Effective Climate Sensitivity Research Articles

Causes of Higher Climate Sensitivity in CMIP6 Models

AbstractEquilibrium climate sensitivity, the global surface temperature response to CO doubling, has been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global climate models (GCMs), which attempt to represent all relevant physical processes, provide the most direct means of estimating climate sensitivity via CO quadrupling experiments. Here we show that the closely related effective climate sensitivity has increased substantially in Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8–5.6 K across 27 GCMs and exceeding 4.5 K in 10 of them. This (statistically insignificant) increase is primarily due to stronger positive cloud feedbacks from decreasing extratropical low cloud coverage and albedo. Both of these are tied to the physical representation of clouds which in CMIP6 models lead to weaker responses of extratropical low cloud cover and water content to unforced variations in surface temperature. Establishing the plausibility of these higher sensitivity models is imperative given their implied societal ramifications.

Climate models disagree on the sign of total radiative feedback in the Arctic

Climate feedbacks have been found to strongly impact the observed amplified Arctic warming. However, Arctic amplification is modeled with a wide spread which partly arises from intermodel differences of the various feedbacks. To explain the spread in modeled Arctic warming, feedback uncertainties and their origins are investigated in 13 climate models in an experiment with abruptly quadrupled CO2. While intermodel differences in the cloud feedback, being strongest in the Tropics, have been found to determine the spread of global mean effective climate sensitivity, we find that in the Arctic the cloud feedback is not responsible for the spread of Arctic warming as its contribution is too small. Instead, the spread of Arctic warming is explained by differing estimates of surface albedo and Planck feedbacks which show the largest intermodel differences. Our results indicate that these uncertainties not only arise from different degrees of simulated Arctic warming but also are partly related to the large differences in initial sea ice cover and surface temperatures which contribute to the increased spread in estimated warming compared to lower latitudes. Further investigations of feedback dependencies to the base state are needed to constrain the impact of initial uncertainties and to obtain robust results. The most significant distinction between models is the sign of the total feedback parameter. While all models investigated here simulate a negative global mean total feedback, only half of them also show negative Arctic feedbacks which implies that Arctic local feedbacks alone suffice to stably adjust Arctic surface temperatures in response to a radiative perturbation. The other half exhibits positive total Arctic feedbacks indicating local runaway systems which need to be balanced by decreased meridional heat transports. Whether or not a model features such a behaviour depends upon the strength of the simulated positive surface albedo versus the negative Planck feedback.

Forcings, Feedbacks, and Climate Sensitivity in HadGEM3‐GC3.1 and UKESM1

AbstractClimate forcing, sensitivity, and feedback metrics are evaluated in both the United Kingdom's physical climate model HadGEM3‐GC3.1 at low (‐LL) and medium (‐MM) resolution and the United Kingdom's Earth System Model UKESM1. The effective climate sensitivity (EffCS) to a doubling of CO2 is 5.5 K for HadGEM3.1‐GC3.1‐LL and 5.4 K for UKESM1. The transient climate response is 2.5 and 2.8 K, respectively. While the EffCS is larger than that seen in the previous generation of models, none of the model's forcing or feedback processes are found to be atypical of models, though the cloud feedback is at the high end. The relatively large EffCS results from an unusual combination of a typical CO2 forcing with a relatively small feedback parameter. Compared to the previous U.K. climate model, HadGEM3‐GC2.0, the EffCS has increased from 3.2 to 5.5 K due to an increase in CO2 forcing, surface albedo feedback, and midlatitude cloud feedback. All changes are well understood and due to physical improvements in the model. At higher atmospheric and ocean resolution (HadGEM3‐GC3.1‐MM), there is a compensation between increased marine stratocumulus cloud feedback and reduced Antarctic sea‐ice feedback. In UKESM1, a CO2 fertilization effect induces a land surface vegetation change and albedo radiative effect. Historical aerosol forcing in HadGEM3‐GC3.1‐LL is −1.1 W m−2. In HadGEM3‐GC3.1‐LL historical simulations, cloud feedback is found to be less positive than in abrupt‐4xCO2, in agreement with atmosphere‐only experiments forced with observed historical sea surface temperature and sea‐ice variations. However, variability in the coupled model's historical sea‐ice trends hampers accurate diagnosis of the model's total historical feedback.

Uncertainty in the Evolution of Climate Feedback Traced to the Strength of the Atlantic Meridional Overturning Circulation

AbstractIn most coupled climate models, effective climate sensitivity increases for a few decades following an abrupt CO2 increase. The change in the climate feedback parameter between the first 20 years and the subsequent 130 years is highly model dependent. In this study, we suggest that the intermodel spread of changes in climate feedback can be partially traced to the evolution of the Atlantic Meridional Overturning Circulation. Models with stronger Atlantic Meridional Overturning Circulation recovery tend to project more amplified warming in the Northern Hemisphere a few decades after a quadrupling of CO2. Tropospheric stability then decreases as the Northern Hemisphere gets warmer, which leads to an increase in both the lapse‐rate and shortwave cloud feedbacks. Our results suggest that constraining future ocean circulation changes will be necessary for accurate climate sensitivity projections.

How accurately can the climate sensitivity to hbox {CO}_{2} be estimated from historical climate change?

The equilibrium climate sensitivity (ECS, in K) to hbox {CO}_{2} doubling is a large source of uncertainty in projections of future anthropogenic climate change. Estimates of ECS made from non-equilibrium states or in response to radiative forcings other than hbox {2}times hbox {CO}_{2} are called “effective climate sensitivity” (EffCS, in K). Taking a “perfect-model” approach, using coupled atmosphere–ocean general circulation model (AOGCM) experiments, we evaluate the accuracy with which hbox {CO}_{2} EffCS can be estimated from climate change in the “historical” period (since about 1860). We find that (1) for statistical reasons, unforced variability makes the estimate of historical EffCS both uncertain and biased; it is overestimated by about 10% if the energy balance is applied to the entire historical period, 20% for 30-year periods, and larger factors for interannual variability, (2) systematic uncertainty in historical radiative forcing translates into an uncertainty of {pm },30, {rm to} ,45% (standard deviation) in historical EffCS, (3) the response to the changing relative importance of the forcing agents, principally hbox {CO}_{2} and volcanic aerosol, causes historical EffCS to vary over multidecadal timescales by a factor of two. In recent decades it reached its maximum in the AOGCM historical experiment (similar to the multimodel-mean hbox {CO}_{2} EffCS of 3.6 K from idealised experiments), but its minimum in the real world (1.6 K for an observational estimate for 1985–2011, similar to the multimodel-mean value for volcanic forcing). The real-world variations mean that historical EffCS underestimates hbox {CO}_{2} EffCS by 30% when considering the entire historical period. The difference for recent decades implies that either unforced variability or the response to volcanic forcing causes a much stronger regional pattern of sea surface temperature change in the real world than in AOGCMs. We speculate that this could be explained by a deficiency in simulated coupled atmosphere–ocean feedbacks which reinforce the pattern (resembling the Interdecadal Pacific Oscillation in some respects) that causes the low EffCS. We conclude that energy-balance estimates of hbox {CO}_{2} EffCS are most accurate from periods unaffected by volcanic forcing. Atmosphere GCMs provided with observed sea surface temperature for the 1920s to the 1950s, which was such a period, give a range of about 2.0–4.5 K, agreeing with idealised hbox {CO}_{2} AOGCM experiments; the consistency is a reason for confidence in this range as an estimate of hbox {CO}_{2} EffCS. Unless another explosive volcanic eruption occurs, the first 30 years of the present century may give a more accurate energy-balance historical estimate of this quantity.

Responses of Clouds and Large‐Scale Circulation to Global Warming Evaluated From Multidecadal Simulations Using a Global Nonhydrostatic Model

AbstractThis is the first paper that analyzes data from atmosphere model intercomparison project‐type climate simulations using a cloud‐system‐resolving global nonhydrostatic model without cumulus parameterization focussing particulaly on the relationship between clouds and circulation, and their changes due to global warming. The decrease in fractional coverage of low clouds is key to evaluating cloud radiative effects, because changes in shortwave cloud radiative effects overwhelm those of longwave cloud radiative effects. Thus, improved evaluation of low clouds is important, even in high‐resolution climate simulations. An analysis of heat redistribution by explicitly computed clouds revealed that column‐integrated heating rate due to phase changes correlates highly with vertical velocity at the altitude corresponding to 500 hPa and is closely linked to column water vapor, similar to the present climate result. Using data from year 1 to year 5, the effective climate sensitivity was evaluated to be 3.6−3.7°C. Possible convective aggregation is also examined using an index of modified subsidence fraction and characteristic changes in the number of cold pools. Despite previous idealized‐planet simulations showing more aggregated tropical convection under warmer conditions, here we show a decrease in the subsidence fraction and an increase in the number of smaller cold pools, suggesting that it is possible to realize less convective organization with warming under real atmospheric conditions.

Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6

Abstract. The sixth version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC6, was cooperatively developed by a Japanese modeling community. In the present paper, simulated mean climate, internal climate variability, and climate sensitivity in MIROC6 are evaluated and briefly summarized in comparison with the previous version of our climate model (MIROC5) and observations. The results show that the overall reproducibility of mean climate and internal climate variability in MIROC6 is better than that in MIROC5. The tropical climate systems (e.g., summertime precipitation in the western Pacific and the eastward-propagating Madden–Julian oscillation) and the midlatitude atmospheric circulation (e.g., the westerlies, the polar night jet, and troposphere–stratosphere interactions) are significantly improved in MIROC6. These improvements can be attributed to the newly implemented parameterization for shallow convective processes and to the inclusion of the stratosphere. While there are significant differences in climates and variabilities between the two models, the effective climate sensitivity of 2.6 K remains the same because the differences in radiative forcing and climate feedback tend to offset each other. With an aim towards contributing to the sixth phase of the Coupled Model Intercomparison Project, designated simulations tackling a wide range of climate science issues, as well as seasonal to decadal climate predictions and future climate projections, are currently ongoing using MIROC6.

Estimates of climate system properties incorporating recent climate change

Abstract. Historical time series of surface temperature and ocean heat content changes are commonly used metrics to diagnose climate change and estimate properties of the climate system. We show that recent trends, namely the slowing of surface temperature rise at the beginning of the 21st century and the acceleration of heat stored in the deep ocean, have a substantial impact on these estimates. Using the Massachusetts Institute of Technology Earth System Model (MESM), we vary three model parameters that influence the behavior of the climate system: effective climate sensitivity (ECS), the effective ocean diffusivity of heat anomalies by all mixing processes (Kv), and the net anthropogenic aerosol forcing scaling factor. Each model run is compared to observed changes in decadal mean surface temperature anomalies and the trend in global mean ocean heat content change to derive a joint probability distribution function for the model parameters. Marginal distributions for individual parameters are found by integrating over the other two parameters. To investigate how the inclusion of recent temperature changes affects our estimates, we systematically include additional data by choosing periods that end in 1990, 2000, and 2010. We find that estimates of ECS increase in response to rising global surface temperatures when data beyond 1990 are included, but due to the slowdown of surface temperature rise in the early 21st century, estimates when using data up to 2000 are greater than when data up to 2010 are used. We also show that estimates of Kv increase in response to the acceleration of heat stored in the ocean as data beyond 1990 are included. Further, we highlight how including spatial patterns of surface temperature change modifies the estimates. We show that including latitudinal structure in the climate change signal impacts properties with spatial dependence, namely the aerosol forcing pattern, more than properties defined for the global mean, climate sensitivity, and ocean diffusivity.

Accounting for Changing Temperature Patterns Increases Historical Estimates of Climate Sensitivity

AbstractEight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect, whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the long‐term Otto et al. (2013, https://doi.org/10.1038/ngeo1836) EffCS median and 5–95% confidence interval from 1.9 K (0.9–5.0 K) to 3.2 K (1.5–8.1 K).

Climate sensitivity estimates – sensitivity to radiative forcing time series and observational data

Abstract. Inferred effective climate sensitivity (ECSinf) is estimated using a method combining radiative forcing (RF) time series and several series of observed ocean heat content (OHC) and near-surface temperature change in a Bayesian framework using a simple energy balance model and a stochastic model. The model is updated compared to our previous analysis by using recent forcing estimates from IPCC, including OHC data for the deep ocean, and extending the time series to 2014. In our main analysis, the mean value of the estimated ECSinf is 2.0 ∘C, with a median value of 1.9 ∘C and a 90 % credible interval (CI) of 1.2–3.1 ∘C. The mean estimate has recently been shown to be consistent with the higher values for the equilibrium climate sensitivity estimated by climate models. The transient climate response (TCR) is estimated to have a mean value of 1.4 ∘C (90 % CI 0.9–2.0 ∘C), and in our main analysis the posterior aerosol effective radiative forcing is similar to the range provided by the IPCC. We show a strong sensitivity of the estimated ECSinf to the choice of a priori RF time series, excluding pre-1950 data and the treatment of OHC data. Sensitivity analysis performed by merging the upper (0–700 m) and the deep-ocean OHC or using only one OHC dataset (instead of four in the main analysis) both give an enhancement of the mean ECSinf by about 50 % from our best estimate.

The Active Role of the Ocean in the Temporal Evolution of Climate Sensitivity

AbstractThe temporal evolution of the effective climate sensitivity is shown to be influenced by the changing pattern of sea surface temperature (SST) and ocean heat uptake (OHU), which in turn have been attributed to ocean circulation changes. A set of novel experiments are performed to isolate the active role of the ocean by comparing a fully coupled CO2 quadrupling community Earth System Model (CESM) simulation against a partially coupled one, where the effect of the ocean circulation change and its impact on surface fluxes are disabled. The active OHU is responsible for the reduced effective climate sensitivity and weaker surface warming response in the fully coupled simulation. The passive OHU excites qualitatively similar feedbacks to CO2 quadrupling in a slab ocean model configuration due to the similar SST spatial pattern response in both experiments. Additionally, the nonunitary forcing efficacy of the active OHU (1.7) explains the very different net feedback parameters in the fully and partially coupled responses.

Relationship of tropospheric stability to climate sensitivity and Earth’s observed radiation budget

Climate feedbacks generally become smaller in magnitude over time under CO2 forcing in coupled climate models, leading to an increase in the effective climate sensitivity, the estimated global-mean surface warming in steady state for doubled CO2 Here, we show that the evolution of climate feedbacks in models is consistent with the effect of a change in tropospheric stability, as has recently been hypothesized, and the latter is itself driven by the evolution of the pattern of sea-surface temperature response. The change in climate feedback is mainly associated with a decrease in marine tropical low cloud (a more positive shortwave cloud feedback) and with a less negative lapse-rate feedback, as expected from a decrease in stability. Smaller changes in surface albedo and humidity feedbacks also contribute to the overall change in feedback, but are unexplained by stability. The spatial pattern of feedback changes closely matches the pattern of stability changes, with the largest increase in feedback occurring in the tropical East Pacific. Relationships qualitatively similar to those in the models among sea-surface temperature pattern, stability, and radiative budget are also found in observations on interannual time scales. Our results suggest that constraining the future evolution of sea-surface temperature patterns and tropospheric stability will be necessary for constraining climate sensitivity.

Lower-Tropospheric Mixing as a Constraint on Cloud Feedback in a Multiparameter Multiphysics Ensemble

Abstract Factors and possible constraints to extremely large spread of effective climate sensitivity (ECS) ranging about 2.1–10.4 K are examined by using a large-member ensemble of quadrupling CO2 experiments with an atmospheric general circulation model (AGCM). The ensemble, called the multiparameter multiphysics ensemble (MPMPE), consists of both parametric and structural uncertainties in parameterizations of cloud, cumulus convection, and turbulence based on two different versions of AGCM. The sum of the low- and middle-cloud shortwave feedback explains most of the ECS spread among the MPMPE members. For about half of the perturbed physics ensembles (PPEs) in the MPMPE, variation in lower-tropospheric mixing intensity (LTMI) corresponds well with the ECS variation, whereas it does not for the other half. In the latter PPEs, large spread in optically thick middle-cloud feedback over the equatorial ocean substantially affects the ECS, disrupting the LTMI–ECS relationship. Although observed LTMI can constrain uncertainty in the low-cloud feedback, total uncertainty of the ECS among the MPMPE cannot solely be explained by the LTMI, suggesting a limitation of single emergent constraint for the ECS.

Idealized climate change simulations with a high‐resolution physical model: HadGEM3‐GC2

AbstractIdealized climate change simulations with a new physical climate model, HadGEM3‐GC2 from The Met Office Hadley Centre are presented and contrasted with the earlier MOHC model, HadGEM2‐ES. The role of atmospheric resolution is also investigated. The Transient Climate Response (TCR) is 1.9 K/2.1 K at N216/N96 and Effective Climate Sensitivity (ECS) is 3.1 K/3.2 K at N216/N96. These are substantially lower than HadGEM2‐ES (TCR: 2.5 K; ECS: 4.6 K) arising from a combination of changes in the size of climate feedbacks. While the change in the net cloud feedback between HadGEM3 and HadGEM2 is relatively small, there is a change in sign of its longwave and a strengthening of its shortwave components. At a global scale, there is little impact of the increase in atmospheric resolution on the future climate change signal and even at a broad regional scale, many features are robust including tropical rainfall changes, however, there are some significant exceptions. For the North Atlantic and western Europe, the tripolar pattern of winter storm changes found in most CMIP5 models is little impacted by resolution but for the most intense storms, there is a larger percentage increase in number at higher resolution than at lower resolution. Arctic sea‐ice sensitivity shows a larger dependence on resolution than on atmospheric physics.

Estimating climate sensitivity using two‐zone energy balance models

AbstractEstimates of 2 × CO2 equilibrium climate sensitivity (EqCS) derive from running global climate models (GCMs) to equilibrium. Estimates of effective climate sensitivity (EfCS) are the corresponding quantities obtained using transient GCM output or observations. The EfCS approach uses an accompanying energy balance model (EBM), the zero‐dimensional model (ZDM) being standard. GCM values of EqCS and EfCS vary widely [Intergovernmental Panel on Climate Change range: (1.5, 4.5)°C] and have failed to converge over the past 35 years. Recently, attempts have been made to refine the EfCS approach by using two‐zone (tropical/extratropical) EBMs. When applied using satellite radiation data, these give low and tightly constrained EfCS values, in the neighborhood of 1°C. These low observational EfCS/two‐zone EBM values have been questioned because (a) they disagree with higher observational EfCS/ZDM values and (b) the EfCS/two‐zone EBM values given by GCMs are poorly correlated with the standard GCM sensitivity estimates. The validity of the low observational EfCS/two‐zone EBM values is here explored, with focus on the limitations of the observational EfCS/ZDM approach, the disagreement between the GCM and observational radiative responses to surface temperature perturbations in the tropics, and on the modified EfCS values provided by an extended two‐zone EBM that includes an explicit parameterization of dynamical heat transport. The results support the low observational EfCS/two‐zone EBM values, indicating that objections (a) and (b) to these values both need to be reconsidered. It is shown that in the EBM with explicit dynamical heat transport the traditional formulism of climate feedbacks can break down because of lack of additivity.

Variation in climate sensitivity and feedback parameters during the historical period

AbstractWe investigate the climate feedback parameter α (W m−2 K−1) during the historical period (since 1871) in experiments using the HadGEM2 and HadCM3 atmosphere general circulation models (AGCMs) with constant preindustrial atmospheric composition and time‐dependent observational sea surface temperature (SST) and sea ice boundary conditions. In both AGCMs, for the historical period as a whole, the effective climate sensitivity is ∼2 K (α≃1.7 W m−2 K−1), and α shows substantial decadal variation caused by the patterns of SST change. Both models agree with the AGCMs of the latest Coupled Model Intercomparison Project in showing a considerably smaller effective climate sensitivity of ∼1.5 K (α = 2.3 ± 0.7 W m−2 K−1), given the time‐dependent changes in sea surface conditions observed during 1979–2008, than the corresponding coupled atmosphere‐ocean general circulation models (AOGCMs) give under constant quadrupled CO2 concentration. These findings help to relieve the apparent contradiction between the larger values of effective climate sensitivity diagnosed from AOGCMs and the smaller values inferred from historical climate change.

An Assessment of Direct Radiative Forcing, Radiative Adjustments, and Radiative Feedbacks in Coupled Ocean–Atmosphere Models

AbstractIn this study, radiative kernels are used to separate direct radiative forcing from radiative adjustments to that forcing to quantify the magnitude and intermodel spread of tropospheric and stratospheric adjustments in coupled ocean–atmosphere climate models. Radiative feedbacks are also quantified and separated from radiative forcing by assuming that feedbacks are a linear response to changes in global-mean surface temperature. The direct radiative forcing due to a quadrupling of CO2 is found to have an intermodel spread of ~3 W m−2. In contrast to previous studies, relatively small estimates of cloud adjustments are obtained, which are both positive and negative. This discrepancy is at least partially attributable to small, but nonnegligible, global-mean surface warming in fixed sea surface temperature experiments, which aliases a surface-driven feedback response into estimates of the adjustments. This study suggests that correcting for the bias induced from this global-mean surface warming offers a more accurate estimate of tropospheric adjustments. It is shown that the regional patterns in the tropospheric adjustments tend to oppose the radiative feedback. This compensation is closely tied to spatial inhomogeneities in the initial rate of surface warming, suggesting that a substantial part of the spatial variation in the estimated tropospheric adjustment is an artifact of the linear regression methodology. Even when assuming that the global-mean estimates of the tropospheric adjustments are valid, neglecting them introduces little uncertainty in estimates of the total forcing, feedback, or effective climate sensitivity relative to the intermodel spread in these values.

The Dependence of Radiative Forcing and Feedback on Evolving Patterns of Surface Temperature Change in Climate Models

Abstract Experiments with CO2 instantaneously quadrupled and then held constant are used to show that the relationship between the global-mean net heat input to the climate system and the global-mean surface air temperature change is nonlinear in phase 5 of the Coupled Model Intercomparison Project (CMIP5) atmosphere–ocean general circulation models (AOGCMs). The nonlinearity is shown to arise from a change in strength of climate feedbacks driven by an evolving pattern of surface warming. In 23 out of the 27 AOGCMs examined, the climate feedback parameter becomes significantly (95% confidence) less negative (i.e., the effective climate sensitivity increases) as time passes. Cloud feedback parameters show the largest changes. In the AOGCM mean, approximately 60% of the change in feedback parameter comes from the tropics (30°N–30°S). An important region involved is the tropical Pacific, where the surface warming intensifies in the east after a few decades. The dependence of climate feedbacks on an evolving pattern of surface warming is confirmed using the HadGEM2 and HadCM3 atmosphere GCMs (AGCMs). With monthly evolving sea surface temperatures and sea ice prescribed from its AOGCM counterpart, each AGCM reproduces the time-varying feedbacks, but when a fixed pattern of warming is prescribed the radiative response is linear with global temperature change or nearly so. It is also demonstrated that the regression and fixed-SST methods for evaluating effective radiative forcing are in principle different, because rapid SST adjustment when CO2 is changed can produce a pattern of surface temperature change with zero global mean but nonzero change in net radiation at the top of the atmosphere (~−0.5 W m−2 in HadCM3).

A large ozone-circulation feedback and its implications for global warming assessments.

State-of-the-art climate models now include more climate processes which are simulated at higher spatial resolution than ever1. Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations1,2. Here we present evidence that how stratospheric ozone is represented in climate models can have a first order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere-ocean chemistry-climate model, we find an increase in global mean surface warming of around 1°C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO2 forcing. The difference is primarily attributed to changes in longwave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies1,2 in which participating models often use simplified treatments of atmospheric composition changes that are neither consistent with the specified greenhouse gas forcing scenario nor with the associated atmospheric circulation feedbacks3-5.

Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming

Although current global warming may have a large anthropogenic component, its quantification relies primarily on complex General Circulation Models (GCM’s) assumptions and codes; it is desirable to complement this with empirically based methodologies. Previous attempts to use the recent climate record have concentrated on “fingerprinting” or otherwise comparing the record with GCM outputs. By using CO2 radiative forcings as a linear surrogate for all anthropogenic effects we estimate the total anthropogenic warming and (effective) climate sensitivity finding: ΔT anth = 0.87 ± 0.11 K, $$\uplambda_{{2{\text{x}}{\text{CO}}_{2} ,{\text{eff}}}} = 3.08 \pm 0.58\,{\text{K}}$$ . These are close the IPPC AR5 values ΔT anth = 0.85 ± 0.20 K and $$\uplambda_{{2{\text{x}}{\text{CO}}_{2} }} = 1.5\!-\!4.5\,{\text{K}}$$ (equilibrium) climate sensitivity and are independent of GCM models, radiative transfer calculations and emission histories. We statistically formulate the hypothesis of warming through natural variability by using centennial scale probabilities of natural fluctuations estimated using scaling, fluctuation analysis on multiproxy data. We take into account two nonclassical statistical features—long range statistical dependencies and “fat tailed” probability distributions (both of which greatly amplify the probability of extremes). Even in the most unfavourable cases, we may reject the natural variability hypothesis at confidence levels >99 %.