Retrieval of Aerosol Microphysical Properties ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
URL permanente :
Titre :
Retrieval of Aerosol Microphysical Properties from Multi-Wavelength Mie-Raman Lidar Using Maximum Likelihood Estimation: Algorithm, Performance, and Application
Auteur(s) :
Chang, Yuyang [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Hu, Qiaoyun [Auteur]
Laboratoire d’Optique Atmosphérique - UMR 8518 [LOA]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
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 - UMR 8518 [LOA]
Laboratoire d'Optique Atmosphérique (LOA) - UMR 8518
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
Titre de la revue :
Remote Sensing
Nom court de la revue :
Remote Sens.
Numéro :
14
Pagination :
-
Date de publication :
2023-01-15
ISSN :
2072-4292
Mot(s)-clé(s) en anglais :
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
Discipline(s) HAL :
Planète et Univers [physics]/Océan, Atmosphère
Résumé en anglais : [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 ...
Lire la suite >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.Lire moins >
Lire la suite >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.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CNRS
CNRS
Collections :
Date de dépôt :
2024-01-16T22:54:08Z
2024-02-16T10:32:56Z
2024-02-16T10:32:56Z
Fichiers
- remotesensing-14-06208-v2.pdf
- Non spécifié
- Accès libre
- Accéder au document