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Journal ArticleDOI

Cloud-Screening and Quality Control Algorithms for the AERONET Database

TLDR
In this paper, the authors present a cloud-screening algorithm for ground-based sun-photometer measurements of aerosol optical depth in the Aerosol Robotic Network (AERONET).
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This article is published in Remote Sensing of Environment.The article was published on 2000-09-01. It has received 1311 citations till now. The article focuses on the topics: AERONET & Angstrom exponent.

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Citations
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Journal ArticleDOI

The MODIS Aerosol Algorithm, Products and Validation

TL;DR: In this article, the spectral optical thickness and effective radius of the aerosol over the ocean were validated by comparison with two years of Aerosol Robotic Network (AERONET) data.
Journal ArticleDOI

Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations

TL;DR: In this paper, the AERONET network of ground-based radiometers were used to remotely sense the aerosol absorption and other optical properties in several key locations, and the results showed robust differentiation in both the magnitude and spectral dependence of the absorption, a property driving aerosol climate forcing.
Journal ArticleDOI

Sources and distributions of dust aerosols simulated with the GOCART model

TL;DR: In this article, the global distribution of dust aerosol is simulated with the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model.
References
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Journal ArticleDOI

Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols

TL;DR: In this paper, the spectral variation of α is typically not considered in the analysis and comparison of values from different techniques, and the spectral measurements of τ a from 340 to 1020 nm obtained from ground-based Aerosol Robotic Network radiometers located in various locations where either biomass burning, urban, or desert dust aerosols are prevalent.
Journal ArticleDOI

Objective algorithms for the retrieval of optical depths from ground-based measurements

TL;DR: An algorithm is described that objectively selects data points from a continuous time series and performs the required regression by means of Langley regression to provide intercomparable retrievals of optical depths from widely varying historical data sets.
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