GOES Aerosol/Smoke Product (GASP) over North America: Comparisons to AERONET and MODIS observations-Reference-Cited by-同舟云学术

GOES Aerosol/Smoke Product (GASP) over North America: Comparisons to AERONET and MODIS observations

Published:2007-08-02 Issue:D15 Volume:112 Page:
ISSN:0148-0227
Container-title:Journal of Geophysical Research
language:en
Short-container-title:J. Geophys. Res.

Author:

Prados Ana I.,Kondragunta Shobha,Ciren Pubu,Knapp Kenneth R.

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Earth-Surface Processes,Geochemistry and Petrology,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry,Oceanography,Geophysics

Reference20 articles.

1. Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS);Chu;J. Geophys. Res.,2003

2. Retrieval of aerosol optical thickness from Geostationary Satellite (GOES): Assessment and improvement;Ciren;Eos Trans. AGU,2006

3. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols;Eck;J. Geophys. Res.,1999

4. Using MODIS to estimate cloud contamination of the AVHRR data record;Heidinger;J. Atmos. Oceanic Technol.,2001

5. Global distribution of UV-absorbing aerosols from Nimbus-7/TOMS data;Herman;J. Geophys. Res.,1997

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