Spatial and temporal characteristics of historical surface climate over the Northwest Territories, Canada
Climate change is putting many of the Northwest Territories (NWT) ecosystems, its people and animal populations at risk due to accelerated warming, permafrost thaw, and changing precipitation regimes. As the NWT continues to warm, at disproportionately higher rates when compared to the rest of Canad...
| Main Author: | |
|---|---|
| Format: | Text |
| Language: | English |
| Published: |
Scholars Commons @ Laurier
1480
|
| Subjects: | |
| Online Access: | https://scholars.wlu.ca/etd/2532 https://scholars.wlu.ca/cgi/viewcontent.cgi?article=3681&context=etd |
| Summary: | Climate change is putting many of the Northwest Territories (NWT) ecosystems, its people and animal populations at risk due to accelerated warming, permafrost thaw, and changing precipitation regimes. As the NWT continues to warm, at disproportionately higher rates when compared to the rest of Canada, threats to the stability of NWT’s ecosystems are expected to increase. Consequently, understanding how climate warming has changed historically and its implications on natural ecosystems requires point-to-region-specific, long-term climatic data to elucidate important drivers of observed changes relevant to decision makers at community, Indigenous, Territorial and Federal government levels. However, in situ climate data are limited temporally and spatially across the NWT. Hence, the overarching goal of this research is to enhance and improve the understanding of historical surface climate variables trends and patterns (air temperature, precipitation, and shortwave radiation) and its implications at local and regional scales in the continental NWT by using interpolated, reanalysis and remote sensing climate data. Gridded climate datasets such as interpolated and reanalysis data, can provide reliable estimates for in situ observations to compensate for data scarcity, but it is critical that researchers understand how biases in these datasets can impact runoff simulation in the NWT. Thus, the objective of this dissertation was to assess the similarity between daily in situ station observations and three gridded datasets (ANUSPLIN, ERA-Interim and MERRA-2) from 1980 to 2013 to support hydrological modelling in the NWT subarctic. The ANUSPLIN maximum and minimum temperature at eight locations aligned closely to the corresponding in situ observations and had mean daily biases of less than 0.58°C and 1.33°C, respectively. Precipitation estimates showed that the alternative datasets captured year-to-year variability, but large seasonal biases mainly during spring and summer were evident when precipitation magnitudes were ... |
|---|