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Ning An, Kaicun Wang, Chunlüe Zhou, and Rachel T. Pinker

introduce large uncertainties ( Welch et al. 2008 ). Moreover, many of these satellite sensors have different spectral channels for day and night retrievals, which introduce intrinsic errors to the observations of cloud diurnal variations. New airborne active sensors, such as the Cloud Profiling Radar on board the CloudSat satellite and Cloud–Aerosol Lidar with Orthogonal Polarization on board the CALIPSO satellite, can provide multiple cloud-layer-top and cloud-layer-base heights ( Kim et al. 2011

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A. S. Daloz, E. Nelson, T. L’Ecuyer, A. D. Rapp, and L. Sun

with precipitation are currently limited. Mean values of cloud cover or cloud fraction are often employed to evaluate observations or models (e.g., Walsh et al. 2009 ; Clark and Walsh 2010 ; Dolinar et al. 2016 ), providing interesting information on the representation of the proportion of clouds, but their use alone provides limited insights into the underlying cloud processes. Cloud cover or fraction is also difficult to compare between models and observations, as the classification technique

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Adeyemi A. Adebiyi, Paquita Zuidema, and Steven J. Abel

clouds are not identified and no information on the aerosol vertical structure is provided. Space-based lidar data provide the relationship of the vertical structure of the elevated smoke layers to that of the radiosondes for those few but important days when the lidar sampled locations near St. Helena. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; launched on 28 April 2006) provides

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Daniel Philipp, Martin Stengel, and Bodo Ahrens

mounted on board the CALIPSO satellite are not susceptible to those surface property changes and are therefore used as an accurate reference. With CALIOP the susceptibility of Cloud_cci records to sea ice/ocean surface transitions is determined and corrected if necessary. The COT threshold represents above which CALIOP COT the CALIOP pixel is classified cloudy. A problem that comes along with CALIOP lidar observations is that for cloud optical thicknesses of about 3–5 the lidar becomes attenuated

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Axel J. Schweiger and Jeffrey R. Key

Arctic are about 40% greater than the satellite-based, but only 10%greater in the Norwegian Sea area. Surprisingly, (ISCCP) cloud climatology and surface observations agreebetter during winter than during summer. Possible reasons for these differences are discussed, though it is notpossible to determine which cloud climatology is the "correct" one.1. IntroductionProducts from the International Satellite Cloud Climatology Project (ISCCP) (Rossow and Schiffer 199 1,hereafter RO9 1 ) are designed to

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William C. Conant, V. Ramanathan, Francisco P. J. Valero, and Jens Meywerk

1. Introduction For the past five years, numerous studies ( Ohmura and Gilgon 1993 ; Wild et al. 1995 ; Ramanathan et al. 1995 ; Arking 1996 ) have identified a discrepancy on the order of 10–35 W m −2 between diurnally averaged net surface solar radiation measured at the earth’s surface and that predicted by radiative transfer models. By noting that the models agree with observations at the top of the atmosphere (TOA), Wild et al. attribute the deficit to an absorption by the atmosphere

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Jennifer K. Fletcher, Shannon Mason, and Christian Jakob

(DARDAR) v2 data product, produced by Delanoë and Hogan (2010) and modified by Ceccaldi et al. (2013) . DARDAR provides collocated measurements from three A-Train satellites: the Cloud Profiling Radar on CloudSat , the lidar and infrared radiometer on board Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ), and the Moderate Resolution Imaging Spectroradiometer (MODIS). The DARDAR algorithm uses these measurements to produce a high-resolution (60-m vertical, 1-km

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Frida A.-M. Bender, Anders Engström, and Johannes Karlsson

al. 2008 ; Caldwell et al. 2013 ; Noda and Satoh 2014 ). Recently, however, it has been shown that the radiative properties of these clouds have improved their agreement with observations, over a generation of model development, from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) ( Engström et al. 2014 ). Engström et al. (2014) showed that the relation between albedo and cloud fraction in the CMIP5 models is close to linear, indicating an

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Tiangang Yuan, Siyu Chen, Jianping Huang, Dongyou Wu, Hui Lu, Guolong Zhang, Xiaojun Ma, Ziqi Chen, Yuan Luo, and Xiaohui Ma

–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) retrievals and first found that TD dust can be entrained to 9 km and then be transported toward the south to the northern slopes of the TP in the summer. Liu et al. (2008) further found that the TD is the primary dust contributor to the TP. Moreover, the aerosol optical depth (AOD) over the TP has a closer correlation with that over the TD in the summer than that in the spring ( Xia et al. 2008 ). Simulations further showed that the

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Yali Luo, Hui Wang, Renhe Zhang, Weimiao Qian, and Zhengzhao Luo

CloudSat / Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) ( Stephens et al. 2002 , 2008a ) data, as well as ground-based precipitation measurements, reanalysis data, and weather maps. TRMM is well designed to characterize convection intensity by detecting the precipitation part of convective cloud system. CloudSat / CALIPSO , on the other hand, can capture the whole convective system, from the convective core to the stratiform precipitation region and to the

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