Changes In Cloud Radiative Forcing Research Articles

Differences in Radiative Forcing, Not Sensitivity, Explain Differences in Summertime Land Temperature Variance Change Between CMIP5 and CMIP6

AbstractHow summertime temperature variability will change with warming has important implications for climate adaptation and mitigation. CMIP5 simulations indicate a compound risk of extreme hot temperatures in western Europe from both warming and increasing temperature variance. CMIP6 simulations, however, indicate only a moderate increase in temperature variance that does not covary with warming. To explore this intergenerational discrepancy in CMIP results, we decompose changes in monthly temperature variance into those arising from changes in sensitivity to forcing and changes in forcing variance. Across models, sensitivity increases with local warming in both CMIP5 and CMIP6 at an average rate of 5.7 ([3.7, 7.9]; 95% c.i.) × 10−3°C per W m−2 per °C warming. We use a simple model of moist surface energetics to explain increased sensitivity as a consequence of greater atmospheric demand (∼70%) and drier soil (∼40%) that is partially offset by the Planck feedback (∼−10%). Conversely, forcing variance is stable in CMIP5 but decreases with warming in CMIP6 at an average rate of −21 ([−28, −15]; 95% c.i.) W2 m−4 per °C warming. We examine scaling relationships with mean cloud fraction and find that mean forcing variance decreases with decreasing cloud fraction at twice the rate in CMIP6 than CMIP5. The stability of CMIP6 temperature variance is, thus, a consequence of offsetting changes in sensitivity and forcing variance. Further work to determine which models and generations of CMIP simulations better represent changes in cloud radiative forcing is important for assessing risks associated with increased temperature variance.

Direct observations of the multi-year seasonal mean diurnal variations of TOA cloud radiative forcing over tropics using Megha-Tropiques-ScaRaB/3

Diurnal variation of cloud radiative forcing (CRF) is a major factor that controls the global radiation balance. This study presents multi-year seasonal mean diurnal variations of longwave cloud radiative forcing (LWCRF) and daytime shortwave cloud radiative forcing (SWCRF) at the top of atmosphere over tropics, derived from the broadband radiation measurements made by ScaRaB/3 onboard the low-inclination Megha-Tropiques satellite. The largest LWCRF (60–80 Wm−2) occurs over the oceanic regions of the east equatorial Indian Ocean and the western Pacific during all seasons, as well as the South Pacific Convergence Zone, the northeast Bay of Bengal, Amazon region, central and southern Africa and north Indian landmass (monsoon trough) during the local summer. Diurnal variations of 15–25 Wm−2 in LWCRF (20–35% of the mean) are observed with peak values occurring at 18–21 local time (LT) over continents and 00–06 LT over oceans. The minimum LWCRF occurs at 09–12 LT throughout the tropics. Over convective regions, SWCRF maximizes at 12–15 LT (− 220 to − 300 Wm−2) and has a higher magnitude over continents due to early convection occurrence, indicating the importance of diurnal phase. Certain specific features including the CRF associated with the double inter-tropical convergence zone, day-night changes in net CRF, and the effect of El Ni $$\stackrel{\sim }{\mathrm{n}}$$ o on CRF are also presented. The net CRF and its zonal variations are strikingly similar during the normal and El Ni $$\stackrel{\sim }{\mathrm{n}}$$ o periods because the changes in LWCRF and SWCRF are mutually compensated.

Probabilistic reasoning about measurements of equilibrium climate sensitivity: combining disparate lines of evidence

Where policy and science intersect, there are always issues of ambiguous and conflicting lines of evidence. Combining disparate information sources is mathematically complex; common heuristics based on simple statistical models easily lead us astray. Here, we use Bayesian Nets (BNs) to illustrate the complexity in reasoning under uncertainty. Data from joint research at Resources for the Future and NASA Langley are used to populate a BN for predicting equilibrium climate sensitivity (ECS). The information sources consist of measuring the rate of decadal temperature rise (DTR) and measuring the rate of percentage change in cloud radiative forcing (CRF), with both the existing configuration of satellites and with a proposed enhanced measuring system. The goal of all measurements is to reduce uncertainty in equilibrium climate sensitivity. Subtle aspects of probabilistic reasoning with concordant and discordant measurements are illustrated. Relative to the current prior distribution on ECS, we show that after 30 years of observing with the current systems, the 2σ uncertainty band for ECS would be shrunk on average to 73% of its current value. With the enhanced systems over the same time, it would be shrunk to 32% of its current value. The actual shrinkage depends on the values actually observed. These results are based on models recommended by the Social Cost of Carbon methodology and assume a Business as Usual emissions path.

Quantitative analysis of surface warming amplification over the Tibetan Plateau after the late 1990s using surface energy balance equation

AbstractLand surface warming is amplified over the Tibetan Plateau (TP) compared with the global climate warming hiatus since the end of the 1990s. Based on in situ observations and two reanalysis datasets, the processes involved were investigated by calculating partial temperature changes using the surface energy budget equation. The results indicated that the enhanced downward longwave radiation under clear‐sky condition and the positive surface albedo feedback (SAF) related to the reduced snow cover are responsible for the pronounced surface warming, especially in winter. Meanwhile, the changes in cloud radiative forcing, surface sensible and latent heat fluxes (H + LE), and heat storage (Q) had a much weaker cooling effect. These results indicate that the enhancement of downward clear‐sky longwave radiative fluxes and SAF have played an important role in the accelerated surface warming over the TP during recent decades.

Systematic Changes in Cloud Radiative Forcing with Aerosol Loading for Deep Clouds in the Tropics

Abstract It has been widely recognized that aerosols can modify cloud properties, but it remains uncertain how much the changes and associated variations in cloud radiative forcing are related to aerosol loading. Using 4 yr of A-Train satellite products generated from CloudSat, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite, and the Aqua satellite, the authors investigated the systematic changes of deep cloud properties and cloud radiative forcing (CRF) with respect to changes in aerosol loading over the entire tropics. Distinct correlations between CRF and aerosol loading were found. Systematic variations in both shortwave and longwave CRF with increasing aerosol index over oceans and aerosol optical depth over land for mixed-phase clouds were identified, but little change was seen in liquid clouds. The systematic changes are consistent with the microphysical effect and the aerosol invigoration effect. Although this study cannot fully exclude the influence of other factors, attempts were made to explore various possibilities to the extent that observation data available can offer. Assuming that the systematic dependence originates from aerosol effects, changes in CRF with respect to aerosol loading were examined using satellite retrievals. Mean changes in shortwave and longwave CRF from very clean to polluted conditions ranged from −192.84 to −296.63 W m−2 and from 18.95 to 46.12 W m−2 over land, respectively, and from −156.12 to −170.30 W m−2 and from 6.76 to 11.67 W m−2 over oceans, respectively.

Long-term aerosol-mediated changes in cloud radiative forcing of deep clouds at the top and bottom of the atmosphere over the Southern Great Plains

Abstract. Aerosols can alter the macro- and micro-physical properties of deep convective clouds (DCCs) and their radiative forcing (CRF). This study presents what is arguably the first long-term estimate of the aerosol-mediated changes in CRF (AMCRF) for deep cloud systems derived from decade-long continuous ground-based and satellite observations, model simulations, and reanalysis data. Measurements were made at the US Department of Energy's Atmospheric Radiation Measurement Program's Southern Great Plains (SGP) site. Satellite retrievals are from the Geostationary Operational Environmental Satellite. Increases in aerosol loading were accompanied by the thickening of DCC cores and the expansion and thinning of anvils, due presumably to the aerosol invigoration effect (AIV) and the aerosol microphysical effect. Meteorological variables dictating these cloud processes were investigated. Consistent with previous findings, the AIV is most significant when the atmosphere is moist and unstable with weak wind shear. Such aerosol-mediated systematic changes in DCC core thickness and anvil size alter CRF at the top of atmosphere (TOA) and at the surface. Using extensive observations, ~300 DCC systems were identified over a 10 years period at the SGP site (2000–2011) and analyzed. Daily mean AMCRF at the TOA and at the surface are 29.3 W m−2 and 22.2 W m−2, respectively. This net warming effect due to changes in DCC microphysics offsets the cooling resulting from the first aerosol indirect effect.

Efficiency of clouds on shortwave radiation using experimental data

An extended data set of ground-based measurements of shortwave radiation, and cloud optical depth (COD) has been used to evaluate the surface cloud radiative forcing (CRF) in the shortwave range under overcast conditions (confirmed with sky images) at Granada, Spain. CRF varies in linear way with the logarithm of the COT showing a high correlation. The slope of the regression line (b) exhibits a clear dependence on solar zenith angle (SZA). The change in CRF per COD-unit is the cloud forcing efficiency (CFE), which is defined as the CRF derivate with respect to COD. In this case, CFE=b/COD. Experimental CFE varies between −160Wm−2 per COD-unit for SZA=14° and COD=1, and −0.3Wm−2 per COD-unit for SZA=80° and COD=50. The largest values of CFE are observed at low SZA and low COD. These empirical results are corroborated by radiative transfer simulations carried out by LibRadtran code.

Computing and Partitioning Cloud Feedbacks Using Cloud Property Histograms. Part I: Cloud Radiative Kernels

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.

Seasonality of polar surface warming amplification in climate simulations

The IPCC AR4 global warming climate simulations reveal a pronounced seasonality of polar warming amplification with maximum warming amplification in winter and minimum in summer. In this paper, we study the relative importance of surface albedo feedback (SAF), changes in cloud radiative forcing (CRF), changes in surface sensible and latent heat fluxes, changes in heat storage, and changes in the clear‐sky downward infrared radiation in causing the strong seasonality of polar warming amplification by calculating partial temperature changes due to each of these processes using the surface energy budget equation. The main thermodynamic factor for a small polar warming amplification in summer is that the positive SAF is largely cancelled out by the negative surface CRF feedback in summer. The positive SAF is relatively much weaker in winter compared to its amplitude in summer, therefore does not contribute to the pronounced polar warming amplification in winter. The seasonal cycle of polar surface warming amplification, in terms of both spatial patterns and temporal amplitude, closely follows the seasonal cycle of the warming due to changes in clear‐sky downward longwave radiation alone, indicating the importance of the atmospheric processes, such as water vapor feedback and dynamical feedbacks associated with the enhancement of poleward moist static energy transport, in causing the pronounced seasonality of polar warming amplification.

Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4

Simulations of late 20th and 21st century Arctic cloud amount from 20 global climate models (GCMs) in the Coupled Model Intercomparison Project phase 3 (CMIP3) dataset are synthesized and assessed. Under recent climatic conditions, GCMs realistically simulate the spatial distribution of Arctic clouds, the magnitude of cloudiness during the warmest seasons (summer–autumn), and the prevalence of low clouds as the predominant type. The greatest intermodel spread and most pronounced model error of excessive cloudiness coincides with the coldest seasons (winter–spring) and locations (perennial ice pack, Greenland, and the Canadian Archipelago). Under greenhouse forcing (SRES A1B emissions scenario) the Arctic is expected to become cloudier, especially during autumn and over sea ice, in tandem with cloud decreases in middle latitudes. Projected cloud changes for the late 21st century depend strongly on the simulated modern (late 20th century) annual cycle of Arctic cloud amount: GCMs that correctly simulate more clouds during summer than winter at present also tend to simulate more clouds in the future. The simulated Arctic cloud changes display a tripole structure aloft, with largest increases concentrated at low levels (below 700 hPa) and high levels (above 400 hPa) but little change in the middle troposphere. The changes in cloud radiative forcing suggest that the cloud changes are a positive feedback annually but negative during summer. Of potential explanations for the simulated Arctic cloud response, local evaporation is the leading candidate based on its high correlation with the cloud changes. The polar cloud changes are also significantly correlated with model resolution: GCMs with higher spatial resolution tend to produce larger future cloud increases.

Cloud variability, radiative forcing and meridional temperature gradients in a general circulation model

Due to the non-linearity of cloud—radiation interaction in general circulation models (GCMs), the time-mean cloud radiative forcing (CRF) is in general different from the CRF of time-mean clouds. This implies that a change in temporal cloud variability induces a change in radiative forcing even if there is no change in time-mean cloud properties. Here we investigate this variability contribution to CRF quantitatively in the National Center for Atmospheric Research Community Climate Model 3.6 GCM. In a reference run, the variability contribution is found to account for 35% of the global-mean climatological CRF. The variability contribution peaks in the mid-latitudes and is shown to be driven by synoptic eddy activity. In a climate change experiment, where the atmospheric CO2 is quadrupled, the change in cloud variability offsets 40% of the change in CRF due to the change in mean clouds. It is found that almost all of this effect is due to variability in cloud fraction rather than in cloud water content, and it is traced to the non-linearity introduced by the model’s treatment of vertical cloud overlap. This study indicates the possibility of an eddy variability-climate feedback that has not been extensively studied and quantified in the past.

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.

Global mean cloud feedbacks in idealized climate change experiments

Global mean cloud feedbacks in ten atmosphere‐only climate models are estimated in perturbed sea surface temperature (SST) experiments and the results compared to doubled CO2 experiments using mixed‐layer ocean versions of these same models. The cloud feedbacks in any given model are generally not consistent: the sign of the net cloud radiative feedback may vary according to the experimental design. However, both sets of experiments indicate that the variation of the total climate feedback across the models depends primarily on the variation of the net cloud feedback. Changes in different cloud types show much greater consistency between the two experiments for any individual model and amongst the set of models analyzed here. This suggests that the SST perturbation experiments may provide useful information on the processes associated with cloud changes which is not evident when analysis is restricted to feedbacks defined in terms of the change in cloud radiative forcing.

An alternative method to calculate cloud radiative forcing: Implications for quantifying cloud feedbacks

A modification to the traditional cloud radiative forcing (CRF) formula is presented. This alternative approach uses incident–rather than absorbed–solar radiation to calculate shortwave cloud radiative forcing at the surface. By removing the competing influence of surface albedo on CRF, the new formula more effectively isolates the impact of clouds and cloud changes under different climatic regimes. The removal of surface albedo effects makes the change in CRF a more useful measure of cloud feedback, although other factors (such as changes in clear‐sky solar absorption) can still muddle the interpretation. I present examples from GCM greenhouse simulations that demonstrate how this new formula can help to differentiate between actual cloud feedbacks versus apparent ones induced by snow and ice meltback using the traditional CRF equation. The results suggest that changes in surface albedo contribute approximately 20 to 40% of the high‐latitude CRF anomaly using the standard formula applied to an equilibrium 2 × CO2 simulation and about 50% to the greater Arctic when used on 21st‐century transient greenhouse experiments.

Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO2 and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.

On the Use of Cloud Forcing to Estimate Cloud Feedback

Abstract Uncertainty in cloud feedback is the leading cause of discrepancy in model predictions of climate change. The use of observed or model-simulated radiative fluxes to diagnose the effect of clouds on climate sensitivity requires an accurate understanding of the distinction between a change in cloud radiative forcing and a cloud feedback. This study compares simulations from different versions of the GFDL Atmospheric Model 2 (AM2) that have widely varying strengths of cloud feedback to illustrate the differences between the two and highlight the potential for changes in cloud radiative forcing to be misinterpreted.

A modeling study on the climate impacts of black carbon aerosols

A three‐dimensional interactive aerosol‐climate model has been developed and used to study the climatic impact of black carbon (BC) aerosols. When compared with the model's natural variability, significant global‐scale changes caused by BC aerosols occurred in surface latent and sensible heat flux, surface net long‐wave radiative flux, planetary boundary layer height, convective precipitation (all negative), and low‐cloud coverage (positive), all closely related to the hydrological cycle. The most significant regional change caused by BC revealed in this study is in precipitation that occurs in the tropics (shift of precipitation center in the ITCZ) and in the middle and high latitudes of the Northern Hemisphere (change in snow depth). Influenced by BC caused changes in cloud cover and surface albedo, the interactive model provides smaller positive all‐sky forcing at the top of atmosphere (TOA) and larger negative forcing at the surface than the offline diagnostics (the direct forcings). The actual solar radiative forcings by BC derived from the interactive model also exhibit significant interannual variations that are up to 4 times as large as their means. Based on the revealed changes in cloud radiative forcing by BC, a non‐Twomey‐Albrecht indirect forcing by BC that alters radiative budgets by changing cloud cover via thermodynamics rather than microphysics is also defined. It has been demonstrated that with an absolute amount more than 2 times higher than that of the TOA forcing, the surface forcing by BC is a very important factor in analyzing the climatic impact of BC. The result of this study suggests that with a constant annual emission of 14 TgC, BC aerosols do not cause a significant change in global‐mean surface temperature. The calculated surface temperature change is determined by a subtle balance among changes in surface energy budget as well as in the hydrological cycle, all caused by BC forcing and often compensate each other. The result of this study shows that the influences of BC aerosols on climate and environment are more significant in regional scale than in global scale. Important feedbacks between BC radiative effects and climate dynamics revealed in this study suggest the importance of using interactive aerosol‐climate models to address the issues related to the climate impacts of aerosols.

Some doubts concerning a link between cosmic ray fluxes and global cloudiness

Svensmark and Friis‐Christensen (1997, henceforth SFC) showed a strong correlation between cosmic ray flux and ISCCP total cloudiness between 1984 and 1990. They concluded that ionisation by cosmic rays, more prevalent at times of lower solar activity, might explain apparent correlations between solar activity and climate through changes in cloud radiative forcing. We have extended SFC's approach with a study of the different cloud types, restricting our analysis to the period 1985 to 1988 during which the ISCCP calibration is believed to be stable. We find no clear relationship between individual cloud types and cosmic ray flux. Inclusion of data at high latitudes decreases the amplitude of the apparent correlation although ionisation by cosmic rays is greatest at high latitudes. Thin high cloud shows an increase throughout the period such that the combined effect of the changes in cloud types suggests an almost monotonic increase in cloud radiative forcing between 1985 and 1988 which is not related to cosmic ray activity.

A possible change in cloud radiative forcing due to aircraft exhaust

Aircraft exhaust may reduce the crystal size in natural cirrus. This work investigates the change in cloud radiative forcing from such a size reduction by assuming a constant ice water content. A 1‐dim model with radiative properties that depend on the mean crystal size is used to compute the radiative transfer for an atmospheric column. The results show that the negative shortwave cloud forcing is enhanced with smaller crystals as they mainly increase the reflectivity of clouds. The change in the longwave cloud forcing is always positive although its magnitude depends strongly on the ice water path. The weighted sum of SW and LW cloud forcings depends on the mean crystal size, surface albedo and ice water content. It appears that there is a range of diameters between 15 and 25 µm where the response to a reduction in crystal size is fairly insensitive. Below and above this range the change is negative or positive, respectively. In regions of dense airtraffic the magnitude of the change in cloud forcing could be on the order of 0.3 W m−2 under the assumption of a 20% decrease of the mean crystal size from about 30 µm to 24 µm. Aircraft exhaust thus has the potential to affect the climate but the results should be taken with caution as they are based on parameterized optical properties for cirrus clouds.

Comparison of the seasonal change in cloud‐radiative forcing from atmospheric general circulation models and satellite observations

We compare seasonal changes in cloud‐radiative forcing (CRF) at the top of the atmosphere from 18 atmospheric general circulation models, and observations from the Earth Radiation Budget Experiment (ERBE). To enhance the CRF signal and suppress interannual variability, we consider only zonal mean quantities for which the extreme months (January and July), as well as the northern and southern hemispheres, have been differenced. Since seasonal variations of the shortwave component of CRF are caused by seasonal changes in both cloudiness and solar irradiance, the latter was removed. In the ERBE data, seasonal changes in CRF are driven primarily by changes in cloud amount. The same conclusion applies to the models. The shortwave component of seasonal CRF is a measure of changes in cloud amount at all altitudes, while the longwave component is more a measure of upper level clouds. Thus important insights into seasonal cloud amount variations of the models have been obtained by comparing both components, as generated by the models, with the satellite data. For example, in 10 of the 18 models the seasonal oscillations of zonal cloud patterns extend too far poleward by one latitudinal grid.