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.

Statistical post-processing of weather and environmental forecasts issued by numerical models, including the Regional Deterministic Prediction System (RDPS), reduces systematic bias and error variance of raw numerical forecasts. This is achieved by establishing an optimal relationship between observations recorded at stations and co-located numerical model outputs. The Updatable Model Output Statistics (UMOS) system at Environment Canada carries out this task. The statistical relationships are built using the Model Output Statistics (MOS) method and a multiple linear regression (MLR) technic. The weather and environmental variables being statistically post-processed by UMOS include air temperature and dew point temperature at approximately 1.5 meters above ground as well as wind speed and direction at 10 meters above ground or at the anemometer level in the case of a buoy. The absence of a statistically post-processed forecast can be caused by a missing statistical model due to insufficient observation data quality or quantity. In addition, the absence of a post-processed forecast for wind direction could also be due to weak forecasted wind components preventing the calculation of reliable results. The forecasts of wind speed and direction are produced from independent statistical post-processing models. Geographical coverage includes weather stations across Canada. Statistically post-processed forecasts is available at the same frequency of emission as the numerical model producing the raw forecasts and at 3-hourly lead times for the RDPS.

The Costal Flooding Risk Index in GeoJSON format is a geo and time referenced polygon product issued by the Meteorological Service of Canada (MSC) to articulate the coastal flooding risk, impact and probability. Products are issued daily by Storm Prediction Centres and intended to provide early notification, out to 5 days, of coastal flooding due to astronomical tide, storm surge and wave impacts.

Statistical post-processing of weather and environmental forecasts issued by numerical models, including the Global Deterministic Prediction System (GDPS), reduces systematic bias and error variance of raw numerical forecasts. This is achieved by establishing an optimal relationship between observations recorded at stations and co-located numerical model outputs. The Updatable Model Output Statistics (UMOS) system at Environment Canada carries out this task. The statistical relationships are built using the Model Output Statistics (MOS) method and a multiple linear regression (MLR) technic. The weather and environmental variable being statistically post-processed by UMOS consists of air temperature at approximately 1.5 meters above ground. The absence of a statistically post-processed forecast can be caused by a missing statistical model due to insufficient observation data quality or quantity. Geographical coverage includes weather stations across Canada. Statistically post-processed forecasts are available at the same frequency of emission as the numerical model producing the raw forecasts and at 3-hourly lead times up to 144 hours (6 days) for the GDPS.

Standardized zoning v1**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Flood zones standard v1**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

V1 standard bike paths**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Climate Normals and Averages are used to summarize or describe the average climatic conditions of a particular location. At the completion of each decade, Environment and Climate Change Canada updates its Climate Normals for as many locations and as many climatic characteristics as possible. The Climate Normals, Averages and Extremes offered here are based on Canadian climate stations with at least 15 years of data between 1981 to 2010.

The residual materials collection calendar distributed according to the partners' standard.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Standardized waste collection v1**This third party metadata element was translated using an automated translation tool (Amazon Translate).**