A Virtual Climate station is the result of threading together climate data from proximate current and historical stations to construct a long term threaded data set. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. The length of the time series of virtual stations is often greater than 100 years. A Virtual Climate station is always named for an “Area” rather than a point, e.g. Winnipeg Area, to indicate that the data are drawn from that area (within a 20km radius from the urban center) rather than a single precise location.

The Air Quality Health Index (AQHI) is a scale designed to help quantify the quality of the air in a certain region on a scale from 1 to 10. When the amount of air pollution is very high, the number is reported as 10+. It also includes a category that describes the health risk associated with the index reading (e.g. Low, Moderate, High, or Very High Health Risk). The AQHI is calculated based on the relative risks of a combination of common air pollutants that are known to harm human health, including ground-level ozone, particulate matter, and nitrogen dioxide. The AQHI formulation captures only the short term or acute health risk (exposure of hour or days at a maximum). The formulation of the AQHI may change over time to reflect new understanding associated with air pollution health effects. The AQHI is calculated from data observed in real time, without being verified (quality control).

Current conditions and forecasts for selected Canadian cities. Raw XML data are used to generate each city page on the Environment Canada web site https://www.weather.gc.ca/.

Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Snowfall for each day of the year. Daily elements include: Greatest Snowfall.

Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Temperature for each day of the year. Daily elements include: High Maximum, Low Maximum, High Minimum, Low Minimum.

Climate observations are derived from two sources of data. The first are Daily Climate Stations producing one or two observations per day of temperature, precipitation. The second are hourly stations that typically produce more weather elements e.g. wind or snow on ground.

Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Precipitation for each day of the year. Daily elements include: Greatest Precipitation.

The Air Quality Health Index (AQHI) is a scale designed to help quantify the quality of the air in a certain region on a scale from 1 to 10. When the amount of air pollution is very high, the number is reported as 10+. It also includes a category that describes the health risk associated with the index reading (e.g. Low, Moderate, High, or Very High Health Risk). The AQHI is calculated based on the relative risks of a combination of common air pollutants that are known to harm human health, including ground-level ozone, particulate matter, and nitrogen dioxide. The AQHI formulation captures only the short term or acute health risk (exposure of hour or days at a maximum). The formulation of the AQHI may change over time to reflect new understanding associated with air pollution health effects. The AQHI is calculated from data observed in real time, without being verified (quality control).

The Canadian Lightning Detection Network (CLDN) provides lightning monitoring across most of Canada. The data distributed here represents a spatio-temporal aggregation of the observations of this network available with an accuracy of a few hundred meters. More precisely, every 10 minutes, the reported observations are processed in the following way: The location of observed lightning (cloud-to-ground and intra-cloud) in the last 10 minutes is extracted. Using a regular horizontal grid of about 2.5km by 2.5km, the number of observed lightning flashes within each grid cell is calculated. These grid data are normalized by the exact area of each cell (in km2) and by the accumulation period (10min) to obtain an observed flash density expressed in km-2 and min-1. A mask is applied to remove data located more than 250km from Canadian land or sea borders.

The Regional Ice-Ocean Prediction System (RIOPS) is based on the NEMO-CICE ice-ocean model and produces regional sea ice and ocean analyses and 84 hours forecasts daily based at [00, 06, 12, 18] UTC on a subset of the 1/12° resolution global tri-polar grid (ORCA12). RIOPS assimilates data (gridded CCMEP analysis SST product, SLA from satellite altimetry, in situ observations) using a multivariate reduced order Kalman filter and includes a 3DVar ice concentration analysis (assimilating satellite remote sensing and Canadian Ice Service ice charts). Atmospheric fluxes for 84 hours forecasts are calculated using fields from a blending of the Regional Deterministic Prediction System (RDPS) and the Global Deterministic Prediction System (GDPS).