Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15217
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorWong, MS-
dc.creatorJin, X-
dc.creatorLiu, Z-
dc.creatorNichol, JE-
dc.creatorYe, S-
dc.creatorJiang, P-
dc.creatorChan, PW-
dc.date.accessioned2015-10-13T08:28:13Z-
dc.date.available2015-10-13T08:28:13Z-
dc.identifier.urihttp://hdl.handle.net/10397/15217-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wong, M. S., Jin, X., Liu, Z., Nichol, J. E., Ye, S., Jiang, P., & Chan, P. W. (2015). Geostationary satellite observation of precipitable water vapor using an Empirical Orthogonal Function (EOF) based reconstruction technique over eastern China. Remote Sensing, 7(5), (Suppl. ), 5879-5900 is available athttps://dx.doi.org/10.3390/rs70505879en_US
dc.subjectDiurnal cycleen_US
dc.subjectEmpirical orthogonal functionen_US
dc.subjectGeostationary satelliteen_US
dc.subjectPrecipitable water vaporen_US
dc.titleGeostationary satellite observation of precipitable water vapor using an Empirical Orthogonal Function (EOF) based reconstruction technique over eastern Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage5879-
dc.identifier.epage5900-
dc.identifier.volume7-
dc.identifier.issue5-
dc.identifier.doi10.3390/rs70505879-
dcterms.abstractWater vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT) data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF) decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, May 2015, v. 7, no. 5, p. 5879-5900-
dcterms.isPartOfRemote sensing-
dcterms.issued2015-
dc.identifier.scopus2-s2.0-84930021123-
dc.identifier.eissn2072-4292-
dc.identifier.rosgroupid2014001048-
dc.description.ros2014-2015 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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