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Regularized inversion of microphysical atmospheric particle parameters - theory and application

  • Retrieving the distribution of aerosols in the atmosphere via remote sensing techniques is a highly complex task that requires dealing with a wide range of different problems stemming both from Physics and Mathematics. We focus on retrieving this distribution from multi-wavelength lidar data for aerosol ensembles consisting of spherical particles via an iterative regularization technique. The optical efficiencies for spherical scatterers are examined to account for the behavior of the underlying integral equation. The ill-posedness of the problem and the conditioning of the discretized problem are analyzed. Some critical points in the model, like the assumed wavelength-independence of the refractive index and the fixed grid of investigated refractive indices, are studied with regard to their expected impact on the regularized solution. A new Monte-Carlo type method is proposed for retrieval of the refractive index. To validate the results, the developed algorithm is applied to two measurement cases of burning biomass gained fromRetrieving the distribution of aerosols in the atmosphere via remote sensing techniques is a highly complex task that requires dealing with a wide range of different problems stemming both from Physics and Mathematics. We focus on retrieving this distribution from multi-wavelength lidar data for aerosol ensembles consisting of spherical particles via an iterative regularization technique. The optical efficiencies for spherical scatterers are examined to account for the behavior of the underlying integral equation. The ill-posedness of the problem and the conditioning of the discretized problem are analyzed. Some critical points in the model, like the assumed wavelength-independence of the refractive index and the fixed grid of investigated refractive indices, are studied with regard to their expected impact on the regularized solution. A new Monte-Carlo type method is proposed for retrieval of the refractive index. To validate the results, the developed algorithm is applied to two measurement cases of burning biomass gained from multi-wavelength Raman lidar.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Lukas Osterloh, Christine BöckmannORCiDGND, Doina Nicolae, Anca Nemuc
DOI:https://doi.org/10.1016/j.jcp.2012.11.040
ISSN:0021-9991
Titel des übergeordneten Werks (Englisch):Journal of computational physics
Verlag:Elsevier
Verlagsort:San Diego
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2013
Erscheinungsjahr:2013
Datum der Freischaltung:26.03.2017
Freies Schlagwort / Tag:Inverse ill-posed problem; Lidar remote sensing; Microphysical particle properties; Regularization
Band:237
Ausgabe:11
Seitenanzahl:16
Erste Seite:79
Letzte Seite:94
Fördernde Institution:European Union seventh framework program through ITARS project [289923]
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
Peer Review:Referiert
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