Retrieval of Aerosol Microphysical Properties ...
Document type :
Article dans une revue scientifique: Article original
DOI :
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Title :
Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie-Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application
Author(s) :
Chang, Yuyang [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Hu, Qiaoyun [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Goloub, Philippe [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Veselovskii, Igor [Auteur]
A. M. Prokhorov General Physics Institute [GPI]
Podvin, Thierry [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Hu, Qiaoyun [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Goloub, Philippe [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Veselovskii, Igor [Auteur]
A. M. Prokhorov General Physics Institute [GPI]
Podvin, Thierry [Auteur]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
Journal title :
Remote Sensing
Abbreviated title :
Remote Sens.
Volume number :
14
Pages :
-
Publication date :
2023-01-15
ISSN :
2072-4292
English keyword(s) :
maximum likelihood estimation
retrieval of height-resolved aerosol microphysical properties
analysis of lidar measurements
retrieval of height-resolved aerosol microphysical properties
analysis of lidar measurements
HAL domain(s) :
Planète et Univers [physics]/Océan, Atmosphère
English abstract : [en]
Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative ...
Show more >Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (Vt), effective radius (Reff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.Show less >
Show more >Lidar plays an essential role in monitoring the vertical variation of atmospheric aerosols. However, due to the limited information that lidar measurements provide, ill-posedness still remains a big challenge in quantitative lidar remote sensing. In this study, we describe the Basic algOrithm for REtrieval of Aerosol with Lidar (BOREAL), which is based on maximum likelihood estimation (MLE), and retrieve aerosol microphysical properties from extinction and backscattering measurements of multi-wavelength Mie–Raman lidar systems. The algorithm utilizes different types of a priori constraints to better constrain the solution space and suppress the influence of the ill-posedness. Sensitivity test demonstrates that BOREAL could retrieve particle volume size distribution (VSD), total volume concentration (Vt), effective radius (Reff), and complex refractive index (CRI = n − ik) of simulated aerosol models with satisfying accuracy. The application of the algorithm to real aerosol events measured by LIlle Lidar AtmosphereS (LILAS) shows it is able to realize fast and reliable retrievals of different aerosol scenarios (dust, aged-transported smoke, and urban aerosols) with almost uniform and simple pre-settings. Furthermore, the algorithmic principle allows BOREAL to incorporate measurements with different and non-linearly related errors to the retrieved parameters, which makes it a flexible and generalized algorithm for lidar retrieval.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CNRS
CNRS
Collections :
Submission date :
2024-01-16T22:54:08Z
2024-02-16T10:32:56Z
2024-02-16T10:32:56Z
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