Longwave Cloud Radiative Effect Research Articles

Cloud Radiative Effects Associated With Daily Weather Regimes

AbstractUsing high temporal resolution satellite observations and reanalysis data, we classify daily weather into distinct regimes and quantify their associated cloud radiative effect (CRE) to better understand the roles of various weather systems in affecting Earth's top‐of‐atmosphere radiation budget. These regimes include non‐precipitation, drizzle, wet non‐storm, and storm days, which encompass atmospheric rivers (AR), tropical storms (TS), and mesoscale convection systems (MCS). We find that precipitation (wet) days account for roughly 80% (60%) of global longwave (LW) and shortwave (SW) CREs due to their large frequency and high intensity in CRE. Despite being rare globally (13%), AR, TS, and MCS days together account for 32% of global LW CRE and 27% of SW CRE due to their higher intensity in LW and SW CRE. These results enhance our understanding of how various weather systems, particularly severe storms, influence Earth's radiative balance, and will help to better constrain climate models.

Thin Clouds Control the Cloud Radiative Effect Along the Sc‐Cu Transition

AbstractIn situ and spaceborne studies reveal the prevalence of thin clouds in the major Stratocumulus‐to‐Cumulus Transition (SCT) regions. Using instantaneous satellite and reanalysis data, this study investigates the properties of thin clouds in the Southeast Pacific Ocean and their impact on the cloud radiative effect (CRE). Our findings demonstrate that thin clouds are intrinsic to the SCT. The overcast stratocumulus‐dominated regime exhibits a minimal presence of thin clouds, which become notably prominent after the clouds breakup into the cumulus‐dominated regime. The regime dependence of the occurrence of thin clouds is also observed in terms of the marine cold‐air outbreak parameter and the sea surface temperature. Thin clouds at a given cloud cover significantly modulate the shortwave (SW) and longwave (LW) components of CRE. SW CRE decreases by 46 %–65 % with increasing thin cloud cover. They account for a larger variance in cloud albedo than the combined influence of the liquid water path and effective radius. Furthermore, LW CRE decreases by about 12 %–52 % with thin cloud cover. An increase in the fraction of thin clouds also leads to a larger fraction of negative SW CRE offset by positive LW CRE at a given cloud cover. This LW compensation ranges from approximately 8 % at overcast cloud cover to as much as 19 % at about 50 % cloud cover. These findings elucidate the crucial role of thin clouds, and thus cloud morphology, in modulating CRE and underscore the necessity of their accurate representation in climate models.

The Impact of Rotation on Tropical Climate, the Hydrologic Cycle, and Climate Sensitivity

AbstractThis work explores the impact of rotation on tropical convection and climate. As our starting point, we use the RCEMIP experiments as control simulations and run additional simulations with rotation. Compared to radiative convective equilibrium (RCE) experiments, rotating RCE (RRCE) experiments have a more stable and humid atmosphere with higher precipitation rates. The intensity of the overturning circulation decreases, water vapor is cycled through the troposphere at a slower rate, the subsidence fraction decreases, and the climate sensitivity increases. Several of these changes can be attributed to an increased flux of latent and sensible heat that results from an increase of near‐surface wind speed with rotation shortly after model initialization. The increased climate sensitivity results from changes of both the longwave cloud radiative effect and the longwave clear‐sky radiative fluxes. This work demonstrates the sensitivity of atmospheric humidity and surface fluxes of moisture and temperature to rotation.

Understanding changes in cloud simulations from E3SM version 1 to version 2

Abstract. This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (Cloud Layers Unified By Binormals, CLUBB); microphysical parameterization (MG2); and deep-convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds and clouds with optical depth larger than 3.6 over the stratocumulus-to-cumulus transition regimes, where the shortwave cloud radiative effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning done in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to an improved SWCRE and longwave cloud radiative effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the SO. They have a relatively smaller impact on clouds than CLUBB tuning and ZM tuning do. This study offers additional insights into clouds simulated in E3SMv2 by utilizing multiple data sets and the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) diagnostic tool as well as sensitivity tests. The improved understanding will benefit future E3SM developments.

Tropical Cirrus Are Highly Sensitive to Ice Microphysics Within a Nudged Global Storm‐Resolving Model

AbstractCirrus dominate the longwave radiative budget of the tropics. For the first time, the variability in cirrus properties and longwave cloud radiative effects (CREs) that arises from using different microphysical schemes within nudged global storm‐resolving simulations from a single model, is quantified. Nudging allows us to compute radiative biases precisely using coincident satellite measurements and to fix the large‐scale dynamics across our set of simulations to isolate the influence of microphysics. We run 5‐day simulations with four commonly‐used microphysics schemes of varying complexity (SAM1MOM, Thompson, M2005 and P3) and find that the tropical average longwave CRE varies over 20 W m−2 between schemes. P3 best reproduces observed longwave CRE. M2005 and P3 simulate cirrus with realistic frozen water path but unrealistically high ice crystal number concentrations which commonly hit limiters and lack the variability and dependence on frozen water content seen in aircraft observations. Thompson and SAM1MOM have too little cirrus.

Significant changes in cloud radiative effects over Southwestern United States during the COVID-19 flight reduction period

Aircraft-induced clouds (AICs) are one of the most visible anthropogenic atmospheric phenomena, which mimic the natural cirrus clouds and perturb global radiation budget by reducing incoming shortwave (SW) radiation and trapping outgoing longwave (LW) radiation. The COVID-19 pandemic has caused a 70 % global decline in flight numbers from mid-March to October 2020, which provided a unique opportunity to examine the climatic impact of AICs. Among various regions, Western Europe and the Contiguous United States experienced the most substantial reduction in air traffic during the COVID-19 pandemic. Interestingly, only the Southwestern United States demonstrated a significant decrease in cirrus clouds, leading to notable changes in shortwave (SW) and longwave (LW) cloud radiative effects. Such changes were likely due to the reduction in AICs. However, further investigations indicated that this region also experienced abnormal high pressure and low relative humidity in the middle and upper atmosphere, resulting in unusual subsidence and dryness that prohibit the formation and maintenance of cirrus cloud. While it remains challenging to quantify the exact climatic impact of reduced AICs, the remarkable anomalies documented in this study provide valuable observational benchmark for future modelling studies of the climatic impact AICs.

On the Consistency of Ice Cloud Optical Models for Spaceborne Remote Sensing Applications and Broadband Radiative Transfer Simulations

AbstractAqua satellite Moderate Resolution Imaging Spectroradiometer (MODIS) 1‐km observations are collocated with Clouds and the Earth's Radiant Energy System (CERES) fields of view taken during July 2008 afternoon satellite passes over the equatorial western Pacific Ocean. Radiation simulations are compared with collocated CERES observations to better understand the sensitivity of computed fluxes to two ice cloud broadband radiation parameterization schemes and inferred ice cloud characteristics. In particular, the radiation computational schemes and ice cloud property retrievals are based on two respective ice particle models, the MODIS Collection 6 (MC6) aggregate model and a more microphysically consistent two‐habit model (THM). The simulation results show that both MC6 and THM overestimate the shortwave (SW) and longwave (LW) cloud radiative effects at the top of the atmosphere, as compared to the CERES observations; the difference between the MC6 and THM‐based ice cloud retrievals is too small to compensate for the differences between the two model‐based radiation schemes. Therefore, the present finding suggests that broadband radiative simulations are more sensitive to the radiation parameterization scheme than to the input cloud properties retrieved using the corresponding ice cloud particle optical property model.

Sensitivities of cloud radiative effects to large-scale meteorology and aerosols from global observations

Abstract. The radiative effects of clouds make a large contribution to the Earth's energy balance, and changes in clouds constitute the dominant source of uncertainty in the global warming response to carbon dioxide forcing. To characterize and constrain this uncertainty, cloud-controlling factor (CCF) analyses have been suggested that estimate sensitivities of clouds to large-scale environmental changes, typically in cloud-regime-specific multiple linear regression frameworks. Here, local sensitivities of cloud radiative effects to a large number of controlling factors are estimated in a regime-independent framework from 20 years (2001–2020) of near-global (60∘ N–60∘ S) satellite observations and reanalysis data using statistical learning. A regularized linear regression (ridge regression) is shown to skillfully predict anomalies of shortwave (R2=0.63) and longwave cloud radiative effects (CREs) (R2=0.72) in independent test data on the basis of 28 CCFs, including aerosol proxies. The sensitivity of CREs to selected CCFs is quantified and analyzed. CRE sensitivities to sea surface temperature and estimated inversion strength are particularly pronounced in low-cloud regions and generally in agreement with previous studies. The analysis of CRE sensitivities to three-dimensional wind field anomalies reflects the fact that CREs in tropical ascent regions are mainly driven by variability of large-scale vertical velocity in the upper troposphere. In the subtropics, CRE is sensitive to free-tropospheric zonal and meridional wind anomalies, which are likely to encapsulate information on synoptic variability that influences subtropical cloud systems by modifying wind shear and thus turbulence and dry-air entrainment in stratocumulus clouds, as well as variability related to midlatitude cyclones. Different proxies for aerosols are analyzed as CCFs, with satellite-derived aerosol proxies showing a larger CRE sensitivity than a proxy from an aerosol reanalysis, likely pointing to satellite aerosol retrieval biases close to clouds, leading to overestimated aerosol sensitivities. Sensitivities of shortwave CREs to all aerosol proxies indicate a pronounced cooling effect from aerosols in stratocumulus regions that is counteracted to a varying degree by a longwave warming effect. The analysis may guide the selection of CCFs in future sensitivity analyses aimed at constraining cloud feedback and climate forcings from aerosol–cloud interactions using data from both observations and global climate models.

Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition

Abstract. Climate change is particularly noticeable in the Arctic. The most common type of cloud at these latitudes is mixed-phase stratocumulus. These clouds occur frequently and persistently during all seasons and play a critical role in the Arctic energy budget. Previous observations in the central (north of 80∘ N) Arctic have shown a high occurrence of prolonged periods of a shallow, single-layer mixed-phase stratocumulus at the top of the boundary layer (BL; altitudes ∼ 300 to 400 m). However, recent observations from the summer of 2018 instead showed a prevalence of a two-layer boundary-layer cloud system. Here we use large-eddy simulation to examine the maintenance of one of the cloud systems observed in the summer of 2018 and the sensitivity of the cloud layers to different micro- and macro-scale parameters. We find that the model generally reproduces the observed thermodynamic structure well, with two near-neutrally stratified layers in the BL caused by a low cloud (located within the first few hundred meters) capped by a lower-altitude temperature inversion and an upper cloud layer (based around one kilometer or slightly higher) capped by the main temperature inversion of the BL. The simulated cloud structure is persistent unless there are low aerosol number concentrations (≤ 5 cm−3), which cause the upper cloud layer to dissipate, or high large-scale wind speeds (≥ 8.5 m s−1), which erode the lower inversion and the related cloud layer. The changes in cloud structure alter both the short- and longwave cloud radiative effect at the surface. This results in changes in the net radiative effect of the modeled cloud system, which can impact the surface melting or freezing. The findings highlight the importance of better understanding and representing aerosol sources and sinks over the central Arctic Ocean. Furthermore, they underline the significance of meteorological parameters, such as the large-scale wind speed, for maintaining the two-layer boundary-layer cloud structure encountered in the lower atmosphere of the central Arctic.

Forcing, Cloud Feedbacks, Cloud Masking, and Internal Variability in the Cloud Radiative Effect Satellite Record

Abstract Satellite observations show a near-zero trend in the top-of-atmosphere global-mean net cloud radiative effect (CRE), suggesting that clouds did not further cool nor heat the planet over the last two decades. The causes of this observed trend are unknown and can range from effective radiative forcing (ERF) to cloud feedbacks, cloud masking, and internal variability. We find that the near-zero NetCRE trend is a result of a significant negative trend in the longwave (LW) CRE and a significant positive trend in the shortwave (SW) CRE, cooling and heating the climate system, respectively. We find that it is exceptionally unlikely (<1% probability) that internal variability can explain the observed LW and SW CRE trends. Instead, the majority of the observed LWCRE trend arises from cloud masking wherein increases in greenhouse gases reduce OLR in all-sky conditions less than in clear-sky conditions. In SWCRE, rapid cloud adjustments to greenhouse gases, aerosols, and natural forcing agents (ERF) explain a majority of the observed trend. Over the northeast Pacific, we show that ERF, hitherto an ignored factor, contributes as much as cloud feedbacks to the observed SWCRE trend. Large contributions from ERF and cloud masking to the global-mean LW and SW CRE trends are supplemented by negative LW and positive SW cloud feedback trends, which are detectable at 80%–95% confidence depending on the observational uncertainty assumed. The large global-mean LW and SW cloud feedbacks cancel, leaving a small net cloud feedback that is unconstrained in sign, implying that clouds could amplify or dampen global warming.

Seasonality of the QBO Impact on Equatorial Clouds

AbstractThe Quasi‐Biennial Oscillation (QBO) dominates the interannual variability in the tropical lower stratosphere and is characterized by the descent of alternating easterly and westerly zonal winds. The QBO impact on tropical clouds and convection has received great attention in recent years due to its implications for weather and climate. In this study, a 15‐year record of high vertical resolution cloud observations from CALIPSO and a 50 hPa zonal wind QBO index from ERA5 are used to document the QBO impact on equatorial (10°S–10°N) clouds. Observations from radio occultations, the CERES instrument, and the ERA5 reanalysis are also used to document the QBO impact on temperature, cloud radiative effect (CRE), and zonal wind, respectively. It is shown that the QBO impact on zonal mean equatorial cloud fraction has a strong seasonality. The strongest cloud fraction response to the QBO occurs in boreal spring and early summer, which extends from above the mean tropopause to ∼12.5 km and results in a significant longwave CRE anomaly of 1 W/m2. The seasonality of the QBO impact on cloud fraction is synchronized with the QBO impacts on temperature and zonal wind in the tropical upper troposphere.

Evaluating two diagnostic schemes of cloud-fraction parameterization using the CloudSat data

Cloud fraction affects both shortwave and longwave cloud radiative effects, strongly regulating the Earth's energy budget and thus climate change in both observation and model simulations. This study evaluates two diagnostic cloud-fraction parameterization schemes, namely the Xu-Randall scheme and the Sundqvist scheme, using a novel approach. Unlike previous evaluation studies that compared schemes embedded in a climate model and could not identify the exact sources for the biases, this study obtained all inputs to the schemes by upscaling the CloudSat (quasi) observations. Hence, the scheme-observation discrepancies can be mostly attributed to deficiencies of the cloud-fraction parameterization, providing clear insights for model improvement.Results show that both schemes predict total cloud fraction close to the observation, overestimate high-level cloud fraction over the tropics, and underestimate low- and middle-level cloud fraction around 60°S and 60°N. Overall, the Xu-Randall scheme is relatively closer to the observation than the Sundqvist scheme. The Xu-Randall scheme produces a relatively more-realistic seasonal variation of cloud fraction, while the Sundqvist scheme underestimates low-level cloud fraction at all latitudes in all seasons. It is further revealed that the observed cloud fraction tends to vary with relative humidity (RH) in a non-monotonous way for clouds of any phase. Neither scheme can capture this non-monotonicity. Both schemes tend to overestimate the change rate of cloud fraction with RH and predict excessive cloud fraction when RH approaches 100%, especially for the ice-phase clouds. In addition, the biases are exacerbated in both schemes when the horizontal/vertical grid sizes are decreased/increased, respectively. Implications for future cloud-fraction parameterization improvement are also discussed.

Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)

Abstract. The impacts of the ice-crystal size distribution shape parameter (μi) were considered in the two-moment bulk cloud microphysics scheme of the Community Atmosphere Model Version 6 (CAM6). The μi's impact on the statistical mean radii of ice crystals can be analyzed based on their calculating formulas. Under the same mass (qi) and number (Ni), the ratios of the mass-weighted radius (Rqi, not related to μi) to other statistical mean radii (e.g., effective radiative radius) are completely determined by μi. Offline tests show that μi has a significant impact on the cloud microphysical processes owing to the μi-induced changes in ice-crystal size distribution and statistical mean radii (excluding Rqi). Climate simulations show that increasing μi would lead to higher qi and lower Ni in most regions, and these impacts can be explained by the changes in cloud microphysical processes. After increasing μi from 0 to 5, the longwave cloud radiative effect increases (stronger warming effect) by 5.58 W m−2 (25.11 %), and the convective precipitation rate decreases by −0.12 mm d−1 (7.64 %). In short, the impacts of μi on climate simulations are significant, and the main influence mechanisms are also clear. This suggests that the μi-related processes deserve to be parameterized in a more realistic manner.

Cirrus cloud thinning using a more physically based ice microphysics scheme in the ECHAM-HAM general circulation model

Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth's terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. Consistent with previous approaches using ECHAM-HAM, with the P3 scheme and the higher RH thresholds for cirrus cloud formation, we do not find a significant cooling response in any of our simulations. The most notable response from our extreme case is the reduction in the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by about 50 %, from 9.9 W m−2 with the original cloud fraction approach down to 4.9 W m−2 using the new cloud fraction RH thresholds that allow partial grid-box coverage of cirrus clouds above ice saturation, unlike the original approach. Even with this reduction with the updated cloud fraction approach, the TOA anomalies from overseeding far exceed those reported in previous studies. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we drastically reduce overseeding, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA anomalies regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not confirm the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect for most of our simulations. Our results also show feedbacks on lower-lying mixed-phase and liquid clouds through the reduction in ice crystal sedimentation that reduces cloud droplet depletion and results in stronger cloud albedo effects. However, this is outweighed by stronger longwave trapping from cirrus clouds with more numerous and smaller ice crystals. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale.

The surface longwave cloud radiative effect derived from space lidar observations

Abstract. Clouds warm the surface in the longwave (LW), and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE has been estimated over more than 2 decades using space-based radiometers (2000–2021) and over the 5-year period ending in 2011 using the combination of radar, lidar and space-based radiometers. Previous work comparing these two types of retrievals has shown that the radiometer-based cloud amount has some bias over icy surfaces. Here we propose new estimates of the global surface LW CRE from space-based lidar observations over the 2008–2020 time period. We show from 1D atmospheric column radiative transfer calculations that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple parameterizations between surface LW CRE and five cloud properties that are well observed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-based lidar: opaque cloud cover and altitude and thin cloud cover, altitude, and emissivity. We evaluate this new surface LWCRE–LIDAR product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages as well as to ground-based observations at specific locations. This evaluation shows good correlations between this new product and other datasets. Our estimate appears to be an improvement over others as it appropriately captures the annual variability of the surface LW CRE over bright polar surfaces and it provides a dataset more than 13 years long.

Diverse cloud radiative effects and global surface temperature simulations induced by different ice cloud optical property parameterizations

The representation of ice cloud optical properties in climate models has long been a difficult problem. Very different ice cloud optical property parameterization schemes developed based on very different assumptions of ice particle shape habits, particle size distributions, and surface roughness conditions, are used in various models. It is not clear as to how simulated climate variables are affected by the ice cloud optical property parameterizations. A total of five ice cloud optical property parameterization schemes, including three based on the ice habit mixtures suitable for general ice clouds, mid-latitude synoptic ice clouds, and tropical deep convective ice clouds, and the other two based on single ice habits (smooth hexagonal column and severely roughened column aggregate), are developed under a same framework and are implemented in the National Center for Atmospheric Research Community Atmospheric Model version 5. A series of atmosphere-only climate simulations are carried out for each of the five cases with different ice parameterizations. The differences in the simulated top of the atmosphere shortwave and longwave cloud radiative effects (CREs) are evaluated, and the global averaged net CRE differences among different cases range from − 1.93 to 1.03 Wm−2. The corresponding changes in simulated surface temperature are found to be most prominent on continental regions which amount to several degrees in Kelvin. Our results indicate the importance of choosing a reasonable ice cloud optical property parameterization in climate simulations.

Arctic cloud properties and associated radiative effects in the three newer reanalysis datasets (ERA5, MERRA-2, JRA-55): Discrepancies and possible causes

Arctic cloud properties and associated radiative effects were investigated by comparing three newly available reanalysis datasets (i.e., ERA5, MERRA-2, and JRA-55) with CloudSat-CALIPSO (CC) observations. Cloud fractions (CFs) in different datasets exhibited different spatial and temporal variations: ERA5 and MERRA-2 exhibited large cloudiness over sea ice in winter, while JRA-55 exhibited relatively larger cloudiness over the open ocean in summer. This difference was related primarily to excessive low-level clouds over sea ice in winter in ERA5 and MERRA-2, especially near the surface (i.e., 1000 hPa). All datasets used in this study exhibited similar spatial distribution of ice water path and liquid water path (LWP), but the reanalyses underestimated both ice and liquid compared to CloudSat retrievals. Despite their similar spatial patterns, relative proportions were considerably different among the reanalyses, which can be attributed to the different phase-partitioning parameterizations. Longwave (LW) cloud radiative effects (CREs) exhibited more consistent variations among the datasets compared to CFs, with large discrepancies being evident in winter. In addition, MERRA-2 exhibited significantly larger LW CRE at low LWPs (i.e., LWP < 30 g m−2) owing to the large CF near the surface. Shortwave (SW) CREs were also affected by the CF and cloud water path (CWP), thereby exhibiting lower values in JRA-55 owing to low CF and CWP. The SW CRE change rate with increasing LWP was largest in MERRA-2, followed by JRA-55 and ERA5; these differences are associated with different dependence of the reduced downward SW radiation by clouds on LWP among the different datasets.

Calculating the Climatology and Anomalies of Surface Cloud Radiative Effect Using Cloud Property Histograms and Cloud Radiative Kernels

Cloud radiative kernels (CRK) built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere (TOA) fluxes, and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes, which determines the regional surface temperature change and variability. In this study, CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model (RRTM). Longwave cloud radiative effect (CRE) at the surface is primarily driven by cloud base properties, while TOA CRE is primarily decided by cloud top properties. For this reason, the standard version of surface CRK is a function of latitude, longitude, month, cloud optical thickness (τ) and cloud base pressure (CBP), and the TOA CRK is a function of latitude, longitude, month, τ and cloud top pressure (CTP). Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present, the surface CRKs on CBP-τ histograms were converted to CTP-τ fields using the statistical relationship between CTP, CBP and τ obtained from collocated CloudSat and MODIS observations. For both climate model outputs and satellites observations, the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes. The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth’s Radiant Energy System (CERES) surface irradiances products.

Understanding the surface temperature response and its uncertainty to CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt;, black carbon, and sulfate

Abstract. Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.

Effects of Cloud Microphysics on the Vertical Structures of Cloud Radiative Effects over the Tibetan Plateau and the Arctic

The Tibetan Plateau (TP) and the Arctic are both cold, fragile, and sensitive to global warming. However, they have very different cloud radiative effects (CRE) and influences on the climate system. In this study, the effects of cloud microphysics on the vertical structures of CRE over the two regions are analyzed and compared by using CloudSat/CALIPSO satellite data and the Rapid Radiative Transfer Model. Results show there is a greater amount of cloud water particles with larger sizes over the TP than over the Arctic, and the supercooled water is found to be more prone to exist over the former than the latter, making shortwave and longwave CRE, as well as the net CRE, much stronger over the TP. Further investigations indicate that the vertical structures of CRE at high altitudes are primarily dominated by cloud ice water, while those at low altitudes are dominated by cloud liquid and mixed-phase water. The liquid and mixed-phase water results in a strong shallow heating (cooling) layer above the cooling (heating) layer in the shortwave (longwave) CRE profiles, respectively.