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Analysis of Temperature extremes in Canadian Cities using CMIP6 Data



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An ever-growing Canadian urban population could be severely impacted by increase in temperature. Canada’s mean temperature is projected to increase by 6-8°C towards the end of the 21st century. The consequence of rising temperatures is an increased likelihood of extreme temperature events like heatwaves and wildfires. The thesis aims to assess changes in extreme temperature in large Canadian urban areas. The research will help in developing mitigation measures like urban planning, which help cope with changing temperature extremes. Predicting urban temperature change will require rigorous assessment of climate models, to account for the uncertainty in projecting temperature in large urban agglomerates. CMIP6 ensemble of models, provide an opportunity for assessment of urban-based projections. The models however, would need to be of fine resolution to fully capture its variability since urban temperature is heavily influenced by local urban features that contribute to Urban heat island (UHI). Historical maximum and minimum temperature trends are analyzed for eighteen urban areas in the Canada with population greater than 250,000 and use twelve CMIP6 models of fine resolution (<1°), and four tier-one emission scenarios to assess maximum, minimum, and mean temperature trends in future. An efficient observation dataset, Serially based station data (SCDNA), was used as a reference observation dataset and a novel bias-correction technique, the Semi-Parametric Quantile Mapping method (SPQM), was used to bias-correct future temperature data. Extreme temperature events were analyzed with the help of eight selected indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), across all the emission scenarios for all the cities in the study. The indices were computed for the entire future time-period (2021-2100) and for three time-slices, T1 (2021-2050), T2 (2040-2070) and T3 (2070-2100) to assess temporal variability. The magnitude, frequency, and duration of the occurrence of extreme events can be analyzed effectively using the ETCCDI indices, classified as absolute, threshold, and duration Indices and percentile indices. The historical temperature trends in Canadian cities were found to be related with urban features like elevation and population-growth but not strongly linked with urban area. Other features of UHI were deemed essential to understand the transitioning of historical and future temperature trends in Canada. Four emission scenarios predict increasing mean temperatures in all Canadian cities, except for the optimistic emission scenario (SSP1-2.6), which shows a marginal decreasing trend in the last quarter of the 21st century. Uneven changes are noted in all the projected indices, for example, in the annual maxima of daily maximum temperature (TXx), i.e., an increase of 0.5 °C and 0.6 °C per decade over the T1 and T2 respectively, and 0.99°C for T3 for the SSP5-8.5. Results show faster rates of warming across Canadian cities especially for the higher emission scenarios (SSP3-7.0 and SSP5-8.5). Spatial trends of extreme temperature indices correlate with temperature trends in individual climate zones in Canada, and the cities associated with a zone, expectedly experience similar trends. Cities in the Prairies and the Great Lakes zones, experience the highest increasing trends over the absolute and threshold indices in the higher emission scenarios, whereas the cities in the Canadian coasts experience higher increasing trends in the percentile indices. Lower emission scenarios also point towards increasing spatial trends in all Canadian cities. The coastal cities also experience the highest trends for the warm-spell duration index (WSDI) and a decreasing trend in the cold-spell duration index (CSDI). Spatial patterns of duration indices in the Canadian coastal cities point towards hotter summers, and milder winters, whereas the cities in the Canadian prairies, the Great Lakes, and Quebec will experience hotter summers with longer durations of extremely hot weather, in addition to persistence of harsher winters. Temperature projections have several applications, for example, in civil engineering applications, where temperature has a great role in the estimation and assessment of concrete and reinforcement deterioration. Another field of research is urban-based mortality studies, a consequence of the increasing frequency and duration of extreme temperature events. Heat-wave analysis, estimated through extreme temperature indices, forms the basis for estimating mortality rates from heat waves and other extreme temperature events. Climate models and CMIP6 models have systematic errors in their development and hence can only predict temperature projections with a limited degree of confidence. An extension of the work in this thesis could be the use of various model performance indicators, that quantitatively assess the performance of temperature projections made by CMIP6 models in Canadian cities. The future temperature projections and estimations of heat waves provide a scientific basis for a better understanding of the temperature patterns and temperature-related extreme events in Canadian cities and thus help facilitate climate change adaptation.



CMIP6, Urban temperature



Master of Science (M.Sc.)


Civil and Geological Engineering


Civil Engineering


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