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??.     

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.     

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.     

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.     

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.     

Relative contribution of feedback processes to Arctic amplification of temperature change in MIROC GCM

The finding that surface warming over the Arctic exceeds that over the rest of the world under global warming is a robust feature among general circulation models (GCMs). While various mechanisms have been proposed, quantifying their relative contributions is an important task in order to understand model behavior. Here we apply a recently proposed feedback analysis technique to an atmosphere–ocean GCM under two and four times CO₂ concentrations which approximately lead to seasonally and annually sea ice-free climates. The contribution of feedbacks to Arctic temperature change is investigated. The surface warming in the Arctic is contributed by albedo, water vapour and large-scale condensation feedbacks and reduced by the evaporative cooling feedback. The surface warming contrast between the Arctic and the global averages (AA) is maintained by albedo and evaporative cooling feedbacks. The latter contributes to AA predominantly by cooling the low latitudes more than the Arctic. Latent heat transport into the Arctic increases and hence evaporative cooling plus large-scale condensation feedback contributes positively to AA. On the other hand, dry-static energy transport into the Arctic decreases and hence dynamical heating feedback contributes negatively to AA. An important contribution is thus made via changes in hydrological cycle and not via the ‘dry’ heat transport process. A larger response near the surface than aloft in the Arctic is maintained by the albedo, water vapour, and dynamical heating feedbacks, in which the albedo and water vapour feedbacks contribute through warming the surface more than aloft, and the dynamical heating feedback contributes by cooling aloft more than the surface. In our experiments, ocean and sea ice dynamics play a secondary role. It is shown that a different level of CO₂ increase introduces a latitudinal and seasonal difference into the feedbacks.     

Effects of Clouds and Aerosols on Surface Radiation Budget Inferred from DOE AMF at Shouxian, China

Based on data collected during the first U.S.Department of Energy(DOE) Atmospheric Radiation Measurement(ARM) field campaigns at Shouxian,eastern China in 2008,the effects of clouds and aerosols on the surface radiation budget during the period October-December 2008 were studied.The results revealed that the largest longwave(LW),shortwave(SW),and net Aerosol Radiative Effects(AREs) are 12.7,-37.6,and-24.9 W m-2,indicating that aerosols have LW warming impact,a strong SW cooling effect,and a net cooling effect on the surface radiation budget at Shouxian during the study period 15 October-15 December 2008.The SW cloud radiative forcing(CRF) is-135.1 W m-2,much cooler than ARE(about 3.6 times),however,the LW CRF is 43.6 W m-2,much warmer than ARE,and resulting in a net CRF of-91.5 W m-2,about 3.7 times of net ARE.These results suggest that the clouds have much stronger LW warming effect and SW cooling effect on the surface radiation budget than AREs.The net surface radiation budget is dominated by SW cooling effect for both ARE and CRF.Furthermore,the precipitatable clouds(PCs) have the largest SW cooling effect and LW warming effect,while optically thin high clouds have the smallest cooling effect and LW warming on the surface radiation budget.Comparing the two selected caseds,CloudSat cloud radar reflectivity agrees very well with the AMF(ARM Mobile Facility) WACR(W-band ARM Cloud Radar) measurements,particularly for cirrus cloud case.These result will provide a ground truth to validate the model simulations 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.     

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     

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 selected. The average longwave, shortwave, and net cloud feedbacks in East Asia are-0.68 ± 1.20, 1.34 ± 1.08, and 0.66 ± 0.40 W m~(-2) K~(-1)(±2σ), respectively, among which the net feedback is dominated by the positive shortwave feedback. Positive feedback in SM is the strongest of all subregions, mainly due to the contributions of nimbostratus and stratus. In East Asia, short-term feedback in spring is primarily caused by marine stratus in SM, in summer is primarily driven by deep convective cloud in TM, in autumn is mainly caused by land nimbostratus in SM, and in winter is mainly driven by land stratus in SM. Cloud feedback in East Asia is chiefly driven by decreases in mid-level and low cloud fraction owing to the changes in relative humidity, and a decrease in low cloud optical thickness due to the changes in cloud water content.     

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.     

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.     

Coupling between subtropical cloud feedback and the local hydrological cycle in a climate model

In HadGEM2-A, AMIP experiments forced with observed sea surface temperatures respond to uniform and patterned +4 K SST perturbations with strong positive cloud feedbacks in the subtropical stratocumulus/trade cumulus transition regions. Over the subtropical Northeast Pacific at 137°W/26°N, the boundary layer cloud fraction reduces considerably in the AMIP +4 K patterned SST experiment. The near-surface wind speed and the air-sea temperature difference reduces, while the near-surface relative humidity increases. These changes limit the local increase in surface evaporation to just 3 W/m² or 0.6 %/K. Previous studies have suggested that increases in surface evaporation may be required to maintain maritime boundary layer cloud in a warmer climate. This suggests that the supply of water vapour from surface evaporation may not be increasing enough to maintain the low level cloud fraction in the warmer climate in HadGEM2-A. Sensitivity tests which force the surface evaporation to increase substantially in the +4 K patterned SST experiment result in smaller changes in boundary layer cloud and a weaker cloud feedback in HadGEM2-A, supporting this idea. Although global mean surface evaporation in climate models increases robustly with global temperature (and the resulting increase in atmospheric radiative cooling), local values may increase much less, having a significant impact on cloud feedback. These results suggest a coupling between cloud feedback and the hydrological cycle via changes in the patterns of surface evaporation. A better understanding of both the factors controlling local changes in surface evaporation and the sensitivity of clouds to such changes may be required to understand the reasons for inter-model differences in subtropical cloud feedback.     

用红外和水汽两个通道的卫星测值指定云迹风的高度

提出了一种改进的用红外和水汽两个通道的测值指定云迹风高度的算法。利用红外水汽散点图和云迹风本身自动地将有低云的目标区、有半透明卷云的目标区、有密蔽高云的目标区分开。在有低云的目标区和有密蔽高云的目标区用红外一个通道指定云高。在有半透明卷云的目标区用红外和水汽两个通道指定云高。在用两个通道的测值指定云高时，假定卷云高度以上不存在水汽，以红外和水汽两个通道亮温相同这个方程与两个通道辐射测值线性相关的方程联立解出云的高度     

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.     

Radiation Exchange Between Stratus Clouds and Polar Marine Surfaces

The radiative energy exchange between arctic sea-ice and stratiform clouds is studied by means of aircraft measurements and a two-stream radiation transfer model. The data have been obtained by flights of two identically instrumented aircraft during the Radiation and Eddy Flux Experiments REFLEX I in autumn 1991 and REFLEX II in winter 1993 over the arctic marginal ice zone of Fram Strait. The instrumental equipment comprised Eppley pyranometers and pyrgeometers, which measure the solar and terrestrial upwelling and downwelling hemispheric radiation flux densities, and a line-scan-camera on one aircraft to monitor the surface structure of the sea-ice. An empirical parametrization of the albedo of partly ice-covered ocean surfaces is obtained from the data, which describes the albedo increasing linearly with the concentration of the snow-covered sea-ice and with the cosine of the sun zenith angle at sun elevations below 10°. Cloud optical parameters, such as single scattering albedo, asymmetry factor and shortwave and longwave height-dependent extinction coefficient are determined by adjusting modeled radiation flux densities to observations. We found significant influence of the multiple reflection of shortwave radiation between the ice surface and the cloud base on the radiation regime. Consistent with the data, a radiation transfer model shows that stratus clouds of 400 m thickness with common cloud parameters may double the global radiation at the surface of sea-ice compared to open water values. The total cloud-surface-albedo under these circumstances is 30% larger over sea-ice than over water. Parametrizations of the global and reflected radiation above and below stratus clouds are proposed on the basis of the measurements and modeling. The upwelling and downwelling longwave emission of stratus clouds with thicknesses of more than 500 m can be satisfactorily estimated by Stefan's law with an emissivity of nearly 1 and when the maximum air temperature within the cloud is used.     

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%.     

Effect of surface albedo, water vapour, and atmospheric aerosols on the cloud-free shortwave radiative budget in the Arctic

This study is based on ground-based measurements of downward surface shortwave irradiance (SW), columnar water vapour (wv), and aerosol optical depth (τ) obtained at Thule Air Base (Greenland) in 2007–2010, together with MODIS observations of the surface shortwave albedo (A). Radiative transfer model calculations are used in combination with measurements to separate the radiative effect of A (ΔSW_A), wv (ΔSW_wv), and aerosols (ΔSW_τ) in modulating SW in cloud-free conditions. The shortwave radiation at the surface is mainly affected by water vapour absorption, which produces a reduction of SW as low as ?100 Wm^?2 (?18%). The seasonal change of A produces an increase of SW by up to +25 Wm^?2 (+4.5%). The annual mean radiative effect is estimated to be ?(21–22) Wm^?2 for wv, and +(2–3) Wm^?2 for A. An increase by +0.065 cm in the annual mean wv, to which corresponds an absolute increase in ΔSW_wv by 0.93 Wm^?2 (4.3%), has been observed to occur between 2007 and 2010. In the same period, the annual mean A has decreased by ?0.027, with a corresponding decrease in ΔSW_A by 0.41 Wm^?2 (?14.9%). Atmospheric aerosols produce a reduction of SW as low as ?32 Wm^?2 (?6.7%). The instantaneous aerosol radiative forcing (RF_τ) reaches values of ?28 Wm^?2 and shows a strong dependency on surface albedo. The derived radiative forcing efficiency (FE_τ) for solar zenith angles between 55° and 70° is estimated to be (?120.6 ± 4.3) for 0.1 < A < 0.2, and (?41.2 ± 1.6) Wm^?2 for 0.5 < A < 0.6.     

Cloud albedo feedback and the super greenhouse effect in a global coupled GCM

Two competing cloud-radiative feedbacks identified in previous studies i.e., cloud albedo feedback and the super greenhouse effect, are examined in a sensitivity study with a global coupled ocean-atmosphere general circulation model. Cloud albedo feedback is strengthened in a sensitivity experiment by lowering the sea-surface temperature (SST) threshold in the specified cloud albedo feedback scheme. This simple parameterization requires coincident warm SSTs and deep convection for upper-level cloud albedos to increase. The enhanced cloud albedo feedback in the sensitivity experiment results in decreased maximum values of SST and cooler surface temperatures over most areas of the planet. There is also a cooling of the tropical troposphere with attendant global changes of atmospheric circulation reminiscent of those observed during La Niña or cold events in the Southern Oscillation. The strengthening of the cloud albedo feedback only occurs over warm tropical oceans (e.g., the western Pacific warm pool), where there is increased albedo, decreased absorbed solar radiation at the surface, stronger surface westerlies, enhanced westward currents, lower temperatures, and decreased precipitation and evaporation. However, the weakened convection over the tropical western Pacific Ocean alters the large-scale circulation in the tropics such that there is increased upper-level divergence over tropical land areas and the tropical Indian Ocean. This results in increased precipitation in those regions and intensified monsoonal regimes. The enhanced precipitation over tropical land areas produces increased clouds and albedo and wetter and cooler land surfaces. These additional contributions to decreased absorbed solar input at the surface combine with similar changes over the tropical oceans to produce the global cooling associated with the stronger cloud albedo feedback. Increased low-level moisture convergence and precipitation over the tropical Indian Ocean enhance slightly the super greenhouse effect there. But the stronger cloud albedo feedback is still the dominant effect, although cooling of SSTs in that region is less than in the tropical western Pacific Ocean. The sensitivity experiment demonstrates how a regional change of radiative forcing is quickly transmitted globally through a combination of radiative and dynamical processes in the coupled model. This study points to the uncertainties involved with the parameterization of cloud albedo and the major implications of such parameterizations concerning the maximum values of SST, global climate sensitivity, and climate change.Support is provided by the Office of Health and Environmental Research of the U.S. Department of Energy, as part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.