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Gang Luo, Paul A. Davis, Larry L. Stowe, and E. Paul McClain

typeinformation as well. Once verified against surface andother meteorological observations, and by intercomparison with other global satellite cloud datasets suchas the International Satellite Cloud Climatology Project(ISCCP) ( Rossow et al. 1993 ) and the Air Force's RealTime Nephanalysis (Hamill et al. 1992 ), the CLAVRII algorithm could become operational at the NationalEnvironmental Satellite, Data, and Information Serviceand available to the scientific community. If it showsc 1995 American

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Shaima L. Nasiri and Bryan A. Baum

. Further work is being performed to minimize this classification error. b. THORPEX: 26 February 2003 On 26 February 2003, an Aqua cloud product validation mission was conducted out of Hickam Air Force Base in Honolulu, Hawaii. The ER-2 launched at 2200 UTC and landed at 0320 UTC (27 February 2003). At 2342 UTC the ER-2 obtained coincident measurements with the Aqua satellite along a flight track parallel to the satellite suborbital track, but offset by about 500 km, corresponding to a 40° satellite

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Robert R. Czys

-Duran, P. A., 1970: Observation of microstructure in two cumuli. Preprints, Conf on Cloud Physics, Fort Collins, CO, 173174.Vali, G., M. K. Politovich and D. Baumgardner, 1981: Conduct of cloud spectra measurements. Final Report to the Air Force Geophysics Laboratory, Contract AFGL-TR-81-0122.Warner, J., 1969: The Microstructure of Cumulus Clouds. Part I.General Features of the Droplet Spectrum. J. Atmos. Sci., 26,1049-1059.

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Kyo-Sun Sunny Lim, Laura D. Riihimaki, Yan Shi, Donna Flynn, Jessica M. Kleiss, Larry K. Berg, William I. Gustafson Jr., Yunyan Zhang, and Karen L. Johnson

1. Introduction Various types of clouds have different radiative forcing ( Chen et al. 2000 ); thus, an accurate cloud-type classification is necessary to understand the role of clouds on the energy budget and the regional/global hydrological cycle. Mace et al. (2006) and McFarlane et al. (2013) categorized cloud types based on typical values of cloud top, cloud base, and physical thickness of cloud layers, over the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM

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Michael D. King, Steven Platnick, Ping Yang, G. Thomas Arnold, Mark A. Gray, Jérôme C. Riedi, Steven A. Ackerman, and Kuo-Nan Liou

1. Introduction A knowledge of cloud radiative properties and their variation in space and time is especially crucial to the understanding of the radiative forcing of climate. High quality multispectral imagery acquired from high-altitude aircraft or satellite platforms is the most efficient and reliable means of fulfilling these observational requirements. Between 18 May and 6 June 1998, the National Aeronautics and Space Administration (NASA) ER-2 high-altitude research aircraft conducted 11

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Zhe Wang, Zhenhui Wang, Xiaozhong Cao, Jiajia Mao, Fa Tao, and Shuzhen Hu

for Photogrammetry and Remote Sensing, 1162–1169. Ramanathan , V. , R. D. Cess , E. F. Harrison , P. Minnis , B. R. Barkstrom , E. Ahmad , and D. Hartmann , 1989 : Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment . Science , 243 , 57 – 63 , https://doi.org/10.1126/science.243.4887.57 . 10.1126/science.243.4887.57 Sekelsky , S. M. , and R. E. Mcintosh , 1996 : Cloud observations with a polarimetric 33 GHz and 95 GHz radar

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James A. Coakley Jr., Michael A. Friedman, and William R. Tahnk

radius in marine stratocumulus clouds. J. Atmos. Sci , 58 , 2912 – 2926 . 10.1175/1520-0469(2001)058<2912:VOODAE>2.0.CO;2 Welch, R. M. , and Wielicki B. A. , 1985 : A radiative parameterization of stratocumulus cloud fields. J. Atmos. Sci , 42 , 2888 – 2897 . 10.1175/1520-0469(1985)042<2888:ARPOSC>2.0.CO;2 Wetzel, M. A. , and Stowe L. L. , 1999 : Satellite-observed patterns in stratus microphysics, aerosol optical thickness, and shortwave radiative forcing. J. Geophys. Res , 104

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Insa Meinke, Beate Geyer, Frauke Feser, and Hans von Storch

the water cycle are adversely affected by the spectral nudging manipulation. More specifically, in this paper we analyze the impact of spectral nudging on the simulation of cloudiness as it is a key component of the water and energy cycle. To do so, we compare cloud statistics simulated with the regional atmospheric model REMO ( Jacob and Podzun 1997 ) with satellite-derived cloudiness of the International Satellite Cloud Climatology Project (ISCCP) during the Pilot Study for Intensive Data

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Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sebastian A. Stewart, and Phillip C. Haftings

radiative forcing, as cirrus are known to both warm and cool the atmosphere depending on their varying physical properties. Furthermore, the ability to detect multilayered cloud scenes is improved with the V3 algorithm. The results show that 91% of clouds in 2012 at the NASA GSFC project site were recorded as single-layer clouds according to the V2 retrieval compared with 81% for V3. In a brief comparison, V3 retrievals show closer agreement to CALIPSO in both high-cloud occurrence frequency and mean

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Larry L. Stowe, Paul A. Davis, and E. Paul McClain

their radiative forcing. The initial effort to do this is the AVHRR Pathfinder Atmosphere project ( UCAR 1994 ). It uses cloud classified radiances and total cloud amount from CLAVR-1 to compute estimates of broadband radiation budget parameters at the top of the atmosphere for “all” and “clear-sky” conditions and aerosol optical thickness over the oceans. This is done on a daily, pentad, and monthly basis, and on a 110-km equal-area global grid for all NOAA afternoon satellites since NOAA-7

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