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K. Franklin Evans

1. Introduction Variational assimilation of visible and infrared radiances by numerical models in cloudy skies requires forward and adjoint radiative transfer models capable of handling scattering. When cloud properties are the target of the assimilation, visible and near-infrared satellite radiances should be considered because reflected solar radiation provides important information about cloud water path and particle size (e.g., Twomey and Cocks 1982 ). Due to heavy computational costs and

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Frédérick Chosson, Jean-Louis Brenguier, and Lothar Schüller

particles. Hence, Twomey (1977) hypothesized that, in liquid water clouds, an anthropogenic increase of the number concentration of cloud condensation nuclei (CCN) would result in an increase of the cloud droplet number concentration (CDNC) and, at constant LWP, in an increase of the cloud albedo. This process is referred to as the first aerosol indirect effect (AIE). In GCMs, cloud radiative transfer simulations are currently performed by assuming that the cloud is a horizontally uniform layer, with

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Quanhua Liu and Fuzhong Weng

1. Introduction The radiative transfer community requires multifunctional, rapid, and accurate radiance and radiance gradient models for satellite data assimilation, sensor design and specification, calibration, and validation of remote sensing data, research, and education. To achieve these goals, the Joint Center for Satellite Data Assimilation (JCSDA) in the United States has developed a framework for a Community Radiative Transfer (RT) Model (CRTM). The framework is prepared based on the

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Robin J. Hogan and Jonathan K. P. Shonk

models is transport of radiation through cloud sides. In current climate models, radiation is allowed to enter or leave a cloud in a model level only through its base or top. Full 3D radiative transfer calculations have demonstrated that this can lead to substantial errors in cloud radiative forcing, particularly for cumulus clouds (e.g., Pincus et al. 2005 ), deep convection ( DiGiuseppe and Tompkins 2003 ), aircraft contrails ( Gounou and Hogan 2007 ), and cirrus uncinus ( Zhong et al. 2008 ). The

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Richard Essery, Peter Bunting, Aled Rowlands, Nick Rutter, Janet Hardy, Rae Melloh, Tim Link, Danny Marks, and John Pomeroy

remote sensing algorithms, therefore, often include simple representations of radiative transfer in canopies. Variants of Beer’s law or two-stream approximations are generally used (e.g., Sellers et al. 1986 ; Verseghy et al. 1993 ); these treat canopies as horizontally homogeneous turbid media and only predict the average radiation. The radiative environment beneath real canopies, however, is highly heterogeneous because of sun flecks, canopy gaps, and clearings on wide ranges of length scales

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Wei-Liang Lee and K. N. Liou

1. Introduction Energy transfer across the sea surface is crucial to the understanding of the general circulation of the ocean. Shortwave radiation from the sun contributes most of the heat fluxes that penetrate the air–sea interface and are subsequently absorbed throughout the ocean mixed layer. Solar radiative transfer differs from other air–sea interaction processes such as wind stress, evaporation, precipitation, and sensible cooling that occur only at the sea surface. Ohlmann et al. (1996

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Andrew K. Heidinger, Christopher O’Dell, Ralf Bennartz, and Thomas Greenwald

1. Introduction Difficulties in the accurate and rapid simulation of radiation that is multiply scattered have limited the use of satellite infrared and microwave observations in cloudy regions for data assimilation in numerical weather prediction (NWP) schemes. This paper presents a technique that allows for computationally efficient modeling of azimuthally symmetric radiative transfer in moderately scattering atmospheres. Azimuthally symmetric radiation refers to radiation that has no

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Feng Zhang, Jia-Ren Yan, Jiangnan Li, Kun Wu, Hironobu Iwabuchi, and Yi-Ning Shi

1. Introduction Radiative transfer (RT) is a key issue in climate modeling and remote sensing. In most numerical radiative transfer algorithms, the atmosphere is divided into many homogeneous layers. The inherent optical properties (IOPs) are then fixed within each layer, and variations of IOPs inside each layer are ignored, effectively regarding each layer as internally homogeneous. The standard RT solutions are based on this assumption of internal homogeneity ( Lenoble 1985 ; Toon et al

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Guanglin Tang, Ping Yang, George W. Kattawar, Xianglei Huang, Eli J. Mlawer, Bryan A. Baum, and Michael D. King

1. Introduction It is commonly assumed that cloud longwave scattering is unimportant for estimating the atmospheric energy budget and thus is neglected in general circulation model (GCM) irradiance simulations and in radiative transfer simulations for deriving the radiation budgets from retrieved cloud optical properties. A number of studies indicate a range of overestimates of top-of-the-atmosphere (TOA) longwave irradiance resulting from neglecting longwave scattering. For example, Stephens

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Fred G. Rose, David A. Rutan, Thomas Charlock, G. Louis Smith, and Seiji Kato

clouds and radiative swath (CRS) ( Charlock et al. 1997 , 2006 ), contains modeled irradiances computed by a two-stream radiative transfer model for nearly all CERES footprints. Because estimated global surface irradiance often relies on satellite observations, computations test the accuracy of modeled irradiance by such a radiative transfer model ( Wielicki et al. 1995 ). The CERES project derives TOA irradiances from observed radiances using angular distribution models ( Loeb et al. 2005

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