{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90954"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90954","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Analysis of long-term precipitation sequencing patterns in North America","abstract":"Precipitation sequencing, or the overall temporal pattern of precipitation events and the persistence of those events, is an important factor in describing nonstationarity in climate variability. It is a vital, yet often overlooked part of developing long-term climate predictions. Precipitation sequencing, which is based on rainfall of all magnitudes, is not well understood in part because much of recent research has focused on changes solely in extreme precipitation. This study examines precipitation sequencing pattern changes in North America over a study period of 1880-2010, and compares sequencing changes for both nonextreme and extreme rainfall. Results reveal nonstationarity in precipitation sequencing in North America and indicate that changes in non-extreme rainfall are greater in magnitude and more prevalent than those in extreme rainfall. Analysis of the spatial variation of non-extreme precipitation sequencing reveals both continent-scale trends and, unexpectedly, strongly localized, regional trends. Results not only validate questions about the assumption of stationarity in climate models and studies but illustrate the importance of conducting precipitation studies at the proper scale in order to capture significant local trends. Incorporation of both elements into climate models can improve the robustness of long-term predictions. Results from this analysis reveal the need for increased study of non-extreme rainfall and for moving away from the assumption of stationarity in precipitation patterns when developing climate predictions. Additionally, results may shed light on the regional nature of precipitation sequencing changes and its drivers, which may help scientists make better decisions when choosing which climate models fit their studies.","abstract_html":"Precipitation sequencing, or the overall temporal pattern of precipitation events and the persistence of those events, is an important factor in describing nonstationarity in climate variability. It is a vital, yet often overlooked part of developing long-term climate predictions. Precipitation sequencing, which is based on rainfall of all magnitudes, is not well understood in part because much of recent research has focused on changes solely in extreme precipitation. This study examines precipitation sequencing pattern changes in North America over a study period of 1880-2010, and compares sequencing changes for both nonextreme and extreme rainfall. Results reveal nonstationarity in precipitation sequencing in North America and indicate that changes in non-extreme rainfall are greater in magnitude and more prevalent than those in extreme rainfall. Analysis of the spatial variation of non-extreme precipitation sequencing reveals both continent-scale trends and, unexpectedly, strongly localized, regional trends. Results not only validate questions about the assumption of stationarity in climate models and studies but illustrate the importance of conducting precipitation studies at the proper scale in order to capture significant local trends. Incorporation of both elements into climate models can improve the robustness of long-term predictions. Results from this analysis reveal the need for increased study of non-extreme rainfall and for moving away from the assumption of stationarity in precipitation patterns when developing climate predictions. Additionally, results may shed light on the regional nature of precipitation sequencing changes and its drivers, which may help scientists make better decisions when choosing which climate models fit their studies.","abstract_has_math":false,"creators":["Roque, Susana Lucia"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Kumar, Praveen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T21:18:02Z","date_published":"2016-07-07T21:18:02Z","updated_at":"2026-07-22T22:26:34Z","subjects":["Precipitation sequencing","Nonstationarity","Non-extreme precipitation"],"languages":["en"],"rights":["Copyright 2016 Susana L. 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Roque"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90954"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Precipitation sequencing, or the overall temporal pattern of precipitation events and the persistence of those events, is an important factor in describing nonstationarity in climate variability. It is a vital, yet often overlooked part of developing long-term climate predictions. Precipitation sequencing, which is based on rainfall of all magnitudes, is not well understood in part because much of recent research has focused on changes solely in extreme precipitation. This study examines precipitation sequencing pattern changes in North America over a study period of 1880-2010, and compares sequencing changes for both nonextreme and extreme rainfall. Results reveal nonstationarity in precipitation sequencing in North America and indicate that changes in non-extreme rainfall are greater in magnitude and more prevalent than those in extreme rainfall. Analysis of the spatial variation of non-extreme precipitation sequencing reveals both continent-scale trends and, unexpectedly, strongly localized, regional trends. Results not only validate questions about the assumption of stationarity in climate models and studies but illustrate the importance of conducting precipitation studies at the proper scale in order to capture significant local trends. Incorporation of both elements into climate models can improve the robustness of long-term predictions. Results from this analysis reveal the need for increased study of non-extreme rainfall and for moving away from the assumption of stationarity in precipitation patterns when developing climate predictions. Additionally, results may shed light on the regional nature of precipitation sequencing changes and its drivers, which may help scientists make better decisions when choosing which climate models fit their studies.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01","The student, Susana Roque, accepted the attached license on 2016-04-27 at 17:00.","The student, Susana Roque, submitted this Thesis for approval on 2016-04-27 at 17:06.","This Thesis was approved for publication on 2016-04-28 at 10:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9461 on 2016-07-07 at 14:17:57","Made available in DSpace on 2016-07-07T21:18:02Z (GMT). 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It is a vital, yet often overlooked part of developing long-term climate predictions. Precipitation sequencing, which is based on rainfall of all magnitudes, is not well understood in part because much of recent research has focused on changes solely in extreme precipitation. This study examines precipitation sequencing pattern changes in North America over a study period of 1880-2010, and compares sequencing changes for both nonextreme and extreme rainfall. Results reveal nonstationarity in precipitation sequencing in North America and indicate that changes in non-extreme rainfall are greater in magnitude and more prevalent than those in extreme rainfall. Analysis of the spatial variation of non-extreme precipitation sequencing reveals both continent-scale trends and, unexpectedly, strongly localized, regional trends. Results not only validate questions about the assumption of stationarity in climate models and studies but illustrate the importance of conducting precipitation studies at the proper scale in order to capture significant local trends. Incorporation of both elements into climate models can improve the robustness of long-term predictions. Results from this analysis reveal the need for increased study of non-extreme rainfall and for moving away from the assumption of stationarity in precipitation patterns when developing climate predictions. Additionally, results may shed light on the regional nature of precipitation sequencing changes and its drivers, which may help scientists make better decisions when choosing which climate models fit their studies.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01","The student, Susana Roque, accepted the attached license on 2016-04-27 at 17:00.","The student, Susana Roque, submitted this Thesis for approval on 2016-04-27 at 17:06.","This Thesis was approved for publication on 2016-04-28 at 10:02.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9461 on 2016-07-07 at 14:17:57","Made available in DSpace on 2016-07-07T21:18:02Z (GMT). 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