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).

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.

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/.

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 Regional Ensemble storm Surge Prediction System (RESPS) produces storm surge forecasts using the DalCoast ocean model. DalCoast (Bernier and Thompson 2015) is a storm surge forecast system for the east coast of Canada based on the depth-integrated, barotropic and linearized form of the Princeton Ocean Model. The model is forced by the 10 meters winds and sea level pressure from the Global Ensemble Prediction System (GEPS).

HREPA is part of the NSRPS (National Surface and River Prediction System) experimental system dependent on two other systems. It uses surface station observations and radar QPEs pre-processed by HRDPA and disturbed trial fields generated by the Canadian Land Data Assimilation System (CaLDAS). HREPA produces four precipitation analyses per day on 6-hour accumulations valid at synoptic times (00, 06, 12, and 18 UTC). Each analysis set contains 24 members plus the control member. A quality index (confidence index) is also available on the same grid as the precipitation fields. Finally, two percentiles, 25th and 75th, estimated on these sets are also provided for each synoptic hour. Currently, there is only a high-resolution version of the system, whose domain covers Canada and the northern United States with a horizontal resolution of about 2.5km.

A station is a site on a river or lake where water quantity (water level and flow) are collected and recorded.

The High Resolution Deterministic Land Prediction System (HRDLPS) produces high-resolution medium-range forecasts of land surface, subsurface variables, and of near-surface atmospheric variables (1.5 m temperature and dewpoint, 10 m wind). HRDLPS is initialized with analysis and trial fields provided by the Canadian Land Data Assimilation System of the National Surface and River Prediction System (CaLDAS-NSRPS). The system is then driven with atmospheric forecasts provided by the HRDPS over the first two days of integration and by the GDPS over the next four days. Predictions are performed twice a day. The system runs on a grid with a 2.5 km horizontal spacing covering Canada and part of the USA.

CaLDAS-NSRPS was installed as an experimental system within the National Surface and River Prediction System (NSRPS) at Environment and Climate Change Canada's (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP) in July 2019. CaLDAS-NSRPS is a continuous offline land-surface assimilation system, which provides analyses of the land surface every 3 h over the domain of the High-Resolution Deterministic Prediction System (HRDPS) at a 2.5 km grid spacing. The emphasis in CaLDAS-NSRPS is to focus upon the assimilation of satellite based remote sensing observations to provide the optimal initial conditions for the predictive components of the NSRPS, the High Resolution Deterministic/Ensemble Land Surface Prediction System (HRDLPS/HRELPS) and the Deterministic/Ensemble Hydrological Prediction Systems (DHPS/EHPS). CaLDAS-NSRPS is launched 4 times per day, at 0000, 0600, 1200, and 1800 UTC.

MetNotes are a geo- and time-referenced, free form polygon product issued by MSC that complement today's location-based dissemination systems. The concise text of a MetNote (similar to a Tweet) is consistent with communication today where people are seeking information at a glance. Meteorologists will issue a MetNote to add contextual and/or impact information to complement the public forecast that is valid over a specific area, for a specific time range.