Temperature in Canada decreased to -2.98 celsius in 2024 from -2.89 celsius in 2023. This dataset includes a chart with historical data for Canada Average Temperature.

In 2023, the average temperature in Canada was *** degrees Celsius above the 1961 to 1990 reference value. The warmest year so far in Canadian history was 2010, when the average temperature reached three degrees Celsius above the reference value.

The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. Indicators of Temperature change in Canada show the yearly and seasonal surface air temperature departures for the years 1948 to 2018. As well, they present a spatial distribution of surface air temperature departures for the year 2018. An annual departure (or anomaly) is the difference between the value for a given year and a baseline value. The baseline values used in these indicators are the annual and seasonal temperature averages for the reference period of 1961 to 1990 (often referred to as the 1961–1990 normal). The Temperature change in Canada indicators help show how Canada's surface air temperature has changed since nationwide recording of consistent and comparable climate observations began in 1948. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See supplementary documentation for data sources and details on how those data were collected and how the indicators were calculated. Supplemental Information Canadian Environmental Sustainability Indicators - Home page: https://www.canada.ca/environmental-indicators

30-year Average Number of Days with Minimum Daily Temperature above 20 °C is defined as the count of climate days during the year where the minimum daily temperature was above 20 °C. These values are calculated across Canada in 10x10 km cells

Average annual temperatures in Canada are projected to rise under the different Representative Concentration Pathways (RCP), based on the historic baseline of *** degrees Celsius (°C). Under the RCP *** intermediate emission scenario, it is expected that temperatures will rise to *** °C in the next decades and to *** °C by mid-century. Temperatures will continue to rise to reach *** °C by 2099, following the same scenario.

Departures of temperature and precipitation from 1961 to 1990 normal, by Canada and climatic regions.

According to high emissions forecast scenario, Canada's mean temperature is estimated to change by 2.3 degrees Celsius between 2031 and 2050. Northern Canada is estimated to see the biggest temperature changes, with figures above the national average, at 1.8 degrees Celsius or 2.7 degrees Celsius, depending on a low or high emission scenario.

This feature service includes data on common variables of climate for Canada. Layers in this map service include daylight hours in December and June (solstice months), annual min, max, and mean temperatures, total rainfall and total snowfall. Data for all layers represent mean values from 1951 to 1980.Map Service published and hosted by Esri Canada, © 2020.Content Source(s):'Land Potential DataBase', Version 1.0, National Soil DataBase, Agriculture and Agri-Food Canada. 1997.'Climate5180', Version 1.0, National Soil DataBase, Agriculture and Agri-Food Canada. 1997.Coordinate System: Web Mercator Auxiliary Sphere (WKID 102100)

Growing Degree Days (GDDs) are used to estimate the growth and development of plants and insects during the growing season. Insect and plant development are very dependent on temperature and the daily accumulation of heat. The amount of heat required to move a plant or pest to the next development stage remains constant from year to year. However, the actual amount of time (days) can vary considerably from year to year because of weather conditions. Base temperatures are a point below which development does not occur for the organism in question. Base 0 temperatures are commonly used for cereals. These values are calculated across Canada in 10x10 km cells.

This dataset provides values for TEMPERATURE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Gridded monthly mean temperature anomalies derived from daily minimum, maximum and mean surface air temperatures (degrees Celsius) and anomalies derived from daily total precipitation is available at a 50km resolution across Canada. The Canadian gridded data (CANGRD) are interpolated from homogenized temperature (i.e., AHCCD datasets). Homogenized temperatures incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The anomalies are the difference between the temperature for a given year or season and a baseline value (defined as the average over 1961-1990 as the reference period). The yearly and seasonal temperature anomalies were computed for the years 1948 to 2017. The data will continue to be updated every year. For precipitation, the Canadian gridded data (CANGRD) are interpolated from adjusted precipitation (i.e., AHCCD datasets). Adjusted precipitation data incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The anomalies are the percentage difference between the value for a given year or season and a baseline value (defined as the average over 1961-1990 as the reference period). The yearly and seasonal relative precipitation anomalies were computed for the years 1948 to 2014. The data will be updated as time permits.

Monthly 30-year Average Mean Temperature represents the average monthly mean temperature calculated at a given location averaged across a 30 year period (1961-1991, 1971-2000, 1981-2010, 1991-2020). These values are calculated across Canada in 10x10 km cells.

Weather and climate extremes are often associated with substantial adverse impacts on society and the environment. Assessment of changes in extremes is of great and broad interest. This study first homogenizes daily minimum and maximum surface air temperatures recorded at 146 stations in Canada. In order to assess changes in one-in-20 year extremes (i.e., extremes with a 20-year return period) in temperature, annual maxima and minima of both daily minimum temperatures and daily maximum temperatures are derived from the homogenized daily temperature series and analyzed with a recently developed extreme value analysis approach based on a tree of generalized extreme value distributions (including stationary and non-stationary cases). The procedure is applied to estimate the changes over the period 1911 to 2010 at 115 stations, located mainly in southern Canada, and over the period 1961 to 2010 at 146 stations across Canada (including 37 stations in the North). The results show that warming is strongest for extreme low temperature and weakest for extreme high temperature and is much stronger in the Canadian Arctic than in southern Canada. Warming is stronger in winter than in summer and stronger during nighttime than daytime of the same season.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows four maps of the mean daily temperatures for January, April, July and October averaged over the 30 year period, circa 1921-1950. The mean temperature for any day is the average of the maximum and minimum temperatures for that day. The mean daily temperature for any month is the average of the mean temperatures for each day of that month.

The instrumentation was installed in June 1988 and was initially maintained by the Arctic Adaptation Division Canadian Climate Centre, Atmospheric Environment Service (CCC/AES) with field support by Geological Survey of Canada (GSC). It consists of a Campbell Scientific CR10 micrologger with meteorological sensors for air temperature an relative humidity, wind speed and direction, and solar incoming radiation. It also supports a snow depth sensor, an experimental vegetation temperature and four ground temperatures. It is powered by a 25-AH, 12-volt gel cell (a second gel cell was added in 1989) charged by a 10-watt solar panel. Hourly and Daily sampling was carried out. Data have been quality controlled and fully documented (see documentation files accompanying the data). The High Arctic Integrated Research and Monitoring Area (IRMA) of the GSC was established on Fosheim Peninsula to support interdisciplinary studies related to environmental change. Research carried out between 1989 and 1994, had as primary objective to determine relationships between geomorphic processes and climate in order to help predict the potential geologic impact of global change. Establishment of detailed paleoclimatic records for this region has also been considered essential to provide a context for ongoing climate change. Paleoecological studies (records of peat cores, lakes cores, ice cores, sea cores and archeological records) in concert with other methodologies have been used to outline climatic variability (short, middle or long-term variabilities) and are a primary research component in the region. A major compilation of 20 papers has been produced (see Garneau in press) involving 34 participants from government, universities and industry. The synthesis includes the results from studies of modern conditions (climate, flora and fauna), quaternary geology and glacial history, paleoenvironmental records (i.e. ice cores, ocean, lakes, peat, archeological sites), permafrost dynamics and hydrologic systems. Nine appendices complete the document including a comprehensive bibliography and various data series (climate, vegetation, insects, geophysics, plant and arthropod macrofossils and radiocarbon dates) to provide background forfuture projects in the area. These data are on the CAPS Version 1.0 CD-ROM, and were identified for inclusion through the efforts of Kathy Young, Ph.D. graduate of Department of Geography, McMaster University, Hamilton, Ontario.

The data consist of homogenized daily maximum, minimum and mean surface air temperatures for more than 330 locations in Canada; adjusted daily rainfall, snowfall and total precipitation for more than 460 locations. The data are given for the entire period of observation. Please refer to the papers below for detailed information regarding the procedures for homogenization and adjustment. References: Mekis, É. and L.A. Vincent, 2011: An overview of the second generation adjusted daily precipitation dataset for trend analysis in Canada. Atmosphere-Ocean, 49(2), 163-177. Vincent, L. A., X. L. Wang, E. J. Milewska, H. Wan, F. Yang, and V. Swail, 2012. A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis, J. Geophys. Res., 117, D18110, doi:10.1029/2012JD017859. Wang, X.L, Y. Feng, L. A. Vincent, 2013. Observed changes in one-in-20 year extremes of Canadian surface air temperatures. Atmosphere-Ocean. Doi:10.1080/07055900.2013.818526.

The map shows the mean January daily temperature based on the 30-year period 1941-1970. The lowest mean January daily temperatures are below -35 degrees Celsius and are located on Ellesmere Island and on Axel Heiberg Island and south of the Boothia Peninsula in Nunavut. The highest mean January daily temperatures are above 0 degrees Celsius and are located on the west coast of British Columbia. Generally, the mean increases from north to south, from -35 to -2.5 degrees Celsius. In Canada temperature regimes change drastically from season to season, and even within a season there are often marked changes which affect the whole nature and character of outside activities. The major factors that affect temperature are latitude and thus the length of daylight; elevation; distribution of land and water; and prevailing winds and storm tracks. Although the least direct and the least intense incoming solar radiation occurs in December, there is a lag in the cooling of the Earth’s surface. As a result, the coldest month in Canada is normally January. All temperature reporting stations in Canada are equipped with self-registering maximum and minimum thermometers, which are mounted in standard louvred instrument shelters. Ideally, the shelters are located a little more than a metre above the ground in open spaces that are considered to be representative of the area. The thermometers are read once or several times each day to obtain daily maximum and minimum temperature values. Daily values of maximum and minimum temperature are collected every month from approximately 2000 stations across Canada. From these data, various statistics, such as monthly means, are calculated. The mean daily maximum temperature for any month is the mean of all daily maximum temperatures recorded in that particular month for the period of record. The mean daily minimum temperature is calculated similarly. The mean daily temperature for the month is the average of the mean daily maximum and mean daily minimum values. For obvious socio-economic reasons, the climatological stations used in the analysis are not uniformly located across Canada. The majority are situated in populated areas along the southern fringe of the country. In the mountainous regions of western Canada, most of the stations are located in accessible valleys, and the pattern of the maps is generally indicative of valley conditions only. No attempt was made to allow for detailed topographic effects, as such a pattern would be too complicated to display on the scale used.

Contained within the 2nd Edition (1915) of the Atlas of Canada is a plate that shows 9 maps. Four maps show the average possible hours of sunshine for Canada in the summer months. There is a map for the entire summer and individual maps for each of the summer months (June, July, and August. The other five maps show the number of days during the year with temperatures above 32 degrees F (0 degrees C), 40 degrees F (4.4 degrees C), 50 degrees F (10 degrees C), 60 degrees F (15.6 degrees C) and 70 degrees F (21.1 degrees C). The temperature differences are indicated with solid or dashed red lines indicating the number of days each portion of Canada will experience above temperatures indicated. In some of the maps, major railway systems are shown.

As cities face rising temperatures, increased frequency of extreme weather events, and altered precipitation patterns, buildings are subjected to increasing energy demand, heat stress, thermal comfort issues, and decreased service life. Therefore, evaluating building performance under changing climate conditions is essential for building sustainable and resilient communities. Unique climate characteristics of cities, such as the urban heat island effect, are not well simulated by global or regional climate models, and is therefore often not included in typical building analyses. Consequently, a computationally efficient approach is used to generate “urbanized” climate data, derived from regional climate models, to prepare building simulation climate data that incorporate urban effects. We demonstrate this process using existing climate data for Toronto airport’s weather station and extend it to prepare projections for scenarios where nature-based solutions, such as increased greenery and albedo, were implemented. We find significant improvements in the representation of the urban heat island and subsequent cooling effects of nature-based solutions in the urbanized climate data. This dataset allows building practitioners to evaluate building performance under historical and potential future changes in climate, considering the complex interactions within the urban canopy and the implementation of mitigation efforts such as nature-based solutions.

This dataset contains hourly historical and future weather files for use in building simulations for the city of Toronto, Canada. While similar weather files are usually based on measurements taken at a city's nearby airport, the current dataset utilizes a novel statistical-dynamical downscaling technique which involves the use of the dynamical Weather Research and Forecasting (WRF) model combined with a statistical approach and climate projections from an ensemble of 15 Canadian Regional Climate Model 4 (CanRCM4) to generate urban climate data which includes the effects of the urban heat island and different nature-based solutions (NBS) as mitigation strategies (such as increasing surface albedo and greenery). Additionally, different levels of implementation of these mitigation strategies were produced, for example, when the albedo is increased to 0.40 (ALBD40) and 0.80 (ALBD80), and similarly for the green and combined scenarios, GRN40, GRN80, COMB40, and COMB80. The URBAN scenario is considered the control case where the urban heat island effects are accounted for in the data, but the NBS scenarios are not yet implemtned.

The data are stored in large CSV files, where the rows consists of all 15 realizations of the CanRCM4 ensemble and the variables make up the columns. For example, each 31-year period is repeated 15 times, once for each of the RCM realizations. Therefore, there are 4,073,400 (15x31x8760) rows in each file. We recommend viewing the data using packages from Python or R.

The historical and future global warming thresholds and their corresponding time periods are as follows:

Global Warming Scenario

Time Period

Historical

1991-2021

Global Warming 0.5ºC

2003-2033

Global Warming 1.0ºC

2014-2044

Global Warming 1.5ºC

2024-2054

Global Warming 2.0ºC

2034-2064

Global Warming 2.5ºC

2042-2072

Global Warming 3.0ºC

2051-2081

Global Warming 3.5ºC

2064-2094

The following variables are included in the files:

Variable Description

RUN Run number (R1-R15) of Canadian Regional Climate Model, CanRCM4 large ensemble associated with the selected reference year data

YEAR Year associated with the record

MONTH Month associated with the record

DAY Day of the month associated with the record

HOUR Hour associated with the record

YDAY Day of the year associated with the record

DRI_kJPerM2 Direct horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)

DHI_kJperM2 Diffused horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)

DNI_kJperM2 Direct normal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)

GHI_kJperM2 Global horizontal irradiance in kJ/m2 (total from previous HOUR to the HOUR indicated)

TCC_Percent Instantaneous total cloud cover at the HOUR in % (range: 0-100)

RAIN_Mm Total rainfall in mm (total from previous HOUR to the HOUR indicated)

WDIR_ClockwiseDegFromNorth Instantaneous wind direction at the HOUR in degrees (measured clockwise from the North)

WSP_MPerSec Instantaneous wind speed at the HOUR in meters/sec

RHUM_Percent Instantaneous relative humidity at the HOUR in %

TEMP_K Instantaneous temperature at the HOUR in Kelvin

ATMPR_Pa Instantaneous atmospheric pressure at the HOUR in Pascal

SnowC_Yes1No0 Instantaneous snow-cover at the HOUR (1 - snow; 0 - no snow)

SNWD_Cm Instantaneous snow depth at the HOUR in cm

Gridded monthly, seasonal and annual mean temperature anomalies derived from daily minimum, maximum and mean surface air temperatures (degrees Celsius) is available at a 50km resolution across Canada. The Canadian gridded data (CANGRD) are interpolated from homogenized temperature (i.e., AHCCD datasets). Homogenized temperatures incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The anomalies are the difference between the temperature for a given year or season and a baseline value (defined as the average over 1961-1990 as the reference period). The yearly and seasonal temperature anomalies were computed for the years 1948 to 2017. The data will continue to be updated every year.