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 estimated. In addition, this study used gridded data as a substitute for in situ observations in the Cold Regions Hydrological Model (CRHM) to simulate runoff. Simulated runoff generated when using ANUSPLIN and ERA-Interim data as inputs in CRHM captures the timing and magnitude of freshet and baseflow generally well at Scotty Creek. This study suggests that gridded datasets can provide reasonable estimates of in situ climate data in data sparse regions and reinforced that the accuracy in representing in situ observations over the NWT improves as the spatial resolution of interpolated dataset increases. This research also highlighted that when comparing datasets, it is important use multiple metrics and graphical methods to discern systematic biases.
The presence of oceanic-atmospheric teleconnections patterns can influence weather patterns in northern regions which may lead to an increase in climate related wildland fires. The impact of the Arctic Dipole (AD) anomaly, a northern atmospheric teleconnection, on NWT’s surface climate has not been explored. Hence, the second objective of this dissertation used the ANUSPLIN dataset to assess the effects of the AD anomaly on local climate (air temperature, precipitation, and snowmelt) during a 66-year period (1950-2015). For all seasons, from 1950 to 2015, the occurrence of 64 strong positive and 56 strong negative AD modes were identified. The AD pattern revealed significant year-to-year fluctuation, with more frequent strong negative modes observed in the 2000s. In summer, when AD is in its strong negative mode, there is increased variance in the range of local air temperature, which is amplified in the southern, lake and foothill regions of the Taiga Plains. During strong positive AD modes, local air temperature anomalies increased (\u3e0.8°C) when compared to long-term mean temperature during summer months. Positive AD modes also lead to earlier commencement of snowmelt by an average of 3 to 5 days. The air temperature/snowmelt onset north–south amplification to the AD is linked to the position and intensity of the geopotential heights ridge axis over the continental NWT. A weak correlation was found between the AD and seasonal precipitation despite high correlation association between the AD and local air temperature in summer.
Finally, the spatiotemporal patterns of incoming surface shortwave radiation (SSR) were analysed and quantified for the continental NWT to enhance understanding of northern ecosystems energy balance that are undergoing environmental changes. The third objective of this dissertation addressed this knowledge gap by assessing annual and seasonal trends in SSR receipt and to explore relationship between SSR and lake surface water temperature (LSWT) during the warm season. Consequently, the quantity of SSR that reaches Earth’s surface may vary. In this study, it is observed that SSR trends display a significant temporal and spatial dependency on NWT’s ecozones between 1980 and 2020. The annual mean SSR since 1980 decreased by ~0.8 Wm-2decade-1 in the Taiga Plains and Northern Arctic ecozones, with mixture of increasing and decreasing trends in both Taiga Shield and Southern Arctic ecozones. Seasonally, SSR decreased significantly in the summer since 1980 over the majority of the Taiga Plains ecozone, with a reduction rate that ranged between 0.6 and 14.6 Wm-2decade-1. The LSWT in small lakes was positively associated with SSR, while the LSWT in medium and large lakes showed a mix of positive and negative correlation coefficients. The linkage between total cloud cover and SSR in the NWT was largely negative for spring, summer and autumn seasons, with the Taiga Plains ecozone displaying the largest negative correlation. Long-term changes in SSR in the NWT will have an impact on the seasonal and annual energy balance of the region\u27s lakes. The impact of SSR changes on lake energy balances will have a wide range of consequences, particularly for NWT communities that rely on lakes for their transportation networks. These networks are already being adversely impacted by climate change-driven alterations in warming lake ice phenology.
The collective findings of this study demonstrate the feasibility of using gridded and remote sensing datasets to characterize historical changes in local and regional weather and climate, building an understanding of northern climatology and providing best estimates of long-term trends with implications for ecosystem change in the future, such as increased rates of shrubification and frequency of wildland fires. In the absence of consistent in situ climate data, these gridded and remote sensing datasets aid our understanding of the physical links between climate change and northern ecosystems, which must be accounted for in forecast models used to predict future hydroclimate scenarios and to provide enhance climate services in northern regions. Improved understanding of how local and regional climate has changed in the NWT will inform policymakers in their efforts to develop and improve climate adaptation and mitigation policies in local communities across the territory
