Climate change is one of the most challenging and defining issues that has resulted in substantial societal, economic, and environmental impacts across the world. To assess the potential climate change impact, climate projections are generated with General Circulation Models (GCMs). However, the climate change signals remain uncertain and GCMs have difficulty in representing regional climate features. Therefore, comprehensive knowledge of climate change signals and reliable high-resolution climate projections are highly desired. This dissertation aims to address such challenges by developing climate projections with multi-model ensembles for climate impact assessment. This includes: i) developing multi-model ensembles to analyze global changes in all water components within the hydrological cycle and quantify the uncertainties with GCM projections; ii) development of bias correction models for generating high-resolution daily maximum and minimum temperature projections with individual GCMs and multi-model ensemble means over Canada; iii) proposing bias correction models with individual GCMs and multi-model ensemble means for high-resolution daily precipitation projections for Canada. The proposed models are capable of developing high-resolution climate projections at a regional scale and exploring the climate change signals. The reliable climate projections generated could provide valuable information for formulating appropriate climate change mitigation and adaptation strategies across the world. / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29260 |
| Date | January 2024 |
| Creators | Li, Xinyi |
| Contributors | Li, Zhong, Civil Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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