The DOI matches its Crossref record.
Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust
Open accessAbstract
The possibility of using shape mixtures of randomly oriented spheroids for modeling desert dust aerosol light scattering is discussed. For reducing calculation time, look‐up tables were simulated for quadrature coefficients employed in the numerical integration of spheroid optical properties over size and shape. The calculations were done for 25 bins of the spheroid axis ratio ranging from ∼0.3 (flattened spheroids) to ∼3.0 (elongated spheroids) and for 41 narrow size bins covering the size parameter range from ∼0.012 to ∼625. The look‐up tables were arranged into a software package, which allows fast, accurate, and flexible modeling of scattering by randomly oriented spheroids with different size and shape distributions. In order to evaluate spheroid model and explore the possibility of aerosol shape identification, the software tool has been integrated into inversion algorithms for retrieving detailed aerosol properties from laboratory or remote sensing polarimetric measurements of light scattering. The application of this retrieval technique to laboratory measurements by Volten et al. (2001) has shown that spheroids can closely reproduce mineral dust light scattering matrices. The spheroid model was utilized for retrievals of aerosol properties from atmospheric radiation measured by AERONET ground‐based Sun/sky‐radiometers. It is shown that mixtures of spheroids allow rather accurate fitting of measured spectral and angular dependencies of observed intensity and polarization. Moreover, it is shown that for aerosol mixtures with a significant fraction of coarse‐mode particles (radii ≥ ∼1 μm), the nonsphericity of aerosol particles can be detected as part of AERONET retrievals. The retrieval results indicate that nonspherical particles with aspect ratios ∼1.5 and higher dominate in desert dust plumes, while in the case of background maritime aerosol spherical particles are dominant. Finally, the potential of using AERONET derived spheroid mixtures for modeling the effects of aerosol particle nonsphericity in other remote sensing techniques is discussed. For example, the variability of lidar measurements (extinction to backscattering ratio and signal depolarization ratio) is illustrated and analyzed. Also, some potentially important differences in the sensitivity of angular light scattering to parameters of nonspherical versus spherical aerosols are revealed and discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Sensor Capability and Atmospheric Correction in Ocean Colour Remote Sensing
Emberton, S., Chittka, L., Cavallaro, A., & Wang, M. (2015) · Remote Sensing · doi:10.3390/rs8010001 · Cited by 486
Chin, M., Diehl, T., Tan, Q., Prospero, J. M., Kahn, R. A., Remer, L. A., Yu, H., Sayer, A. M., Bian, H., Geogdzhayev, I. V., et al. (2014) · Atmospheric Chemistry and Physics · doi:10.5194/acp-14-3657-2014 · Cited by 311
Self-citationRosenberg, P. D., Dean, A. R., Williams, P. I., Dorsey, J. R., Minikin, A., Pickering, M. A., & Petzold, A. (2012) · Atmospheric Measurement Techniques · doi:10.5194/amt-5-1147-2012 · Cited by 154
A review of advances in the retrieval of aerosol properties by remote sensing multi-angle technology
Si, Y., Lu, Q., Zhang, X., Hu, X., Wang, F., Li, L., & Gu, S. (2021) · Atmospheric Environment · doi:10.1016/j.atmosenv.2020.117928 · Cited by 44
Simulating the Regional Impact of Dust on the Middle East Climate and the Red Sea
Osipov, S., & Stenchikov, G. (2018) · Journal of Geophysical Research: Oceans · doi:10.1002/2017jc013335 · Cited by 27
Metadata
- Authors
- Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J., Sorokin, M., & Slutsker, I.
- Venue
- Journal of Geophysical Research: Atmospheres
- Publisher
- American Geophysical Union (AGU)
- Published
- 2006-06-15
- Volume
- 111
- Issue
- D11
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W1990646419
- Cited by
- 1,615
- References
- 0
- FWCI
- 37.12
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. https://app.cochat.ai/papers/10.1029/2005jd006619
- The paper
- Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J., Sorokin, M., & Slutsker, I. (2006). Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2005jd006619
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.