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K. M. Markowicz, P. J. Flatau, A. E. Kardas, J. Remiszewska, K. Stelmaszczyk, and L. Woeste

1. Introduction The role of atmospheric aerosols in modifying the radiation budget of the earth–atmosphere climate system is being increasingly understood and recognized ( Hansen et al. 1997 ; Haywood et al. 1999 ; Ramanathan et al. 2001 ). There are still large uncertainties of the aerosol radiative forcing on regional scales ( Houghton et al. 2001 ) because of the lack of sufficient knowledge of aerosols’ optical, physical, and chemical properties and their large spatial and temporal

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Ping Yang, Lei Bi, Bryan A. Baum, Kuo-Nan Liou, George W. Kattawar, Michael I. Mishchenko, and Benjamin Cole

habit prescription ( Baum et al. 2005 , 2011 ; Yue et al. 2007 ; Baran 2009 ). The resulting bulk-scattering properties are used in radiative transfer models to simulate the reflectance and transmittance associated with ice clouds over a range of conditions, and are tabulated in lookup tables (LUTs) for use in subsequent data reduction to infer ice cloud optical thickness and effective particle size from airborne or satellite observations ( Platnick et al. 2003 ; King et al. 2004 ; Huang et al

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T. H. Cheng, X. F. Gu, L. F. Chen, T. Yu, and G. L. Tian

. Optically thin cirrus have been identified as one of the major unsolved elements in weather and climate research, largely because of their unique optical properties and altitude ( McFarquhar et al. 2000 ). They affect the earth’s radiation budget because they reflect incoming solar radiation back to space and they absorb and re-emit terrestrial radiation ( Liou 1986 ; Lynch 1996 ). The radiative effect of the optically thin cirrus is determined by the optical and microphysical properties. Thus, studies

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Emma Järvinen, Martin Schnaiter, Guillaume Mioche, Olivier Jourdan, Valery N. Shcherbakov, Anja Costa, Armin Afchine, Martina Krämer, Fabian Heidelberg, Tina Jurkat, Christiane Voigt, Hans Schlager, Leonid Nichman, Martin Gallagher, Edwin Hirst, Carl Schmitt, Aaron Bansemer, Andy Heymsfield, Paul Lawson, Ugo Tricoli, Klaus Pfeilsticker, Paul Vochezer, Ottmar Möhler, and Thomas Leisner

1. Introduction Convective systems are an important source of ice particles in the upper troposphere (e.g., Jensen et al. 1996 ; Gayet et al. 2012a ; Frey et al. 2011 ) and the lowermost stratosphere ( de Reus et al. 2009 ). Ice particles found in the anvil outflows are usually formed in the lower and warmer part of the convective cell, and therefore their microphysical and optical properties differ from in situ formed ice particles (e.g., McFarquhar and Heymsfield 1996 ; Lawson et al

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Jason Cole, Howard W. Barker, Norman G. Loeb, and Knut von Salzen

well as their optical properties, macrophysical structure, and resulting radiative fluxes. This sort of analysis is best done when using cloud properties and radiative fluxes that are coincident, and physically consistent, in space and time. A common approach to evaluate GCMs is to use histograms of cloud top pressure and cloud optical thickness which are then used to relate biases in cloud properties to biases in all-sky TOA CREs ( Zhang et al. 2005 ; Wyant et al. 2006 ). However, this can be

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H. Wang, R. T. Pinker, P. Minnis, and M. M. Khaiyer

( Ramanathan 1986 ; Pinker and Laszlo 1992 ; Li and Leighton 1993 ; Stephens et al. 1994 ; Gupta et al. 1999 ; Mueller et al. 2004 ; Raschke et al. 1991 ; Rigollier et al. 2004 ; Whitlock et al. 1995 ; Lefèvre et al. 2007 ). Most models have been designed for use with a particular satellite and, frequently, cloud optical properties are inferred from a single visible channel. The use of multichannel information is expected to provide a more accurate description of cloud optical properties and

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W. J. Koshak

1. Introduction The study by Koshak (2010) showed that the distributions of ground and cloud flash optical characteristics, as seen from the Optical Transient Detector (OTD), overlap appreciably. Therefore, space-based flash-type discrimination (on a flash-by-flash basis) is fundamentally difficult. However, Koshak (2010) also indicated that the mean values of the optical characteristics for ground and cloud flashes are distinct, so that an analysis of a sample of N flashes could possibly

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Kuan-Man Xu

cloud overlap assumption for each ECMWF grid that is divided into a number of subgrid cells or subcolumns. The Fu–Liou radiation model ( Fu and Liou 1992 ) is used to compute the cloud optical depth and radiative fluxes for each subcolumn. A threshold on cloud optical depth is used to determine the cloud-top height while selection criteria for DC cloud objects are used to select subcolumns for producing the pdfs of cloud physical properties. These steps are discussed in detail below. First, each

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C. G. Schmitt and A. J. Heymsfield

calculated for the dataset was 0.801 for solid crystals and 0.815 when the hollowness factor was considered. Following the same calculation as Schmitt et al. (2006) , consideration of the scattering properties of hollow crystals would yield a surface radiation increase of 2.5 W m −2 for a cirrus cloud with an optical depth of 0.5 for the wavelength range between 380 and 780 nm. 5. Summary and conclusions In this note we have reported the investigation of the frequency of hollows in the ends of bullet

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K. Franklin Evans

linear, and adjoint models. Section 3 describes testing of the forward, tangent linear, and adjoint models, and shows examples of the adjoint sensitivities for cloud model fields. 2. The SHDOMPP and SHDOMPPDA algorithms a. SHDOMPP SHDOMPP calculates unpolarized radiative transfer in a plane-parallel medium for either collimated solar and/or thermal emission sources of radiation. The optical properties of the medium input to SHDOMPP are assumed to be uniform in each layer, which is different from

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