{"id":{"repo_id":"colostate","oai_identifier":"oai:mountainscholar.org:10217/167066"},"canonical_url":"https://search.dev.ndltd.org/etd/colostate/oai:mountainscholar.org:10217/167066","repository":{"repo_id":"colostate","name":"Colorado State University","base_url":"https://api.mountainscholar.org/server/oai/request"},"display":{"title":"Radar multi-sensor (RAMS) quantitative precipitation estimation (QPE)","abstract":"Quantitative precipitation estimation (QPE) continues to be one of the principal objectives for weather researchers and forecasters. The ability of radar to measure over broad spatial areas in short temporal successions encourages its application in the pursuit of accurate rainfall estimation, where radar reflectivity-rainfall (Z-R) relations have been traditionally used to derive quantitative precipitation estimation. The purpose of this research is to present the development of a regional dual polarization QPE process known as the RAdar Multi-Sensor QPE (RAMS QPE). This scheme applies the dual polarization radar rain rate estimation algorithms developed at Colorado State University into an adaptable QPE system. The methodologies used to combine individual radar scans, and then merge them into a mosaic are described. The implementation and evaluation is performed over a domain that occurs over a complex terrain environment, such that local radar coverage is compromised by blockage. This area of interest is concentrated around the Pigeon River Basin near Asheville, NC. In this mountainous locale, beam blockage, beam overshooting, orographic enhancement, and the unique climactic conditions complicate the development of reliable QPE's from radar. The QPE precipitation fields evaluated in this analysis will stem from the dual polarization radar data obtained from the local NWS WSR-88DP radars as well as the NASA NPOL research radar.","abstract_html":"Quantitative precipitation estimation (QPE) continues to be one of the principal objectives for weather researchers and forecasters. The ability of radar to measure over broad spatial areas in short temporal successions encourages its application in the pursuit of accurate rainfall estimation, where radar reflectivity-rainfall (Z-R) relations have been traditionally used to derive quantitative precipitation estimation. The purpose of this research is to present the development of a regional dual polarization QPE process known as the RAdar Multi-Sensor QPE (RAMS QPE). This scheme applies the dual polarization radar rain rate estimation algorithms developed at Colorado State University into an adaptable QPE system. The methodologies used to combine individual radar scans, and then merge them into a mosaic are described. The implementation and evaluation is performed over a domain that occurs over a complex terrain environment, such that local radar coverage is compromised by blockage. This area of interest is concentrated around the Pigeon River Basin near Asheville, NC. In this mountainous locale, beam blockage, beam overshooting, orographic enhancement, and the unique climactic conditions complicate the development of reliable QPE's from radar. The QPE precipitation fields evaluated in this analysis will stem from the dual polarization radar data obtained from the local NWS WSR-88DP radars as well as the NASA NPOL research radar.","abstract_has_math":false,"creators":["Willie, Delbert Darrell, author","Chandrasekar, V., advisor","Mielke, Paul, committee member","Jayasumana, Anura P., committee member","Notaros, Branislav, committee member"],"institution":"Colorado State University. Libraries","degree_name":"Doctor of Philosophy (Ph.D.)","degree_level":"Doctoral","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-27T19:12:57Z","subjects":["QPE","X-band","rainfall","dual polarization"],"languages":["eng","English"],"rights":["Copyright 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."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://doi.org/10.25675/3.018362"],"render_values":[{"text":"https://doi.org/10.25675/3.018362","href":"https://doi.org/10.25675/3.018362","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10217/167066","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Willie, Delbert Darrell, author","Chandrasekar, V., advisor","Mielke, Paul, committee member","Jayasumana, Anura P., committee member","Notaros, Branislav, committee member"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-08-28T14:34:59Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-08-14T06:30:24Z"]},{"key":"dc:date.issued","label":"Date","values":["2015"]},{"key":"dc:publisher","label":"Institution","values":["Colorado State University. Libraries"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (Ph.D.)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Colorado State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["QPE","X-band","rainfall","dual polarization"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 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."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10217/167066","https://doi.org/10.25675/3.018362"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Quantitative precipitation estimation (QPE) continues to be one of the principal objectives for weather researchers and forecasters. The ability of radar to measure over broad spatial areas in short temporal successions encourages its application in the pursuit of accurate rainfall estimation, where radar reflectivity-rainfall (Z-R) relations have been traditionally used to derive quantitative precipitation estimation. The purpose of this research is to present the development of a regional dual polarization QPE process known as the RAdar Multi-Sensor QPE (RAMS QPE). This scheme applies the dual polarization radar rain rate estimation algorithms developed at Colorado State University into an adaptable QPE system. The methodologies used to combine individual radar scans, and then merge them into a mosaic are described. The implementation and evaluation is performed over a domain that occurs over a complex terrain environment, such that local radar coverage is compromised by blockage. This area of interest is concentrated around the Pigeon River Basin near Asheville, NC. In this mountainous locale, beam blockage, beam overshooting, orographic enhancement, and the unique climactic conditions complicate the development of reliable QPE's from radar. The QPE precipitation fields evaluated in this analysis will stem from the dual polarization radar data obtained from the local NWS WSR-88DP radars as well as the NASA NPOL research radar."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["born digital","doctoral dissertations"]},{"key":"dc:title","label":"Title","values":["Radar multi-sensor (RAMS) quantitative precipitation estimation (QPE)"]}]}],"canonical_facts":{"dc:creator":["Willie, Delbert Darrell, author","Chandrasekar, V., advisor","Mielke, Paul, committee member","Jayasumana, Anura P., committee member","Notaros, Branislav, committee member"],"dc:date.accessioned":["2015-08-28T14:34:59Z"],"dc:date.available":["2017-08-14T06:30:24Z"],"dc:date.issued":["2015"],"dc:description.abstract":["Quantitative precipitation estimation (QPE) continues to be one of the principal objectives for weather researchers and forecasters. The ability of radar to measure over broad spatial areas in short temporal successions encourages its application in the pursuit of accurate rainfall estimation, where radar reflectivity-rainfall (Z-R) relations have been traditionally used to derive quantitative precipitation estimation. The purpose of this research is to present the development of a regional dual polarization QPE process known as the RAdar Multi-Sensor QPE (RAMS QPE). This scheme applies the dual polarization radar rain rate estimation algorithms developed at Colorado State University into an adaptable QPE system. The methodologies used to combine individual radar scans, and then merge them into a mosaic are described. The implementation and evaluation is performed over a domain that occurs over a complex terrain environment, such that local radar coverage is compromised by blockage. This area of interest is concentrated around the Pigeon River Basin near Asheville, NC. In this mountainous locale, beam blockage, beam overshooting, orographic enhancement, and the unique climactic conditions complicate the development of reliable QPE's from radar. The QPE precipitation fields evaluated in this analysis will stem from the dual polarization radar data obtained from the local NWS WSR-88DP radars as well as the NASA NPOL research radar."],"dc:format.medium":["born digital","doctoral dissertations"],"dc:identifier.uri":["http://hdl.handle.net/10217/167066","https://doi.org/10.25675/3.018362"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["Colorado State University. Libraries"],"dc:rights":["Copyright 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:subject":["QPE","X-band","rainfall","dual polarization"],"dc:title":["Radar multi-sensor (RAMS) quantitative precipitation estimation (QPE)"],"dc:type":["Text"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy (Ph.D.)"],"thesis:institution_name":["Colorado State University"]},"updated_at":"2026-07-27T19:12:57Z"}