All Variables

Below is a library of all variables available within ClimateData.ca. Use the filter to limit your search to specific types of data.

Intensity Duration Frequency (IDF) curves relate short-duration rainfall intensity with its frequency of occurrence and are often used for flood forecasting and urban drainage design.

Intense precipitation events can deliver large amounts of rain over short periods of time. This rain, as well as related flooding, can overwhelm storm drains, flood basements, wash out bridges and roads, and trigger landslides. To reduce the risk of these impacts, engineers, hydrologists, planners and decision makers need accurate information about extreme rainfall events. IDF curves are one important source of this information.

Climate change is expected to increase extreme rainfall in Canada. Because of this, IDF curves based on historical observations alone are inappropriate for long-term decision-making. To account for climate change impacts to extreme rainfall and IDF curves, Environment and Climate Change Canada recommends use of a scaling methodology.

Additional guidance about integrating climate change into IDF curves can be found on the Learning Zone. For further technical information on how IDF Curves are produced, please refer to Environment and Climate Change Canada’s Engineering Climate Datasets page or contact the Engineering Climate Services Unit at [email protected].

Climate Normals describe the average climate conditions of a particular location over a 30-year period.

At the end of each decade, Environment and Climate Change Canada calculates a new set of climate normals using observations from that decade. All member countries of the World Meteorological Organisation calculate climate normals. As they describe the most recent average climate conditions for a location, they are often used to put extreme events into context.

The climate normals offered here are based on Canadian climate stations with at least 15 years of data available during the current 30-year normal period.