Retrieval of Atmospheric Microphysical Parameters Using Triple-Wavelength Lidar: Influencing Factors and Case Studies Under Clean and Lightly Polluted Urban Conditions.
Saved in:
| Title: | Retrieval of Atmospheric Microphysical Parameters Using Triple-Wavelength Lidar: Influencing Factors and Case Studies Under Clean and Lightly Polluted Urban Conditions. |
|---|---|
| Authors: | Hua, Hangbo1 (AUTHOR) hangbo.h@cjlu.edu.cn, Li, Mingxuan1 (AUTHOR), Huang, Dongliang1 (AUTHOR) |
| Source: | Remote Sensing. Jun2026, Vol. 18 Issue 12, p1981. 23p. |
| Subjects: | LIDAR, Particle size distribution, Mie scattering, Atmospheric aerosols, Refractive index, Extinction coefficients (Optics) |
| Abstract: | Highlights: What are the main findings? A retrieval framework for aerosol microphysical parameters was developed for a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar under limited-channel conditions. Complex refractive index, particle size range, and lidar ratio were identified as key factors controlling the retrieved size distribution and effective radius, while typical cases revealed clear differences between clean and lightly polluted conditions. What are the implications of the main findings? The proposed parameter-search optimization strategy improves the stability and reliability of aerosol microphysical retrievals from limited-channel ground-based lidar observations. The method provides practical support for investigating the vertical structure of urban aerosols and their responses to different weather conditions. To address the limited constraints of ground-based lidar with few channels in retrieving aerosol microphysical parameters in urban atmospheres, this study developed a method to retrieve aerosol volume size distribution and effective radius from a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar system. The method uses 3β + 2α optical quantities as input constraints, applies Mie scattering theory as the forward model, parameterizes the volume size distribution with B-spline functions, and achieves stable solutions through Tikhonov regularization and cross-validation. To reduce uncertainties in prior parameters, including the complex refractive index, particle size range, and lidar ratio, an optimization strategy based on parameter search, retrieval reconstruction, and error minimization was introduced. Numerical simulations showed that the method reproduced the main features of a bimodal lognormal aerosol volume size distribution with good feasibility and stability. Two case studies further showed fine-mode dominance and decreasing extinction coefficient, depolarization ratio, and effective radius with height under good air quality conditions, but enhanced coarse-mode contribution and effective radius in the upper cloud-influenced layer under lightly polluted conditions, as inferred from the combined variations in RSCS, extinction coefficient, depolarization ratio, and effective radius. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Highlights: What are the main findings? A retrieval framework for aerosol microphysical parameters was developed for a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar under limited-channel conditions. Complex refractive index, particle size range, and lidar ratio were identified as key factors controlling the retrieved size distribution and effective radius, while typical cases revealed clear differences between clean and lightly polluted conditions. What are the implications of the main findings? The proposed parameter-search optimization strategy improves the stability and reliability of aerosol microphysical retrievals from limited-channel ground-based lidar observations. The method provides practical support for investigating the vertical structure of urban aerosols and their responses to different weather conditions. To address the limited constraints of ground-based lidar with few channels in retrieving aerosol microphysical parameters in urban atmospheres, this study developed a method to retrieve aerosol volume size distribution and effective radius from a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar system. The method uses 3β + 2α optical quantities as input constraints, applies Mie scattering theory as the forward model, parameterizes the volume size distribution with B-spline functions, and achieves stable solutions through Tikhonov regularization and cross-validation. To reduce uncertainties in prior parameters, including the complex refractive index, particle size range, and lidar ratio, an optimization strategy based on parameter search, retrieval reconstruction, and error minimization was introduced. Numerical simulations showed that the method reproduced the main features of a bimodal lognormal aerosol volume size distribution with good feasibility and stability. Two case studies further showed fine-mode dominance and decreasing extinction coefficient, depolarization ratio, and effective radius with height under good air quality conditions, but enhanced coarse-mode contribution and effective radius in the upper cloud-influenced layer under lightly polluted conditions, as inferred from the combined variations in RSCS, extinction coefficient, depolarization ratio, and effective radius. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 20724292 |
| DOI: | 10.3390/rs18121981 |
