On the observational determination of climate sensitivity and its implications

We estimate climate sensitivity from observations, using the deseasonalized fluctuations in sea surface temperatures (SSTs) and the concurrent fluctuations in the top-of-atmosphere (TOA) outgoing radiation from the ERBE (1985–1999) and CERES (2000–2008) satellite instruments. Distinct periods of warming and cooling in the SSTs were used to evaluate feedbacks. An earlier study (Lindzen and Choi, 2009) was subject to significant criticisms. The present paper is an expansion of the earlier paper where the various criticisms are taken into account. The present analysis accounts for the 72 day precession period for the ERBE satellite in a more appropriate manner than in the earlier paper. We develop a method to distinguish noise in the outgoing radiation as well as radiation changes that are forcing SST changes from those radiation changes that constitute feedbacks to changes in SST. We demonstrate that our new method does moderately well in distinguishing positive from negative feedbacks and in quantifying negative feedbacks. In contrast, we show that simple regression methods used by several existing papers generally exaggerate positive feedbacks and even show positive feedbacks when actual feedbacks are negative. We argue that feedbacks are largely concentrated in the tropics, and the tropical feedbacks can be adjusted to account for their impact on the globe as a whole. Indeed, we show that including all CERES data (not just from the tropics) leads to results similar to what are obtained for the tropics alone — though with more noise. We again find that the outgoing radiation resulting from SST fluctuations exceeds the zerofeedback response thus implying negative feedback. In contrast to this, the calculated TOA outgoing radiation fluxes from 11 atmospheric models forced by the observed SST are less than the zerofeedback response, consistent with the positive feedbacks that characterize these models. The results imply that the models are exaggerating climate sensitivity.     

The vertical distribution of climate forcings and feedbacks from the surface to top of atmosphere

The radiative forcings and feedbacks that determine Earth’s climate sensitivity are typically defined at the top-of-atmosphere (TOA) or tropopause, yet climate sensitivity itself refers to a change in temperature at the surface. In this paper, we describe how TOA radiative perturbations translate into surface temperature changes. It is shown using first principles that radiation changes at the TOA can be equated with the change in energy stored by the oceans and land surface. This ocean and land heat uptake in turn involves an adjustment of the surface radiative and non-radiative energy fluxes, with the latter being comprised of the turbulent exchange of latent and sensible heat between the surface and atmosphere. We employ the radiative kernel technique to decompose TOA radiative feedbacks in the IPCC Fourth Assessment Report climate models into components associated with changes in radiative heating of the atmosphere and of the surface. (We consider the equilibrium response of atmosphere-mixed layer ocean models subjected to an instantaneous doubling of atmospheric CO₂). It is shown that most feedbacks, i.e., the temperature, water vapor and cloud feedbacks, (as well as CO₂ forcing) affect primarily the turbulent energy exchange at the surface rather than the radiative energy exchange. Specifically, the temperature feedback increases the surface turbulent (radiative) energy loss by 2.87 W m^?2 K^?1 (0.60 W m^?2 K^?1) in the multimodel mean; the water vapor feedback decreases the surface turbulent energy loss by 1.07 W m^?2 K^?1 and increases the surface radiative heating by 0.89 W m^?2 K^?1; and the cloud feedback decreases both the turbulent energy loss and the radiative heating at the surface by 0.43 and 0.24 W m^?2 K^?1, respectively. Since changes to the surface turbulent energy exchange are dominated in the global mean sense by changes in surface evaporation, these results serve to highlight the fundamental importance of the global water cycle to Earth’s climate sensitivity.     

Non-linear climate feedback analysis in an atmospheric general circulation model

 A method is described for evaluating the ‘partial derivatives’ of globally averaged top-of-atmosphere (TOA) radiation changes with respect to basic climate model physical parameters. This method is used to analyse feedbacks in the Australian Bureau of Meteorology Research Centre general circulation model. The parameters considered are surface temperature, water vapour, lapse rate and cloud cover. The climate forcing which produces the changes is a globally uniform sea surface temperature (SST) perturbation. The first and second order differentials of model parameters with respect to the forcing (i.e. SST changes) are estimated from quadratic least square fitting. Except for total cloud cover, variables are found to be strong functions of global SST. Strongly non-linear variations of lapse rate and high cloud amount and height appear to relate to the non-linear response in penetrative convection. Globally averaged TOA radiation differentials with respect to model parameters are also evaluated. With the exception of total cloud contributions, a high correlation is generally found to exist, on the global mean level, between TOA radiation and the respective parameter perturbations. The largest non-linear terms contributing to radiative changes are those due to lapse rate and high cloud. The contributions of linear and non-linear terms to the overall radiative response from a 4 K SST perturbation are assessed. Significant non-linear responses are found to be associated with lapse rate, water vapour and cloud changes. Although the exact magnitude of these responses is likely to be a function of the particular model as well as the imposed SST perturbation pattern, the present experiments flag these as processes which cannot properly be understood from linear theory in the evaluation of climate change sensitivity. Received: 16 January 1997/Accepted: 9 May 1997     

Atmospheric radiative feedbacks associated with transient climate change and climate variability

This study examines in detail the ‘atmospheric’ radiative feedbacks operating in a coupled General Circulation Model (GCM). These feedbacks (defined as the change in top of atmosphere radiation per degree of global surface temperature change) are due to responses in water vapour, lapse rate, clouds and surface albedo. Two types of radiative feedback in particular are considered: those arising from century scale ‘transient’ warming (from a 1% per annum compounded CO₂ increase), and those operating under the model’s own unforced ‘natural’ variability. The time evolution of the transient (or ‘secular’) feedbacks is first examined. It is found that both the global strength and the latitudinal distributions of these feedbacks are established within the first two or three decades of warming, and thereafter change relatively little out to 100 years. They also closely approximate those found under equilibrium warming from a ‘mixed layer’ ocean version of the same model forced by a doubling of CO₂. These secular feedbacks are then compared with those operating under unforced (interannual) variability. For water vapour, the interannual feedback is only around two-thirds the strength of the secular feedback. The pattern reveals widespread regions of negative feedback in the interannual case, in turn resulting from patterns of circulation change and regions of decreasing as well as increasing surface temperature. Considering the vertical structure of the two, it is found that although positive net mid to upper tropospheric contributions dominate both, they are weaker (and occur lower) under interannual variability than under secular change and are more narrowly confined to the tropics. Lapse rate feedback from variability shows weak negative feedback over low latitudes combined with strong positive feedback in mid-to-high latitudes resulting in no net global feedback—in contrast to the dominant negative low to mid-latitude response seen under secular climate change. Surface albedo feedback is, however, slightly stronger under interannual variability—partly due to regions of extremely weak, or even negative, feedback over Antarctic sea ice in the transient experiment. Both long and shortwave global cloud feedbacks are essentially zero on interannual timescales, with the shortwave term also being very weak under climate change, although cloud fraction and optical property components show correlation with global temperature both under interannual variability and transient climate change. The results of this modelling study, although for a single model only, suggest that the analogues provided by interannual variability may provide some useful pointers to some aspects of climate change feedback strength, particularly for water vapour and surface albedo, but that structural differences will need to be heeded in such an analysis.     

A new framework for isolating individual feedback processes in coupled general circulation climate models. Part I: formulation

This paper proposes a coupled atmosphere–surface climate feedback–response analysis method (CFRAM) as a new framework for estimating climate feedbacks in coupled general circulation models with a full set of physical parameterization packages. The formulation of the CFRAM is based on the energy balance in an atmosphere–surface column. In the CFRAM, the isolation of partial temperature changes due to an external forcing or an individual feedback is achieved by solving the linearized infrared radiation transfer model subject to individual energy flux perturbations (external or due to feedbacks). The partial temperature changes are addable and their sum is equal to the (total) temperature change (in the linear sense). The decomposition of feedbacks is based on the thermodynamic and dynamical processes that directly affect individual energy flux terms. Therefore, not only those feedbacks that directly affect the TOA radiative fluxes, such as water vapor, clouds, and ice-albedo feedbacks, but also those feedbacks that do not directly affect the TOA radiation, such as evaporation, convections, and convergence of horizontal sensible and latent heat fluxes, are explicitly included in the CFRAM. In the CFRAM, the feedback gain matrices measure the strength of individual feedbacks. The feedback gain matrices can be estimated from the energy flux perturbations inferred from individual parameterization packages and dynamical modules. The inter-model spread of a feedback gain matrix would help us to detect the origins of the uncertainty of future climate projections in climate model simulations.     

Climate feedback efficiency and synergy

Earth’s climate sensitivity to radiative forcing induced by a doubling of the atmospheric CO₂ is determined by feedback mechanisms, including changes in atmospheric water vapor, clouds and surface albedo, that act to either amplify or dampen the response. The climate system is frequently interpreted in terms of a simple energy balance model, in which it is assumed that individual feedback mechanisms are additive and act independently. Here we test these assumptions by systematically controlling, or locking, the radiative feedbacks in a state-of-the-art climate model. The method is shown to yield a near-perfect decomposition of change into partial temperature contributions pertaining to forcing and each of the feedbacks. In the studied model water vapor feedback stands for about half the temperature change, CO₂-forcing about one third, while cloud and surface albedo feedback contributions are relatively small. We find a close correspondence between forcing, feedback and partial surface temperature response for the water vapor and surface albedo feedbacks, while the cloud feedback is inefficient in inducing surface temperature change. Analysis suggests that cloud-induced warming in the upper tropical troposphere, consistent with rising convective cloud anvils in a warming climate enhances the negative lapse-rate feedback, thereby offsetting some of the warming that would otherwise be attributable to this positive cloud feedback. By subsequently combining feedback mechanisms we find a positive synergy acting between the water vapor feedback and the cloud feedback; that is, the combined cloud and water vapor feedback is greater than the sum of its parts. Negative synergies surround the surface albedo feedback, as associated cloud and water vapor changes dampen the anticipated climate change induced by retreating snow and ice. Our results highlight the importance of treating the coupling between clouds, water vapor and temperature in a deepening troposphere.     

Climate sensitivity to cloud optical properties

A radiative–convective model was developed to investigate the sensitivity of climate to cloud optical properties and the related feedback processes. This model demonstrates that the Earth's surface temperature increases with cloud optical depth when the clouds are very thin but decreases with cloud optical depth when the cloud shortwave (solar) radiative forcing is larger than the cloud longwave (terrestrial) radiative forcing. When clouds are included in the model, the magnitude of the greenhouse effect due to a doubling of the CO₂ concentration varies with the cloudoptical depth: the thicker the clouds, the weaker the greenhouse warming. In addition, a small variation in the cloud droplet size has a larger impact on the equilibrium state temperature in the lower atmosphere than the warming caused by a doubling of the CO₂ concentration: a 2% increase in the average cloud droplet size per degree increase in temperature doubles the warming caused by the doubling of the CO₂ concentration. These findings suggest that physically reliable correlations between the cloud droplet size and macrophysical meteorological variables such as temperature, wind and water vapor fields are needed on a global climate scale to assess the climate impact of increases in greenhouse gases.     

Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs

The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.     

中国地区云对地-气系统辐射强迫温度效应的气候研究

文中利用地球辐射平衡试验 (ERBE)和国际卫星云气候计划 (ISCCP)提供的地 气系统行星反射率、射出长波辐射 (OLR)和云量资料 ,计算了中国地区年、月平均总云量对地 气系统短波辐射、长波辐射以及净辐射强迫的温度效应和敏感性系数 ,并讨论了云对各辐射分量强迫的温度效应与总云量的关系。结果表明 :地 气系统云辐射强迫温度效应与总云量间具有较明显的曲线相关。云辐射强迫温度效应及其敏感性系数具有明显的时空变化特点。就中国全国平均而言 ,各月地 气系统云辐射强迫净温度效应一般表现为降温作用。     

Quantifying contributions of climate feedbacks to tropospheric warming in the NCAR CCSM3.0

In this study, a coupled atmosphere-surface “climate feedback-response analysis method” (CFRAM) was applied to the slab ocean model version of the NCAR CCSM3.0 to understand the tropospheric warming due to a doubling of CO₂ concentration through quantifying the contributions of each climate feedback process. It is shown that the tropospheric warming displays distinct meridional and vertical patterns that are in a good agreement with the multi-model mean projection from the IPCC AR4. In the tropics, the warming in the upper troposphere is stronger than in the lower troposphere, leading to a decrease in temperature lapse rate, whereas in high latitudes the opposite it true. In terms of meridional contrast, the lower tropospheric warming in the tropics is weaker than that in high latitudes, resulting in a weakened meridional temperature gradient. In the upper troposphere the meridional temperature gradient is enhanced due to much stronger warming in the tropics than in high latitudes. Using the CFRAM method, we analyzed both radiative feedbacks, which have been emphasized in previous climate feedback analysis, and non-radiative feedbacks. It is shown that non-radiative (radiative) feedbacks are the major contributors to the temperature lapse rate decrease (increase) in the tropical (polar) region. Atmospheric convection is the leading contributor to temperature lapse rate decrease in the tropics. The cloud feedback also has non-negligible contributions. In the polar region, water vapor feedback is the main contributor to the temperature lapse rate increase, followed by albedo feedback and CO₂ forcing. The decrease of meridional temperature gradient in the lower troposphere is mainly due to strong cooling from convection and cloud feedback in the tropics and the strong warming from albedo feedback in the polar region. The strengthening of meridional temperature gradient in the upper troposphere can be attributed to the warming associated with convection and cloud feedback in the tropics. Since convection is the leading contributor to the warming differences between tropical lower and upper troposphere, and between the tropical and polar regions, this study indicates that tropical convection plays a critical role in determining the climate sensitivity. In addition, the CFRAM analysis shows that convective process and water vapor feedback are the two major contributors to the tropical upper troposphere temperature change, indicating that the excessive upper tropospheric warming in the IPCC AR4 models may be due to overestimated warming from convective process or underestimated cooling due to water vapor feedback.     

Changes in polar amplification in response to increasing warming in CMIP6

由于全球变暖,极地地区的气候经历了明显的变暖放大.在本项研究中,我们根据CMIP6模式的三种变暖情景(SSP1-2,6,SSP2-4.5和SSP5-8.5)下,极地放大变化对各个反馈机制(包括普朗克,温度递减率,云,水蒸气,反照率反馈,CO2强迫,海洋热吸收和大气热传输)的响应进行了分析.结果表明,通过用“辐射核”方法...     

On the vertical extent of atmospheric feedbacks

This study addresses the question: what vertical regions contribute the most to water vapor, surface temperature, lapse rate and cloud fraction feedback strengths in a general circulation model? Multi-level offline radiation perturbation calculations are used to diagnose the feedback contribution from each model level. As a first step, to locate regions of maximum radiative sensitivity to climate changes, the top of atmosphere radiative impact for each feedback is explored for each process by means of idealized parameter perturbations on top of a control (1?×?CO₂) model climate. As a second step, the actual feedbacks themselves are calculated using the changes modelled from a 2?×?CO₂ experiment. The impact of clouds on water vapor and lapse rate feedbacks is also isolated using `clear sky' calculations. Considering the idealized changes, it is found that the radiative sensitivity to water vapor changes is a maximum in the tropical lower troposphere. The sensitivity to temperature changes has both upper and lower tropospheric maxima. The sensitivity to idealized cloud changes is positive (warming) for upper level cloud increases but negative (cooling) for lower level increases, due to competing long and shortwave effects. Considering the actual feedbacks, it is found that water vapor feedback is a maximum in the tropical upper troposphere, due to the large relative increases in specific humidity which occur there. The actual lapse rate feedback changes sign with latitude and is a maximum (negative) again in the tropical upper troposphere. Cloud feedbacks reflect the general decrease in low- to mid-level low-latitude cloud, with an increase in the very highest cloud. This produces a net positive (negative) shortwave (longwave) cloud feedback. The role of clouds in the strength of the water vapor and lapse rate feedbacks is also discussed.     

On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates

This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO₂) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO₂ radiative forcing. By considering tropospheric adjustments to CO₂ as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO₂ is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO₂), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.     

Cloud-radiation feedbacks in a general circulation model and their dependence on cloud modelling assumptions

The general circulation model (GCM) used in this study includes a prognostic cloud scheme and a rather detailed radiation scheme. In a preceding paper, we showed that this model was more sensitive to a global perturbation of the sea surface temperatures than most other models with similar physical parametrization. The experiments presented here show how this feature might depend on some of the cloud modelling assumptions. We have changed the temperature at which the water clouds are allowed to become ice clouds and analyzed separately the feedbacks associated with the variations of cloud cover and cloud radiative properties. We show that the feedback effect associated with cloud radiative properties is positive in one case and negative in the other. This can be explained by the elementary cloud radiative forcing and has implications concerning the use of the GCMs for climate sensitivity studies.     

Climate sensitivity and response

Results from climate change simulations indicate a reasonably robust proportionality between global mean radiative forcing and global mean surface air temperature response. The "constant" of proportionality is a measure of the overall strength of climate feedback processes and hence of global climate sensitivity. Geographically, however, temperature response patterns are generally not proportional to, nor do they resemble, their parent forcing patterns. Temperature response patterns, nevertheless, exhibit a remarkable additivity whereby the sum of response patterns for different forcings closely resembles the response pattern for the sum of the forcings. The geographical distribution of contributions to the climate sensitivity/feedback are obtained diagnostically from simulations with the Canadian Centre for Climate Modelling and Analysis (CCCma) coupled global climate model (GCM). There is positive feedback over high-latitude oceans, over northern land areas, and over the equatorial Pacific. The remaining regions over oceans and tropical land areas exhibit negative feedback. The feedback results are decomposed into components associated with short-and longwave radiative processes and in terms of cloud-free atmosphere/surface and cloud feedbacks. While the geographic pattern of the feedbacks may generally be linked to local processes, all feedback processes display regions of both positive and negative values (except for the solar atmosphere/surface feedback associated with the retreat of ice and snow which is positive) and all vary from place to place so that there is no simple physical picture that operates everywhere. The stable geographical pattern of the feedback is a consequence of the balance between local physical processes rather than the dominance of a particular process. The feedback results indicate that, to first order, temperature response patterns are determined by the geographical pattern of local feedback processes. The feedback processes act to localize forcing changes and to generate temperature response patterns which depend firstly on the pattern of feedbacks and only secondarily on the pattern of the forcing. The geographical distribution of feedback processes can be regarded as a feature of the climate model (and by inference of the climate system) and not (or only comparatively weak) functions of forcing and climate state. An illustrative model is able to reproduce qualitatively the kinds of forcing/temperature response behavior seen in the CCCma GCM including the quasi-independence of forcing and response patterns, the additivity of temperature response patterns, and the resulting "non-constancy" of the global climate sensitivity.     

The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO₂ concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO₂. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.     

Towards constraining climate sensitivity by linear analysis of feedback patterns in thousands of perturbed-physics GCM simulations

A linear analysis is applied to a multi-thousand member “perturbed physics" GCM ensemble to identify the dominant physical processes responsible for variation in climate sensitivity across the ensemble. Model simulations are provided by the distributed computing project, climate prediction.net . A principal component analysis of model radiative response reveals two dominant independent feedback processes, each largely controlled by a single parameter change. The leading EOF was well correlated with the value of the entrainment coefficient—a parameter in the model’s atmospheric convection scheme. Reducing this parameter increases high vertical level moisture causing an enhanced clear sky greenhouse effect both in the control simulation and in the response to greenhouse gas forcing. This effect is compensated by an increase in reflected solar radiation from low level cloud upon warming. A set of ‘secondary’ cloud formation parameters partly modulate the degree of shortwave compensation from low cloud formation. The second EOF was correlated with the scaling of ice fall speed in clouds which affects the extent of cloud cover in the control simulation. The most prominent feature in the EOF was an increase in longwave cloud forcing. The two leading EOFs account for 70% of the ensemble variance in λ—the global feedback parameter. Linear predictors of feedback strength from model climatology are applied to observational datasets to estimate real world values of the overall climate feedback parameter. The predictors are found using correlations across the ensemble. Differences between predictions are largely due to the differences in observational estimates for top of atmosphere shortwave fluxes. Our validation does not rule out all the strong tropical convective feedbacks leading to a large climate sensitivity.     

Climate sensitivity and climate change under strong forcing

A version of the National Centre for Atmospheric Research (NCAR) coupled climate model is integrated under current climate conditions and in a series of experiments with climate forcings ranging from modest to very strong. The purpose of the experiments is to investigate the nature and behaviour of the climate feedback/sensitivity of the model, its evolution with time and climate state, the robustness of model parameterizations as forcing levels increase, and the possibility of a “runaway” warming under strong forcing. The model is integrated for 50 years, or to failure, after increasing the solar constant by 2.5, 10, 15, 25, 35, and 45% of its control value. The model successfully completes 50 years of integration for the 2.5, 10, 15, and 25% solar constant increases but fails for increases of 35% and 45%. The effective global climate sensitivity evolves with time and analysis indicates that a new equilibrium will be obtained for the 2.5, 10, and 15% cases but that runaway warming is underway for the 25% increase in solar constant. Feedback processes are analysed both locally and globally in terms of longwave and shortwave, clear-sky/surface, and cloud forcing components. Feedbacks in the system must be negative overall and of sufficient strength to balance the positive forcing if the system is to attain a new equilibrium. Longwave negative feedback processes strengthen in a reasonably linear fashion as temperature increases but shortwave feedback processes do not. In particular, solar cloud feedback becomes less negative and, for the 25% forcing case, eventually becomes positive, resulting in temperatures that “run away”. The conditions under which a runaway climate warming might occur have previously been investigated using simpler models. For sufficiently strong forcing, the greenhouse effect of increasing water vapour in a warmer atmosphere is expected to overwhelm the negative feedback of the longwave cooling to space as temperature increases. This is not, however, the reason for the climate instability experienced in the GCM. Instead, the model experiences a “cloud feedback” warming whereby the decrease in cloudiness that occurs when temperature increases beyond a critical value results in an increased absorption of solar radiation by the system, leading to the runaway warming.     

On tropospheric adjustment to forcing and climate feedbacks

Motivated by findings that major components of so-called cloud ??feedbacks?? are best understood as rapid responses to CO₂ forcing (Gregory and Webb in J Clim 21:58?C71, 2008), the top of atmosphere (TOA) radiative effects from forcing, and the subsequent responses to global surface temperature changes from all ??atmospheric feedbacks?? (water vapour, lapse rate, surface albedo, ??surface temperature?? and cloud) are examined in detail in a General Circulation Model. Two approaches are used: applying regressions to experiments as they approach equilibrium, and equilibrium experiments forced separately by CO₂ and patterned sea surface temperature perturbations alone. Results are analysed using the partial radiative perturbation (??PRP??) technique. In common with Gregory and Webb (J Clim 21:58?C71, 2008) a strong positive addition to ??forcing?? is found in the short wave (SW) from clouds. There is little evidence, however, of significant global scale rapid responses from long wave (LW) cloud, nor from surface albedo, SW water vapour or ??surface temperature??. These responses may be well understood to first order as classical ??feedbacks????i.e. as a function of global mean temperature alone and linearly related to it. Linear regression provides some evidence of a small rapid negative response in the LW from water vapour, related largely to decreased relative humidity (RH), but the response here, too, is dwarfed by subsequent response to warming. The large rapid SW cloud response is related to cloud fraction changes??and not optical properties??resulting from small cloud decreases ranging from the tropical mid troposphere to the mid latitude lower troposphere, in turn associated with decreased lower tropospheric RH. These regions correspond with levels of enhanced heating rates and increased temperatures from the CO₂ increase. The pattern of SW cloud fraction response to SST changes differs quite markedly to this, with large positive radiation responses originating in the upper troposphere, positive contributions in the lowest levels and patterns of positive/negative contributions in mid latitude low levels. Overall SW cloud feedback was diagnosed as negative, due to the substantial negative SW feedback in cloud optical properties more than offsetting these. This study therefore suggests the rapid response to CO₂ forcing is (apart from a possible small negative response from LW water vapour) essentially confined to cloud fraction changes affecting SW radiation, and further that significant feedbacks with temperature occur in all cloud components (including this one), and indeed in all other classically understood ??feedbacks??.     

辐射参数化方案对一个海气耦合模式云和辐射模拟的影响

比较Morcrette辐射方案和Fu_Liou辐射方案对NCC/IAP T63海气耦合模式云和辐射模拟的影响, 结果表明:两种方案模拟的大气顶入射辐射存在明显的差异; 晴空大气Fu_Liou方案的短波吸收能力在全球普遍较Morcrette方案低; 在60°S~60°N之间, Fu_Liou方案模拟的行星反照率更接近于ERBE卫星观测; 在对大气顶净辐射的模拟上, 除了冬季的太平洋和大西洋东岸云量明显减少的部分地区外, Fu_Liou方案对大气顶净辐射的模拟总体上较Morcrette方案有了较为明显的改善; Fu_Liou方案模拟的海洋低层云显著减少, 而热带地区高云的模拟明显增加; 由于采用了“二元云量”算法, 尽管云量有所减少, Fu_Liou方案模拟的云短波吸收作用仍有所增强, 一定程度上改进了Morcrette方案云的短波吸收作用偏弱的现象。