This is a polygon dataset illustrating the areal extent (surface and subsurface) of the Haynes aquifer. It is in ESRI shapefile format.

This dataset is a grid of the thickness of the Haynes aquifer within the Paskapoo Formation. The Haynes aquifer is a regionally extensive body of sand that lies in the bottom part of the Paskapoo Formation. The isopach was created from the modelled results of the average sandiness of 25 m thick slices in boreholes completed within the Paskapoo Formation. Parts of the aquifer are as much as 100 m thick, particularly in the west near the deformation belt and in a region west of the city of Red Deer. The bulk of the unit averages about 50 m in thickness. Given the great range in elevation of the top of the unit, but the relatively uniform thickness of the bulk of the aquifer, we inferred that most of the Haynes aquifer was deposited prior to major deformation with only the western-most parts showing evidence of infill of enhanced accommodation space. Most of the Haynes aquifer is overlain by thick muddy sediments of the Lacombe Member and only outcrops along its eastern edge.

This is a 1000 m cell-sized raster grid dataset of the top of the sandstone of the Haynes member of the Paskapoo Formation. We mapped the sandstone using 3-D geostatistical modelling algorithms from data derived from sand calculations of 25 m thick slice intervals of the Paskapoo Formation. We selected the >55% sand isovalue to define sandstone, based on the results of mini-models that show vertical hydraulic connections being established if sand abundance is 55% or greater. This grid represents the upper surface of that three-dimensional body defined by the >55% sand threshold value. Alberta Geological Survey Bulletin 66 provides a detailed description of how the unit was defined. The dataset is in ESRI ASCII grid format.

This service shows the proportion of average total income of households which is spent on shelter costs by census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Shelter-cost-to-income ratio is calculated for private households living in owned or rented dwellings who reported a total household income greater than zero.Private households living in band housing, located on an agricultural operation that is operated by a member of the household, and households who reported a zero or negative total household income are excluded.The relatively high shelter-costs-to-household income ratios for some households may have resulted from the difference in the reference period for shelter costs and household total income data. The reference period for shelter cost data is 2016, while household total income is reported for the year 2015. As well, for some households, the 2015 household total income may represent income for only part of a year.For additional information refer to the 2016 Census Dictionary for 'Total income' and 'Shelter cost'.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

This service shows the proportion of average total income of households which is spent on shelter costs by census division. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.Shelter-cost-to-income ratio is calculated for private households living in owned or rented dwellings who reported a total household income greater than zero.Private households living in band housing, located on an agricultural operation that is operated by a member of the household, and households who reported a zero or negative total household income are excluded.The relatively high shelter-costs-to-household income ratios for some households may have resulted from the difference in the reference period for shelter costs and household total income data. The reference period for shelter cost data is 2016, while household total income is reported for the year 2015. As well, for some households, the 2015 household total income may represent income for only part of a year.For additional information refer to the 2016 Census Dictionary for 'Total income' and 'Shelter cost'.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.

The Regional Ensemble Prediction System (REPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the current day out to 3 days into the future. The probabilistic predictions are based on 20 ensemble members that are perturbed through their initial and boundary conditions as well as physical tendencies. A control member that is not perturbed is also available. Atmospheric elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage includes Canada and the United States. Data is available at a horizontal resolution of 10 km. Data is available on ten vertical levels. Predictions are performed four times a day.

This digital data release includes adsorption isotherm and proximate analysis results of selected samples for shale- and siltstone-hosted hydrocarbons. The strata evaluated include the: - basal Banff Formation, - Colorado Group, - Duvernay Formation, - Exshaw Formation, - Montney Formation, - Muskwa Formation, - Wilrich Member, - Nordegg Member, and - Rierdon Formation.

This dataset represents the 2010 electoral districts of New Brunswick as polygons. Each district is represented by one Member of the Legislative Assembly (MLA). Attributes: District names, District Number, Poll numbers, MLA Names

This dataset represents the 2020 electoral districts of New Brunswick as polygons. Each district is represented by one Member of the Legislative Assembly (MLA). Attributes: District names, District Number, Poll numbers, MLA Names

The Global Ensemble Prediction System (GEPS) carries out physics calculations to arrive at probabilistic predictions of atmospheric elements from the current day out to 16 days into the future (up to 39 days twice a week on Mondays and Thursdays at 00UTC for calculating forecast anomalies). The GEPS produces different outlooks (scenarios) to estimate the forecast uncertainties due to the nonlinear (chaotic) behavior of the atmosphere. The probabilistic predictions are based on an ensemble of 20 scenarios that differ in their initial conditions, their physics parameters which are randomly perturbed by a Stochastic Parameter Perturbation (SPP) method, and the stochastic perturbations (kinetic energy). A control member that is not perturbed is also available. Weather elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage is global. Data is available on some fifteen vertical levels on a global latitude-longitude uniform grid with 0.5 degree horizontal resolution (about 39km). Predictions are performed twice a day.