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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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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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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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L. A. Remer, Y. J. Kaufman, D. Tanré, S. Mattoo, D. A. Chu, J. V. Martins, R.-R. Li, C. Ichoku, R. C. Levy, R. G. Kleidman, T. F. Eck, E. Vermote, and B. N. Holben

diversity, MODIS has the unique ability to retrieve aerosol optical thickness with greater accuracy and to retrieve parameters characterizing aerosol size ( Tanré et al. 1996 ; Tanré et al. 1997 ). The results section of this paper shows that MODIS’s ability to separate aerosols by size can be used as a proxy for separating human-generated aerosol from natural sources, which aids substantially in estimating global human-induced aerosol forcing ( Kaufman et al. 2002 ). The first MODIS instrument was

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Gottfried Hänel and Kurt Bullrich

particle numbers per cma at theearth's surface and at specific heights. Also compiledare the total optical thickness rD of the aerosol particles within the atmosphere, the percentage fractionsof rD coming from the different main layers, i.e.,lO0(rm/ro), lO0(r~m/r~) and lO0(rmn/rn), as wellas the percentage fraction of r~ coming from thelowest kilometer of the atmosphere, i.e.,to, for the standard case. For the inversion case, thepercentage fraction of r~ coming from the singlesublayer with the number K

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M. Griggs

APmL1979 M. GRIGGS 695Satellite Observations of Atmospheric Aerosols During the EOMET Cruise M. GRIGGS Science Applications, Inc., La Jolla, California 92038(Manuscript received 29 September 1978, in final form 18 December 1978) ABSTRACT Measurements of the atmospheric aerosol optical thickness were made during the 1977

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K. M. Markowicz, P. J. Flatau, J. Remiszewska, M. Witek, E. A. Reid, J. S. Reid, A. Bucholtz, and B. Holben

columnar aerosol optical properties and aerosol size distribution. The annual cycle mostly is due to seasonal dust production and, therefore, aerosol optical thickness (AOT) is negatively correlated with the Ångström exponent. The maximum of AOT is observed during the summer and reaches 0.45 at 500 nm. Based on the Meteorological Satellite (Meteosat), observations in both the UV–visible and the infrared spectrum ( Deepshikha et al. 2005 ) derive the dust-absorbing efficiency over the north Indian Ocean

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Alexander Smirnov, Brent N. Holben, Yoram J. Kaufman, Oleg Dubovik, Thomas F. Eck, Ilya Slutsker, Christophe Pietras, and Rangasayi N. Halthore

Aerosol Robotic Network (AERONET) in five island locations in the Pacific and Atlantic Oceans. The AERONET solar attenuation and sky brightness measurements are used to derive the spectral optical thickness and size distribution of the column ambient aerosol. In contrast to in situ measurements, AERONET remote measurements do not characterize the aerosol chemical composition, but measure the optical properties of the aerosol, unaffected by sampling and drying processes inherent in in situ methods. The

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Akiko Higurashi and Teruyuki Nakajima

characteristics, such as the total content, composition, etc., on a global scale. A use of satellites is very effective to study aerosol optical properties on a large scale. So far, most of the aerosol remote sensing studies have been made using National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) channel 1 and/or 2. Stowe et al. (1992) produced global maps of the aerosol optical thickness at wavelength of 0.5 μ m over ocean area using channel-1 radiances

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