Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/100763
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorChen, Ben_US
dc.creatorLiu, Zen_US
dc.creatorWong, WKen_US
dc.creatorWoo, WCen_US
dc.date.accessioned2023-08-11T03:13:17Z-
dc.date.available2023-08-11T03:13:17Z-
dc.identifier.issn0739-0572en_US
dc.identifier.urihttp://hdl.handle.net/10397/100763-
dc.language.isoenen_US
dc.publisherAmerican Meteorological Societyen_US
dc.rights© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).en_US
dc.titleDetecting water vapor variability during heavy precipitation events in Hong Kong using the GPS tomographic techniqueen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1001en_US
dc.identifier.epage1019en_US
dc.identifier.volume34en_US
dc.identifier.issue5en_US
dc.identifier.doi10.1175/JTECH-D-16-0115.1en_US
dcterms.abstractWater vapor has a strong influence on the evolution of heavy precipitation events due to the huge latent heat associated with the phase change process of water. Accurate monitoring of atmospheric water vapor distribution is thus essential in predicting the severity and life cycle of heavy rain. This paper presents a systematic study on the application of tomographic solutions to investigate water vapor variations during heavy precipitation events. Using global positioning system (GPS) observations, the wet refractivity field was constructed at a temporal resolution of 30 min for three heavy precipitation events occurring in Hong Kong, China, in 2010-14. The zenith wet delay (ZWD) is shown to be a good indicator in observing the water vapor evolution in heavy rain events. The variabilities of water vapor at five altitude layers (< 1000, 1000-2000, 2000-3000, 3000-5000, and > 5000 m) were examined. It revealed that water vapor above 3000 m has larger fluctuation than that under 3000 m, though it accounts for only 10%-25% of the total amount of water vapor. The relative humidity fields derived from tomographic results revealed moisture variation, accumulation, saturation, and condensation during the heavy rain events. The water vapor variabilities observed by tomography have been validated using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and radiosonde data. The results positively demonstrated the potential of using water vapor tomographic technique for detecting and monitoring the evolution of heavy rain events.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of atmospheric and oceanic technology, May 2017, v. 34, no. 5, p. 1001-1019en_US
dcterms.isPartOfJournal of atmospheric and oceanic technologyen_US
dcterms.issued2017-05-
dc.identifier.scopus2-s2.0-85019603015-
dc.identifier.eissn1520-0426en_US
dc.description.validate202305 bckw-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberLSGI-0375-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6747227-
dc.description.oaCategoryVoR alloweden_US
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