{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/110593"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/110593","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Internal and structural variability in global urban climate projections in CMIP6","abstract":"Climate change is projected to impose substantial impacts and climate-driven threats to urban areas. Effective development decisions and local actions to manage these risks rely on robust climate projections that are specific to built landscapes. A robust modeling framework to address uncertainty in local- or regional-scale climate change should include the roles of internal variability, model parametric and structural uncertainty, and scenario uncertainty. Quantitative attributions of the structure of these uncertainties have been typically done for non-urban surfaces at regional scales using multi-modeled (e.g. Coupled Model Intercomparison Project) grid cell means. Such analysis for local-scale urban areas, however, has never been achieved due to the near-universal lack of physical-based urban land parameterization in the state-of-the-art Earth system models (ESMs). This study assesses such variability structure through a novel multi-model urban emulator framework. I built a credible XGB-based urban climate emulator by utilizing the Community Earth System Model (CESM) simulation results. The emulator was then applied to 22-26 CMIP6 models to generate urban climatic responses under four SSPs. The structural variability was obtained by combining emulated results from different CMIP models, and the internal variability was assessed using the CESM-LE (large ensemble) simulations. Results show that there is an obvious structural variability of urban temperature change across CMIP models, ranging from 2-6 K, which aligns with that of background temperature change and increases with time. The structural variability of both urban and background temperature change also varies geographically and seasonally, and has a similar pattern with each other, with the Eurasia region demonstrating higher variability in both summer and winter. The internal variability of urban temperature change across CESM members with a magnitude of approximately 1.5 K, on the other hand, is consistent over the timescale of a century, which also differs slightly in different regions and seasons, and accords with the background temperature variability.","abstract_html":"Climate change is projected to impose substantial impacts and climate-driven threats to urban areas. Effective development decisions and local actions to manage these risks rely on robust climate projections that are specific to built landscapes. A robust modeling framework to address uncertainty in local- or regional-scale climate change should include the roles of internal variability, model parametric and structural uncertainty, and scenario uncertainty. Quantitative attributions of the structure of these uncertainties have been typically done for non-urban surfaces at regional scales using multi-modeled (e.g. Coupled Model Intercomparison Project) grid cell means. Such analysis for local-scale urban areas, however, has never been achieved due to the near-universal lack of physical-based urban land parameterization in the state-of-the-art Earth system models (ESMs). This study assesses such variability structure through a novel multi-model urban emulator framework. I built a credible XGB-based urban climate emulator by utilizing the Community Earth System Model (CESM) simulation results. The emulator was then applied to 22-26 CMIP6 models to generate urban climatic responses under four SSPs. The structural variability was obtained by combining emulated results from different CMIP models, and the internal variability was assessed using the CESM-LE (large ensemble) simulations. Results show that there is an obvious structural variability of urban temperature change across CMIP models, ranging from 2-6 K, which aligns with that of background temperature change and increases with time. The structural variability of both urban and background temperature change also varies geographically and seasonally, and has a similar pattern with each other, with the Eurasia region demonstrating higher variability in both summer and winter. The internal variability of urban temperature change across CESM members with a magnitude of approximately 1.5 K, on the other hand, is consistent over the timescale of a century, which also differs slightly in different regions and seasons, and accords with the background temperature variability.","abstract_has_math":false,"creators":["Zhang, Yiwen"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Environ Engr in Civil Engr","degree_department":null,"school":null,"contributors":["Zhao, Lei"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-09-17T01:13:32Z","date_published":"2021-09-17T01:13:32Z","updated_at":"2026-07-22T22:24:52Z","subjects":["multi-model global urban climate projections","CMIP6","urban climate uncertainty"],"languages":["en"],"rights":["Copyright 2021 Yiwen Zhang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/110593","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhao, Lei"]},{"key":"dc:creator","label":"Author","values":["Zhang, Yiwen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-09-17T01:13:32Z","2021-04-28","2021-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environ Engr in Civil Engr"]},{"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":["multi-model global urban climate projections","CMIP6","urban climate uncertainty"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Yiwen Zhang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/110593"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Climate change is projected to impose substantial impacts and climate-driven threats to urban areas. Effective development decisions and local actions to manage these risks rely on robust climate projections that are specific to built landscapes. A robust modeling framework to address uncertainty in local- or regional-scale climate change should include the roles of internal variability, model parametric and structural uncertainty, and scenario uncertainty. Quantitative attributions of the structure of these uncertainties have been typically done for non-urban surfaces at regional scales using multi-modeled (e.g. Coupled Model Intercomparison Project) grid cell means. Such analysis for local-scale urban areas, however, has never been achieved due to the near-universal lack of physical-based urban land parameterization in the state-of-the-art Earth system models (ESMs). This study assesses such variability structure through a novel multi-model urban emulator framework. I built a credible XGB-based urban climate emulator by utilizing the Community Earth System Model (CESM) simulation results. The emulator was then applied to 22-26 CMIP6 models to generate urban climatic responses under four SSPs. The structural variability was obtained by combining emulated results from different CMIP models, and the internal variability was assessed using the CESM-LE (large ensemble) simulations. Results show that there is an obvious structural variability of urban temperature change across CMIP models, ranging from 2-6 K, which aligns with that of background temperature change and increases with time. The structural variability of both urban and background temperature change also varies geographically and seasonally, and has a similar pattern with each other, with the Eurasia region demonstrating higher variability in both summer and winter. The internal variability of urban temperature change across CESM members with a magnitude of approximately 1.5 K, on the other hand, is consistent over the timescale of a century, which also differs slightly in different regions and seasons, and accords with the background temperature variability.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Yiwen Zhang, accepted the attached license on 2021-04-28 at 10:14.","The student, Yiwen Zhang, submitted this Thesis for approval on 2021-04-28 at 10:21.","This Thesis was approved for publication on 2021-04-28 at 16:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16600 on 2021-09-16 at 16:49:14","Made available in DSpace on 2021-09-17T01:13:32Z (GMT). No. of bitstreams: 2 ZHANG-THESIS-2021.pdf: 9648157 bytes, checksum: bd15dd7e7b9855ae32158fc1fb697904 (MD5) LICENSE.txt: 4208 bytes, checksum: f9660c9cb01d5b06aba9fa320ad76f1f (MD5) Previous issue date: 2021-04-28"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Internal and structural variability in global urban climate projections in CMIP6"]}]}],"canonical_facts":{"dc:contributor":["Zhao, Lei"],"dc:creator":["Zhang, Yiwen"],"dc:date":["2021-09-17T01:13:32Z","2021-04-28","2021-05"],"dc:description":["Climate change is projected to impose substantial impacts and climate-driven threats to urban areas. Effective development decisions and local actions to manage these risks rely on robust climate projections that are specific to built landscapes. A robust modeling framework to address uncertainty in local- or regional-scale climate change should include the roles of internal variability, model parametric and structural uncertainty, and scenario uncertainty. Quantitative attributions of the structure of these uncertainties have been typically done for non-urban surfaces at regional scales using multi-modeled (e.g. Coupled Model Intercomparison Project) grid cell means. Such analysis for local-scale urban areas, however, has never been achieved due to the near-universal lack of physical-based urban land parameterization in the state-of-the-art Earth system models (ESMs). This study assesses such variability structure through a novel multi-model urban emulator framework. I built a credible XGB-based urban climate emulator by utilizing the Community Earth System Model (CESM) simulation results. The emulator was then applied to 22-26 CMIP6 models to generate urban climatic responses under four SSPs. The structural variability was obtained by combining emulated results from different CMIP models, and the internal variability was assessed using the CESM-LE (large ensemble) simulations. Results show that there is an obvious structural variability of urban temperature change across CMIP models, ranging from 2-6 K, which aligns with that of background temperature change and increases with time. The structural variability of both urban and background temperature change also varies geographically and seasonally, and has a similar pattern with each other, with the Eurasia region demonstrating higher variability in both summer and winter. The internal variability of urban temperature change across CESM members with a magnitude of approximately 1.5 K, on the other hand, is consistent over the timescale of a century, which also differs slightly in different regions and seasons, and accords with the background temperature variability.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo terms","The student, Yiwen Zhang, accepted the attached license on 2021-04-28 at 10:14.","The student, Yiwen Zhang, submitted this Thesis for approval on 2021-04-28 at 10:21.","This Thesis was approved for publication on 2021-04-28 at 16:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16600 on 2021-09-16 at 16:49:14","Made available in DSpace on 2021-09-17T01:13:32Z (GMT). No. of bitstreams: 2 ZHANG-THESIS-2021.pdf: 9648157 bytes, checksum: bd15dd7e7b9855ae32158fc1fb697904 (MD5) LICENSE.txt: 4208 bytes, checksum: f9660c9cb01d5b06aba9fa320ad76f1f (MD5) Previous issue date: 2021-04-28"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/110593"],"dc:language":["en"],"dc:rights":["Copyright 2021 Yiwen Zhang"],"dc:subject":["multi-model global urban climate projections","CMIP6","urban climate uncertainty"],"dc:title":["Internal and structural variability in global urban climate projections in CMIP6"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Environ Engr in Civil Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:52Z"}