Abstract

Feedbacks determine the efficiency with which the climate system comes back into equilibrium in response to a radiative perturbation. Although feedbacks are integrated quantities, the processes from which they arise have rich spatial structures that alter the distribution of top of atmosphere (TOA) net radiation. Here, the authors investigate the implications of the structure of climate feedbacks for the change in poleward energy transport as the planet warms over the twenty-first century in a suite of GCMs. Using radiative kernels that describe the TOA radiative response to small perturbations in temperature, water vapor, and surface albedo, the change in poleward energy flux is partitioned into the individual feedbacks that cause it.

This study finds that latitudinal gradients in the sum of climate feedbacks reinforce the preexisting latitudinal gradient in TOA net radiation, requiring that the climate system transport more energy to the poles on a warming planet. This is primarily due to structure of the water vapor and cloud feedbacks, which are strongly positive at low latitudes and decrease dramatically with increasing latitude. Using the change in surface fluxes, the authors partition the anomalous poleward energy flux between the atmosphere and ocean and find that reduced heat flux from the high-latitude ocean further amplifies the equator-to-pole gradient in atmospheric energy loss. This implied reduction in oceanic poleward energy flux requires the atmosphere to increase its share of the total poleward energy transport. As is the case for climate sensitivity, the largest source of intermodel spread in the change in poleward energy transport can be attributed to the shortwave cloud feedback.

Abstract

Currently available satellite data can be used to track the response of clouds and humidity to intense precipitation events. A compositing technique centered in space and time on locations experiencing high rain rates is used to detail the characteristic evolution of several quantities measured from a suite of satellite instruments. Intense precipitation events in the convective tropics are preceded by an increase in low-level humidity. Optically thick cold clouds accompany the precipitation burst, which is followed by the development of spreading upper-level anvil clouds and an increase in upper-tropospheric humidity over a broader region than that occupied by the precipitation anomalies. The temporal separation between the convective event and the development of anvil clouds is about 3 h. The humidity increase at upper levels and the associated decrease in clear-sky longwave emission persist for many hours after the convective event. Large-scale vertical motions from reanalysis show a coherent evolution associated with precipitation events identified in an independent dataset: precipitation events begin with stronger upward motion anomalies in the lower troposphere, which then evolve toward stronger upward motion anomalies in the upper troposphere, in conjunction with the development of anvil clouds. Greater upper-tropospheric moistening and cloudiness are associated with larger-scale and better-organized convective systems, but even weaker, more isolated systems produce sustained upper-level humidity and clear-sky outgoing longwave radiation anomalies.

Abstract

The 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.

Abstract

This study proposes a novel technique for computing cloud feedbacks using histograms of cloud fraction as a joint function of cloud-top pressure (CTP) and optical depth (τ). These histograms were generated by the International Satellite Cloud Climatology Project (ISCCP) simulator that was incorporated into doubled-CO₂ simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project. The authors use a radiative transfer model to compute top of atmosphere flux sensitivities to cloud fraction perturbations in each bin of the histogram for each month and latitude. Multiplying these cloud radiative kernels with histograms of modeled cloud fraction changes at each grid point per unit of global warming produces an estimate of cloud feedback. Spatial structures and globally integrated cloud feedbacks computed in this manner agree remarkably well with the adjusted change in cloud radiative forcing. The global and annual mean model-simulated cloud feedback is dominated by contributions from medium thickness (3.6 < τ ≤ 23) cloud changes, but thick (τ > 23) cloud changes cause the rapid transition of cloud feedback values from positive in midlatitudes to negative poleward of 50°S and 70°N. High (CTP ≤ 440 hPa) cloud changes are the dominant contributor to longwave (LW) cloud feedback, but because their LW and shortwave (SW) impacts are in opposition, they contribute less to the net cloud feedback than do the positive contributions from low (CTP > 680 hPa) cloud changes. Midlevel (440 < CTP ≤ 680 hPa) cloud changes cause positive SW cloud feedbacks that are 80% as large as those due to low clouds. Finally, high cloud changes induce wider ranges of LW and SW cloud feedbacks across models than do low clouds.

Abstract

Cloud radiative kernels and histograms of cloud fraction, both as functions of cloud-top pressure and optical depth, are used to quantify cloud amount, altitude, and optical depth feedbacks. The analysis is applied to doubled-CO₂ simulations from 11 global climate models in the Cloud Feedback Model Intercomparison Project.

Global, annual, and ensemble mean longwave (LW) and shortwave (SW) cloud feedbacks are positive, with the latter nearly twice as large as the former. The robust increase in cloud-top altitude in both the tropics and extratropics is the dominant contributor to the positive LW cloud feedback. The negative impact of reductions in cloud amount offsets more than half of the positive impact of rising clouds on LW cloud feedback, but the magnitude of compensation varies considerably across the models. In contrast, robust reductions in cloud amount make a large and virtually unopposed positive contribution to SW cloud feedback, though the intermodel spread is greater than for any other individual feedback component. Overall reductions in cloud amount have twice as large an impact on SW fluxes as on LW fluxes, such that the net cloud amount feedback is moderately positive, with no models exhibiting a negative value. As a consequence of large but partially offsetting effects of cloud amount reductions on LW and SW feedbacks, both the mean and intermodel spread in net cloud amount feedback are smaller than those of the net cloud altitude feedback. Finally, the study finds that the large negative cloud feedback at high latitudes results from robust increases in cloud optical depth, not from increases in total cloud amount as is commonly assumed.

Abstract

Emergent constraints are quantities that are observable from current measurements and have skill predicting future climate. This study explores 19 previously proposed emergent constraints related to equilibrium climate sensitivity (ECS; the global-average equilibrium surface temperature response to CO₂ doubling). Several constraints are shown to be closely related, emphasizing the importance for careful understanding of proposed constraints. A new method is presented for decomposing correlation between an emergent constraint and ECS into terms related to physical processes and geographical regions. Using this decomposition, one can determine whether the processes and regions explaining correlation with ECS correspond to the physical explanation offered for the constraint. Shortwave cloud feedback is generally found to be the dominant contributor to correlations with ECS because it is the largest source of intermodel spread in ECS. In all cases, correlation results from interaction between a variety of terms, reflecting the complex nature of ECS and the fact that feedback terms and forcing are themselves correlated with each other. For 4 of the 19 constraints, the originally proposed explanation for correlation is borne out by our analysis. These four constraints all predict relatively high climate sensitivity. The credibility of six other constraints is called into question owing to correlation with ECS coming mainly from unexpected sources and/or lack of robustness to changes in ensembles. Another six constraints lack a testable explanation and hence cannot be confirmed. The fact that this study casts doubt upon more constraints than it confirms highlights the need for caution when identifying emergent constraints from small ensembles.

Abstract

Idealized experiments performed with the Community Atmospheric Model 5.3 indicate that the width and strength of the Hadley circulation (HC) are sensitive to the location of sea surface temperature (SST) increases. The HC edge shifts poleward in response to SST increases over the subtropical regions near and on the equatorward flank of the HC edge, and shifts equatorward in response to warming over the tropical area except for the western Pacific Ocean and Indian Ocean. The HC is strengthened in response to SST increases over the intertropical convergence zone (ITCZ) and is weakened in response to SST increases over the subsidence branch of the HC in the subtropics. Tropical SST increases off the ITCZ tend to weaken the HC in the corresponding hemisphere and strengthen the HC in the opposite hemisphere. These results could be used to explain the simulated HC changes induced by recent SST variations, and it is estimated that more than half of the SST-induced HC widening in 1980–2014 is caused by changes in the spatial pattern of SST.

Abstract

Model evidence for the “pattern effect” assumes that global climate models (GCMs) faithfully simulate how clouds respond to varying sea surface temperature (SST) patterns and associated meteorological perturbations. We exploit time-invariant satellite-based estimates of the sensitivity of marine low clouds to meteorological perturbations to estimate how these clouds responded to time-varying SST patterns and meteorology between 1870 and 2014. GCMs and reanalyses provide estimates of the historical meteorological changes. Observations suggest that increasing estimated inversion strength (EIS) between 1980 and 2014 produced a negative low cloud feedback, opposite to the positive feedback expected from increasing CO₂. This indicates that the processes responsible for marine cloud changes from 1980 to the near present are distinct from those associated with an increase in CO₂. We also observationally constrain the difference between the historical near-global marine low cloud feedback, ${\lambda }_{\text{cloud}}^{\text{hist}}$ , and that arising from increasing CO₂, ${\lambda }_{\text{cloud}}^{4\text{xCO2}}$ . We find that this cloud feedback pattern effect depends strongly on time period and reanalysis dataset, and that varying changes in EIS and SST with warming explain much of its variability. Between 1980 and 2014, we estimate that ${\lambda }_{\text{cloud}}^{4\text{xCO2}}-{\lambda }_{\text{cloud}}^{\text{hist}}=0.78\pm 0.21{\hspace{0.17em}\mathrm{W}\hspace{0.17em}\mathrm{m}}^{-2}{\hspace{0.17em}\mathrm{K}}^{-1}$ (90% confidence) assuming meteorological changes from the Multiple Reanalysis Ensemble, implying a total pattern effect (that arising from all climate feedbacks) of 1.86 ± 0.45 W m⁻² K⁻¹. This observational evidence corroborates previous quantitative estimates of the pattern effect, which heretofore relied largely upon GCM-based cloud changes. However, disparate historical meteorological changes across individual reanalyses contribute to considerable uncertainty in its magnitude.

Abstract

An emergent constraint (EC) is a popular model evaluation technique, which offers the potential to reduce intermodel variability in projections of climate change. Two examples have previously been laid out for future surface albedo feedbacks (SAF) stemming from loss of Northern Hemisphere (NH) snow cover (SAF_snow) and sea ice (SAF_ice). These processes also have a modern-day analog that occurs each year as snow and sea ice retreat from their seasonal maxima, which is strongly correlated with future SAF across an ensemble of climate models. The newly released CMIP6 ensemble offers the chance to test prior constraints through out-of-sample verification, an important examination of EC robustness. Here, we show that the SAF_snow EC is equally strong in CMIP6 as it was in past generations, while the SAF_ice EC is also shown to exist in CMIP6, but with different, slightly weaker characteristics. We find that the CMIP6 mean NH SAF exhibits a global feedback of 0.25 ± 0.05 W m⁻² K⁻¹, or ~61% of the total global albedo feedback, largely in line with prior generations despite its increased climate sensitivity. The NH SAF can be broken down into similar contributions from snow and sea ice over the twenty-first century in CMIP6. Crucially, intermodel variability in seasonal SAF_snow and SAF_ice is largely unchanged from CMIP5 because of poor outlier simulations of snow cover, surface albedo, and sea ice thickness. These outliers act to mask the noted improvement from many models when it comes to SAF_ice, and to a lesser extent SAF_snow.

Abstract

The extratropical shortwave (SW) cloud feedback is primarily due to increases in extratropical liquid cloud extent and optical depth. Here, we examine the response of extratropical (35°–75°) marine cloud liquid water path (LWP) to a uniform 4-K increase in sea surface temperature (SST) in global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and variants of the HadGEM3-GC3.1 GCM. Compositing is used to partition data into periods inside and out of cyclones. The response of extratropical LWP to a uniform SST increase and associated atmospheric response varies substantially among GCMs, but the sensitivity of LWP to cloud controlling factors (CCFs) is qualitatively similar. When all other predictors are held constant, increasing moisture flux drives an increase in LWP. Increasing SST, holding all other predictors fixed, leads to a decrease in LWP. The combinations of these changes lead to LWP, and by extension reflected SW, increasing with warming in both hemispheres. Observations predict an increase in reflected SW over oceans of 0.8–1.6 W m⁻² per kelvin SST increase (35°–75°N) and 1.2–1.9 W m⁻² per kelvin SST increase (35°–75°S). This increase in reflected SW is mainly due to increased moisture convergence into cyclones because of increasing available moisture. The efficiency at which converging moisture is converted into precipitation determines the amount of liquid cloud. Thus, cyclone precipitation processes are critical to constraining extratropical cloud feedbacks.