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.     

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.     

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%.     

Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles

Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections.     

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.     

Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models

 This study compares radiative fluxes and cloudiness fields from three general circulation models (the HadAM4 version of the Hadley Centre Unified model, cycle 16r2 of the ECMWF model and version LMDZ 2.0 of the LMD GCM), using a combination of satellite observations from the Earth Radiation Budget Experiment (ERBE) and the International Satellite Cloud Climatology Project (ISCCP). To facilitate a meaningful comparison with the ISCCP C1 data, values of column cloud optical thickness and cloud top pressure are diagnosed from the models in a manner consistent with the satellite view from space. Decomposing the cloud radiative effect into contributions from low-medium- and high-level clouds reveals a tendency for the models' low-level clouds to compensate for underestimates in the shortwave cloud radiative effect caused by a lack of high-level or mid-level clouds. The low clouds fail to compensate for the associated errors in the longwave. Consequently, disproportionate errors in the longwave and shortwave cloud radiative effect in models may be taken as an indication that compensating errors are likely to be present. Mid-level cloud errors in the mid-latitudes appear to depend as much on the choice of the convection scheme as on the cloud scheme. Convective and boundary layer mixing schemes require as much consideration as cloud and precipitation schemes when it comes to assessing the simulation of clouds by models. Two distinct types of cloud feedback are discussed. While there is reason to doubt that current models are able to simulate potential `cloud regime' type feedbacks with skill, there is hope that a model capable of simulating potential `cloud amount' type feedbacks will be achievable once the reasons for the remaining differences between the models are understood. Received: 23 January 2000 / Accepted: 24 January 2001     

Perturbed physics ensemble using the MIROC5 coupled atmosphere–ocean GCM without flux corrections: experimental design and results

In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere–ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studies using a CGCM applied flux corrections, because perturbations in parameters can lead to large radiation imbalances at the top of the atmosphere and climate drifts. We developed a method to prevent climate drifts in PPE experiments using the MIROC5 CGCM without flux corrections. We simultaneously swept 10 parameters in atmosphere and surface schemes. The range of CS (estimated from our 35 ensemble members) was not wide (2.2–3.2?°C). The shortwave cloud feedback related to changes in middle-level cloud albedo dominated the variations in the total feedback. We found three performance metrics for the present climate simulations of middle-level cloud albedo, precipitation, and ENSO amplitude that systematically relate to the variations in shortwave cloud feedback in this PPE.     

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.     

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.     

Global energy budget changes to high latitude North Atlantic cooling and the tropical ITCZ response

The intertropical convergence zone (ITCZ) in atmospheric general circulation models (coupled to slab ocean) shift southwards in response to northern extratropical cooling. Previous studies have demonstrated the utility of diagnosing the atmospheric energy fluxes in interpreting this teleconnection. This study investigates the nature of global energy flux changes in response to North Atlantic high latitude cooling applied to the Community Atmosphere Model version 3 coupled to a slab ocean, focusing on key local and remote feedbacks that collectively act to alter the energy budget and atmospheric energy transport. We also investigate the relative roles of tropical sea surface temperature (SST) and energy flux changes in the ITCZ response to North Atlantic cooling. Using a radiative kernel technique, we quantify the effects of key feedbacks—temperature, cloud and water vapor, to the top-of-the-atmosphere radiative flux changes. The results show only partial local energy flux compensation to the initial perturbation in the high latitudes, originating from the negative temperature feedback and opposed by positive shortwave albedo and longwave water vapor feedbacks. Thus, an increase in the atmospheric energy transport to the Northern extratropics is required to close the energy budget. The additional energy flux providing this increase comes from top-of-the-atmosphere radiative flux increase over the southern tropics, primarily from cloud, temperature and longwave water vapor feedbacks, and largely as a consequence of increased deep convection. It has been previously argued that the role of tropical SST changes was secondary to the role played by the atmospheric energy flux requirements in controlling the ITCZ shifts, proposing that the SST response is a result of the surface energy budget and not a driver of the precipitation response. Using a set of idealized simulations with the fixed tropical SSTs, we demonstrate that the ITCZ shifts are not possible without the tropical SST changes and suggest that the tropical SSTs are a more suitable driver of tropical precipitation shifts compared to the atmospheric energy fluxes. In our simulations, the ITCZ shifts are influenced mainly by the local (tropical) SST forcing, apparently independent of the actual high latitude energy demand.     

层状云微物理参数反演及其辐射效应的个例研究

利用毫米波云雷达、微波辐射计联合反演方法,对2015年11月11日安徽寿县的一次层状云过程的云参数进行了反演,将所得云参数加入到SBDART辐射传输模式中,进行辐射通量计算,并将计算的地面辐射通量与观测的地面辐射通量进行了对比分析。研究表明:1)利用毫米波雷达和微波辐射计数据联合反演的云参数比较可靠;2)利用SBDART模式并结合反演的云参数,可以准确实时地计算地面及其他高度层的长短波辐射通量;3)在反演的云参数中,光学厚度对地面各种辐射通量的影响是最大的,云层的光学厚度越大,到达地面的太阳短波辐射越小,地面反射短波辐射也越小。另外云底温度越高,云体向下发射的红外长波辐射越大。地面向上的长波辐射是地面温度的普朗克函数,随地面温度而变;4)云对地面的短波辐射强迫为负值,对地面有降温的作用。云对地面的长波辐射强迫是一个正值,对地面有一个增温的作用;5)云对地面的净辐射强迫随时间变化很大,它的正负与太阳高度角和云参数有关。     

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     

A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity

Low-latitude cloud distributions and cloud responses to climate perturbations are compared in near-current versions of three leading U.S. AGCMs, the NCAR CAM 3.0, the GFDL AM2.12b, and the NASA GMAO NSIPP-2 model. The analysis technique of Bony et al. (Clim Dyn 22:71–86, 2004) is used to sort cloud variables by dynamical regime using the monthly mean pressure velocity ω at 500 hPa from 30S to 30N. All models simulate the climatological monthly mean top-of-atmosphere longwave and shortwave cloud radiative forcing (CRF) adequately in all ω-regimes. However, they disagree with each other and with ISCCP satellite observations in regime-sorted cloud fraction, condensate amount, and cloud-top height. All models have too little cloud with tops in the middle troposphere and too much thin cirrus in ascent regimes. In subsidence regimes one model simulates cloud condensate to be too near the surface, while another generates condensate over an excessively deep layer of the lower troposphere. Standardized climate perturbation experiments of the three models are also compared, including uniform SST increase, patterned SST increase, and doubled CO₂ over a mixed layer ocean. The regime-sorted cloud and CRF perturbations are very different between models, and show lesser, but still significant, differences between the same model simulating different types of imposed climate perturbation. There is a negative correlation across all general circulation models (GCMs) and climate perturbations between changes in tropical low cloud cover and changes in net CRF, suggesting a dominant role for boundary layer cloud in these changes. For some of the cases presented, upper-level clouds in deep convection regimes are also important, and changes in such regimes can either reinforce or partially cancel the net CRF response from the boundary layer cloud in subsidence regimes. This study highlights the continuing uncertainty in both low and high cloud feedbacks simulated by GCMs.     

Analysis of Short-term Cloud Feedback in East Asia Using Cloud Radiative Kernels

Cloud radiative kernels were built by BCC_RAD(Beijing Climate Center radiative transfer model) radiative transfer code. Then, short-term cloud feedback and its mechanisms in East Asia(0.5°S-60.5°N, 69.5°-150.5°E) were analyzed quantitatively using the kernels combined with MODIS satellite data from July 2002 to June 2018. According to the surface and monsoon types, four subregions in East Asia—the Tibetan Plateau, northwest, temperate monsoon(TM), and subtropical monsoon(SM)—were selec...     

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.     

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.     

Transient climate changes in a perturbed parameter ensemble of emissions-driven earth system model simulations

We describe results from a 57-member ensemble of transient climate change simulations, featuring simultaneous perturbations to 54 parameters in the atmosphere, ocean, sulphur cycle and terrestrial ecosystem components of an earth system model (ESM). These emissions-driven simulations are compared against the CMIP3 multi-model ensemble of physical climate system models, used extensively to inform previous assessments of regional climate change, and also against emissions-driven simulations from ESMs contributed to the CMIP5 archive. Members of our earth system perturbed parameter ensemble (ESPPE) are competitive with CMIP3 and CMIP5 models in their simulations of historical climate. In particular, they perform reasonably well in comparison with HadGEM2-ES, a more sophisticated and expensive earth system model contributed to CMIP5. The ESPPE therefore provides a computationally cost-effective tool to explore interactions between earth system processes. In response to a non-intervention emissions scenario, the ESPPE simulates distributions of future regional temperature change characterised by wide ranges, and warm shifts, compared to those of CMIP3 models. These differences partly reflect the uncertain influence of global carbon cycle feedbacks in the ESPPE. In addition, the regional effects of interactions between different earth system feedbacks, particularly involving physical and ecosystem processes, shift and widen the ESPPE spread in normalised patterns of surface temperature and precipitation change in many regions. Significant differences from CMIP3 also arise from the use of parametric perturbations (rather than a multimodel ensemble) to represent model uncertainties, and this is also the case when ESPPE results are compared against parallel emissions-driven simulations from CMIP5 ESMs. When driven by an aggressive mitigation scenario, the ESPPE and HadGEM2-ES reveal significant but uncertain impacts in limiting temperature increases during the second half of the twenty-first century. Emissions-driven simulations create scope for development of errors in properties that were previously prescribed in coupled ocean–atmosphere models, such as historical CO₂ concentrations and vegetation distributions. In this context, historical intra-ensemble variations in the airborne fraction of CO₂ emissions, and in summer soil moisture in northern hemisphere continental regions, are shown to be potentially useful constraints, subject to uncertainties in the relevant observations. Our results suggest that future climate-related risks can be assessed more comprehensively by updating projection methodologies to support formal combination of emissions-driven perturbed parameter and multi-model earth system model simulations with suitable observational constraints. This would provide scenarios underpinned by a more complete representation of the chain of uncertainties from anthropogenic emissions to future climate outcomes.     

GRIST模式夏季气候回测试验中东亚降水季节内特征的评估

将自主研发的包含对流参数化、宏观云凝结、云微观物理参数化在内的湿物理过程（简称PhysCN）引入全球-区域一体化预测系统（Global-to-Regional Integrated forecast SysTem,GRIST）。通过大气模式比较计划（AMIP）10 a连续积分考察了PhysCN较原有方案（简称PhysC）对模拟的全球气候基本态的影响。结果显示,PhysCN更真实地重现了热带降水的气候分布特征和季节变化。相比PhysC,PhysCN减少了赤道辐合带（ITCZ）、热带太平洋和印度洋上空的虚假降水,改善了双ITCZ偏差。PhysCN在热带对流层顶附近和中、高纬度地区形成了比PhysC更多的冰云,增强了长波云辐射效应。但另一方面,由于单冰云微物理方案中采用一个变量类别考虑所有冰相粒子,导致中、高纬度低层云冰比湿比PhysC中更大。宏观云凝结中采用基于冰面相对湿度的方法诊断冰云量,使低云更密实,减弱了短波云辐射效应,也使全球净辐射收支偏差大于PhysC模拟结果。研究证明了PhysCN湿物理方案在GRIST模式中的稳定性与合理性,但也展示出冰云诊断和云微物理参数化的协调性有待进一步改进。     

Cloud Radiative Effects and Changes Simulated by the Coupled Model Intercomparison Project Phase 5 Models

Using 32 CMIP5(Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects(CREs) in the historical run driven by observed external radiative forcing for 1850–2005, and their future changes in the RCP(Representative Concentration Pathway) 4.5 scenario runs for2006–2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics,four models—ACCESS1.0, ACCESS1.3, Had GEM2-CC, and Had GEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average.All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about-0.99% K~(-1)and net radiative warming of 0.46 W m~(-2)K~(-1), suggesting a role of positive feedback to global warming.     

Boundary layer stability and Arctic climate change: a feedback study using EC-Earth

Amplified Arctic warming is one of the key features of climate change. It is evident in observations as well as in climate model simulations. Usually referred to as Arctic amplification, it is generally recognized that the surface albedo feedback governs the response. However, a number of feedback mechanisms play a role in AA, of which those related to the prevalent near-surface inversion have received relatively little attention. Here we investigate the role of the near-surface thermal inversion, which is caused by radiative surface cooling in autumn and winter, on Arctic warming. We employ idealized climate change experiments using the climate model EC-Earth together with ERA-Interim reanalysis data to show that boundary-layer mixing governs the efficiency by which the surface warming signal is ‘diluted’ to higher levels. Reduced vertical mixing, as in the stably stratified inversion layer in Arctic winter, thus amplifies surface warming. Modelling results suggest that both shortwave—through the (seasonal) interaction with the sea ice feedback—and longwave feedbacks are affected by boundary-layer mixing, both in the Arctic and globally, with the effect on the shortwave feedback dominating. The amplifying effect will decrease, however, with climate warming because the surface inversion becomes progressively weaker. We estimate that the reduced Arctic inversion has slowed down global warming by about 5% over the past 2 decades, and we anticipate that it will continue to do so with ongoing Arctic warming.