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Yiyi Huang, Xiquan Dong, Baike Xi, Erica K. Dolinar, Ryan E. Stanfield, and Shaoyue Qiu

( Bromwich et al. 2000 , 2002 ), and overall assessments including surface temperature, radiative fluxes, wind speed, and precipitation ( Lindsay et al. 2014 ). Other studies have focused on clouds and/or radiative fluxes. For example, Walsh et al. (2009) evaluated cloud and radiation properties in four reanalyses (NCEP–NCAR reanalysis, ERA-40, NARR, and JRA-25) using surface observations from the Atmospheric Radiation Measurement (ARM) Program Northern Slope of Alaska (NSA) site at Barrow, Alaska

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F. Tornow, C. Domenech, J. N. S. Cole, N. Madenach, and J. Fischer

its inhomogeneous three-dimensional structure ( Cahalan et al. 1994 ; Barker et al. 1996 ; Hogan et al. 2019 ). This complexity, combined with the need for computationally efficient radiative transfer calculations require climate models to make simplifying assumptions (e.g., Fu and Liou 1992 ; Clough et al. 2005 ; Bender et al. 2006 ; Pincus et al. 2003 ). The benchmark to assess the realism of a climate models’ radiative response is TOA radiative fluxes ( Ramanathan 1987 ; Bony et al. 1992

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M. J. Kay, M. A. Box, Thomas Trautmann, and Jochen Landgraf

accurate ( Box et al. 1993 ). While we will present results for both (spectrally integrated) actinic flux and net flux in realistic atmospheres, our major focus will be on the actinic flux as it is the key quantity for computing radiative heating rates and photodissociation frequencies. Section 2 outlines the computational details and includes definitions of actinic and net fluxes, as well as the model parameters. The exact form of the radiative transfer equation depends on the various parameters that

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J. H. Joseph, W. J. Wiscombe, and J. A. Weinman

2452 JOURNAL OF THE ATMOSPHERIC SCIENCES VO~.UME33The Delta-Eddington Apprwrlmafion for Radiative Flux Transfer j. H. JOSEPH~ AND W. J. WISCOMBE National Center fo~ Atmospheric Research? Boulder, Colo. 80303 J. A. Wv. xs~A~Department of Meteorology, University of Wisconsin, Madison, Wis. 53706(Manuscript received 30 March 1976, in revised form 16 August 1976)ABSTRACT This

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Michael J. Foster and Dana E. Veron

transfer calculations are performed and matched to the presence of cluster members and then evaluated using observed surface fluxes. To extend the derived relationship between cloud field structure and radiative fluxes throughout the tropics, the clustering algorithm is also applied to data from the ARM CART Manus and Darwin facilities. A comparison of the observed cloud regimes to those simulated in a GCM is performed using output from the Community Climate System Model, version 3.0 (CCSM3). Using the

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Jeffrey N. Cuzzi, Thomas P. Ackerman, and Leland C. Helmle

APRIL 1982 NOTES AND CORRESPONDENCE 917NOTES AND CORRESPONDENCEThe Delta-Four-Stream Approximation for Radiative Flux Transfer JEFFREY N. CuzzI AND THOMAS P. ACKERMAN1Space Science Division, Ames Research Center,' NASA, Moffett Field, CA 94035 LELAND C. HELMLE Informatics, Inc., Palo Alto, CA (3 April 1981 and 30 November 1981)ABSTRACT - We present an approximate

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Xia Sun, Heather A. Holmes, and Hui Xiao

–atmosphere coupling in numerical weather prediction. In addition to sensible and latent heat fluxes, surface radiative fluxes are major terms in the surface energy budget. Cloud cover impacts the surface radiative fluxes and, therefore the surface energy budget, and simulating the correct cloud cover is important to model cold-air pool (CAP) formation and evolution ( Hughes et al. 2015 ). Biases in simulated radiative fluxes can lead to modeling deficiencies in surface heating and surface melting when snow is

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Martin Wild, Atsumu Ohmura, Hans Gilgen, and Erich Roeckner

M^Y 1995 WILD ET AL. 1309Validation of General Circulation Model Radiative Fluxes Using Surface ObservationsMARTIN WILD, ATSUMU OHMURA, HANS GILGEN Swiss Federal Institute of Technology, Zurich, Switzerland ERICH ROECKNERMax Planck Institute for Meteorology, Hamburg, Germany(Manuscript received 2 May 1994, in final form 3 October 1994) ABSTRACT

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Patrick C. Taylor

1. Introduction The diurnal cycle is a fundamental Earth system variability driven by the 24-h cycle of solar insolation. Cloud properties, surface temperature, precipitation, and surface and top-of-the-atmosphere (TOA) radiative fluxes exhibit robust diurnal cycles (e.g., Gray and Jacobson 1977 ; Minnis and Harrison 1984 ; Hartmann and Recker 1986 ; Harrison et al. 1988 ; Yang and Slingo 2001 ; Taylor 2012 ). The existence of the diurnal cycle influences the climate system by modifying

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Xiaolei Niu and Rachel T. Pinker

the changes in ozone, cloudiness, and surface albedo were dealt with in Bernhard et al. (2007) . In a comprehensive investigation by Dong et al. (2010) using 10 yr of cloud and radiative flux observations collected by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program at the North Slope of Alaska (NSA), it is reported that the longwave cloud-radiative forcing (CRF) has a high positive correlations (0.8–0.9) with cloud fraction, liquid water path, and radiating

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