Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9377
DC FieldValueLanguage
dc.contributor.authorPark, Nowook-
dc.contributor.authorHong, Sungwook-
dc.contributor.authorKyriakidis, Phaedon-
dc.contributor.authorLee, Woojoo-
dc.contributor.authorLyu, Sangjin-
dc.contributor.otherΚυριακίδης, Φαίδων-
dc.date.accessioned2017-02-01T15:32:45Z-
dc.date.available2017-02-01T15:32:45Z-
dc.date.issued2016-08-17-
dc.identifier.citationInternational Journal of Remote Sensing, 2016, vol. 37, no. 16, pp. 3858-3869en_US
dc.identifier.issn01431161-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/9377-
dc.description.abstractThis article presents a geostatistical approach for downscaling precipitation products from passive microwave satellites with geostationary Meteorological Satellite observations. More precisely, the Advanced Microwave Scanning Radiometer 2 (AMSR2) precipitation (daily level 3 product) with 0.25° spatial resolution and the Communication, Ocean and Meteorological Satellite (COMS) infrared (IR) data with 5 km spatial resolution were used for the downscaling experiment over the Korean peninsula. Brightness temperature data observed at COMS IR 1 and water vapour channels were incorporated for downscaling via area-to-point residual Kriging with non-linear regression. The evaluation results with densely sampled Automatic Weather Station data revealed that incorporating the COMS IR observations with the AMSR2 precipitation showed similar error statistics to those of the AMSR2 precipitation because of the limitations of IR observations themselves and the inherent errors of the AMSR2 precipitation product over land. However, the area-based evaluation using information entropy indicated that incorporating the COMS observations resulted in more detailed spatial variation in the final product than direct downscaling of the AMSR2 precipitation. In addition, local precipitation patterns could be captured when there were regions with missing precipitation values in the AMSR2 product. Consequently, the downscaling result is useful for understanding the local precipitation patterns with an accuracy similar to that provided by microwave satellite observations. It is also suggested that the spatial variability in the downscaling result and errors in input low-resolution data should be considered when downscaling coarse resolution data using fine resolution auxiliary variables.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Remote Sensingen_US
dc.rights©Taylor & Francisen_US
dc.subjectAdvanced Microwave Scanning Radiometer 2en_US
dc.subjectAMSR2en_US
dc.subjectCOMSen_US
dc.subjectGeostatistical approachen_US
dc.titleGeostatistical downscaling of AMSR2 precipitation with COMS infrared observationsen_US
dc.typeArticleen_US
dc.collaborationInha Universityen_US
dc.collaborationSejong Universityen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationKorea Meteorological Administrationen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsSubscriptionen_US
dc.countrySouth Koreaen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1080/01431161.2016.1204031en_US
dc.relation.issue16en_US
dc.relation.volume37en_US
cut.common.academicyear2020-2021en_US
dc.identifier.spage3858en_US
dc.identifier.epage3869en_US
item.openairetypearticle-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.languageiso639-1en-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-4222-8567-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.journal.journalissn1366-5901-
crisitem.journal.publisherTaylor & Francis-
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