Effective Climate Sensitivity Research Articles

Slab Ocean Component of the Energy Exascale Earth System Model (E3SM): Development, Evaluation, and Application to Understanding Earth System Sensitivity

AbstractThis work describes the implementation and evaluation of the Slab Ocean Model component of the Energy Exascale Earth System Model version 2 (E3SMv2‐SOM) and its application to understanding the climate sensitivity to ocean heat transports (OHTs) and CO2 forcing. E3SMv2‐SOM reproduces the baseline climate and Equilibrium Climate Sensitivity (ECS) of the fully coupled E3SMv2 experiments reasonably well, with a pattern correlation close to 1 and a global mean bias of less than 1% of the fully coupled surface temperature and precipitation. Sea ice extent and volume are also well reproduced in the SOM. Consistent with general model behavior, the ECS estimated from the SOM (4.5 K) exceeds the effective climate sensitivity obtained from extrapolation to equilibrium in the fully coupled model (4.0 K). The E3SMv2 baseline climate also shows a large sensitivity to OHT strengths, with a global surface temperature difference of about 4.0°C between high‐/low‐OHT experiments with prescribed forcings derived from fully coupled experiments with realistic/weak ocean circulation strengths. Similar to their forcing pattern, the surface temperature response occurs mainly over the subpolar regions in both hemispheres. However, the Southern Ocean shows more surface temperature sensitivity to high/low‐OHT forcing due to a positive/negative shortwave cloud radiative effect caused by decreases/increases in mid‐latitude marine low‐level clouds. This large temperature sensitivity also causes an overcompensation between the prescribed OHTs and atmosphere heat transports. The SOM's ECS estimate is also sensitive to the prescribed OHT and the associated baseline climate it is initialized from; the high‐OHT ECS is 0.5 K lower than the low‐OHT ECS.

Constraints on Southern Ocean Shortwave Cloud Feedback From the Hydrological Cycle

AbstractShifts in Southern Ocean (SO, 40–85°S) shortwave cloud feedback (SWFB) toward more positive values are the dominant contributor to higher effective climate sensitivity (ECS) in Coupled Model Intercomparison Project Phase 6 (CMIP6) models. To provide an observational constraint on the SO SWFB, we use a simplified physical model to connect SO SWFB with the response of column‐integrated liquid water mass (LWP) to warming and the susceptibility of albedo to LWP in 50 CMIP5 and CMIP6 GCMs. In turn, we predict the responses of SO LWP using a cloud‐controlling factor (CCF) model. The combination of the CCF model and radiative susceptibility explains about 50% of the variance in the GCM‐simulated SWFB in the SO. Observations of SW radiation fluxes, LWP, and CCFs from reanalysis are used to constrain the SO SWFB. Observations suggest a SO LWP increase in response to warming and albedo susceptibility to LWP that is on the lower end relative to GCMs. The overall constraint on the contribution of SO to global mean SWFB is −0.168 to +0.051 W m−2 K−1, relative to −0.277 to +0.270 Wm−2 K−1. In summary, observations suggest SO SWFB is less likely to be as extremely positive as predicted by some CMIP6 GCMs, but more likely to range from moderately negative to weakly positive.

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

Cloud properties and their projected changes in CMIP models with low to high climate sensitivity

Abstract. Since the release of the first Coupled Model Intercomparison Project version 6 (CMIP6) simulations, one of the most discussed topics is the higher effective climate sensitivity (ECS) of some of the models, resulting in an increased range of ECS values in CMIP6 compared to previous CMIP phases. An important contribution to ECS is the cloud climate feedback. Although climate models have continuously been developed and improved over the last few decades, a realistic representation of clouds remains challenging. Clouds contribute to the large uncertainties in modeled ECS, as projected changes in cloud properties and cloud feedbacks also depend on the simulated present-day fields. In this study, we investigate the representation of both cloud physical and radiative properties from a total of 51 CMIP5 and CMIP6 models. ECS is used as a simple metric to group the models, as the sensitivity of the physical cloud properties to warming is closely related to cloud feedbacks, which in turn are known to have a large contribution to ECS. Projected changes in the cloud properties in future scenario simulations are analyzed by the ECS group. In order to help with interpreting the projected changes, model results from historical simulations are also analyzed. The results show that differences in the net cloud radiative effect as a reaction to warming among the three model groups are driven by changes in a range of cloud regimes rather than individual regions. In polar regions, high-ECS models show a weaker increase in the net cooling effect of clouds, due to warming, than the low-ECS models. At the same time, high-ECS models show a decrease in the net cooling effect of clouds over the tropical ocean and the subtropical stratocumulus regions, whereas low-ECS models show either little change or even an increase in the cooling effect. Over the Southern Ocean, the low-ECS models show a higher sensitivity of the net cloud radiative effect to warming than the high-ECS models.

Causes of Reduced Climate Sensitivity in E3SM From Version 1 to Version 2

AbstractThe effective climate sensitivity in the Department of Energy's Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present‐day atmosphere‐only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener‐Bergeron‐Findeisen (WBF) efficiency strongly reduces present‐day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large‐eddy modeling studies but might not be due to the right physical reasons. The reduced mid‐latitude cloud feedback may be more plausible because more realistic present‐day mixed‐phase clouds are produced through the change in the WBF efficiency.

A new conceptual model ofglobaloceanheatuptake.

We formulate a new conceptual model, named "MT2", to describe global ocean heat uptake, as simulated by atmosphere-ocean general circulation models (AOGCMs) forced by increasing atmospheric CO2, as a function of global-mean surface temperature change T and the strength of the Atlantic meridional overturning circulation (AMOC, M). MT2 has two routes whereby heat reaches the deep ocean. On the basis of circumstantial evidence, we hypothetically identify these routes as low- and high-latitude. In low latitudes, which dominate the global-mean energy balance, heat uptake is temperature-driven and described by the two-layer model, with global-mean T as the temperature change of the upper layer. In high latitudes, a proportion p (about 14%) of the forcing is taken up along isopycnals, mostly in the Southern Ocean, nearly like a passive tracer, and unrelated to T. Because the proportion p depends linearly on the AMOC strength in the unperturbed climate, we hypothesise that high-latitude heat uptake and the AMOC are both affected by some characteristic of the unperturbed global ocean state, possibly related to stratification. MT2 can explain several relationships among AOGCM projections, some found in this work, others previously reported: Ocean heat uptake efficiency correlates strongly with the AMOC. Global ocean heat uptake is not correlated with the AMOC. Transient climate response (TCR) is anticorrelated with the AMOC. T projected for the late twenty-first century under high-forcing scenarios correlates more strongly with the effective climate sensitivity than with the TCR.

Time‐Evolving Radiative Feedbacks in the Historical Period

AbstractWe investigate the time‐dependence of radiative feedback in the historical period (since the late 19th century), by analyzing experiments using coupled atmosphere–ocean climate models with historical greenhouse gas, anthropogenic aerosol, and natural forcings, each separately. We find that radiative feedback depends on forcing agent, primarily through the effect of cloud on shortwave radiation, because the various forcings cause different changes in global‐mean tropospheric stability per degree of global‐mean temperature change. The large time‐variation of historical feedback driven by observed sea surface temperature change alone, with no forcing agents, is also consistent with tropospheric stability change, and differs from the similarly large and significant historical time‐variation of feedback that is simulated in response to all forcing agents together. We show that the latter results from the varying relative sizes of individual forcings. We highlight that volcanic forcing is especially important for understanding the time‐variation, because it stimulates particularly strong feedbacks that tend to reduce effective climate sensitivity. We relate this to stability changes due to enhanced surface temperature response in the Indo‐Pacific warm pool.

Effective climate sensitivity distributions from a 1D model of global ocean and land temperature trends, 1970–2021

Current theoretically based Earth system models (ESMs) produce Effective Climate Sensitivities (EffCS) that range over a factor of three, with 80% of those models producing stronger global warming trends for 1970–2021 than do observations. To make a more observationally based estimate of EffCS, a 1D time-dependent forcing-feedback model of temperature departures from energy equilibrium is used to match measured ranges of global-average surface and sub-surface land and ocean temperature trends during 1970–2021. In response to two different radiative forcing scenarios, a full range of three model free parameters are evaluated to produce fits to a range of observed surface temperature trends (± 2σ) from four different land datasets and three ocean datasets, as well as deep-ocean temperature trends and borehole-based trend retrievals over land. Land-derived EffCS are larger than over the ocean, and EffCS is lower using the newer Shared Socioeconomic Pathways (SSP245, 1.86 °C global EffCS, ± 34% range 1.48–2.15 °C) than the older Representative Concentration Pathway forcing (RCP6, 2.49 °C global average EffCS, ± 34% range 2.04–2.87 °C). The strongest dependence of the EffCS results is on the assumed radiative forcing dataset, underscoring the role of radiative forcing uncertainty in determining the sensitivity of the climate system to increasing greenhouse gas concentrations from observations alone. The results are consistent with previous observation-based studies that concluded EffCS during the observational period is on the low end of the range produced by current ESMs.

Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications

Abstract. As the number of models in Coupled Model Intercomparison Project (CMIP) archives increase from generation to generation, there is a pressing need for guidance on how to interpret and best use the abundance of newly available climate information. Users of the latest CMIP6 seeking to draw conclusions about model agreement must contend with an “ensemble of opportunity” containing similar models that appear under different names. Those who used the previous CMIP5 as a basis for downstream applications must filter through hundreds of new CMIP6 simulations to find several best suited to their region, season, and climate horizon of interest. Here we present methods to address both issues, model dependence and model subselection, to help users previously anchored in CMIP5 to navigate CMIP6 and multi-model ensembles in general. In Part I, we refine a definition of model dependence based on climate output, initially employed in Climate model Weighting by Independence and Performance (ClimWIP), to designate discrete model families within CMIP5 and CMIP6. We show that the increased presence of model families in CMIP6 bolsters the upper mode of the ensemble's bimodal effective equilibrium climate sensitivity (ECS) distribution. Accounting for the mismatch in representation between model families and individual model runs shifts the CMIP6 ECS median and 75th percentile down by 0.43 ∘C, achieving better alignment with CMIP5's ECS distribution. In Part II, we present a new approach to model subselection based on cost function minimization, Climate model Selection by Independence, Performance, and Spread (ClimSIPS). ClimSIPS selects sets of CMIP models based on the relative importance a user ascribes to model independence (as defined in Part I), model performance, and ensemble spread in projected climate outcome. We demonstrate ClimSIPS by selecting sets of three to five models from CMIP6 for European applications, evaluating the performance from the agreement with the observed mean climate and the spread in outcome from the projected mid-century change in surface air temperature and precipitation. To accommodate different use cases, we explore two ways to represent models with multiple members in ClimSIPS, first, by ensemble mean and, second, by an individual ensemble member that maximizes mid-century change diversity within the CMIP overall. Because different combinations of models are selected by the cost function for different balances of independence, performance, and spread priority, we present all selected subsets in ternary contour “subselection triangles” and guide users with recommendations based on further qualitative selection standards. ClimSIPS represents a novel framework to select models in an informed, efficient, and transparent manner and addresses the growing need for guidance and simple tools, so those seeking climate services can navigate the increasingly complex CMIP landscape.

UKESM1.1: development and evaluation of an updated configuration of the UK Earth System Model

Abstract. Many Coupled Model Intercomparison Project phase 6 (CMIP6) models have exhibited a substantial cold bias in the global mean surface temperature (GMST) in the latter part of the 20th century. An overly strong negative aerosol forcing has been suggested as a leading contributor to this bias. An updated configuration of UK Earth System Model (UKESM) version 1, UKESM1.1, has been developed with the aim of reducing the historical cold bias in this model. Changes implemented include an improved representation of SO2 dry deposition, along with several other smaller modifications to the aerosol scheme and a retuning of some uncertain parameters of the fully coupled Earth system model. The Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, a six-member historical ensemble and a subset of future scenario simulations are completed. In addition, the total anthropogenic effective radiative forcing (ERF), its components and the effective and transient climate sensitivities are also computed. The UKESM1.1 preindustrial climate is warmer than UKESM1 by up to 0.75 K, and a significant improvement in the historical GMST record is simulated, with the magnitude of the cold bias reduced by over 50 %. The warmer climate increases ocean heat uptake in the Northern Hemisphere oceans and reduces Arctic sea ice, which is in better agreement with observations. Changes to the aerosol and related cloud properties are a driver of the improved GMST simulation despite only a modest reduction in the magnitude of the negative aerosol ERF (which increases by +0.08 W m−2). The total anthropogenic ERF increases from 1.76 W m−2 in UKESM1 to 1.84 W m−2 in UKESM1.1. The effective climate sensitivity (5.27 K) and transient climate response (2.64 K) remain largely unchanged from UKESM1 (5.36 and 2.76 K respectively).

Increasing Precipitation Efficiency Amplifies Climate Sensitivity by Enhancing Tropical Circulation Slowdown and Eastern Pacific Warming Pattern

AbstractThe role of precipitation efficiency (PE)—the fraction of column‐integrated condensate that reaches the surface as rain—in the global temperature response to CO2 rise is yet to be quantified. Here we employ 36 limited‐domain cloud resolving models (CRMs) from the Radiative‐Convective Equilibrium Model Intercomparison Project and find that they strongly imply higher PE at warmer temperatures. We then analyze 35 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 and find that increasing PE is associated with tropical circulation slowdown and greater eastern equatorial Pacific warming. These changes trigger pan‐tropical positive cloud feedback through stratiform anvil cloud reduction and stratocumulus suppression, resulting in higher Effective Climate Sensitivity (ECS). We find that in 24 of 35 GCMs matching the CRMs in simulating increasing PE with greenhouse warming, mean ECS is 1 K higher than in PE‐decreasing GCMs. Thus, further constraining PE sensitivity to temperature could reduce uncertainty over future climate projections.

Changes to population-based emergence of climate change from CMIP5 to CMIP6

The Coupled Model Intercomparison Project Phase 6 (CMIP6) model ensemble projects climate change emerging soonest and most strongly at low latitudes, regardless of the emissions pathway taken. In terms of signal-to-noise (S/N) ratios of average annual temperatures, these models project earlier and stronger emergence under the Shared Socio-economic Pathways than the previous generation did under corresponding Representative Concentration Pathways. Spatial patterns of emergence also change between generations of models; under a high emissions scenario, mid-century S/N is lower than previous studies indicated in Central Africa, South Asia, and parts of South America, West Africa, East Asia, and Western Europe, but higher in most other populated areas. We show that these global and regional changes are caused by a combination of higher effective climate sensitivity in the CMIP6 ensemble, as well as changes to emissions pathways, component-wise effective radiative forcing, and region-scale climate responses between model generations. We also present the first population-weighted calculation of climate change emergence for the CMIP6 ensemble, quantifying the number of people exposed to increasing degrees of abnormal temperatures now and into the future. Our results confirm the expected inequity of climate change-related impacts in the decades between now and the 2050 target for net-zero emissions held by many countries. These findings underscore the importance of concurrent investments in both mitigation and adaptation.

Potential for bias in effective climate sensitivity from state-dependent energetic imbalance

Abstract. To estimate equilibrium climate sensitivity from a simulation where a step change in carbon dioxide concentrations is imposed, a common approach is to linearly extrapolate temperatures as a function of top-of-atmosphere energetic imbalance to estimate the equilibrium state (“effective climate sensitivity”). In this study, we find that this estimate may be biased in some models due to state-dependent energetic leaks. Using an ensemble of multi-millennial simulations of climate model response to a constant forcing, we estimate equilibrium climate sensitivity through Bayesian calibration of simple climate models which allow for responses from subdecadal to multi-millennial timescales. Results suggest potential biases in effective climate sensitivity in the case of particular models where radiative tendencies imply energetic imbalances which differ between pre-industrial and quadrupled CO2 states, whereas for other models even multi-thousand-year experiments are insufficient to predict the equilibrium state. These biases draw into question the utility of effective climate sensitivity as a metric of warming response to greenhouse gases and underline the requirement for operational climate sensitivity experiments on millennial timescales to better understand committed warming following a stabilization of greenhouse gases.

Antarctic Ice‐Sheet Meltwater Reduces Transient Warming and Climate Sensitivity Through the Sea‐Surface Temperature Pattern Effect

AbstractCoupled global climate models (GCMs) generally fail to reproduce the observed sea‐surface temperature (SST) trend pattern since the 1980s. The model‐observation discrepancies may arise in part from the lack of realistic Antarctic ice‐sheet meltwater input in GCMs. Here we employ two sets of CESM1‐CAM5 simulations forced by anomalous Antarctic meltwater fluxes over 1980–2013 and through the 21st century. Both show a reduced global warming rate and an SST trend pattern that better resembles observations. The meltwater drives surface cooling in the Southern Ocean and the tropical southeast Pacific, in turn increasing low‐cloud cover and driving radiative feedbacks to become more stabilizing (corresponding to a lower effective climate sensitivity). These feedback changes can contribute as substantially as ocean heat uptake efficiency changes in reducing the global warming rate. Accurately projecting historical and future warming thus requires improved representation of Antarctic meltwater and its impacts.

An Investigation of the Effective Climate Sensitivity in GFDL’s New Climate Models CM4.0 and SPEAR

Abstract Despite a relatively low climate sensitivity indicated by atmospheric-only simulations with uniform sea surface temperature (SST) warming, GFDL’s new climate model CM4.0 participating in CMIP6 and the seasonal-to-decadal prediction system SPEAR, both of which use an identical atmospheric model AM4.0, produce relatively high effective climate sensitivity (EffCS). The substantial increase in CM4.0’s EffCS is found to be caused by additional positive forcing associated with the CO2 fertilization effect on vegetation, enhanced positive feedback due to stronger reduction in Southern Hemisphere (SH) sea ice concentration (SIC), and clouds whose feedback depends on SST warming patterns. Compared to a SPEAR run using a static vegetation model (SPEAR-SV), CM4.0 produces roughly 30% larger EffCS, among which roughly 1/3 of the increase is due to dynamical vegetation with the rest due primarily to changes in SIC. Although cloud feedback does not explain the key feedback differences among CM4.0, SPEAR, and SPEAR-SV, it is the primary cause of the models’ increase (less negative) in TOA net feedback during the later period of their quadrupling CO2 simulations due to changes in their SST warming patterns. Moreover, CM4.0’s SST warming pattern and its effects on cloud feedback appear to be the leading cause of CM4.0’s EffCS increase compared to the earlier generation GFDL model ESM2M, which produces one of the lowest EffCS values among CMIP5 models. In comparison, CM4.0’s enhanced reduction in SH SICs plays a slightly less important role in its increase in EffCS compared to ESM2M.

Observational Constraint on the Climate Sensitivity to Atmospheric CO2 Concentrations Changes Derived from the 1971–2017 Global Energy Budget

Abstract The estimate of the historical effective climate sensitivity (histeffCS) is revisited with updated historical observations of the global energy budget in order to derive an observational constraint on the effective sensitivity of climate to CO2 (CO2effCS). A regression method based on observations of the energy budget over 1971–2017 is used to estimate the histeffCS (4.34 [2.17; 22.83] K: median and 5%–95% range). Then, climate model simulations are used to evaluate the distance between the histeffCS and the CO2effCS. The observational estimate of the histeffCS and the distance between the histeffCS and the CO2effCS are combined to derive an observational constraint on CO2effCS of 5.46 [2.40; 35.61] K. The main sources of uncertainty in the CO2effCS estimate comes from the uncertainty in aerosol forcing and in the top of the atmosphere energy imbalance. Further uncertainty arises from the pattern effect correction estimated from climate models. There is confidence in the lower end of the 5%–95% range derived from our method because it relies only on reliable recent data and it makes full use of the observational record since 1971. This important result suggests that observations of the global energy budget since 1971 are poorly consistent with climate sensitivity to CO2 below 2.4 K. Unfortunately, the upper end of the 5%–95% range derived from the regression method is above 30 K. This means that the observational constraint derived from observations of the global energy budget since 1971 is too weak (i.e., the uncertainty is too large) to provide any relevant information on the credibility of high CO2effCS.

Future Climate Change Under SSP Emission Scenarios With GISS‐E2.1

AbstractThis paper presents the response to anthropogenic forcing in the GISS‐E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non‐interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One‐Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1‐G) and HYCOM (E2.1‐H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1‐2.6, SSP2‐4.5, SSP4‐6.0, and SSP5‐8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high‐mitigation scenarios SSP1‐1.9 and SSP1‐2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1‐H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5‐8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1‐G (−1.21 × 106 km2/°C) and E2.1‐H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5‐8.5 in the E2.1‐G model, comparable to the reduction in the corresponding CMIP5 GISS‐E2 RCP8.5 simulation. Both low‐end scenarios SSP1‐1.9 and SSP1‐2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

Extratropical Shortwave Cloud Feedbacks in the Context of the Global Circulation and Hydrological Cycle

AbstractShortwave (SW) cloud feedback (SWFB) is the primary driver of uncertainty in the effective climate sensitivity (ECS) predicted by global climate models (GCMs). ECS for several GCMs participating in the sixth assessment report exceed 5K, above the fifth assessment report “likely” maximum (4.5K) due to extratropical SWFB's that are more positive than those simulated in the previous generation of GCMs. Here we show that across 57 GCMs Southern Ocean SWFB can be predicted from the sensitivity of column‐integrated liquid water mass (LWP) to moisture convergence and to surface temperature. The response of LWP to moisture convergence and the response of albedo to LWP anti‐correlate across GCMs. This is because GCMs that simulate a larger response of LWP to moisture convergence tend to have higher mean‐state LWPs, which reduces the impact of additional LWP on albedo. Observational constraints suggest a modestly negative Southern Ocean SWFB— inconsistent with extreme ECS.

Interpreting Differences in Radiative Feedbacks From Aerosols Versus Greenhouse Gases

AbstractExperiments with seven Coupled Model Intercomparison Project phase 6 models were used to assess the climate feedback parameter for net historical, historical greenhouse gas (GHG) and anthropogenic aerosol forcings. The net radiative feedback is found to be more amplifying (higher effective climate sensitivity) for aerosol than GHG forcing, and hence also less amplifying for net historical (GHG + aerosol) than GHG only. We demonstrate that this difference is consistent with their different latitudinal distributions. Historical aerosol forcing is most pronounced in northern extratropics, where the boundary layer is decoupled from the free troposphere, so the consequent temperature change is confined to low altitude and causes low‐level cloud changes. This is caused by change in stability, which also affects upper‐tropospheric clear‐sky emission, affecting both shortwave and longwave radiative feedbacks. This response is a feature of extratropical forcing generally, regardless of its sign or hemisphere.

Asymmetric Warming/Cooling Response to CO2 Increase/Decrease Mainly Due To Non‐Logarithmic Forcing, Not Feedbacks

AbstractWe explore the CO2 dependence of effective climate sensitivity (SG) with symmetric abrupt and transient CO2 forcing, spanning the range 1/8×, 1/4×, 1/2×, 2×, 4×, and 8×CO2, using two state‐of‐the‐art fully coupled atmosphere‐ocean‐sea‐ice‐land models. In both models, under abrupt CO2 forcing, we find an asymmetric response in surface temperature and SG. The surface global warming at 8×CO2 is more than one third larger than the corresponding cooling at 1/8×CO2, and SG is CO2 dependent, increasing non‐monotonically from 1/8×CO2 to 8×CO2. We find similar CO2 dependence in the transient runs, forced with −1%yr−1CO2 and +1%yr−1CO2 up to 1/8×CO2 and 8×CO2, respectively. The non‐logarithmic radiative forcing—not the changing feedbacks—primarily explains the dependence of SG on CO2, particularly at low CO2 levels. The changing feedbacks, however, explain SG's non‐monotonic behavior.