The launch of CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) in 2006 provided the first opportunity to incorporate information about the vertical distribution of cloud and aerosols directly into global estimates of atmospheric radiative heating. Vertical profiles of radar and lidar backscatter from CloudSat’s Cloud Profiling Radar (CPR) and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard CALIPSO naturally complement Moderate Resolution Imaging Spectroradiometer (MODIS) radiance measurements, providing a nearly complete depiction of the cloud and aerosol properties that are essential for deriving high-vertical-resolution profiles of longwave (LW) and shortwave (SW) radiative fluxes and heating rates throughout the atmosphere. This study describes a new approach for combining vertical cloud and aerosol information from CloudSat and CALIPSO with MODIS data to assess impacts of clouds and aerosols on top-of-atmosphere (TOA) and surface radiative fluxes. The resulting multisensor cloud–aerosol product is used to document seasonal and annual mean distributions of cloud and aerosol forcing globally from June 2006 through April 2011. Direct comparisons with Clouds and the Earth’s Radiant Energy System (CERES) TOA fluxes exhibit a close correlation, with improved errors relative to CloudSat-only products. Sensitivity studies suggest that remaining uncertainties in SW fluxes are dominated by uncertainties in CloudSat liquid water content estimates and that the largest sources of LW flux uncertainty are prescribed surface temperature and lower-tropospheric humidity. Globally and annually averaged net TOA cloud radiative effect is found to be −18.1 W m−2. The global, annual mean aerosol direct radiative effect is found to be −1.6 ± 0.5 W m−2 (−2.5 ± 0.8 W m−2 if only clear skies over the ocean are considered), which, surprisingly, is more consistent with past modeling studies than with observational estimates that were based on passive sensors.

Four different types of estimates of the surface downwelling longwave radiative flux (DLR) are reviewed. One group of estimates synthesizes global cloud, aerosol, and other information in a radiation model that is used to calculate fluxes. Because these synthesis fluxes have been assessed against observations, the global-mean values of these fluxes are deemed to be the most credible of the four different categories reviewed. The global, annual mean DLR lies between approximately 344 and 350 W m−2 with an error of approximately ±10 W m−2 that arises mostly from the uncertainty in atmospheric state that governs the estimation of the clear-sky emission. The authors conclude that the DLR derived from global climate models are biased low by approximately 10 W m−2 and even larger differences are found with respect to reanalysis climate data. The DLR inferred from a surface energy balance closure is also substantially smaller that the range found from synthesis products suggesting that current depictions of surface energy balance also require revision. The effect of clouds on the DLR, largely facilitated by the new cloud base information from the CloudSat radar, is estimated to lie in the range from 24 to 34 W m−2 for the global cloud radiative effect (all-sky minus clear-sky DLR). This effect is strongly modulated by the underlying water vapor that gives rise to a maximum sensitivity of the DLR to cloud occurring in the colder drier regions of the planet. The bottom of atmosphere (BOA) cloud effect directly contrast the effect of clouds on the top of atmosphere (TOA) fluxes that is maximum in regions of deepest and coldest clouds in the moist tropics.

High vertical resolution CloudSat radar measurements, supplemented with cloud boundaries and aerosol information from the CALIPSO lidar, are used to examine radiative heating features in the atmosphere that have not previously been characterized by passive sensors. The monthly and annual mean radiative heating/cooling structure for a 4 year period between 2006 and 2010 is derived. The mean atmospheric radiative cooling rate from CloudSat/CALIPSO is 0.98 K d−1 (1.34 K d−1 between 150 and 950 hPa) and is largely a reflection of the Earth's mean water vapor distribution, with sharp vertical gradients introduced by clouds. It is found that there is a minimum in cooling in the tropical lower to middle troposphere, a cooling maximum in the upper‐boundary layer of the Southern Hemisphere poleward of −10° latitude, and a minimum in cooling in the lower boundary layer in the middle to high latitudes of both hemispheres. Clouds tops tend to strongly cool the upper‐boundary layer all year in the midlatitudes to high latitudes of the Southern Hemisphere (where peak seasonal mean winter cooling is 3.4 K d−1), but this cooling is largely absent in the corresponding parts of the Northern Hemisphere during boreal winter, resulting in a hemispheric asymmetry in cloud radiative cooling.

Abstract. A technique is presented that uses attenuated backscatter profiles from the CALIOP satellite lidar to estimate cloud base heights of lower-troposphere liquid clouds (cloud base height below approximately 3 km). Even when clouds are thick enough to attenuate the lidar beam (optical thickness τ≳5), the technique provides cloud base heights by treating the cloud base height of nearby thinner clouds as representative of the surrounding cloud field. Using ground-based ceilometer data, uncertainty estimates for the cloud base height product at retrieval resolution are derived as a function of various properties of the CALIOP lidar profiles. Evaluation of the predicted cloud base heights and their predicted uncertainty using a second statistically independent ceilometer dataset shows that cloud base heights and uncertainties are biased by less than 10 %. Geographic distributions of cloud base height and its uncertainty are presented. In some regions, the uncertainty is found to be substantially smaller than the 480 m uncertainty assumed in the A-Train surface downwelling longwave estimate, potentially permitting the most uncertain of the radiative fluxes in the climate system to be better constrained. The cloud base dataset is available at https://doi.org/10.1594/WDCC/CBASE.

Aerosol direct radiative effects are assessed using multi‐sensor observations from the A‐Train satellite constellation. By leveraging vertical cloud and aerosol information from CloudSat and CALIPSO, this study reports new global estimates of aerosol radiative effects and the component owing to anthropogenic aerosols. We estimate that the global mean aerosol direct radiative effect is −2.40 W/m2 with an error of ± 0.6 W/m2 owing to uncertainties in aerosol type classification and optical depth retrievals. Anthropogenic direct radiative forcing is assessed using new observation‐based aerosol radiative kernels. Anthropogenic aerosols are found to account for 21% of the global radiative effect, or −0.50 ± 0.3 W/m2, mainly from sulfate pollution (−0.54 W/m2) partially offset by absorption from smoke (0.03 W/m2). Uncertainty estimates effectively rule out the possibility that anthropogenic aerosols warm the planet, although strong positive forcing is observed locally where anthropogenic aerosols reside above clouds and bright surfaces.