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Does the Madden‐Julian Oscillation influence aerosol variability?
Author(s) -
Tian Baijun,
Waliser Duane E.,
Kahn Ralph A.,
Li Qinbin,
Yung Yuk L.,
Tyranowski Tomasz,
Geogdzhayev Igor V.,
Mishchenko Michael I.,
Torres Omar,
Smirnov Alexander
Publication year - 2008
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2007jd009372
Subject(s) - madden–julian oscillation , aerosol , total ozone mapping spectrometer , environmental science , advanced very high resolution radiometer , climatology , moderate resolution imaging spectroradiometer , satellite , radiometer , aeronet , atmospheric sciences , meteorology , convection , remote sensing , geology , geography , stratosphere , physics , astronomy , ozone layer
We investigate the modulation of aerosols by the Madden‐Julian Oscillation (MJO) using multiple, global satellite aerosol products: aerosol index (AI) from the Total Ozone Mapping Spectrometer (TOMS) on Nimbus‐7, and aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Advanced Very High Resolution Radiometer (AVHRR) on NOAA satellites. A composite MJO analysis indicates that large variations in the TOMS AI and MODIS/AVHRR AOT are found over the equatorial Indian and western Pacific Oceans where MJO convection is active, as well as the tropical Africa and Atlantic Ocean where MJO convection is weak but the background aerosol level is high. A strong inverse linear relationship between the TOMS AI and rainfall anomalies, but a weaker, less coherent positive correlation between the MODIS/AVHRR AOT and rainfall anomalies, were found. The MODIS/AVHRR pattern is consistent with ground‐based Aerosol Robotic Network data. These results indicate that the MJO and its associated cloudiness, rainfall, and circulation variability systematically influence the variability in remote sensing aerosol retrieval results. Several physical and retrieval algorithmic factors that may contribute to the observed aerosol‐rainfall relationships are discussed. Preliminary analysis indicates that cloud contamination in the aerosol retrievals is likely to be a major contributor to the observed relationships, although we cannot exclude possible contributions from other physical mechanisms. Future research is needed to fully understand these complex aerosol‐rainfall relationships.

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