Title :

The fundamental aerosol models over china region: a cluster analysis of the ground-based remote sensing measurements of total columnar atmosphere

Author(s) :

Li, Zhengqiang [Auteur]
Chinese Academy of Sciences [Beijing] [CAS]
Zhang, Ying [Auteur]
Chinese Academy of Sciences [Beijing] [CAS]
Xu, Hua [Auteur]
Chinese Academy of Sciences [Beijing] [CAS]
Li, Kaitao [Auteur]
Chinese Academy of Sciences [Beijing] [CAS]
Doubovik, Oleg [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Goloub, Philippe [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518

Journal title :

Geophysical Research Letters

Abbreviated title :

Geophys. Res. Lett.

Volume number :

46

Publication date :

2019-05-16

ISSN :

0094-8276

HAL domain(s) :

Physique [physics]

English abstract : [en]

Ten fundamental aerosol models in China are derived from a cluster study based on the ground-based remote sensing measurements of Sun-sky radiometer Observation NETwork. The aerosol size distribution decomposition techniques ...
Show more >Ten fundamental aerosol models in China are derived from a cluster study based on the ground-based remote sensing measurements of Sun-sky radiometer Observation NETwork. The aerosol size distribution decomposition techniques are employed to yield individual fine and coarse mode size distribution functions with independent refractive indices. The total 10,773 records containing 18 kinds of aerosol microphysical parameters are used to yield 10 typical clusters with the verification of clustering robustness. Ten clusters suggest five typical fine particle aerosol models including urban polluted, secondary polluted, combined polluted, polluted fly ash, and continental background, as well as five coarse models including summer fly ash, winter fly ash, primary dust, transported dust, and background dust over China region. The representativeness and coappearance analyses again reveal five dominative aerosol patterns on the base of fundamental models. These models can be used in the chemical model simulation, satellite remote sensing, climate, and environment analyses.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

CNRS
Université de Lille

Collections :

• Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518

Submission date :

2024-01-30T11:45:40Z
2024-02-26T12:49:00Z