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.     

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.     

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.     

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.     

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”方法量化不同反馈机制对地表温度的增温贡献,北极放大(AA)强于南极放大(ANA),由温度递减率反馈主导,其次是反照率和普朗克反馈.此外,海洋的热吸收导致冬季比夏季有更强的极地变暖.在冬季,温度递减率反馈主导了AA大于ANA.AA和ANA的模式间差异随着全球变暖的增强而减小.     

The dynamic greenhouse: Feedback processes that may influence future concentrations of atmospheric trace gases and climatic change

The sensitivity of the climate system to anthropogenic perturbations over the next century will be determined by a combination of feedbacks that amplify or damp the direct radiative effects of increasing concentrations of greenhouse gases. A number of important geophysical climate feedbacks, such as changes in water vapor, clouds, and sea ice albedo, are included in current climate models, but biogeochemical feedbacks such as changes in methane emissions, ocean CO₂ uptake, and vegetation albedo are generally neglected. The relative importance of a wide range of feedbacks is assessed here by estimating the gain associated with each individual process. The gain from biogeochemical feedbacks is estimated to be 0.05–0.29 compared to 0.17–0.77 for geophysical climate feedbacks. The potentially most significant biogeochemical feedbacks are probably release of methane hydrates, changes in ocean chemistry, biology, and circulation, and changes in the albedo of the global vegetation. While each of these feedbacks is modest compared to the water vapor feedback, the biogeochemical feedbacks in combination have the potential to substantially increase the climate change associated with any given initial forcing.The views expressed are the author's: They do not express official views of the U.S. Government or the Environmental Protection Agency.     

Assessment of different metrics for physical climate feedbacks

We quantify the feedbacks from the physical climate system on the radiative forcing for idealized climate simulations using four different methods. The results differ between the methods and differences are largest for the cloud feedback. The spatial and temporal variability of each feedback is used to estimate the averaging scale necessary to satisfy the feedback concept of one constant global mean value. We find that the year-to-year variability, combined with the methodological differences, in estimates of the feedback strength from a single model is comparable to the model-to-model spread in feedback strength of the CMIP3 ensemble. The strongest spatial and temporal variability is in the short-wave component of the cloud feedback. In our simulations, where many sources of natural variability are neglected, long-term averages are necessary to get reliable feedback estimates. Considering the large natural variability and relatively small forcing present in the real world, as compared to the forcing imposed by doubling CO₂ concentrations in the simulations, implies that using observations to constrain feedbacks is a challenging task and requires reliable long-term measurements.     

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??.     

Origins of differences in climate sensitivity, forcing and feedback in climate models

We diagnose climate feedback parameters and CO₂ forcing including rapid adjustment in twelve atmosphere/mixed-layer-ocean (“slab”) climate models from the CMIP3/CFMIP-1 project (the AR4 ensemble) and fifteen parameter-perturbed versions of the HadSM3 slab model (the PPE). In both ensembles, differences in climate feedbacks can account for approximately twice as much of the range in climate sensitivity as differences in CO₂ forcing. In the AR4 ensemble, cloud effects can explain the full range of climate sensitivities, and cloud feedback components contribute four times as much as cloud components of CO₂ forcing to the range. Non-cloud feedbacks are required to fully account for the high sensitivities of some models however. The largest contribution to the high sensitivity of HadGEM1 is from a high latitude clear-sky shortwave feedback, and clear-sky longwave feedbacks contribute substantially to the highest sensitivity members of the PPE. Differences in low latitude ocean regions (30°N/S) contribute more to the range than those in mid-latitude oceans (30–55°N/S), low/mid latitude land (55°N/S) or high latitude ocean/land (55–90°N/S), but contributions from these other regions are required to account fully for the higher model sensitivities, for example from land areas in IPSL CM4. Net cloud feedback components over the low latitude oceans sorted into percentile ranges of lower tropospheric stability (LTS) show largest differences among models in stable regions, mainly due to their shortwave components, most of which are positive in spite of increasing LTS. Differences in the mid-stability range are smaller, but cover a larger area, contributing a comparable amount to the range in climate sensitivity. These are strongly anti-correlated with changes in subsidence. Cloud components of CO₂ forcing also show the largest differences in stable regions, and are strongly anticorrelated with changes in estimated inversion strength (EIS). This is qualitatively consistent with what would be expected from observed relationships between EIS and low-level cloud fraction. We identify a number of cases where individual models show unusually strong forcings and feedbacks compared to other members of the ensemble. We encourage modelling groups to investigate unusual model behaviours further with sensitivity experiments. Most of the models fail to correctly reproduce the observed relationships between stability and cloud radiative effect in the subtropics, indicating that there remains considerable room for model improvements in the future.     

A DIAGNOSTIC STUDY OF FEEDBACK MECHANISM IN GREENHOUSE EFFECTS SIMULATED BY NCAR CCM1

This paper describes a diagnostic study of the feedback mechanism in greenhouse effects of increased CO_2 and oth-er trace gases(CH_4,N_2O and CFCs),simulated by general circulation model.The study is based on two sensitivity exper-iments for doubled CO_2 and the inclusion of other trace gases,respectively,using version one of the community climatemodel(CCM1)developed at the National Centre for Atmospheric Research.A one-dimensional(1-D)and atwo-dimensional(2-D)radiative-convective models are used to diagnose the feedback effect.It shows that thefeedback factors in global and annual mean conditions are in the sequence of surface albedo,water vapor amount,watervapor distribution,cloud height,critical lapse rate and cloud cover,while in zonal and annual mean conditions in thetropical region the above sequence does not change except the two water vapor terms being the largest feedback compo-nents.Among the feedback components,the total water vapor feedback is the largest(about 50%).The diagnosis alsogives a very small feedback of either the cloud cover or the lapse rate,which is substantially different from the 1-Dfeedback analysis by Hansen et al.(1984).The small lapse rate feedback is considered to be partly caused by theconvective adjustment scheme adopted by CCM1 model.The feedback effect for doubled CO_2 is very different from that of the addition of other trace gases because of theirdifferent vertical distributions of radiative forcing although the non-feedback responses of surface air temperature forboth cases are almost the same.For instance,the larger forcing at surface by the addition of other trace gases can causestronger surface albedo feedback than by doubled CO_2.Besides,because of the negative forcing of doubled CO_2 in thestratosphere,cloud height feedback is more intense.The larger surface forcing in the case of other trace gases can also in-fluence atmospheric water vapor amount as well as the water vapor distribution,which will in turn have strongerfeedback effects.All these indicate that it is incorrect to use“effective CO_2”to replace other trace gases in the generalcirculation model.     

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.     

Adjusted radiative forcing and global radiative feedbacks in CNRM-CM5, a closure of the partial decomposition

This study provides a comprehensive global analysis of the climate radiative feedbacks and the adjusted radiative forcing for a CO₂ increase perturbation in the CNRM-CM5 climate model using the partial radiative perturbations (PRP) method. Some methodological key points of the PRP are investigated, with a particular focus on the consideration of the effect of fast adjustments. First, the standard PRP method is applied by neglecting certain fast adjustments. The effect of the field decorrelation is highlighted by performing a PRP across two different periods of a control experiment and by analyzing second-order terms. Sensitivity tests to the field substitution frequency, the sampling period and the perturbed experiment used are performed. The impact of the definition of the top of the climate system (top-of-the-atmosphere or tropopause) in the feedback estimate is also discussed. Secondly, the fast adjustment processes are taken into account by combining the PRP framework with the method of linear regression of the partial net radiative flux change against the mean surface air temperature change using a step forcing experiment. This method allows us to quantify the contribution of the different constituents to the forcing adjustment and to improve the estimation of the radiative feedbacks. It is shown that such decomposition allows the retrieval of the adjusted radiative forcing, the radiative feedbacks and the climate sensitivity as estimated with the linear regression method with a high level of accuracy, validating the partial decomposition.     

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.     

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.     

Planetary albedo in strongly forced climate, as simulated by the CMIP3 models

In an ensemble of general circulation models, the global mean albedo significantly decreases in response to strong CO₂ forcing. In some of the models, the magnitude of this positive feedback is as large as the CO₂ forcing itself. The models agree well on the surface contribution to the trend, due to retreating snow and ice cover, but display large differences when it comes to the contribution from shortwave radiative effects of clouds. The ??cloud contribution?? defined as the difference between clear-sky and all-sky albedo anomalies and denoted as ??CC is correlated with equilibrium climate sensitivity in the models (correlation coefficient 0.76), indicating that in high sensitivity models the clouds to a greater extent act to enhance the negative clear-sky albedo trend, whereas in low sensitivity models the clouds rather counteract this trend. As a consequence, the total albedo trend is more negative in more sensitive models (correlation coefficient 0.73). This illustrates in a new way the importance of cloud response to global warming in determining climate sensitivity in models. The cloud contribution to the albedo trend can primarily be ascribed to changes in total cloud fraction, but changes in cloud albedo may also be of importance.     

Radiative forcing and response of a GCM to ice age boundary conditions: cloud feedback and climate sensitivity

 A general circulation model is used to examine the effects of reduced atmospheric CO₂, insolation changes and an updated reconstruction of the continental ice sheets at the Last Glacial Maximum (LGM). A set of experiments is performed to estimate the radiative forcing from each of the boundary conditions. These calculations are used to estimate a total radiative forcing for the climate of the LGM. The response of the general circulation model to the forcing from each of the changed boundary conditions is then investigated. About two-thirds of the simulated glacial cooling is due to the presence of the continental ice sheets. The effect of the cloud feedback is substantially modified where there are large changes to surface albedo. Finally, the climate sensitivity is estimated based on the global mean LGM radiative forcing and temperature response, and is compared to the climate sensitivity calculated from equilibrium experiments with atmospheric CO₂ doubled from present day concentration. The calculations here using the model and palaeodata support a climate sensitivity of about 1 Wm^-2 K^-1 which is within the conventional range. Received: 8 February 1997 / Accepted: 4 June 1997     

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO₂ doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.     

Quantifying global climate feedbacks, responses and forcing under abrupt and gradual CO2 forcing

Experiments with abrupt CO₂ forcing allow the diagnosis of the response of global mean temperature and precipitation in terms of fast temperature independent adjustments and slow, linear temperature-dependent feedbacks. Here we compare responses, feedbacks and forcings in experiments performed as part of version 5 of the coupled model inter-comparison project (CMIP5). The experiments facilitate, for the first time, a comparison of fully coupled atmosphere-ocean general circulation models (GCM’s) under both linearly increasing and abrupt radiative forcing. In the case of a 1 % per year compounded increase in CO₂ concentration, we find that the non-linear evolution of surface air temperature in time, when combined with the linear evolution of the radiative balance at the top of the atmosphere, results in a feedback parameter and effective climate sensitivity having an offset compared to values computed from abrupt 4× CO₂ forcing experiments. The linear evolution of the radiative balance at the top of the atmosphere also contributes to an offset between the global mean precipitation response predicted in the 1 % experiment using linear theory and that diagnosed from the experiments themselves, and a potential error between the adjusted radiative forcing and that produced using a standard linear formula. The non-linear evolution of temperature and precipitation responses are also evident in the RCP8.5 scenario and have implications for understanding, quantifying and emulating the global response of the CMIP5 climate GCMs.     

Climate feedbacks in a general circulation model incorporating prognostic clouds

 This study performs a comprehensive feedback analysis on the Bureau of Meteorology Research Centre General Circulation Model, quantifying all important feedbacks operating under an increase in atmospheric CO₂. The individual feedbacks are analysed in detail, using an offline radiation perturbation method, looking at long- and shortwave components, latitudinal distributions, cloud impacts, non-linearities under 2xCO₂ and 4xCO₂ warmings and at interannual variability. The water vapour feedback is divided into terms due to moisture height and amount changes. The net cloud feedback is separated into terms due to cloud amount, height, water content, water phase, physical thickness and convective cloud fraction. Globally the most important feedbacks were found to be (from strongest positive to strongest negative) those due to water vapour, clouds, surface albedo, lapse rate and surface temperature. For the longwave (LW) response the most important term of the cloud ‘optical property’ feedbacks is due to the water content. In the shortwave (SW), both water content and water phase changes are important. Cloud amount and height terms are also important for both LW and SW. Feedbacks due to physical cloud thickness and convective cloud fraction are found to be relatively small. All cloud component feedbacks (other than height) produce conflicting LW/SW feedbacks in the model. Furthermore, the optical property and cloud fraction feedbacks are also of opposite sign. The result is that the net cloud feedback is the (relatively small) product of conflicting physical processes. Non-linearities in the feedbacks are found to be relatively small for all but the surface albedo response and some cloud component contributions. The cloud impact on non-cloud feedbacks is also discussed: greatest impact is on the surface albedo, but impact on water vapour feedback is also significant. The analysis method here proves to be a␣powerful tool for detailing the contributions from different model processes (and particularly those of the clouds) to the final climate model sensitivity. Received: 15 June 2000 / Accepted: 10 January 2001     

Why Does FGOALS-gl Reproduce But a Reasonable Little Ice Age a Weak Medieval Warm Period and 20th Century Warming？

To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean Atmosphere-Land-Sea-ice （FGOALS-gl） to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural （solar radiation and volcanic eruptions） and anthropogenic （greenhouse gases and aerosols） forcing agents. The model feedback factors for （model sensitivity to） different forcings were calculated. The results show that the system feedback factor is about 2.5 （W m-2） K-1 in the pre-industrial period, while 1.9 （W m-2） K-1 in the industrial era. Thus, the model＇s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model＇s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation （overestimation） of the response of cloudiness （in-cloud water path）. In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.