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Hui Su and Jonathan H. Jiang

function of large-scale vertical motion, following the methodology put forward by Bony et al. (2004) . Their results showed that both high and low clouds underwent significant changes during the 1998 El Niño and the shift from “top-heavy” to “bottom-heavy” upward motion in the western Pacific appeared to be responsible for the cloud vertical structure change, rather than the mean vertical motion. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite ( CALIPSO ) experiments have

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George Tselioudis, William Rossow, Yuanchong Zhang, and Dimitra Konsta

of several years of cloud vertical structure (CVS) retrievals from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) now makes it possible to investigate the relationship of CVS and the WSs. The study of Zhang et al. (2007) derived tropical cloud clusters applying the same clustering technique to CloudSat histograms of CVSs and found good correspondence and clear physical connections between those clusters and the ones derived from ISCCP PC

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Seiji Kato, Fred G. Rose, David A. Rutan, Tyler J. Thorsen, Norman G. Loeb, David R. Doelling, Xianglei Huang, William L. Smith, Wenying Su, and Seung-Hee Ham

evaluate EBAF-surface irradiances with surface observations. The previous version, Edition 2.8 (Ed2.8) EBAF-surface data product, has been used for the evaluation of surface irradiances of climate models and other data products. These studies identify biases and spread among surface irradiances in models and data products (e.g., Boeke and Taylor 2016 ; Slater 2016 ; Loew et al. 2017 ). In addition, a study by Levine and Boos (2017) shows that intermodal precipitation variation is related to

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Alexander V. Matus, Tristan S. L’Ecuyer, Jennifer E. Kay, Cecile Hannay, and Jean-Francois Lamarque

used in this study builds on the basic 2B-FLXHR framework to include several refinements that are particularly relevant for evaluating aerosol direct effects ( Henderson et al. 2013 ). By including coincident lidar observations from CALIPSO and radiance measurements from MODIS, the representation of thin cirrus, marine stratocumulus, and aerosols have all been improved in the radiative flux calculations. Radiative flux calculations are further constrained using vertically resolved satellite

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D. P. Wylie and W. P. Menzel

.P. WYLIE AND W. P. MENZEL 383ER2 aircraft were incorporated into the McIDAS database for these comparisons. The lidar observations from both sides of the cirrusclouds indicated that cirrus do not have sharp boundaries at their tops, which were found to vary over I to2 km. There were often thin cirrus layers overlayingthicker cirrus and other cloud layers. The thin cirruslayers also had large spatial

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William Randel, Petra Udelhofen, Eric Fleming, Marvin Geller, Mel Gelman, Kevin Hamilton, David Karoly, Dave Ortland, Steve Pawson, Richard Swinbank, Fei Wu, Mark Baldwin, Marie-Lise Chanin, Philippe Keckhut, Karin Labitzke, Ellis Remsberg, Adrian Simmons, and Dong Wu

sampled on the UARS standard pressure grid. For the climatological analyses shown here, we obtained a number of lidar temperature time series (for stations with relatively long records) from the Network for the Detection of Stratospheric Change (NDSC) Web site (available online at http://www.ndsc.ws/ ). The total number of lidar observations and their latitudinal sampling is shown in Fig. 2b . The individual profiles are binned into monthly samples (using all the lidar observations over 1990

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Yulan Hong and Guosheng Liu

whole spectrum of atmospheric ice water ( Wu et al. 2006 , 2009 ). New observations in recent years provide unprecedented possibility for studying and improving the understanding of ice clouds. The Cloud Profiling Radar (CPR) on CloudSat and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) provide global ice cloud retrievals for the first time with vertically resolved values of ice water content (IWC

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Yi Huang, Steven T. Siems, Michael J. Manton, Luke B. Hande, and John M. Haynes

of a single wintertime granule, or overpass, of the CloudSat radar reflectivity, the cloud radar-only (RO) liquid water content ( CloudSat RO LWC) and ice water content (IWC; CloudSat RO IWC) is presented in Fig. 1 , along with the thermodynamic phase from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the visible imagery from MODIS. This particular wintertime example has been selected as it did not intersect any midlatitude cyclones, which are commonly

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Patrick Minnis, Anthony D. Del Genio, Audrey B. Wolf, and Mandana M. Khaiyer

data ( Clothiaux et al. 2000 ). Inclusion of the lidar allows for the filtering of insects, which produce a significant reflectivity during the spring and summer seasons over the ARM SGP site. Another source of error in the cloud radar observations is attenuation during heavy precipitation events, which leads to underestimated cloud-top heights. To mitigate this issue, only times are considered when MPL and MMCR cloud-base estimates are available during dry or lightly precipitating periods. This is

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T. H. M. Stein, C. E. Holloway, I. Tobin, and S. Bony

is aggregated? Anvil clouds are a direct result of deep convection detraining near the tropopause, but are the anvil characteristics such as height, thickness, and relative frequency per deep convective cloud related to the degree of aggregation? To address such questions, we have analyzed individual cloud layers identified over nearly 5 years of data (July 2006–April 2011) from two A-Train satellites, CloudSat and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations

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