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An integrated retrieval framework for multiple polarization, multiple frequency radar networks

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dc.contributor.authorHardin, Joseph C., author
dc.contributor.authorChandrasekar, V., advisor
dc.contributor.authorJayasumana, Anura P., committee member
dc.contributor.authorMielke, Paul, committee member
dc.contributor.authorCheney, Margaret, committee member
dc.date.accessioned2015-08-28T14:35:45Z
dc.date.available2017-08-14T06:30:24Z
dc.date.issued2015
dc.description.abstractRadar networks form the backbone of severe weather and remote sensing in throughout most of the world. These networks provide diverse measurements of weather phenomenon, but ultimately are measuring indirect parameters rather than detecting the physics of the situation. One of the long standing goals of weather remote sensing is to relate the measurements from the various instruments to the physics that give rise to the measurements. Weather radar networks give both a better spatial coverage than single radars, as well as providing multiple looks at the environment. Newly developed radar networks have started to incorporate multiple frequencies and multiple polarizations to take advantage of attributes of different radar frequencies. Raindrops occupy different scattering regimes based on the frequency of the radar being used. Based on this, multiple radars at different wavelengths provide unique information about the microphysical characteristics of the atmosphere. Nonetheless, very little work has been conducted on fusing multiple radar measurements at heterogeneous frequencies to improve microphysical retrievals. This work presents a forward variational algorithm for multiple radar fusion that retrieves microphysical parameters from the atmosphere. The single radar case and the multiple radar case will both be addressed. Ground instrumentation will be used for verification, and the spatial and temporal variability of precipitation microphysics will be discussed.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifier.urihttp://hdl.handle.net/10217/167246
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectinverse problems
dc.subjectweather radar
dc.subjectMicrophysical retrieval
dc.subjectdisdrometer
dc.subjectspatial variability
dc.subject.lcshRemote sensing
dc.titleAn integrated retrieval framework for multiple polarization, multiple frequency radar networks
dc.typeText
dcterms.embargo.expires2017-08-14
dcterms.embargo.terms2017-08-14
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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