Assessing factors contributing to the changes in historical temperature extremes and investigating future changes in extreme events
type: CreativeWork
description: Temperature extremes are among the most studied features in the climate research community using both the observed datasets and the simulated outputs from climate models. Such extremes often lead to irreversible societal, ecological, and economic consequences across the globe. Moreover, projected results from climate models have also indicated that changes in future temperature-related extremes will become more frequent and intense with global warming. Therefore, comprehensive knowledge of long-term changes in the observed temperature extremes cannot only help to detect, attribute, and project climate change but can also enhance the development of effective mitigation and adaptation strategies (at regional or site-specific scales) towards the management of catastrophe caused by the extremes. In this dissertation, the observed spatial and temporal variations in temperature extremes are first analyzed at a hemispheric scale based on the newly developed HadEX3 dataset; the impact of large-scale atmospheric circulation patterns on dynamic changes in temperature extremes has also been examined. Then, future changes in extreme temperature variables at a much smaller scale (e.g., local scale) are investigated through a stepwise clustered downscaling method. Based on the downscaled results, future changes in the properties of moderate and severe heatwave conditions are further analyzed. Comparisons of the projected temperature variables and future heatwaves among different climate models provide valuable information on the ability of the models in simulating the long-term variations of temperature extremes. This research can be used to provide a scientific basis and valuable information to prepare for future changes in extreme heat conditions and mitigate the negative impacts of temperature-related extremes on society and the environment.
abstract: Temperature extremes are among the most studied features in the climate research community using both the observed datasets and the simulated outputs from climate models. Such extremes often lead to irreversible societal, ecological, and economic consequences across the globe. Moreover, projected results from climate models have also indicated that changes in future temperature-related extremes will become more frequent and intense with global warming. Therefore, comprehensive knowledge of long-term changes in the observed temperature extremes cannot only help to detect, attribute, and project climate change but can also enhance the development of effective mitigation and adaptation strategies (at regional or site-specific scales) towards the management of catastrophe caused by the extremes. In this dissertation, the observed spatial and temporal variations in temperature extremes are first analyzed at a hemispheric scale based on the newly developed HadEX3 dataset; the impact of large-scale atmospheric circulation patterns on dynamic changes in temperature extremes has also been examined. Then, future changes in extreme temperature variables at a much smaller scale (e.g., local scale) are investigated through a stepwise clustered downscaling method. Based on the downscaled results, future changes in the properties of moderate and severe heatwave conditions are further analyzed. Comparisons of the projected temperature variables and future heatwaves among different climate models provide valuable information on the ability of the models in simulating the long-term variations of temperature extremes. This research can be used to provide a scientific basis and valuable information to prepare for future changes in extreme heat conditions and mitigate the negative impacts of temperature-related extremes on society and the environment.
author: Zhai, Yuanyuan
language: en
date published: 2022-07
date modified: 2026-07-24T04:03:36Z
provider: University of Regina
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Faculty of Graduate Studies and Research, University of Regina

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10294/15531

PropertyValue
property ID: DOI
value: 10.82465/4347