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Article: Deconvolution filtering of ground-based LIDAR returns from tropospheric aerosols

TitleDeconvolution filtering of ground-based LIDAR returns from tropospheric aerosols
Authors
KeywordsAtmospheric aerosols
Computer simulation
Monte carlo methods
Photons
Troposphere
Issue Date2003
PublisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00340/index.htm
Citation
Applied Physics B: Lasers And Optics, 2003, v. 76 n. 5, p. 587-592 How to Cite?
AbstractA deconvolution filtering model of multiple scattering in ground-based single field of view (SFOV) LIDAR returns is described. It is based on time series deconvolution techniques. The contribution of multiply scattered photons in SFOV LIDAR returns can be numerically modeled by processing LIDAR signals without additional information about aerosol properties and measurement geometry. Deconvolution results are in good agreement with those performed by Monte Carlo calculations, showing that the significance of multiply scattered photons is strongly correlated with aerosol concentration. It is found that, for ground-based LIDAR, the contribution of multiply scattered photons to LIDAR signals is typically below 5% in a clear urban atmosphere, and up to 14% in a very dirty urban atmosphere in Hong Kong during winter seasons.
Persistent Identifierhttp://hdl.handle.net/10722/86200
ISSN
2023 Impact Factor: 2.0
2023 SCImago Journal Rankings: 0.264
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorGao, JLen_HK
dc.contributor.authorNg, CNen_HK
dc.date.accessioned2010-09-06T09:14:02Z-
dc.date.available2010-09-06T09:14:02Z-
dc.date.issued2003en_HK
dc.identifier.citationApplied Physics B: Lasers And Optics, 2003, v. 76 n. 5, p. 587-592en_HK
dc.identifier.issn0946-2171en_HK
dc.identifier.urihttp://hdl.handle.net/10722/86200-
dc.description.abstractA deconvolution filtering model of multiple scattering in ground-based single field of view (SFOV) LIDAR returns is described. It is based on time series deconvolution techniques. The contribution of multiply scattered photons in SFOV LIDAR returns can be numerically modeled by processing LIDAR signals without additional information about aerosol properties and measurement geometry. Deconvolution results are in good agreement with those performed by Monte Carlo calculations, showing that the significance of multiply scattered photons is strongly correlated with aerosol concentration. It is found that, for ground-based LIDAR, the contribution of multiply scattered photons to LIDAR signals is typically below 5% in a clear urban atmosphere, and up to 14% in a very dirty urban atmosphere in Hong Kong during winter seasons.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/00340/index.htmen_HK
dc.relation.ispartofApplied Physics B: Lasers and Opticsen_HK
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectAtmospheric aerosols-
dc.subjectComputer simulation-
dc.subjectMonte carlo methods-
dc.subjectPhotons-
dc.subjectTroposphere-
dc.titleDeconvolution filtering of ground-based LIDAR returns from tropospheric aerosolsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0946-2171&volume=76&issue=5&spage=587&epage=592&date=2003&atitle=Deconvolution+filtering+of+ground-based+LIDAR+returns+from+tropospheric+aerosolsen_HK
dc.identifier.emailNg, CN:cnng@hkucc.hku.hken_HK
dc.identifier.authorityNg, CN=rp00606en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s00340-003-1131-9-
dc.identifier.scopuseid_2-s2.0-0038007565en_HK
dc.identifier.hkuros92566en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0038007565&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume76en_HK
dc.identifier.issue5en_HK
dc.identifier.spage587en_HK
dc.identifier.epage592en_HK
dc.identifier.isiWOS:000183531900015-
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridGao, JL=7404476115en_HK
dc.identifier.scopusauthoridNg, CN=7401705590en_HK
dc.identifier.citeulike6725103-
dc.identifier.issnl0946-2171-

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