Development of a Global Statistical Framework for Estimating Landscape Freeze-Thaw under Changing Climate Conditions with Application to Québec
Seasonal Freeze-Thaw (FT) dynamics are among the most important landscape processes, influencing ground thermal and hydrological characteristics across cold regions. These impacts can further affect the environmental processes, socio-economic, and cultural activities developed around the use of land...
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| Format: | Thesis |
| Language: | English |
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2021
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| Online Access: | https://spectrum.library.concordia.ca/id/eprint/989105/ https://spectrum.library.concordia.ca/id/eprint/989105/7/Hatami_PhD_F2021.pdf |
| Summary: | Seasonal Freeze-Thaw (FT) dynamics are among the most important landscape processes, influencing ground thermal and hydrological characteristics across cold regions. These impacts can further affect the environmental processes, socio-economic, and cultural activities developed around the use of lands and waters. From a physical perspective and at the large spatial and regional scales, temperature and snow depth are the key drivers of variability in the timing and distribution of FT dynamics. However, climate change has significantly affected both temperature and snow depth over the past decades, and thus FT dynamics in time and space. As a result, it is of a great importance to understand and quantify the control of changing climate on FT characteristics and project future states of FT characteristics subject to future climatic projections. This knowledge and modeling capability can provide an invaluable information for agricultural activities, infrastructure design and maintenance, monitoring the ecosystem’s livelihood, and estimating land-induced greenhouse gas emissions due to permafrost degradation. This thesis provides a generic and globally relevant statistical framework to quantify the compound control of temperature and snow depth on FT dynamics over different spatiotemporal scales. A set of gridded observed temperature and snow depth data with the remotely sensed state of the frozen soil are utilized as basis for understanding the climate control on FT dynamics and their spatiotemporal variability. Using these gridded data records, it is possible to greatly overcome the limitations in using station-based data, particularly at higher latitudes. Utilizing future projections of climate models along with a rigorous data processing step and different statistical methodologies, future projections of precipitation type, snow depth, and FT can be obtained over the required spatial and temporal resolutions. Although statistical models have been widely used to address the impact of changing climate on different ... |
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