Shortwave Cloud Feedback Research Articles

Clouds and the Atmospheric Circulation Response to Warming

Abstract The authors study the effect of clouds on the atmospheric circulation response to CO2 quadrupling in an aquaplanet model with a slab ocean lower boundary. The cloud effect is isolated by locking the clouds to either the control or 4xCO2 state in the shortwave (SW) or longwave (LW) radiation schemes. In the model, cloud radiative changes explain more than half of the total poleward expansion of the Hadley cells, midlatitude jets, and storm tracks under CO2 quadrupling, even though they cause only one-fourth of the total global-mean surface warming. The effect of clouds on circulation results mainly from the SW cloud radiative changes, which strongly enhance the equator-to-pole temperature gradient at all levels in the troposphere, favoring stronger and poleward-shifted midlatitude eddies. By contrast, quadrupling CO2 while holding the clouds fixed causes strong polar amplification and weakened midlatitude baroclinicity at lower levels, yielding only a small poleward expansion of the circulation. The results show that 1) the atmospheric circulation responds sensitively to cloud-driven changes in meridional and vertical temperature distribution and 2) the spatial structure of cloud feedbacks likely plays a dominant role in the circulation response to greenhouse gas forcing. While the magnitude and spatial structure of the cloud feedback are expected to be highly model dependent, an analysis of 4xCO2 simulations of CMIP5 models shows that the SW cloud feedback likely forces a poleward expansion of the tropospheric circulation in most climate models.

Quantifying the Sources of Intermodel Spread in Equilibrium Climate Sensitivity

Abstract This study clarifies the causes of intermodel differences in the global-average temperature response to doubled CO2, commonly known as equilibrium climate sensitivity (ECS). The authors begin by noting several issues with the standard approach for decomposing ECS into a sum of forcing and feedback terms. This leads to a derivation of an alternative method based on linearizing the effect of the net feedback. Consistent with previous studies, the new method identifies shortwave cloud feedback as the dominant source of intermodel spread in ECS. This new approach also reveals that covariances between cloud feedback and forcing, between lapse rate and longwave cloud feedbacks, and between albedo and shortwave cloud feedbacks play an important and previously underappreciated role in determining model differences in ECS. Defining feedbacks based on fixed relative rather than specific humidity (as suggested by Held and Shell) reduces the covariances between processes and leads to more straightforward interpretations of results.

Mechanisms of the Negative Shortwave Cloud Feedback in Middle to High Latitudes

Abstract Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. Here the importance of microphysical processes for the negative optical depth feedback is assessed by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. It is found that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, a very robust positive relationship between monthly mean LWP and temperature in CMIP5 models and observations is shown to exist in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. The results indicate that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.

On the influence of poleward jet shift on shortwave cloud feedback in global climate models

AbstractExperiments designed to separate the effect of atmospheric warming from the effect of shifts of the eddy‐driven jet on shortwave (SW) cloud feedback are performed with three global climate models (GCMs). In each model a warming simulation produces a robust SW cloud feedback dipole, with a negative (positive) feedback in the high‐latitudes (subtropics). The cloud brightening in high‐latitudes that characterizes warming simulations is not produced by jet shifts alone in any of the models, but is highly sensitive to perturbations of freezing temperature seen by the cloud microphysics scheme, indicating that thermodynamic mechanisms involving the phase of cloud condensate dominate the SW feedback at high‐latitudes. In one of the models a poleward jet shift causes significant cloud dimming throughout the midlatitudes, but in two models it does not. Differences in cloud response to jet shifts in two of the models are attributed to differences in the shallow convection parameterizations.

Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.

Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results.

The impact of parametrized convection on cloud feedback.

We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.

Insights into low-latitude cloud feedbacks from high-resolution models.

Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes.

Cloud feedbacks on greenhouse warming in the superparameterized climate model SP‐CCSM4

AbstractCloud feedbacks on greenhouse warming are studied in a superparameterized version of the Community Climate System Model (SP‐CCSM4) in an atmospheric component SP‐CAM4 that explicitly simulates cumulus convection. A 150 year simulation in an abrupt quadrupling of CO2 is branched from a control run. It develops moderate positive global cloud feedback and an implied climate sensitivity of 2.8 K comparable to the conventionally parameterized CCSM4 and the median of other modern climate models. All of SP‐CCSM4's positive shortwave cloud feedback is due to a striking decrease in low cloud over land, which is much more pronounced than in most other climate models, including CCSM4. Four other cloud responses – decreased midlevel cloud, more Arctic water and ice cloud, a slight poleward shift of midlatitude storm track cloud, and an upward shift of high clouds – are also typical of conventional global climate models. SP‐CCSM4 does not simulate the large warming‐induced decrease in Southern Ocean cloud found in CCSM4. Two companion uncoupled SP‐CAM4 simulations, one with a uniform 4 K sea‐surface temperature increase and one with quadrupled CO2 but fixed SST, suggest that SP‐CCSM4's global‐scale cloud changes are primarily mediated by the warming, rather than by rapid adjustments to increased CO2. SP‐CAM4 show spatial patterns of cloud response qualitatively similar to the previous‐generation superparameterized SP‐CAM3, but with systematically more positive low cloud feedbacks over low‐latitude land and ocean.

Impact of changes in the formulation of cloud‐related processes on model biases and climate feedbacks

AbstractTo test the impact of modeling uncertainties and biases on the simulation of cloud feedbacks, several configurations of the EC‐Earth climate model are built altering physical parameterizations. An overview of the various radiative feedbacks diagnosed from the reference EC‐Earth configuration is documented for the first time. The cloud feedback is positive and small. While the total feedback parameter is almost insensitive to model configuration, the cloud feedback, in particular its shortwave (SW) component, can vary considerably depending on the model settings. The lateral mass exchange rate of penetrative convection and the conversion rate from condensed water to precipitation are leading uncertain parameters affecting the radiative feedbacks diagnosed. Consistent with other studies, we find a strong correlation between low‐cloud model fidelity and low‐cloud response under global warming. It is shown that this relationship holds only for stratocumulus regimes and is contributed by low‐cloud cover, rather than low‐cloud optical thickness. Model configurations simulating higher stratocumulus cover, which is closer to the observations, exhibit a stronger positive SW cloud feedback. This feedback is likely underestimated in the reference EC‐Earth configuration, over the eastern basins of the tropical oceans. In addition, connections between simulated high‐cloud top altitude in present‐day climate and longwave cloud feedback are discussed.

The diurnal cycle of marine cloud feedback in climate models

We examine the diurnal cycle of marine cloud feedback using high frequency outputs in CFMIP-2 idealised uniform +4 K SST perturbation experiments from seven CMIP5 models. Most of the inter-model spread in the diurnal mean marine shortwave cloud feedback can be explained by low cloud responses, although these do not explain the model responses at the neutral/weakly negative end of the feedback range, where changes in mid and high level cloud properties are more important. All of the models show reductions in marine low cloud fraction in the warmer climate, and these are in almost all cases largest in the mornings when more cloud is present in the control simulations. This results in shortwave cloud feedbacks being slightly stronger and having the largest inter-model spread at this time of day. The diurnal amplitudes of the responses of marine cloud properties to the warming climate are however small compared to the inter-model differences in their diurnally meaned responses. This indicates that the diurnal cycle of cloud feedback is not strongly relevant to understanding inter-model spread in overall cloud feedback and climate sensitivity. A number of unusual behaviours in individual models are highlighted for future investigation.

Individual Feedback Contributions to the Seasonality of Surface Warming

Abstract Using the climate feedback response analysis method, the authors examine the individual contributions of the CO2 radiative forcing and climate feedbacks to the magnitude, spatial pattern, and seasonality of the transient surface warming response in a 1% yr−1 CO2 increase simulation of the NCAR Community Climate System Model, version 4 (CCSM4). The CO2 forcing and water vapor feedback warm the surface everywhere throughout the year. The tropical warming is predominantly caused by the CO2 forcing and water vapor feedback, while the evaporation feedback reduces the warming. Most feedbacks exhibit noticeable seasonal variations; however, their net effect has little seasonal variation due to compensating effects, which keeps the tropical warming relatively invariant all year long. The polar warming has a pronounced seasonal cycle, with maximum warming in fall/winter and minimum warming in summer. In summer, the large cancelations between the shortwave and longwave cloud feedbacks and between the surface albedo feedback warming and the cooling from the ocean heat storage/dynamics feedback lead to a warming minimum. In polar winter, surface albedo and shortwave cloud feedbacks are nearly absent due to a lack of insolation. However, the ocean heat storage feedback relays the polar warming due to the surface albedo feedback from summer to winter, and the longwave cloud feedback warms the polar surface. Therefore, the seasonal variations in the cloud feedback, surface albedo feedback, and ocean heat storage/dynamics feedback, directly caused by the strong annual cycle of insolation, contribute primarily to the large seasonal variation of polar warming. Furthermore, the CO2 forcing and water vapor and atmospheric dynamics feedbacks add to the maximum polar warming in fall/winter.

Low‐cloud optical depth feedback in climate models

AbstractThe relationship between low‐level cloud optical depth and atmospheric and surface air temperature is examined in the control climate of 13 climate models to determine if cloud optical depth‐temperature relationships found in observations are replicated in climate models and if climate model behavior found in control climate simulations provides information about the optical depth feedback in climate warming simulations forced by increasing carbon dioxide. A positive relationship between cloud optical depth and cloud temperature exists in all models for low clouds with relatively cold temperatures at middle and high latitudes, whereas a negative relationship exists for warmer low clouds in the tropics and subtropics. This relationship is qualitatively similar to that in an earlier analysis of satellite observations, although modeled regression slopes tend to be too positive and their intermodel spread is large. In the models, the cold cloud response comes from increases in cloud water content with increasing temperature, while the warm cloud response comes from decreases in physical thickness with increasing cloud temperature. The intermodel and interregional spread of low‐cloud optical depth feedback in climate warming simulations is well predicted by the corresponding spread in the relationships between optical depth and temperature for the current climate, suggesting that this aspect of cloud feedback may be constrained by observations. Because models have a positive bias relative to observations in the optical depth‐temperature relationship, shortwave cloud feedback for climate changes may be more positive than climate models currently simulate.

Characterizing the Climate Feedback Pattern in the NCAR CCSM3-SOM Using Hourly Data

Abstract The climate feedback–response analysis method (CFRAM) was applied to 10-yr hourly output of the NCAR Community Climate System Model, version 3, using the slab ocean model (CCSM3-SOM), to analyze the strength and spatial distribution of climate feedbacks and to characterize their contributions to the global and regional surface temperature Ts changes in response to a doubling of CO2. The global mean bias in the sum of partial Ts changes associated with the CO2 forcing, and each feedback derived with the CFRAM analysis is about 2% of Ts change obtained directly from the CCSM3-SOM simulations. The pattern correlation between the two is 0.94, indicating that the CFRAM analysis using hourly model output is accurate and thus is appropriate for quantifying the contributions of climate feedback to the formation of global and regional warming patterns. For global mean Ts, the largest contributor to the warming is water vapor feedback, followed by the direct CO2 forcing and albedo feedback. The albedo feedback exhibits the largest spatial variation, followed by shortwave cloud feedback. In terms of pattern correlation and RMS difference with the modeled global surface warming, longwave cloud feedback contributes the most. On zonal average, albedo feedback is the largest contributor to the stronger warming in high latitudes than in the tropics. The longwave cloud feedback further amplifies the latitudinal warming contrast. Both the land–ocean warming difference and contributions of climate feedbacks to it vary with latitude. Equatorward of 50°, shortwave cloud feedback and dynamical advection are the two largest contributors. The land–ocean warming difference on the hemispheric scale is mainly attributable to longwave cloud feedback and convection.

The influence of regional feedbacks on circulation sensitivity

Weakening of the tropical overturning circulation in a warmer world is a robust feature in climate models. Here an idealized representation of ocean heat flux drives a Walker cell in an aquaplanet simulation. A goal of the study is to assess the influence of the Walker circulation on the magnitude and structure of climate feedbacks, as well as to global sensitivity. We compare two CO 2 perturbation experiments, one with and one without a Walker circulation, to isolate the differences attributable to tropical circulation and associated zonal asymmetries. For an imposed Walker circulation, the subtropical shortwave cloud feedback is reduced, which manifests as a weaker tropical-subtropical anomalous energy gradient and consequently a weaker slow down of the Hadley circulation, relative to the case without a Walker circulation. By focusing on the coupled feedback circulation system, these results offer insights into understanding changes in atmospheric circulation and hence the hydrological cycle under global warming.

The dependence of transient climate sensitivity and radiative feedbacks on the spatial pattern of ocean heat uptake

The effect of ocean heat uptake (OHU) on transient global warming is studied in a multimodel framework. Simple heat sinks are prescribed in shallow aquaplanet ocean mixed layers underlying atmospheric general circulation models independently and combined with CO2 forcing. Sinks are localized to either tropical or high latitudes, representing distinct modes of OHU found in coupled simulations. Tropical OHU produces modest cooling at all latitudes, offsetting only a fraction of CO2 warming. High‐latitude OHU produces three times more global mean cooling in a strongly polar‐amplified pattern. Global sensitivities in each scenario are set primarily by large differences in local shortwave cloud feedbacks, robust across models. Differences in atmospheric energy transport set the pattern of temperature change. Results imply that global and regional warming rates depend sensitively on regional ocean processes setting the OHU pattern, and that equilibrium climate sensitivity cannot be reliably estimated from transient observations.

Climate sensitivities of two versions of FGOALS model to idealized radiative forcing

Projections of future climate change by climate system models depend on the sensitivities of models to specified greenhouse gases. To reveal and understand the different climate sensitivities of two versions of LASG/IAP climate system model FGOALS-g2 and FGOALS-s2, we investigate the global mean surface air temperature responses to idealized CO2 forcing by using the output of abruptly quadrupling CO2 experiments. The Gregory-style regression method is used to estimate the “radiative forcing” of quadrupled CO2 and equilibrium sensitivity. The model response is separated into a fast-response stage associated with the CO2 forcing during the first 20 years, and a slow-response stage post the first 20 years. The results show that the radiative forcing of CO2 is overestimated due to the positive water-vapor feedback and underestimated due to the fast cloud processes. The rapid response of water vapor in FGOALS-s2 is responsible for the stronger radiative forcing of CO2. The climate sensitivity, defined as the equilibrium temperature change under doubled CO2 forcing, is about 3.7 K in FGOALS-g2 and 4.5 K in FGOALS-s2. The larger sensitivity of FGOALS-s2 is due mainly to the weaker negative longwave clear-sky feedback and stronger positive shortwave clear-sky feedback at the fast-response stage, because of the more rapid response of water vapor increase and sea-ice decrease in FGOALS-s2 than in FGOALS-g2. At the slow-response stage, similar to the fast-response stage, net negative clear-sky feedback is weaker in FGOALS-s2. Nevertheless, the total negative feedback is larger in FGOALS-s2 due to a larger negative shortwave cloud feedback that involves a larger response of total cloud fraction and condensed water path increase. The uncertainties of estimated forcing and net feedback mainly come from the shortwave cloud processes.

Multi‐parameter multi‐physics ensemble (MPMPE): a new approach exploring the uncertainties of climate sensitivity

AbstractTo explore both the parametric and structural uncertainties of climate sensitivity (CS), we have proposed a new general circulation model (GCM) ensemble termed the multi‐parameter multi‐physics ensemble (MPMPE). We used eight multi‐physics ensemble (MPE) models in which the MIROC5 physics schemes were replaced by those of MIROC3. MPMPE consisted of perturbed‐physics ensembles in which the parameter values were swept for each MPE model. MPMPE resulted in a wide range of CS, which was related to the shortwave cloud feedback (SWcld). Coupling between low‐ and mid‐level clouds controlled the differences in the parametric spread of SWcld among the MPE models.

On the Usage of Spectral and Broadband Satellite Instrument Measurements to Differentiate Climate Models with Different Cloud Feedback Strengths

Abstract Top-of-atmosphere radiometric signals associated with different high- and low-cloud–radiative feedbacks have been examined through the use of an observing system simulation experiment (OSSE). The OSSE simulates variations in the spectrally resolved and spectrally integrated signals that are due to a range of plausible feedbacks of the climate system when forced with CO2 concentrations that increase at 1% yr−1. This initial version of the OSSE is based on the Community Climate System Model, version 3 (CCSM3), and exploits the fact that CCSM3 exhibits different cloud feedback strengths for different model horizontal resolutions. In addition to the conventional broadband shortwave albedos and outgoing longwave fluxes, a dataset of shortwave spectral reflectance and longwave spectral radiance has been created. These data have been analyzed to determine simulated satellite instrument signals of poorly constrained cloud feedbacks for three plausible realizations of Earth's climate system produced by CCSM3. These data have been analyzed to estimate the observational record length of albedo, outgoing longwave radiation, shortwave reflectance, or longwave radiance required to differentiate these dissimilar Earth system realizations. Shortwave spectral measurements in visible and near-infrared water vapor overtone lines are best suited to differentiate model results, and a 33% difference in shortwave–cloud feedbacks can be detected with 20 years of continuous measurements. Nevertheless, at most latitudes and with most wavelengths, the difference detection time is more than 30 years. This suggests that observing systems of sufficiently stable calibration would be useful in addressing the contribution of low clouds to the spread of climate sensitivities currently exhibited by the models that report to the Intergovernmental Panel on Climate Change (IPCC).

Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5*

Abstract Using five climate model simulations of the response to an abrupt quadrupling of CO2, the authors perform the first simultaneous model intercomparison of cloud feedbacks and rapid radiative adjustments with cloud masking effects removed, partitioned among changes in cloud types and gross cloud properties. Upon CO2 quadrupling, clouds exhibit a rapid reduction in fractional coverage, cloud-top pressure, and optical depth, with each contributing equally to a 1.1 W m−2 net cloud radiative adjustment, primarily from shortwave radiation. Rapid reductions in midlevel clouds and optically thick clouds are important in reducing planetary albedo in every model. As the planet warms, clouds become fewer, higher, and thicker, and global mean net cloud feedback is positive in all but one model and results primarily from increased trapping of longwave radiation. As was true for earlier models, high cloud changes are the largest contributor to intermodel spread in longwave and shortwave cloud feedbacks, but low cloud changes are the largest contributor to the mean and spread in net cloud feedback. The importance of the negative optical depth feedback relative to the amount feedback at high latitudes is even more marked than in earlier models. The authors show that the negative longwave cloud adjustment inferred in previous studies is primarily caused by a 1.3 W m−2 cloud masking of CO2 forcing. Properly accounting for cloud masking increases net cloud feedback by 0.3 W m−2 K−1, whereas accounting for rapid adjustments reduces by 0.14 W m−2 K−1 the ensemble mean net cloud feedback through a combination of smaller positive cloud amount and altitude feedbacks and larger negative optical depth feedbacks.

An Analysis of the Short-Term Cloud Feedback Using MODIS Data

AbstractThe cloud feedback in response to short-term climate variations is estimated from cloud measurements combined with offline radiative transfer calculations. The cloud measurements are made by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite and cover the period 2000–10. Low clouds provide a strong negative cloud feedback, mainly because of their impact in the shortwave (SW) portion of the spectrum. Midlevel clouds provide a positive net cloud feedback that is a combination of a positive SW feedback partially canceled by a negative feedback in the longwave (LW). High clouds have only a small impact on the net cloud feedback because of a close cancellation between large LW and SW cloud feedbacks. Segregating the clouds by optical depth, it is found that the net cloud feedback is set by a positive cloud feedback due to reductions in the thickest clouds (mainly in the SW) and a cancelling negative feedback from increases in clouds with moderate optical depths (also mainly in the SW). The global average SW, LW, and net cloud feedbacks are +0.30 ±1.10, −0.46 ±0.74, and −0.16 ±0.83 W m−2 K−1, respectively. The SW feedback is consistent with previous work; the MODIS LW feedback is lower than previous calculations and there are reasons to suspect it may be biased low. Finally, it is shown that the apparently small control that global mean surface temperature exerts on clouds, which leads to the large uncertainty in the short-term cloud feedback, arises from statistically significant but offsetting relationships between individual cloud types and global mean surface temperature.