The set contains geospatial data for snow removal sectors in the City of Montreal as well as the boroughs associated with them. The packages on the [snow disposal sites] (/city-of-montreal/depot-snow), the [contracts and transactions] (/city-of-montreal/contrats-transaction-de-neigement) are also available on the portal.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Location of free and paid parking lots available during snow removal operations. The data is also visible on the [Info-Neige MTL] application (https://montreal.ca/sujets/deneigement-des-trottoirs-et-des-rues) and on the [snow removal operations map] (https://montreal.ca/services/carte-des-operations-de-deneigement).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Data set containing the list and location of snow disposal sites used by the City of Montreal during snow loading periods, including information on each site. The packages on the [snow removal sectors] (/city-of-montreal/sector-deenigement), the [contracts and transactions] (/city-of-montreal/contrats-transaction-de-enigement) are also available on the portal.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Snow and ice are important hydrological resources. Their minimum spatial extent here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. The MSI probability is derived from sequence of seventeen 10-day clear-sky composites corresponding to April, 1 to September, 20 warm period for each year since 2000. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period since 2000 have been processed with the special technology developed at the Canada Centre for Remote Sensing (CCRS) as described in Trishchenko, 2016; Trishchenko et al., 2016; 2009, 2006, Trishchenko and Ungureanu, 2021, Khlopenkov and Trishchenko, 2008, Luo et al., 2008. The presence of snow or ice is determined for each pixel of the image based on snow/ice scene identification procedure and the probability if computed for the entire warm season as a ratio of number of snow/ice flags to the total number of pixels available (less or equal to 17). The minimum snow and ice extent can be derived from the probability map by applying a certain threshold. New data version V5.0 replaces previous version V4.0 for all data available since 2000. All MSI files were reprocessed for all MODIS input data based on collection 6.1. The output format has not changed since previous version. It is described in Trishchenko (2024). The impact of input data change is small and can be detected only for time interval 2000-2015. Data starting 2016 has been already derived using MODIS collection 6.1 input. The differences between the MSI data based on MODIS Collection 5 (i.e. MSI V4) versus MODIS Collection 6.1 (i.e. MSI V5), on average, are quite small. The region-wide relative difference in the MSI extent varies from -3.97% to +1.75%. The mean value is -0.14%, the median value is 0.18% and standard deviation is 1.83%. As such, we do not expect any sizeable impact of the version change on our previous conclusions regarding trends and climate variations, except for refining the relative values of statistical parameters within the range of a few percents. References: TRISHCHENKO, A.P., 2024: Probability maps of the annual minimum snow and ice (MSI) presence over April,1 to September, 20 period since 2000 derived from MODIS 250m imagery over Canada and neighbouring regions. Data format description. CCRS, NRCan. 4pp.

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.

The Annual Minimum Snow and Ice (MSI) Extent of the Atlas of Canada National Scale Data, are data sets compiled containing annual data from 2000 to present. The data sets were derived from research published by the Canada Centre for Remote Sensing which classified satellite imagery over Canada and neighbouring regions for the continued presence or absence of snow and ice from April 1 to September 20 each year. The Atlas of Canada MSI products consist of a vector dataset and a raster time-series animation application. VECTOR DATASET The vector dataset has been generalized to display at the scale of 1:1,000,000. TIME-SERIES ANIMATION APPLICATION The time-series animation application has not been generalized from its original scale (250 m pixels). The application is disseminated through the Data Cube Platform, implemented by the Canada Centre for Mapping and Earth Observation, Natural Resources Canada using geospatial big data management techniques. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The time-series is also available as a Web Map Service (WMS) and Web Coverage Service (WCS). CREDIT Source data provided by Alexander P. Trishchenko, Canada Centre for Remote Sensing, Natural Resources Canada Metadata record: https://open.canada.ca/data/en/dataset/808b84a1-6356-4103-a8e9-db46d5c20fcf

GeoMet-Météo du SMC rend publiquement accessible les données du Service météorologique du Canada (SMC) et d'Environnement et Changement climatique Canada (ECCC) via des services web interopérables et des interfaces de programme (API). Par le biais de standards ouverts, ces services donnent rapidement et gratuitement accès à des milliers de jeux de données et produits météorologiques, climatiques et hydrométriques en temps réel et archivés qui peuvent être intégrés dans les applications spécifiques de l'usager et leurs systèmes d'aide à la décision. Les usagers peuvent développer des applications mobiles, créer des cartes interactives en-ligne, ainsi que de visualiser et animer les données du SMC dans des logiciels de bureau. Les services GeoMet du SMC rendent également possible le découpage de données et la reprojection sur demande, tout autant que la conversion de formats et la visualisation personnalisée de couches de données.

This is a map of current snow basin indices across British Columbia. Snow basin index mapping is based on analysis from the River Forecast Centre, and is meant to accompany the Snow Conditions and Water Supply Bulletins that are published for data from January 1st, February 1st, March 1st, April 1st, May 1st, May 15th, June 1st and June 15th each year. Snow data collection is managed by the Ministry of Environment and Climate Change Strategy's Snow Program.

The Canadian Seasonal to Inter-annual Prediction System (CanSIPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the beginning of a month out to up to 12 months into the future, resulting in seasonal forecasts. Atmospheric elements include temperature, precipitation, wind speed and direction and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on a grid at a horizontal resolution of 2.5 degrees and 1 degree and for a few selected vertical levels. In addition, forecast probabilities for below, near, and above normal temperature and precipitation are available at both resolutions. Predictions and corresponding hindcast are made available monthly.

Assess the importance of atmospheric deposition of contaminants as a contributor to ecological impacts of oil sands development and identify sources. • Use snowpack measurements sampled across a gridwork to develop maps of winter-time atmospheric contaminant loadings for the region ~100 km from the major upgrading facilities • Assess long-term trends in winter-time atmospheric deposition • Determine the potential impact of wintertime snowpack mercury loads on tributary river water mercury concentrations (Spring Freshet) using Geographic Information System and hydrological modelling approaches • Compare snowpack loadings to those obtained from precipitation monitoring and compare spatial patterns to PAC air measurements obtained from passive sampling network