Journal article
First Retrieval of Aerosol Vertical Profile With Passive Remote Sensing: Part 1. Development of Algorithm Theoretical Basis
Journal of geophysical research. Atmospheres, Vol.130(21), e2025JD044332
11/16/2025
DOI: 10.1029/2025JD044332
Appears in UI Libraries Support Open Access
Abstract
This paper presents the first part of a two‐part study to develop a new algorithm to retrieve the aerosol vertical extinction profile using the hyperspectral measurements at ultraviolet bands, O2 A‐band and B‐band, from the Tropospheric Monitoring Instrument (TROPOMI). We represent the aerosol vertical profile by the weighted sum of 3–5 most important EOFs (empirical orthogonal function, i.e., eigenvectors) from the principal component analysis (PCA) of the 15‐year record of aerosol extinction profiles from spaceborne lidar Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP). Hence, the retrieval is simplified to derive 3–5 coefficients or weights of corresponding EOFs to capture the variation of aerosol vertical profiles. A new PCA module was developed in the Unified Linearized Vector Radiative Transfer Model (UNL‐VRTM) for calculating the Jacobians of top‐of‐atmosphere (TOA) reflectance with respect to the weights of EOFs, which is used to facilitate the optimal inversion of the EOF weights. The analytical Jacobian calculations are validated against the Jacobians computed from a finite difference method. The averaging kernel analysis for directly retrieving the aerosol extinction profiles from measurements of TROPOMI and high‐resolution metagrating spectropolarimeter for aerosol profiling was provided. Finally, the retrieval experiments with synthetic TROPOMI measurements generated by UNL‐VRTM were conducted to verify the self‐consistency and feasibility of the inversion algorithm on a theoretical basis.
Plain Language Summary
The vertical distribution of aerosols regulates the aerosol impacts on the climate, cloud formation, and surface air quality. While the remote sensing of the aerosol vertical profile from active satellite sensors suffers from the narrow swath, the passive remote sensing provides much wider spatial coverage with lower information content. This study develops a new algorithm to retrieve the aerosol vertical profile from the UV and oxygen absorption bands measured by passive satellite instruments. The major vertical variation modes of the aerosol extinction profiles are derived from the principal component analysis of 15 years of aerosol profile measurements from the spaceborne lidar Cloud‐Aerosol Lidar with Orthogonal Polarization, serving as the prior information for the retrieval. Therefore, retrieving only a few weighting coefficients of these major variation modes from the passive remote sensing is sufficient to reconstruct the aerosol vertical profile. An optimal inversion method is applied for the retrieval based on the Unified Linearized Vector Radiative Transfer Model (UNL‐VRTM). The theoretical feasibility and robustness of the retrieval algorithm are verified via the retrieval experiments with synthetic measurements of Tropospheric Monitoring Instrument generated by UNL‐VRTM.
Key Points
An algorithm is developed to first derive the aerosol vertical profile from ultraviolet (UV) and O2 absorption bands with passive remote sensing
Major eigenvectors from the principal component analysis of 15‐year aerosol profile measurements by spaceborne lidar serve as prior information
The synthetic retrieval experiments confirm the feasibility and robustness of the new retrieval algorithm on a theoretical basis
Details
- Title: Subtitle
- First Retrieval of Aerosol Vertical Profile With Passive Remote Sensing: Part 1. Development of Algorithm Theoretical Basis
- Creators
- Zhendong Lu - University of IowaJun Wang - University of IowaXi Chen - University of IowaXiaoguang Xu - University of Maryland, Baltimore CountyMeng Zhou - University of IowaDejian Fu - Jet Propulsion LaboratoryJonathan H. Jiang - Jet Propulsion Laboratory
- Resource Type
- Journal article
- Publication Details
- Journal of geophysical research. Atmospheres, Vol.130(21), e2025JD044332
- DOI
- 10.1029/2025JD044332
- ISSN
- 2169-897X
- eISSN
- 2169-8996
- Publisher
- Wiley
- Number of pages
- 17
- Grant note
- NASA Remote Sensing Theory program (80NSSC20K1747) NOAA GEO‐XO project (NA23OAR4310303) NASA Instrument Incubator Program (80NSSC25K7305) National Aeronautics and Space Administration (80NM0018D0004) NASA MAIA project (1583456) NASA TEMPO project (SV7‐87011)
- Language
- English
- Date published
- 11/16/2025
- Academic Unit
- Electrical and Computer Engineering; Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
- Record Identifier
- 9985027358702771
Metrics
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