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.     

地球失控增暖可能性的数值模拟

通过改变太阳常数引进强外辐射强迫的变化,利用NCAR气候系统模式CSM1.4,就气候系统对强外辐射强迫下的失控增暖效应进行了初步研究。结果表明:气候对于太阳常数分别增加2.5%、10%与增加25%的响应有所不同,即对于较小的强迫,气候系统的响应是线性的;而对于较大的强迫,响应很可能是非线性的。对于NCAR模式,如果强迫足够大,气候系统将会经历失控增暖。失控增暖的主要趋势并不是最初设想的正的水汽反馈增暖,至少在模式中,不只是“失控的温室效应”增暖,还有“失控的云反馈”增暖。     

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.     

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 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.     

An investigation of the sensitivity of a land surface model to climate change using a reduced form model

 In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. Received: 27 March 2000 / Accepted: 11 September 2000     

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 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%.     

气候模式分辨率对气溶胶气候效应模拟结果的影响

气候模式分辨率作为影响模式模拟结果的重要因素,其对气溶胶与云相互作用的影响尚未全面认识。利用公共大气模型CAM5.3在3种分辨率（2°、1°、0.5°）下,分别采用2000年和1850年气溶胶排放情景进行试验,检验提高分辨率是否能改进气候模式的模拟能力,分析不同分辨率下气溶胶气候效应的异同,探索模式分辨率对气溶胶气候效应数值模拟结果的影响。通过观测资料与模式结果对比发现,提高分辨率可以明显改进模式对总云量、云短波辐射强迫的模拟能力,0.5°分辨率下模拟结果与观测更接近,其他变量并无明显改善。在不同分辨率下,全球平均的气溶胶气候效应较为一致,总云量、云水路径均增加,云短波和长波辐射强迫均加强,而云顶的云滴有效半径和降水均减小,地面气温降低。不同分辨率下,气溶胶增加引起的气溶胶光学厚度、云水路径、地面温度、云短波和长波辐射强迫变化的纬向平均分布相似但大小存在差异;而降水和云量变化的纬向分布与大小均存在较大差异,在区域尺度上还存在较大的不确定性。全球平均而言, 0.5°分辨率下气溶胶的间接辐射强迫相比1°分辨率下的结果降低了2.5%,相比2°分辨率下的结果降低了6.4%。提高模式分辨率可以部分改进模式模拟能力,同时,气溶胶的间接效应随着模式分辨率的提高而减弱。但气溶胶引起的云量、降水的变化在不同分辨率下差异较大,存在较大的不确定性。      

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.     

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.     

Processes shaping the spatial pattern and seasonality of the surface air temperature response to anthropogenic forcing

In the period 1960–2010, the land surface air temperature (SAT) warmed more rapidly over some regions relative to the global mean. Using a set of time-slice experiments, we highlight how different physical processes shape the regional pattern of SAT warming. The results indicate an essential role of anthropogenic forcing in regional SAT changes from the 1970s to 2000s, and show that both surface–atmosphere interactions and large-scale atmospheric circulation changes can shape regional responses to forcing. Single forcing experiments show that an increase in greenhouse gases can lead to regional changes in land surface warming in winter (DJF) due to snow-albedo feedbacks, and in summer (JJA) due to soil-moisture and cloud feedbacks. Changes in anthropogenic aerosol and precursor (AA) emissions induce large spatial variations in SAT, characterized by warming over western Europe, Eurasia, and Alaska. In western Europe, SAT warming is stronger in JJA than in DJF due to substantial increases in clear sky shortwave radiation over Europe, associated with decreases in local AA emissions since the 1980s. In Alaska, the amplified SAT warming in DJF is due to increased downward longwave radiation, which is related to increased water vapor and cloud cover. In this case, although the model was able to capture the regional pattern of SAT change, and the associated local processes, it did not simulate all processes and anomalies correctly. For the Alaskan warming, the model is seen to achieve the correct regional response in the context of a wider North Pacific anomaly that is not consistent with observations. This demonstrates the importance of model evaluation that goes beyond the target variable in detection and attribution studies.     

Direct Climatic Effect of Dust Aerosol in the NCAR Community Atmosphere Model Version 3 （CAM3）

Direct climate responses to dust shortwave and longwave radiative forcing (RF) are studied using the NCAR Community Atmosphere Model Version 3 (CAM3). The simulated RF at the top of the atmosphere (TOA) is-0.45 W m-2 in the solar spectrum and +0.09 W m-2 in the thermal spectrum on a global average. The magnitude of surface RF is larger than the TOA forcing, with global mean shortwave forcing of-1.76 W m-2 and longwave forcing of +0.31 W m-2 . As a result, dust aerosol causes the absorption of 1.1 W m-2 in t...     

RegCM4对中国东部区域气候模拟的辐射收支分析

利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。     

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.     

The disposition of radiative energy in the global climate system: GCM-calculated versus observational estimates

 A comprehensive dataset of direct observations is used to assess the representation of surface and atmospheric radiation budgets in general circulation models (GCMs). Based on combined measurements of surface and collocated top-of-the-atmosphere fluxes at more than 700 sites, a lack of absorption of solar radiation within the atmosphere is identified in the ECHAM3 GCM, indicating that the shortwave atmospheric absorption calculated in the current generation of GCMs, typically between 60 and 70 Wm^-2, is too low by 10–20 Wm^-2. The surface and atmospheric radiation budgets of a new version of the Max-Planck Institute GCM, the ECHAM4, differ considerably from other GCMs in both short- and longwave ranges. The amount of solar radiation absorbed in the atmosphere (90 Wm^-2) is substantially larger than typically found in current GCMs, resulting in a lower absorption at the surface (147 Wm^-2). It is shown that this revised disposition of solar energy within the climate system generally reduces the biases compared to the observational estimates of surface and atmospheric absorption. The enhanced shortwave absorption in the ECHAM4 atmosphere is due to an increase in both simulated clear-sky and cloud absorption compared to ECHAM3. The increased absorption in the cloud-free atmosphere is related to an enhanced absorption of water vapor, and is supported in stand-alone comparisons of the radiation scheme with synchronous observations. The increased cloud absorption, on the other hand, is shown to be predominantly spurious due to the coarse spectral resolution of the ECHAM4 radiation code, thus providing no physical explanation for the “anomalous cloud absorption” phenomenon. Quantitatively, however, an additional increase of atmospheric absorption due to clouds as in ECHAM4 is, at least at low latitudes, not in conflict with the observational estimates, though this does not rule out the possibility that other effects, such as highly absorbing aerosols, could equally contribute to close the gap between models and observations. At higher latitudes, however, the increased cloud absorption is not supported by the observational dataset. Overall, this study points out that not only the clouds, but also the cloud-free atmosphere might be responsible for the discrepancies between observational and simulated estimates of shortwave atmospheric absorption. The smaller absorption of solar radiation at the surface in ECHAM4 is compensated by an increased downward longwave flux (344 Wm^-2), which is larger than in other GCMs. The enhanced downward longwave flux is supported by surface measurements and by a stand-alone validation of the radiation scheme for clear-sky conditions. The enhanced flux also ensures that a sufficient amount of energy is available at the surface to maintain a realistic intensity of the global hydrological cycle. In contrast, a one-handed revision of only the shortwave radiation budget to account for the increased shortwave absorption in GCM atmospheres may induce a global hydrological cycle that is too weak. Received: 26 February 1998 / Accepted: 18 May 1998     

Radiative energy partition and cloud radiative forcing at a Po valley site

Values of downward and upward flux densities of solar and terrestrial radiation were continuously recorded between 1 December 2001 and 30 November 2002 using a four-components radiometer at S. Pietro Capofiume (SPC) in northern Italy (44°39′N, 11°37′E, alt. 11 m a.m.s.l.), which is characterized by a weakly-reflective surface. The aim of the study was to investigate the effects of clouds on surface radiation balance (SRB); the cloud fraction (N) has been retrieved through the inverted form of the parameterization proposed by Kasten and Czeplak [Solar Energy 24 (1980) 177] and cloud types estimated following the methodology of Duchon and O'Malley [J. Appl. Meteorol. 38 (1999) 132]. The cloud radiative forcing (CRF) was evaluated through the Bintanja and Van den Broeke [Int. J. Climatol. 16 (1996) 1281] formula and then associated with cloud type. Experimental results showed that during the measuring period the net shortwave (Sw) balance always decreased with increasing N, whereas the net longwave (Lw) balance increased in all seasons. The net radiation available at the surface decreased with increasing N in all seasons except in winter, where no significant dependency was detected.The analysis of the cloud radiative forcing indicates that all seasons were characterized by a net cooling of the surface except winter, where clouds seem to have no effects on the surface warming or cooling. Taking into account the dependence on solar radiation cycle, an intercomparison between the retrieved cloud types seems to indicate that the effect of stratus was a slight cooling whereas that of cumulus clouds was a stronger cooling of the surface. On the contrary, cirrus clouds seem to have slight warming effect on the surface.The annual trends of mean monthly values of shortwave and longwave radiation balances confirmed that the measurement site is characterized by a temperate climate. Moreover, in spite of the cooling effect of clouds, a monthly radiative energy surplus is available all year long for surface–atmosphere energy exchanges. The analysis is also instrumental for the detection of SRB variations.     

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.     

The modification of greenhouse gas warming by the direct effect of sulphate aerosols

 The Canadian Centre for Climate Modelling and Analysis (CCCma) second generation climate model (GCMII) consists of an atmospheric GCM coupled to mixed layer ocean. It is used to investigate the climate response to a doubling of the CO₂ concentration together with the direct effect of scattering by sulphate aerosols. As expected, the aerosols offset some of the greenhouse gas (GHG) warming; the global annual mean screen temperature change due to doubled CO₂ is 3.4 °C in this model and this is reduced to 2.7 °C when an estimate of the direct effect of anthropogenic sulphate aerosols is included. The pattern of climate response to the comparatively localized aerosol forcing is not itself localized, and it bears a striking resemblance to the response pattern that arises from the globally distributed change in GHG forcing. This “non-local” response to “localized” forcing indicates that the pattern of climate response is determined, to first order, by the overall magnitude of the change in forcing rather than its detailed nature or structure. Feedback processes operating in the system apparently determine this pattern by locally amplifying and suppressing the response to the magnitude of the change in forcing. The influence of the location of the change in forcing is relatively small. These “non-local” and “local” effects of aerosol forcing are characterized and displayed and some of their consequences discussed. Effects on the moisture budget and on the energetics of the global climate are also examined. Received: 10 June 1997 / Accepted: 8 January 1998     

Parametrizations of global thermal emissions for simple climate models

 A new, observationally based, parametrization of the thermal emissions by the Earth-atmosphere system for use in simple climate models is presented and discussed. The parametrization, allowing for the modelling of outgoing longwave fluxes in both clear and cloudy sky conditions, introduces temperature-dependent emissivities in a grey-body formulation, whose expressions are based on data from by the International Satellite Cloud Climatology Program (ISCCP). The proposed parametrization is compared to traditional ones and is used in a simple energy-balance model. It is shown how, unlike the traditional parametrizations, the proposed one correctly reproduces the runaway greenhouse phenomenon, i.e. the impossibility of an equilibrium for values of the solar constant larger than a critical one, which is known to occur in more complex radiative-convective models. It is also seen that the new parametrization induces the existence of a varying number of equilibria, depending on the value of the solar forcing, in agreement with previous studies. Further, the new parametrization is used to explore the effects of clouds on the Earth-atmosphere energy balance. It is found that for certain values of the model parameters the radiative effect of clouds might be either net cooling or net warming, depending on the magnitude of the solar forcing. Received: 12 January 1998 / Accepted: 23 July 1998