Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/2553
DC FieldValueLanguage
dc.contributor.authorAhmad, Khalil A.-
dc.contributor.authorJones, W. Linwood-
dc.contributor.authorKasparis, Takis-
dc.contributor.otherΚασπαρής, Τάκης-
dc.date.accessioned2010-02-18T07:26:40Zen
dc.date.accessioned2013-05-16T08:30:16Z-
dc.date.accessioned2015-12-02T11:35:34Z-
dc.date.available2010-02-18T07:26:40Zen
dc.date.available2013-05-16T08:30:16Z-
dc.date.available2015-12-02T11:35:34Z-
dc.date.issued2008-07-
dc.identifier.citationGeoscience and Remote Sensing Symposium (IGARSS) 2008. IEEE International. pp. IV - 295 - IV - 298en_US
dc.identifier.isbn9781424428076-
dc.identifier.issn2153-7003-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/2553-
dc.description.abstractThis paper describes the development of an oceanic rainfall retrieval algorithm that combines both the simultaneous active (radar backscatter) and passive (microwave brightness temperatures) observations from the SeaWinds scatterometer on the QuikSCAT satellite. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and the National Center for Environmental Prediction (NCEP) wind fields. The rain is retrieved on a wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. Due to its broad swath coverage, SeaWinds affords additional independent sampling of the oceanic rainfall, which may contribute to NASA's future Global Precipitation Mission. Results emphasize the powerful rain detection capabilities of the SeaWinds retrieval algorithm.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© IEEEen_US
dc.subjectRadar measurementsen_US
dc.subjectBrightness temperatureen_US
dc.subjectBackscatteren_US
dc.subjectSpaceborne radaren_US
dc.subjectRadar scatteringen_US
dc.subjectRadar imagingen_US
dc.subjectPassive radaren_US
dc.subjectMicrowave measurementsen_US
dc.subjectRainen_US
dc.subjectSea measurementsen_US
dc.titleAn Improved Oceanic Rainfall Retrieval Algorithm and Results from Seawindsen_US
dc.typeConference Papersen_US
dc.affiliationUniversity of Central Floridaen
dc.collaborationUniversity of Central Floridaen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Geoscience and Remote Sensing Symposium (IGARSS)en_US
dc.identifier.doi10.1109/IGARSS.2008.4779716en_US
dc.dept.handle123456789/54en
cut.common.academicyear2007-2008en_US
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypeconferenceObject-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-3486-538x-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
CORE Recommender
Show simple item record

Page view(s) 50

450
Last Week
0
Last month
2
checked on Dec 22, 2024

Google ScholarTM

Check

Altmetric


Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.