Titre :

Retrieval of aerosol components directly from satellite and ground-based measurements

Auteur(s) :

Li, Lei [Auteur]
Chinese Academy of Meteorological Sciences [CAMS]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Doubovik, Oleg [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Derimian, Yevgeny [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Schuster, Gregory L. [Auteur]
NASA Langley Research Center [Hampton] [LaRC]
Lapionak, Tatsiana [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Litvinov, Pavel [Auteur]
Université de Lille
Ducos, Fabrice [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Fuertes, David [Auteur]
Université de Lille
Chen, Cheng [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Li, Zhengqiang [Auteur]
Chinese Academy of Sciences [Beijing] [CAS]
Lopatin, Anton [Auteur]
Université de Lille
Torres, Benjamin [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Che, Huizheng [Auteur]
Chinese Academy of Meteorological Sciences [CAMS]

Titre de la revue :

Atmospheric Chemistry and Physics

Nom court de la revue :

Atmos. Chem. Phys.

Numéro :

19

Date de publication :

2019-11-04

ISSN :

1680-7316

Discipline(s) HAL :

Physique [physics]

Résumé en anglais : [en]

This study presents a novel methodology for the remote monitoring of aerosol components over large spatial and temporal domains. The concept is realized within the GRASP (Generalized Retrieval of Aerosol and Surface ...
Lire la suite >This study presents a novel methodology for the remote monitoring of aerosol components over large spatial and temporal domains. The concept is realized within the GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm to directly infer aerosol components from the measured radiances. The observed aerosols are assumed to be mixtures of hydrated soluble particles embedded with black carbon, brown carbon, iron oxide, and other (non-absorbing) insoluble inclusions. The complex refractive indices of the dry components are fixed a priori (although the refractive index of the soluble host is allowed to vary with hydration), and the complex refractive indices of the mixture are computed using mixing rules. The volume fractions of these components are derived along with the size distribution and the fraction of spherical particles, as well as the spectral surface reflectance in cases when the satellite data are inverted. The retrieval is implemented as a statistically optimized fit in a continuous space of solutions. This contrasts with most conventional approaches in which the type of aerosol is either associated with a pre-assumed aerosol model that is included in a set of look-up tables, or determined from the analysis of the retrieved aerosol optical parameters (e.g., single scattering albedo, refractive index, among others, provided by the AERONET retrieval algorithm); here, we retrieve the aerosol components explicitly. The approach also bridges directly to the quantities used in global chemical transport models. We first tested the approach with synthetic data to estimate the uncertainty, and then applied it to real ground-based AERONET and spaceborne POLDER/PARASOL observations; thus, the study presents a first attempt to derive aerosol components from satellite observations specifically tied to global chemical transport model quantities. Our results indicate aerosol optical characteristics that are highly consistent with standard products (e.g., R of ∼0.9 for aerosol optical thickness) and demonstrate an ability to separate intrinsic optical properties of fine- and coarse-sized aerosols. We applied our method to POLDER/PARASOL radiances on the global scale and obtained spatial and temporal patterns of the aerosol components that agree well with existing knowledge on aerosol sources and transport features. Finally, we discuss limitations and perspectives of this new technique.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

CNRS
Université de Lille

Collections :

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

Date de dépôt :

2024-01-30T11:45:42Z
2024-02-26T14:07:20Z