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G. Cesana, D. E. Waliser, D. Henderson, T. S. L’Ecuyer, X. Jiang, and J.-L. F. Li

–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ; Winker et al. 2010 ) and CloudSat ( Stephens et al. 2002 ) flying in the A-Train constellation. For example, using CALIPSO measurements, Chepfer et al. (2010) developed a general circulation model (GCM)-oriented cloud product to evaluate climate models (e.g., Cesana and Waliser 2016 ). Based on CloudSat measurements and a radiative transfer model, L’Ecuyer et al. (2008) developed a radiative flux retrieval product called 2

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Arunchandra S. Chandra, Pavlos Kollias, Scott E. Giangrande, and Stephen A. Klein

clear-sky conditions as a function of the normalized z i are shown in Fig. 5 . For comparison, the measurements from Nicholls and LeMone (1980) and Hogan et al. (2009) are shown in the same figure. The limited dataset from aircraft and Doppler lidar observations exhibits great scatter with no evident vertical structure, and it covers the range of the observed values using the insect radar returns. The composite profiles exhibit a smooth vertical structure. This is attributed to the long

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Anish Kumar M. Nair and K. Rajeev

stable and convective atmospheric conditions. Investigations into the vertical distribution of cloud water content and cloud faction observed using CloudSat / Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) data and its comparison with the circulation models and reanalysis data revealed that the high-altitude clouds in observations as well as models are concentrated in the regions with large midtropospheric vertical velocity, warm SST, and low lower

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Tyler J. Thorsen, Seiji Kato, Norman G. Loeb, and Fred G. Rose

-averaged inputs, monthly averages are carefully constructed and the computed fluxes are validated relative to observed values. In particular, a clustering method is developed to allow for the use of active sensor cloud properties from the CloudSat cloud radar ( Stephens et al. 2008 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) lidar ( Winker et al. 2009 , 2010 ). While the application of radiative kernels takes a trivial amount of effort, the initial computations

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Yinghui Liu, Steven A. Ackerman, Brent C. Maddux, Jeffrey R. Key, and Richard A. Frey

. 2003 ; Liu et al. 2004b ; Frey et al. 2008 ; Ackerman et al. 2008 ). While improvements to MODIS cloud detection have been made ( Liu et al. 2004b ; Frey et al. 2008 ), there are still larger errors in nighttime Arctic cloud detection than for most other regions on earth (e.g., Holz et al. 2008 ). The recent availability of observations from CloudSat and Cloud–Aerosol lidar and Infrared Pathfinder Satellite Observation (CALIPSO) provide an unprecedented opportunity to give a complete picture

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Casey J. Wall, Tsubasa Kohyama, and Dennis L. Hartmann

models. This paper is organized as follows: datasets and the methodology of the radiative transfer calculations are described in section 2 , results are given in section 3 , and conclusions are given in section 4 . 2. Data and methods a. Datasets Cloud observations are taken from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) satellite. CALIOP is a lidar that measures high

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Manajit Sengupta, Eugene E. Clothiaux, and Thomas P. Ackerman

liquid water path we developed a simple parameterization of boundary layer cloud radiative properties as a function of solar zenith angle and cloud liquid water path using the observations at the ARM SGP site. We then applied the parameterization to both the observed and modeled cloud liquid water paths and compared the resulting sets of surface irradiances. Using the parameterization to estimate surface irradiance from cloud liquid water path allowed us to avoid the problem of extracting solar

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Jing-Wu Liu, Shang-Ping Xie, Shuang Yang, and Su-Ping Zhang

summer ( Xu et al. 2011 ; Sasaki et al. 2012 ). How SST fronts regulate clouds in the monsoon region remains poorly understood because of the lack of cloud observations over the ocean. Here we close this data gap by synthesizing high-resolution cloud observations from a spaceborne lidar and long-term visual cloud types from ship reports. The Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) measure cloud-top heights with very high spatial resolution (30 m in vertical

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Gerald G. Mace and Forrest J. Wrenn

underscores the nonuniqueness of results from a severely under constrained retrieval algorithm like ISCCP, given the natural variability of hydrometeors in the atmosphere. While much detailed information can be derived from the suite of instruments at the ARM sites, the active remote sensing datasets produced by CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) (CC) provide global hydrometeor layer occurrence information. Using large regional comparisons

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James F. Booth, Catherine M. Naud, and Anthony D. Del Genio

compositing to isolate the warm frontal clouds within the extratropical cyclones from other cloud systems that would be present in any Eulerian analysis, such as the semipermanent cloud features in the midlatitudes or isolated convective systems. Furthermore, to assess the vertical location of GCM biases, we compare model output with vertical transects from CloudSat radar ( Stephens et al. 2002 ) and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO ) lidar ( Winker et al

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