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Jinwon Kim, Yu Gu, and K. N. Liou

. 2003 ), these uncertainties are not expected to influence our study critically considering that we focus on providing qualitative information by prescribing a simple aerosol optical thickness (AOT) value. In our judgment, the OPAC database is so far the best data source for determining the single-scattering properties of spherical aerosols for broadband radiative flux calculations. The single-scattering albedo inferred from remote sensing data can be used to calibrate the existing database once

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Pavel I. Ionov and Andrew K. Mollner

) methods, with sun photometry ( Holben et al. 1998 ) being the most relied on method for calibrating space-based passive sensors ( Kahn et al. 2007 ; Kokhanovsky and de Leeuw 2009 ). Aerosol optical thickness [AOT; or aerosol optical depth (AOD)] is the value of primary interest measured by the passive instruments: It is a column integral (over altitude z ) of aerosol extinction α a that makes no distinction between the contributions from aerosol scattering and aerosol absorption. Active remote

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Mark A. Miller, Mary Jane Bartholomew, and R. Michael Reynolds

contamination of the atmospheric signal. This paper addresses uncertainty in marine FRSR measurements of aerosol optical thickness, τ λA . Subjects ranging from the impact of platform motion on measurement uncertainty through uncertainties in calibration are discussed. A lofty goal, on land as well as at sea, is to measure τ λA with an uncertainty of approximately 0.02 for solar zenith angles from 0° to 70° (3 ≥ m ≥ 1, where m is the atmospheric air mass; m ≅ sec θ e ). The basic issues that

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Y. Fouquart, B. Bonnel, M. Chaoui Roquai, R. Santer, and A. Cerf

28 $OURNAL OF CLIMATE AND APPLIED METEOROLOGY VOLUM-26Observations of Saharan Aerosols: Results of ECLATS. Field Experiment. Part h Optical Thicknesses and Aerosol Size Distributions Y. FOUQUART, B. BOhr~EL, M. CHAOUI ROQUA~ AND R. SANTERUniversitd des Sciences et Techniques de Lille, Laboratoire d'Optique Atmosphg, rique, France A. CERF*Universitd d;4bidjan, Laboratoire

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Mian Chin, Paul Ginoux, Stefan Kinne, Omar Torres, Brent N. Holben, Bryan N. Duncan, Randall V. Martin, Jennifer A. Logan, Akiko Higurashi, and Teruyuki Nakajima

aerosol compositions. Neither field measurements nor satellite observations alone would be sufficient to fully describe the aerosol distributions and its physical, chemical, and optical properties. Therefore, the use of global models becomes critical in integrating the satellite and in situ measurements. On the other hand, the model has to be evaluated by observations before we can place confidence in such a model. A common variable to link the model and measurements is the aerosol optical thickness

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A. Ben Mohamed and J-P. Frangi

DECEMBER 1986 A. BEN MOHAMED AND J.-P. FRANGI 1807Results from Ground-based Monitoring of Spectral Aerosol Optical Thickness andHorizontal Extinction: Some Specific Characteristics of Dusty Sahelian Atmospheres A. BEN MOHAMED AND J.-P~ FRANGI Universit~ de Niamey, Facult~ des Sciences, D~partement de Physique, Niamey, Niger (Manuscript received 14 December 1985, in final form 26

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Mikhail D. Alexandrov, Alexander Marshak, Brian Cairns, Andrew A. Lacis, and Barbara E. Carlson

aerosol variability in the atmospheric system as it relates to the height-resolved turbulence structure and airmass transport. This paper presents a first step in this direction, describing the aerosol optical thickness (AOT) datasets in the framework of scale-invariant (fractal) statistics. We will see that the particular structure of aerosol datasets suggests that the commonly used one-point Gaussian statistics can be complemented by two-point statistics that characterize correlations between

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Tom X-P. Zhao, Larry L. Stowe, Alexander Smirnov, David Crosby, John Sapper, and Charles R. McClain

advance our quantitative understanding of global aerosol characteristics” ( King et al. 1999 ). The second-generation National Oceanic and Atmospheric Administration (NOAA)/National Environmental Satellite Data and Information Service (NESDIS) operational aerosol optical thickness τ retrieval algorithm is used to process data from NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) ( Stowe et al. 1997 ) and the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanners (VIRS

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Gennady K. Korotaev, Sergey M. Sakerin, Aleksandr M. Ignatov, Larry L. Stowe, and E. Paul McClain

Institute, Sevastopol, Crimea, USSR LARRY L. STOWE AND E. PAUL MCCLAINNOAA /NESDIS, Satellite Research Laboratory, Washington, D.C.(Manuscript received 8 April 1992, in final form 4 January 1993) ABSTRACT This paper deals with the problem of aerosol optical thickness (~) retrieval using sun-photometer measurements. The results of the theoretical analysis and computer processing of the dataset collected during the 40thcruise of the R/V Akademik Vernadsky are presented. Accuracy

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Mikhail D. Alexandrov, Igor V. Geogdzhayev, Kostas Tsigaridis, Alexander Marshak, Robert Levy, and Brian Cairns

al. 2009 ; Huneeus et al. 2011 ). As a part of an effort to define new strategies and methodologies for the intercomparison of model and satellite data, it looks promising to include analysis of more detailed characteristics of aerosol variability and go beyond traditional comparison of aerosol optical thickness (AOT) averaged over a geographical region. In particular, structure functions (SFs) provide a uniform description of the strength and spatial scale of AOT fluctuations. The structure

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