-egu21-2863 ◽

2021 ◽

Author(s):

Christopher Smith ◽

Glen Harris ◽

Matthew Palmer ◽

Nicolas Bellouin ◽

William Collins ◽

...

Keyword(s):

Time Series ◽

Radiative Forcing ◽

Climate Model ◽

Full Range ◽

Simple Relationship ◽

Ocean Heat Uptake ◽

Transient Climate Response ◽

Aerosol Forcing ◽

Time Histories ◽

Aerosol Cloud Interactions

Aerosol forcing remains the most uncertain component of the total climate forcing on the Earth system. RFMIP and AerChemMIP contained experiments that allow us to determine time-slice present day (2014 minus 1850) from 17 CMIP6 models, and transient (1850 to 2014, or 2100) aerosol forcing from 11 models. In CMIP6, aerosol present-day aerosol forcing is -1.01 (full range -1.37 to -0.63) W m-2, a range considerably narrower than comprehensive assessments of aerosol forcing from multiple lines of evidence such as AR5 (-1.9 to -0.1 W m-2) or Bellouin et al. 2020 (-2.0 to -0.35 W m-2). The transient experiments also show a diversity in time histories, with most models showing a peak negative aerosol forcing at some time between 1975 and 2010, and recent trends varying from strongly recovering to slightly strengthening aerosol forcing. Models that were run to 2100 under SSP2-4.5 all show a projected weakening aerosol forcing.By fitting a simple relationship of how globally integrated emissions of black carbon, organic carbon and SO2 relate to effective radiative forcing from aerosol-radiation interactions (ERFari) and aerosol-cloud interactions (ERFaci), an emissions to forcing relationship can be determined for these 11 RFMIP and AerChemMIP models. Using a 100,000 member Monte Carlo ensemble of historical aerosol time series, where coefficients are drawn from these model-derived distributions, and total 1850 to 2014 aerosol forcing is taken from the wider distributions of Bellouin et al. (2020), we create a best estimate historical time series for aerosol forcing (with uncertainty) that is constrained to historical warming and observed ocean heat uptake using a simple climate model. This method can also be used to predict aerosol forcing from future emissions scenarios, such as the SSPs and those derived from integrated assessment models, and provides estimates of the likely ranges for equilibrium climate sensitivity and transient climate response based on the historical aerosol forcing.

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Climate versus emission drivers of methane lifetime against loss by tropospheric OH from 1860–2100

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-12021-2012 ◽

2012 ◽

Vol 12 (24) ◽

pp. 12021-12036 ◽

Cited By ~ 47

Author(s):

J. G. John ◽

A. M. Fiore ◽

V. Naik ◽

L. W. Horowitz ◽

J. P. Dunne

Keyword(s):

Greenhouse Gas ◽

Climate Warming ◽

Radiative Forcing ◽

Climate Model ◽

Climate Forcing ◽

Geophysical Fluid Dynamics Laboratory ◽

Atmospheric Methane ◽

Future Evolution ◽

Aerosol Cloud Interactions ◽

Projected Changes

Abstract. With a more-than-doubling in the atmospheric abundance of the potent greenhouse gas methane (CH4) since preindustrial times, and indications of renewed growth following a leveling off in recent years, questions arise as to future trends and resulting climate and public health impacts from continued growth without mitigation. Changes in atmospheric methane lifetime are determined by factors which regulate the abundance of OH, the primary methane removal mechanism, including changes in CH4 itself. We investigate the role of emissions of short-lived species and climate in determining the evolution of methane lifetime against loss by tropospheric OH, (τCH4_OH), in a suite of historical (1860–2005) and future Representative Concentration Pathway (RCP) simulations (2006–2100), conducted with the Geophysical Fluid Dynamics Laboratory (GFDL) fully coupled chemistry-climate model (CM3). From preindustrial to present, CM3 simulates an overall 5% increase in τCH4_OH due to a doubling of the methane burden which offsets coincident increases in nitrogen oxide (NOx emissions. Over the last two decades, however, the τCH4_OH declines steadily, coinciding with the most rapid climate warming and observed slow-down in CH4 growth rates, reflecting a possible negative feedback through the CH4 sink. Sensitivity simulations with CM3 suggest that the aerosol indirect effect (aerosol-cloud interactions) plays a significant role in cooling the CM3 climate. The projected decline in aerosols under all RCPs contributes to climate warming over the 21st century, which influences the future evolution of OH concentration and τCH4_OH. Projected changes in τCH4_OH from 2006 to 2100 range from −13% to &plus;4%. The only projected increase occurs in the most extreme warming case (RCP8.5) due to the near-doubling of the CH4 abundance, reflecting a positive feedback on the climate system. The largest decrease occurs in the RCP4.5 scenario due to changes in short-lived climate forcing agents which reinforce climate warming and enhance OH. This decrease is more-than-halved in a sensitivity simulation in which only well-mixed greenhouse gas radiative forcing changes along the RCP4.5 scenario (5% vs. 13%).

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Quantifying climate feedbacks in the middle atmosphere using WACCM

10.5194/acp-2019-1169 ◽

2020 ◽

Author(s):

Maartje Sanne Kuilman ◽

Qiong Zhang ◽

Ming Cai ◽

Qin Wen

Keyword(s):

Climate Model ◽

Middle Atmosphere ◽

Current Method ◽

Large Error ◽

Climate Feedback ◽

Response Analysis ◽

Minor Importance ◽

Climate Feedbacks ◽

Surface Climate ◽

Direct Forcing

Abstract. The importance of feedback processes in the middle atmosphere for surface and tropospheric climate is increasingly realized. To better understand feedback processes in response to a doubling of CO2 we use the climate feedback response analysis method (CFRAM). We examine the middle atmosphere response to CO2 doubling with respect to the pre-industrial state in the Whole Atmosphere Community Climate Model (WACCM). Globally, the simulated temperature decrease between 200 and 0.01 hPa (~ 12–80 km) is found to be −5.2 K in July and −5.5 K in January in WACCM. The CFRAM calculations show that the direct forcing of CO2 alone would lead to an even stronger cooling of approximately 9 K in the middle atmosphere in both July and January. This cooling is being mitigated by the combined effect of the different feedback processes. The contribution from the ozone feedback causes a warming of approximately 1.5 K, mitigating the cooling due to changes in CO2. Changes in CO2 also lead to changes in the middle atmosphere dynamics. The changes in dynamics play a large role locally, especially above 0.1 hPa. Other feedback processes, which are known to be important in the tropospheric and surface climate, such as the water vapor, albedo and cloud feedbacks are of minor importance in the middle atmosphere,although some effects are seen in the stratosphere, mainly through the responses to sea surface temperature and sea ice changes. It should be noted that there is a relatively large error term associated with the current method in the middle atmosphere, which can be explained by the linearization in the method.

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Why does the climate response to greenhouse warming and greenhouse cooling differ?

10.5194/egusphere-egu21-6534 ◽

2021 ◽

Author(s):

Jennifer Kay ◽

Jason Chalmers

Keyword(s):

Carbon Dioxide ◽

Radiative Forcing ◽

Climate Model ◽

Temperature Response ◽

Greenhouse Warming ◽

Climate Response ◽

Cloud Feedbacks ◽

Surface Climate ◽

Carbon Dioxide Concentrations ◽

Radiative Feedbacks

While the long-standing quest to constrain equilibrium climate sensitivity has resulted in intense scrutiny of the processes controlling idealized greenhouse warming, the processes controlling idealized greenhouse cooling have received less attention. Here, differences in the climate response to increased and decreased carbon dioxide concentrations are assessed in state-of-the-art fully coupled climate model experiments. One hundred and fifty years after an imposed instantaneous forcing change, surface global warming from a carbon dioxide doubling (abrupt-2xCO2, 2.43 K) is larger than the surface global cooling from a carbon dioxide halving (abrupt-0p5xCO2, 1.97 K). Both forcing and feedback differences explain these climate response differences. Multiple approaches show the radiative forcing for a carbon dioxide doubling is ~10% larger than for a carbon dioxide halving. In addition, radiative feedbacks are less negative in the doubling experiments than in the halving experiments. Specifically, less negative tropical shortwave cloud feedbacks and more positive subtropical cloud feedbacks lead to more greenhouse 2xCO2 warming than 0.5xCO2 greenhouse cooling. Motivated to directly isolate the influence of cloud feedbacks on these experiments, additional abrupt-2xCO2 and abrupt-0p5xCO2 experiments with disabled cloud-climate feedbacks were run. Comparison of these &#8220;cloud-locked&#8221; simulations with the original &#8220;cloud active&#8221; simulations shows cloud feedbacks help explain the nonlinear global surface temperature response to greenhouse warming and greenhouse cooling. Overall, these results demonstrate that both radiative forcing and radiative feedbacks are needed to explain differences in the surface climate response to increased and decreased carbon dioxide concentrations.

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How do polar clouds and precipitation affect global warming?

10.5194/egusphere-egu21-6444 ◽

2021 ◽

Author(s):

Jennifer Kay

Keyword(s):

Global Warming ◽

Climate Model ◽

Research Problem ◽

Cloud Feedback ◽

Polar Regions ◽

Unsolved Research Problem ◽

Cloud Feedbacks ◽

Surface Warming ◽

Polar Clouds ◽

Radiative Feedbacks

Understanding the influence of clouds and precipitation on global warming remains an important unsolved research problem. This talk presents an overview of this topic, with a focus on recent observations, theory, and modeling results for polar clouds. After a general introduction, experiments that disable cloud radiative feedbacks or &#8220;lock the clouds&#8221; within a state&#8208;of&#8208;the&#8208;art,&#160; well&#8208;documented, and observationally vetted climate model will be presented. Through comparison of idealized greenhouse warming experiments with and without cloud locking, the sign and magnitude cloud feedbacks can be quantified. Global cloud feedbacks increase both global and Arctic warming by around 25%. In contrast, disabling Arctic cloud feedbacks has a negligible influence on both Arctic and global surface warming. Do observations and theory support a positive global cloud feedback and a weak Arctic cloud feedback?&#160; How does precipitation affect polar cloud feedbacks? What are the implications especially for climate change in polar regions?&#160;&#160;

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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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