{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/90646"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/90646","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Weighted ensemble analysis of extreme precipitation under climate change","abstract":"The frequency or intensity of heavy precipitation has likely increased in North America since 1950s. In order to analyze climate change impacts on extreme precipitation events in Chicago area, historical (1961-2000) and projected (2046-2065, 2081-2100) daily precipitation data are calculated from 13 statistical downscaling general circulation models under 3 CMIP3 emission scenarios: A1B, A2 and B1, as well as from 17 stations in NCDC and CCPN rain gage network. Then precipitation events of different recurrence intervals are calculated through regional frequency analysis and based on average deviation of climate model estimates from observation estimates, tricube weight function is used to assign weights to climate model ensemble. This weight result is further applied to projected quantile estimates to derive weighted expected values and confidence intervals of future extreme precipitation events under different emission scenarios, these results are further compared with current available estimates from NOAA Atlas 14. Finally, maximum entropy method (MEM) is applied to assign weights and the results are compared with those from weighted ensemble method (WEM). It is found that intensity and the confidence intervals of heavy precipitation is likely to increase significantly for about 20% from now to 2050s under all emission scenarios (A1B>A2>B1), afterwards, this increase trend will slow down (B1>A1B>A2). As for the performance of expected value projection based on MEM, it can also provide accurate estimates with high computational efficiency.","abstract_html":"The frequency or intensity of heavy precipitation has likely increased in North America since 1950s. In order to analyze climate change impacts on extreme precipitation events in Chicago area, historical (1961-2000) and projected (2046-2065, 2081-2100) daily precipitation data are calculated from 13 statistical downscaling general circulation models under 3 CMIP3 emission scenarios: A1B, A2 and B1, as well as from 17 stations in NCDC and CCPN rain gage network. Then precipitation events of different recurrence intervals are calculated through regional frequency analysis and based on average deviation of climate model estimates from observation estimates, tricube weight function is used to assign weights to climate model ensemble. This weight result is further applied to projected quantile estimates to derive weighted expected values and confidence intervals of future extreme precipitation events under different emission scenarios, these results are further compared with current available estimates from NOAA Atlas 14. Finally, maximum entropy method (MEM) is applied to assign weights and the results are compared with those from weighted ensemble method (WEM). It is found that intensity and the confidence intervals of heavy precipitation is likely to increase significantly for about 20% from now to 2050s under all emission scenarios (A1B>A2>B1), afterwards, this increase trend will slow down (B1>A1B>A2). As for the performance of expected value projection based on MEM, it can also provide accurate estimates with high computational efficiency.","abstract_has_math":false,"creators":["Zhang, Chen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Cai, Ximing"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-07-07T19:57:59Z","date_published":"2016-07-07T19:57:59Z","updated_at":"2026-07-22T22:26:34Z","subjects":["Ensemble analysis","Extreme precipitation event","Climate change"],"languages":["en"],"rights":["Copyright 2016 Chen Zhang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/90646","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Cai, Ximing"]},{"key":"dc:creator","label":"Author","values":["Zhang, Chen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2016-07-07T19:57:59Z","2016-04-28","2016-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Ensemble analysis","Extreme precipitation event","Climate change"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Chen Zhang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/90646"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The frequency or intensity of heavy precipitation has likely increased in North America since 1950s. In order to analyze climate change impacts on extreme precipitation events in Chicago area, historical (1961-2000) and projected (2046-2065, 2081-2100) daily precipitation data are calculated from 13 statistical downscaling general circulation models under 3 CMIP3 emission scenarios: A1B, A2 and B1, as well as from 17 stations in NCDC and CCPN rain gage network. Then precipitation events of different recurrence intervals are calculated through regional frequency analysis and based on average deviation of climate model estimates from observation estimates, tricube weight function is used to assign weights to climate model ensemble. This weight result is further applied to projected quantile estimates to derive weighted expected values and confidence intervals of future extreme precipitation events under different emission scenarios, these results are further compared with current available estimates from NOAA Atlas 14. Finally, maximum entropy method (MEM) is applied to assign weights and the results are compared with those from weighted ensemble method (WEM). It is found that intensity and the confidence intervals of heavy precipitation is likely to increase significantly for about 20% from now to 2050s under all emission scenarios (A1B>A2>B1), afterwards, this increase trend will slow down (B1>A1B>A2). As for the performance of expected value projection based on MEM, it can also provide accurate estimates with high computational efficiency.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Chen Zhang, accepted the attached license on 2016-04-25 at 17:41.","The student, Chen Zhang, submitted this Thesis for approval on 2016-04-25 at 17:43.","This Thesis was approved for publication on 2016-04-28 at 09:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9474 on 2016-07-07 at 13:33:00","Made available in DSpace on 2016-07-07T19:57:59Z (GMT). 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In order to analyze climate change impacts on extreme precipitation events in Chicago area, historical (1961-2000) and projected (2046-2065, 2081-2100) daily precipitation data are calculated from 13 statistical downscaling general circulation models under 3 CMIP3 emission scenarios: A1B, A2 and B1, as well as from 17 stations in NCDC and CCPN rain gage network. Then precipitation events of different recurrence intervals are calculated through regional frequency analysis and based on average deviation of climate model estimates from observation estimates, tricube weight function is used to assign weights to climate model ensemble. This weight result is further applied to projected quantile estimates to derive weighted expected values and confidence intervals of future extreme precipitation events under different emission scenarios, these results are further compared with current available estimates from NOAA Atlas 14. Finally, maximum entropy method (MEM) is applied to assign weights and the results are compared with those from weighted ensemble method (WEM). It is found that intensity and the confidence intervals of heavy precipitation is likely to increase significantly for about 20% from now to 2050s under all emission scenarios (A1B>A2>B1), afterwards, this increase trend will slow down (B1>A1B>A2). As for the performance of expected value projection based on MEM, it can also provide accurate estimates with high computational efficiency.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2016-07-07 without embargo terms","The student, Chen Zhang, accepted the attached license on 2016-04-25 at 17:41.","The student, Chen Zhang, submitted this Thesis for approval on 2016-04-25 at 17:43.","This Thesis was approved for publication on 2016-04-28 at 09:12.","DSpace SAF Submission Ingestion Package generated from Vireo submission #9474 on 2016-07-07 at 13:33:00","Made available in DSpace on 2016-07-07T19:57:59Z (GMT). No. of bitstreams: 2 ZHANG-THESIS-2016.pdf: 5971854 bytes, checksum: d23253ae4b05d20c3e4ba9976762acde (MD5) LICENSE.txt: 4207 bytes, checksum: d7c6cd37b0e15ba53b29df28ce183ec5 (MD5) Previous issue date: 2016-04-28"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/90646"],"dc:language":["en"],"dc:rights":["Copyright 2016 Chen Zhang"],"dc:subject":["Ensemble analysis","Extreme precipitation event","Climate change"],"dc:title":["Weighted ensemble analysis of extreme precipitation under climate change"],"dc:type":["text"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:34Z"}