Extreme weather event attribution is a climate science approach that explores how events like heat waves, floods, and wildfires are linked to human-caused climate change. By modelling a pre-industrial climate and comparing it to today’s climate, scientists can calculate the influence of human activity on extreme events. Environment and Climate Change Canada’s Rapid Extreme Weather Event Attribution pilot system determines the link between human-caused climate change and heat events across Canada, shortly after they occur. These insights aim to enhance response planning, decision-making, and public understanding of climate impacts.
The map below highlights observed heat events in 2024 that had the largest departures from normal1 in each of the attribution system’s 17 study areas. The statement of likelihood, denoted by the map’s colours, describes whether the heat event was made more or less likely due to human influence on the climate. The probability range quantifies the likelihood statements, with “much more likely,” for example, meaning an event is at least 2x to 10x more likely to occur today compared to a pre-industrial climate. As the map demonstrates, climate change had an impact on extreme heat events across Canada in 2024.
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Each extreme heat event is described in more detail in the following table. In addition to a statement of likelihood for the current climate, the table below also contains a statement of likelihood for a modelled, future climate.2
| Region | Date of peak temperature | Dates of heatwave duration | Peak daily high temperature (°C) | Degrees above normal daily high temperature (°C) | Normal daily high temperature (°C) | Current likelihood(compared to 1850–1900 base period) | Future likelihood(SSP2-4.5, 2081–2100 compared to 1850–1900 base period) |
|---|---|---|---|---|---|---|---|
| Inuvik | 09-Aug | August 6 to August 10 | 26.5 | 13 | 13.5 | Far more likely | Far more likely |
| Kitikmeot | 09-Aug | August 7 to August 12 | 25 | 12.4 | 12.6 | Far more likely | Far more likely |
| Kivalliq | 10-Aug | August 8 to August 14 | 27.1 | 12.2 | 14.9 | Far more likely | Far more likely |
| S. Quebec | 19-Jun | June 18 to June 20 | 29.5 | 10.7 | 18.8 | Much more likely | Far more likely |
| S. Qukiqtaaluk | 23-Sep | September 20 to October 16 | 8.8 | 10.2 | -1.4 | Far more likely | Far more likely |
| Alberta | 10-Jul | July 7 to July 11 | 31.5 | 9.8 | 21.7 | Much more likely | Far more likely |
| Ft. Smith | 18-Jul | July 15 to July 20 | 28.4 | 9.2 | 19.2 | Much more likely | Far more likely |
| S. BC | 21-Jul | July 14 to July 22 | 29.2 | 9.2 | 20 | Much more likely | Far more likely |
| Yukon | 08-Aug | August 5 to August 9 | 24.1 | 8.9 | 15.2 | Much more likely | Far more likely |
| Sask | 19-Jul | July 17 to July 22 | 30.9 | 8 | 22.9 | Much more likely | Much more likely |
| N. BC | 21-Jul | July 17 to July 22 | 24.2 | 7.2 | 17 | Much more likely | Far more likely |
| N. Quebec | 28-Jul | July 28 to July 30 | 24.2 | 7 | 17.2 | Much more likely | Much more likely |
| Atl. Canada | 29-Jul | July 28 to July 31 | 26.1 | 6.7 | 19.4 | Much more likely | Far more likely |
| Manitoba | 30-Jul | July 30 to August 1 | 28.3 | 6.4 | 21.9 | More likely | Much more likely |
| W. Ontario | 27-Jul | July 26 to July 28 | 27.9 | 6.1 | 21.8 | More likely | Much more likely |
| N. Qikiqtaaluk | 12-Sep | September 10 to September 14 | 0.4 | 5.8 | -5.4 | More likely | Much more likely |
| E. Ontario | 01-Aug | July 31 to August 2 | 29.2 | 5.8 | 23.4 | Much more likely | Much more likely |
Visit Environment and Climate Change Canada’s Extreme Weather Event Attribution website to learn more. Visit ClimateData.ca to learn more about future climate changes, explore interactive maps, and analyze how extreme heat events become more frequent and severe under a range of emissions scenarios.
1 Here “normal” is defined as the average high temperature over a 31-day period centered on the peak temperature day (15 days before and 15 days after), calculated using 1991–2020 climate data for the region.
2 Here the “future climate” is calculated using an ensemble of CMIP6 GCMs running the SSP2-4.5 emissions scenario over the 2081-2100 time period.
This project was undertaken with the support of:
