Longwave Cloud Research Articles

Suppression of Cold Weather Events over High-Latitude Continents in Warm Climates

AbstractRecent studies, using Lagrangian single-column atmospheric models, have proposed that in warmer climates more low clouds would form as maritime air masses advect into Northern Hemisphere high-latitude continental interiors during winter (DJF). This increase in low cloud amount and optical thickness could reduce surface radiative cooling and suppress Arctic air formation events, partly explaining both the warm winter high-latitude continental interior climate and frost-intolerant species found there during the Eocene and the positive lapse-rate feedback in future Arctic climate change scenarios. Here the authors examine the robustness of this low-cloud mechanism in a three-dimensional atmospheric model that includes large-scale dynamics. Different warming scenarios are simulated under prescribed CO2 and sea surface temperature, and the sensitivity of winter temperatures and clouds over high-latitude continental interior to mid- and high-latitude sea surface temperatures is examined. Model results show that winter 2-m temperatures on extreme cold days increase about 50% faster than the winter mean temperatures and the prescribed SST. Low cloud fraction and surface longwave cloud radiative forcing also increase in both the winter mean state and on extreme cold days, consistent with previous Lagrangian air-mass studies, but with cloud fraction increasing for different reasons than proposed by previous work. At high latitudes, the cloud longwave warming effect dominates the shortwave cooling effect, and the net cloud radiative forcing at the surface tends to warm high-latitude land but cool midlatitude land. This could contribute to the reduced meridional temperature gradient in warmer climates and help explain the greater warming of winter cold extremes relative to winter mean temperatures.

INVESTIGATION OF CLOUDS AND CLOUD RADIATIVE FORCING ON THE WINDWARD SIDE OF THE MADAGASCAR MOUNTAIN CHAINS

Abstract. Clouds affect the radiative energy balance of the earth–atmosphere system by reflecting and trapping the radiation. The cooling occurs over the earth by reflecting the incoming solar radiation and warming by trapping the outgoing longwave terrestrial radiation. In this paper an attempt has been carried out to understand the clouds and cloud radiative forcing over the windward side of the Madagascar mountain chain. The study was carried out using the Clouds and Earth’s Radiant Energy System (CERES) data June–September from 2000 to 2016. Over the windward side, clouds tend to cool whereas on the leeward side, clouds tend to warm marginally. During this period, peak value of shortwave cloud forcing and the longwave cloud forcing are −45 W m−2 and +15 W m−2 respectively. Generally, the clouds are restricted to low level in the windward side. We also examined the association between the cloud radiative forcing and cloud physical properties such as cloud optical depth, cloud, cloud top temperature and cover amount. The cloud optical depth (−0.74 correlation value) and cloud cover amount (−0.51 correlation value) show better correlation with net cloud radiative cooling. The surface pressure of the Madagascar is also correlated with the net cooling over the windward side.

Space lidar observations constrain longwave cloud feedback

Some of the most challenging questions in atmospheric science relate to how clouds will respond as the climate warms. On centennial scales, the response of clouds could either weaken or enhance the warming due to greenhouse gas emissions. Here we use space lidar observations to quantify changes in cloud altitude, cover, and opacity over the oceans between 2008 and 2014, together with a climate model with a lidar simulator to also simulate these changes in the present-day climate and in a future, warmer climate. We find that the longwave cloud altitude feedback, found to be robustly positive in simulations since the early climate models and backed up by physical explanations, is not the dominant longwave feedback term in the observations, although it is in the model we have used. These results suggest that the enhanced longwave warming due to clouds might be overestimated in climate models. These results highlight the importance of developing a long-term active sensor satellite record to reduce uncertainties in cloud feedbacks and prediction of future climate.

Time Evolution of the Cloud Response to Moisture Intrusions into the Arctic during Winter

AbstractNorthward fluxes of moisture and sensible heat into the Arctic affect the atmospheric stability, sea ice and snow cover, clouds, and surface energy budget. Intense moisture fluxes into the Arctic are called moisture intrusions; some can lead to basinwide increases in downward longwave radiation (DLR) at the surface, called downward infrared (IR) events. Using the ERA-Interim reanalysis from 1990 to 2016, this study investigated the time evolution of cloud amount and cloud properties and their impact on the surface radiation fluxes in response to Arctic moisture intrusions and downward IR events during winter for better understanding of the Arctic moisture intrusions. A composite analysis revealed several key features: moisture intrusions produce more clouds and higher cloud liquid and ice water content; positive cloud amount anomalies can persist for over 10 days over the Arctic Ocean during downward IR events; positive high-level and middle-level cloud anomalies are evident in the early stage, and positive low-level cloud anomalies are evident in the late stage. Greater clear-sky DLR and longwave cloud radiative forcing (CRF) over the Arctic Ocean accompany the greater all-sky DLR during the downward IR events. Greater clear-sky DLR can be attributed to higher air temperatures and higher total column water vapor, while greater longwave CRF is the result of larger cloud amount and cloud water content. Longwave CRF anomalies account for approximately 40% of the all-sky DLR anomalies.

A Comparison of Cloud Classification Methodologies: Differences Between Cloud and Dynamical Regimes

AbstractClassifications of cloud data into Cloud Regimes (CRs) and compositing based on meteorological parameters, Dynamic Regimes (DRs), are often used in the analysis of clouds. We compare CR and DR classifications to understand the relative merits of these approaches and develop a comparison methodology for future studies. We apply the Self‐Organizing Map technique to International Satellite Cloud Climatology Project (ISCCP) D1 joint histograms to produce a CR and ERA‐Interim pressure vertical velocity output to produce a DR. The CR created improves the separation between high‐level CRs compared to previous work. Composites of ISCCP joint histogram data using the DR produce coherent groupings similar to those in the CR scheme particularly in regions of ascent. Both classifications display coherent geographical patterns and reproduce relationships between vertical velocity and cloud properties. However, the CR produces more coherent clusters with higher intracluster similarity and a greater range of independent cloud classes. Independent tests of composites using ISCCP FD output show that the regional variability of longwave cloud radiative effect for particular nodes are significantly higher in the DR than the CR scheme suggesting a poorer classification. Composite mean CloudSat reflectivity‐altitude joint histograms represent all major cloud types in the CR scheme, while the current DR grouping is less coherent and misses classes. This suggests that the CR scheme is a more useful classification than the DR scheme based solely on vertical velocity data. Contingency table analysis indicates a low association between these classifications, suggesting combining these schemes would be valuable.

Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model

AbstractThis study provides comprehensive insight into the notable differences in clouds and precipitation simulated by the Energy Exascale Earth System Model Atmosphere Model version 0 and version 1 (EAMv1). Several sensitivity experiments are conducted to isolate the impact of changes in model physics, resolution, and parameter choices on these differences. The overall improvement in EAMv1 clouds and precipitation is primarily attributed to the introduction of a simplified third‐order turbulence parameterization Cloud Layers Unified By Binormals (along with the companion changes) for a unified treatment of boundary layer turbulence, shallow convection, and cloud macrophysics, though it also leads to a reduction in subtropical coastal stratocumulus clouds. This lack of stratocumulus clouds is considerably improved by increasing vertical resolution from 30 to 72 layers, but the gain is unfortunately subsequently offset by other retuning to reach the top‐of‐atmosphere energy balance. Increasing vertical resolution also results in a considerable underestimation of high clouds over the tropical warm pool, primarily due to the selection for numerical stability of a higher air parcel launch level in the deep convection scheme. Increasing horizontal resolution from 1° to 0.25° without retuning leads to considerable degradation in cloud and precipitation fields, with much weaker tropical and subtropical short‐ and longwave cloud radiative forcing and much stronger precipitation in the intertropical convergence zone, indicating poor scale awareness of the cloud parameterizations. To avoid this degradation, significantly different parameter settings for the low‐resolution (1°) and high‐resolution (0.25°) were required to achieve optimal performance in EAMv1.

Sensitivity Study of Anthropogenic Aerosol Indirect Forcing through Cirrus Clouds with CAM5 Using Three Ice Nucleation Parameterizations

Quantifying the radiative forcing due to aerosol–cloud interactions especially through cirrus clouds remains challenging because of our limited understanding of aerosol and cloud processes. In this study, we investigate the anthropogenic aerosol indirect forcing (AIF) through cirrus clouds using the Community Atmosphere Model version 5 (CAM5) with a state-of-the-art treatment of ice nucleation. We adopt a new approach to isolate anthropogenic AIF through cirrus clouds in which ice nucleation parameterization is driven by prescribed pre-industrial (PI) and present-day (PD) aerosols, respectively. Sensitivities of anthropogenic ice AIF (i.e., anthropogenic AIF through cirrus clouds) to different ice nucleation parameterizations, homogeneous freezing occurrence, and uncertainties in the cloud microphysics scheme are investigated. Results of sensitivity experiments show that the change (PD minus PI) in global annual mean longwave cloud forcing (i.e., longwave anthropogenic ice AIF) ranges from 0.14 to 0.35 W m–2, the change in global annual mean shortwave cloud forcing (i.e., shortwave anthropogenic ice AIF) from –0.47 to –0.20 W m–2, and the change in net cloud forcing from –0.12 to 0.05 W m–2. Our results suggest that different ice nucleation parameterizations are an important factor for the large uncertainty of anthropogenic ice AIF. Furthermore, improved understanding of the spatial and temporal occurrence characteristics of homogeneous freezing events and the mean states of cirrus cloud properties are also important for constraining anthropogenic ice AIF.

Aerosol-induced intensification of cooling effect of clouds during Indian summer monsoon

Measurements and models show that enhanced aerosol concentrations can modify macro- and micro-physical properties of clouds. Here, we examine the effect of aerosols on continental mesoscale convective cloud systems during the Indian summer monsoon and find that these aerosol–cloud interactions have a net cooling effect at the surface and the top-of-atmosphere. Long-term (2002–2016) satellite data provide evidence of aerosol-induced cloud invigoration effect (AIvE) during the Indian summer monsoon. The AIvE leads to enhanced formation of thicker stratiform anvil clouds at higher altitudes. These AIvE-induced stratiform anvil clouds are also relatively brighter because of the presence of smaller sized ice particles. As a result, AIvE-induced increase in shortwave cloud radiative forcing is much larger than longwave cloud radiative forcing leading to the intensified net cooling effect of clouds over the Indian summer monsoon region. Such aerosol-induced cooling could subsequently decrease the surface diurnal temperature range and have significant feedbacks on lower tropospheric turbulence in a warmer and polluted future scenario.

How important are future marine and shipping aerosol emissions in a warming Arctic summer and autumn?

Abstract. Future sea ice retreat in the Arctic in summer and autumn is expected to affect both natural and anthropogenic aerosol emissions: sea ice acts as a barrier between the ocean and the atmosphere, and reducing it increases dimethyl sulfide and sea salt emissions. Additionally, a decrease in the area and thickness of sea ice could lead to enhanced Arctic ship traffic, for example due to shorter routes of cargo ships. Changes in the emissions of aerosol particles can then influence cloud properties, precipitation, surface albedo, and radiation. Next to changes in aerosol emissions, clouds will also be affected by increases in Arctic temperatures and humidities. In this study, we quantify how future aerosol radiative forcings and cloud radiative effects might change in the Arctic in late summer (July–August) and early autumn (September–October). Simulations were conducted for the years 2004 and 2050 with the global aerosol–climate model ECHAM6-HAM2. For 2050, simulations with and without additional ship emissions in the Arctic were carried out to quantify the impact of these emissions on the Arctic climate. In the future, sea salt as well as dimethyl sulfide emissions and burdens will increase in the Arctic. The increase in cloud condensation nuclei, which is due to changes in aerosol particles and meteorology, will enhance cloud droplet number concentrations over the Arctic Ocean (+10 % in late summer and +29 % in early autumn; in-cloud values averaged between 75 and 90∘ N). Furthermore, both liquid and total water path will increase (+10 % and +8 % in late summer; +34 % and +26 % in early autumn) since the specific humidity will be enhanced due to higher temperatures and the exposure of the ocean's surface. Changes in both aerosol radiative forcings and cloud radiative effects at the top of the atmosphere will not be dominated by the aerosol particles and clouds themselves but by the decrease in surface albedo (and by the increase in surface temperature for the longwave cloud radiative effect in early autumn). Mainly due to the reduction in sea ice, the aerosol radiative forcing will become less positive (decreasing from 0.53 to 0.36 W m−2 in late summer and from 0.15 to 0.11 W m−2 in early autumn). The decrease in sea ice is also mainly responsible for changes in the net cloud radiative effect, which will become more negative in late summer (changing from −36 to −46 W m−2). Therefore, the cooling component of both aerosols and clouds will gain importance in the future. We found that future Arctic ship emissions related to transport and oil and gas extraction (Peters et al., 2011) will not have a large impact on clouds and radiation: changes in aerosols only become significant when we increase these ship emissions by a factor of 10. However, even with 10-fold ship emissions, the net aerosol radiative forcing shows no significant changes. Enhanced black carbon deposition on snow leads to a locally significant but very small increase in radiative forcing over the central Arctic Ocean in early autumn (no significant increase for average between 75 and 90∘ N). Furthermore, the 10-fold higher ship emissions increase the optical thickness and lifetime of clouds in late summer (net cloud radiative effect changing from −48 to −52 W m−2). These aerosol–cloud effects have a considerably larger influence on the radiative forcing than the direct effects of particles (both aerosol particles in the atmosphere and particles deposited on snow). In summary, future ship emissions of aerosols and their precursor gases might have a net cooling effect, which is small compared to other changes in future Arctic climate such as those caused by the decrease in surface albedo.

Sensitivity of Radiative‐Convection Equilibrium to Divergence Damping in GFDL‐FV3‐Based Cloud‐Resolving Model Simulations

AbstractUsing a nonhydrostatic model based on a version of Geophysical Fluid Dynamics Laboratory's FV3 dynamical core at a cloud‐resolving resolution in radiative‐convective equilibrium (RCE) configuration, the sensitivity of the mean RCE climate to the magnitude and scale‐selectivity of the divergence damping is explored. Divergence damping is used to reduce small‐scale noise in more realistic configurations of this model. This sensitivity is tied to the strength (and width) of the convective updrafts, which decreases (increases) with increased damping and acts to organize the convection, dramatically drying out the troposphere and increasing the outgoing longwave radiation. Increased damping also results in a much‐broadened precipitation probability distribution and larger extreme values, as well as reduction in cloud fraction, which correspondingly decreases the magnitude of shortwave and longwave cloud radiative effects. Solutions exhibit a monotonic dependence on the strength of the damping and asymptotically converge to the inviscid limit. While the potential dependence of RCE simulations on resolution and microphysical assumptions are generally appreciated, these results highlight the potential significance of the choice of subgrid numerical diffusion in the dynamical core.

Improvement of the Simulation of Cloud Longwave Scattering in Broadband Radiative Transfer Models

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

The Potential of a Multidecade Spaceborne Lidar Record to Constrain Cloud Feedback

AbstractSynthetic multidecadal spaceborne lidar records are used to examine when a cloud response to anthropogenic forcing would be detectable from spaceborne lidar observations. The synthetic records are generated using long‐term cloud changes predicted by two Coupled Model Intercomparison Program 5 models seen through the COSP/lidar (CFMIP, Cloud Feedback Model Intercomparison Project, Observation Simulators Package) and cloud interannual variability observed by the CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar during the past decade. CALIPSO observations do not show any significant trend yet. Our analysis of the synthetic time series suggests that the tropical cloud longwave feedback and the Southern Ocean cloud shortwave feedback might be constrained with 70% confidence with, respectively, a 20‐year and 29‐year uninterrupted lidar‐in‐space record. A 27‐year record might be needed to separate the two different model predictions in the tropical subsidence clouds. Assuming that combining the CALIPSO and Earth‐CARE (Earth Clouds, Aerosols and Radiation Explorer) missions will lead to a spaceborne lidar record of at least 16 years, we examine the impact of gaps and calibration offsets between successive missions. A 2‐year gap between Earth‐CARE and the following spaceborne lidar would have no significant impact on the capability to constrain the cloud feedback if all the space lidars were perfectly intercalibrated. Any intercalibration shift between successive lidar missions would delay the capability to constrain the cloud feedback mechanisms, larger shifts leading to longer delays.

MJO Prediction Skill of the Subseasonal-to-Seasonal Prediction Models

Abstract The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides a major source of tropical and extratropical predictability on a subseasonal time scale. This study conducts a quantitative evaluation of the MJO prediction skill in state-of-the-art operational models, participating in the subseasonal-to-seasonal (S2S) prediction project. The relationship of MJO prediction skill with model biases in the mean moisture fields and in the longwave cloud–radiation feedbacks is also investigated. The S2S models exhibit MJO prediction skill out to a range of 12 to 36 days. The MJO prediction skills in the S2S models are affected by both the MJO amplitude and phase errors, with the latter becoming more important at longer forecast lead times. Consistent with previous studies, MJO events with stronger initial MJO amplitude are typically better predicted. It is found that the sensitivity to the initial MJO phase varies notably from model to model. In most models, a notable dry bias develops within a few days of forecast lead time in the deep tropics, especially across the Maritime Continent. The dry bias weakens the horizontal moisture gradient over the Indian Ocean and western Pacific, likely dampening the organization and propagation of the MJO. Most S2S models also underestimate the longwave cloud–radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelope. The models with smaller bias in the mean horizontal moisture gradient and the longwave cloud–radiation feedbacks show higher MJO prediction skills, suggesting that improving those biases would enhance MJO prediction skill of the operational models.

Cloud Longwave Scattering Effect and Its Impact on Climate Simulation

The cloud longwave (LW) scattering effect has been ignored in most current climate models. To investigate its climate impact, we apply an eight-stream DIScrete Ordinates Radiative Transfer (DISORT) scheme to include the cloud LW scattering in the General circulation model version of the LongWave Rapid Radiative Transfer Model (RRTMG_LW) and the Community Atmospheric Model Version 5 (CAM5). Results from the standalone RRTMG_LW and from diagnostic runs of CAM5 (no climate feedback) show that the cloud LW scattering reduces the upward flux at the top of the atmosphere and leads to an extra warming effect in the atmosphere. In the interactive runs with climate feedback included in CAM5, the cloud LW scattering effect is amplified by the water vapor-temperature feedback in a warmer atmosphere and has substantial influences on cloud fraction and specific humidity. The thermodynamic feedbacks are more significant in the northern hemisphere and the resulting meridional temperature gradient is different between the two hemispheres, which strengthens the southern branch of Hadley circulation, and modulates the westerly jet near 50° S and the upper part of Walker circulation. Our study concludes that the cloud LW scattering effect could have complex impacts on the global energy budget and shall be properly treated in future climate models.

An Economical Analytical Equation for the Integrated Vertical Overlap of Cumulus and Stratus

AbstractBy extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

Role of microphysical parameterizations with droplet relative dispersion in IAP AGCM 4.1

Previous studies have shown that accurate descriptions of the cloud droplet effective radius (Re) and the autoconversion process of cloud droplets to raindrops (Ar) can effectively improve simulated clouds and surface precipitation, and reduce the uncertainty of aerosol indirect effects in GCMs. In this paper, we implement cloud microphysical schemes including two-moment Ar and Re considering relative dispersion of the cloud droplet size distribution into version 4.1 of the Institute of Atmospheric Physics’s atmospheric GCM (IAP AGCM 4.1), which is the atmospheric component of the Chinese Academy of Sciences’ Earth System Model. Analysis of the effects of different schemes shows that the newly implemented schemes can improve both the simulated shortwave and longwave cloud radiative forcings, as compared to the standard scheme, in IAP AGCM 4.1. The new schemes also effectively enhance the large-scale precipitation, especially over low latitudes, although the influences of total precipitation are insignificant for different schemes. Further studies show that similar results can be found with the Community Atmosphere Model, version 5.1.

The observed relationship of cloud to surface longwave radiation and air temperature at Ny-Ålesund, Svalbard

Ten-year (2004–2013) observations of cloud and surface shortwave (SW) and longwave (LW) fluxes at Ny-Ålesund were analysed to investigate monthly variations in cloudiness and their impacts on the surface LW radiation budget and near-surface temperature (Ts). The cloud fraction (CF) showed distinct monthly variations, high in summer (0.90) and lower in winter (0.79). The downward SW flux increased from March and showed a peak (~200 W m−2) in June. In contrast, the downward LW (LWD) flux increased from ~200 W m−2 in February to ~300 W m−2 in July. Both LWD and upward LW (LWU) fluxes and their difference increased during winter as lowest cloud base height (LCBH) decreased and CF increased. Ts difference and both LW fluxes difference (ΔLWD and ΔLWU), calculated as the difference in monthly mean Ts and LW between all-sky and cloud-free conditions, were highly correlated (R2 = 0.68 for LWD and R2 = 0.92 for LWU). Dramatic changes in Ts, CF and LW fluxes at Ny-Ålesund were closely associated with cold and warm air mass advection on a multi-day time scale. The average Ts under low-level clouds (LCBH ≤ 2 km) was estimated as −7.4 ± 6.1 °C due to warm air masses advected from the North Atlantic Ocean and Barents Sea, whereas the average Ts on cloud-free days was −14.5 ± 5.7 °C because of cold air mass advection from the pole. However, the duration of low-level clouds may not be long enough to drive such large Ts variations. 75-percentile of low-level cloud conditions at Ny-Ålesund persisted up to 2.3 days, whereas cloud-free and high-altitude cloud (LCBH > 2 km) conditions lasted for approximately 0.8 and 0.5 days, respectively. This implies that cloud LW effects on several warm days may be larger than the monthly average, but may not be accumulated enough to induce surface warming due to abrupt Ts drop associated with cold air mass advection.

Using Space Lidar Observations to Decompose Longwave Cloud Radiative Effect Variations Over the Last Decade

AbstractMeasurements of the longwave cloud radiative effect (LWCRE) at the top of the atmosphere assess the contribution of clouds to the Earth warming but do not quantify the cloud property variations that are responsible for the LWCRE variations. The CALIPSO space lidar observes directly the detailed profile of cloud, cloud opacity, and cloud cover. Here we use these observations to quantify the influence of cloud properties on the variations of the LWCRE observed between 2008 and 2015 in the tropics and at global scale. At global scale, the method proposed here gives good results except over the Southern Ocean. We find that the global LWCRE variations observed over ocean are mostly due to variations in the opaque cloud properties (82%); transparent cloud columns contributed 18%. Variation of opaque cloud cover is the first contributor to the LWCRE evolution (58%); opaque cloud temperature is the second contributor (28%).

The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated

Abstract. According to climate model simulations, the changing altitude of middle and high clouds is the dominant contributor to the positive global mean longwave cloud feedback. Nevertheless, the mechanisms of this longwave cloud altitude feedback and its magnitude have not yet been verified by observations. Accurate, stable, and long-term observations of a metric-characterizing cloud vertical distribution that are related to the longwave cloud radiative effect are needed to achieve a better understanding of the mechanism of longwave cloud altitude feedback. This study shows that the direct measurement of the altitude of atmospheric lidar opacity is a good candidate for the necessary observational metric. The opacity altitude is the level at which a spaceborne lidar beam is fully attenuated when probing an opaque cloud. By combining this altitude with the direct lidar measurement of the cloud-top altitude, we derive the effective radiative temperature of opaque clouds which linearly drives (as we will show) the outgoing longwave radiation. We find that, for an opaque cloud, a cloud temperature change of 1 K modifies its cloud radiative effect by 2 W m−2. Similarly, the longwave cloud radiative effect of optically thin clouds can be derived from their top and base altitudes and an estimate of their emissivity. We show with radiative transfer simulations that these relationships hold true at single atmospheric column scale, on the scale of the Clouds and the Earth's Radiant Energy System (CERES) instantaneous footprint, and at monthly mean 2° × 2° scale. Opaque clouds cover 35 % of the ice-free ocean and contribute to 73 % of the global mean cloud radiative effect. Thin-cloud coverage is 36 % and contributes 27 % of the global mean cloud radiative effect. The link between outgoing longwave radiation and the altitude at which a spaceborne lidar beam is fully attenuated provides a simple formulation of the cloud radiative effect in the longwave domain and so helps us to understand the longwave cloud altitude feedback mechanism.

Impact of Multiple Scattering on Longwave Radiative Transfer Involving Clouds

AbstractGeneral circulation models (GCMs) are extensively used to estimate the influence of clouds on the global energy budget and other aspects of climate. Because radiative transfer computations involved in GCMs are costly, it is typical to consider only absorption but not scattering by clouds in longwave (LW) spectral bands. In this study, the flux and heating rate biases due to neglecting the scattering of LW radiation by clouds are quantified by using advanced cloud optical property models, and satellite data from Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth's Radiant Energy System (CERES), and Moderate Resolution Imaging Spectrometer (MODIS) merged products (CCCM). From the products, information about the atmosphere and clouds (microphysical and buck optical properties, and top and base heights) is used to simulate fluxes and heating rates. One‐year global simulations for 2010 show that the LW scattering decreases top‐of‐atmosphere (TOA) upward flux and increases surface downward flux by 2.6 and 1.2 W/m2, respectively, or approximately 10% and 5% of the TOA and surface LW cloud radiative effect, respectively. Regional TOA upward flux biases are as much as 5% of global averaged outgoing longwave radiation (OLR). LW scattering causes approximately 0.018 K/d cooling at the tropopause and about 0.028 K/d heating at the surface. Furthermore, over 40% of the total OLR bias for ice clouds is observed in 350–500 cm−1. Overall, the radiative effects associated with neglecting LW scattering are comparable to the counterpart due to doubling atmospheric CO2 under clear‐sky conditions.