Statistically downscaled multi-model ensembles of maximum temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. The 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of downscaled maximum temperature (°C) are available for the historical time period, 1951-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in maximum temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected change in maximum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected maximum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of maximum temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled maximum temperature (°C) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of downscaled CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

Statistically downscaled multi-model ensembles of mean temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). Historical gridded minimum and maximum temperature datasets of Canada (ANUSPLIN) were used as the respective downscaling targets. The 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of downscaled mean temperature (°C) are available for the historical time period, 1951-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

This dataset represents the digital compilation of the Mineral Assessment Airborne surveys of the Province of Saskatchewan.This dataset represents the digital compilation of the Mineral Assessment Airborne surveys of the Province of Saskatchewan.  This data shows Mineral Assessment Work Catalogue: Outlines of areas and descriptions of work submitted for mineral assessment credits (Airborne surveys). This is an ongoing assemblage of mineral assessment airborne surveys. The data was created as a file geodatabase feature class and output for public distribution.**Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse.  They are therefore identical and share the same refresh schedule.

Annual and five-year (5YA) average wet deposition maps for the ammonium ion are available. The file formats include geodatabase files (*.gdb) compatible with geospatial software (e.g. ESRI ArcGIS) and KMZ files compatible with virtual globe software (e.g. Google Earth™). Maps can also be viewed online via Open Maps and the ArcGIS online viewer. Annual deposition from each site was screened for completeness using the following criteria: (1) precipitation amounts were recorded for >90% of the year and >60% of each quarter, and (2) ammonium concentrations were reported for >70% of the precipitation measured over the year and for >60% of each quarter. Five-year average wet deposition values are averaged annual deposition values with a completeness criterion >60% for the five-year period. Units for wet deposition fluxes are in kg of NH4 per hectare per year (kg ha-1 y-1). Sources of measurement data and spatial interpolation method are described here: https://doi.org/10.18164/e8896575-1fb8-4e53-8acd-8579c3c055c2. Recommended citation: Environment and Climate Change Canada, [year published]. NH4 Wet Deposition Maps. Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada. [URL/DOI], accessed [date].Recommended acknowledgement: The author(s) acknowledge Environment and Climate Change Canada for the provision of Canada-U.S. wet deposition kriging maps accessed from the Government of Canada Open Government Portal at open.canada.ca, and the data providers referenced therein.

Background:More than 80% of the heat produced in the Earth's crust comes from granitoid rocks. When granitoid rocks form they naturally concentrate radioactive elements such as U, Th, and K, and the radiogenic decay of these elements is an exothermic reaction. The radioactive decay of these elements within a granitoid body may generate local heat anomalies and elevated geothermal gradient at relatively shallow crustal levels. In combination with other local rock properties (e.g, porosity, permeability, thermal conductivity), radiogenic heat has the potential to generate a geothermal resource. The decay of radioactive elements converts mass into radiation energy, which in turn gets converted to heat. While all naturally radioactive isotopes generate some heat, significant heat generation only occurs from the decay of 238 U ,235 U ,232 Th and 40 K. Therefore, potential heat production is governed by the concentrations of U ,Th and K in the rock. In igneous rocks, radiogenic heat production is dependent on the bulk chemistry of the rock and decreases from acidic (e.g. granite) through basic to ultra basic rock types. Therefore, granites with anomalously high concentrations of U ,Th and K are targets for calculating potential radiogenic heat production. Potential radiogenic heat production (A)from plutonic rocks can be calculated using this equation:A (\\u03BCW/m 3 )=10 -5 \\u1D29 (9.52c u +2.56c K +3.48c Th )where "c" is the concentration of radioactive elements "U" and "Th" in ppm, and "K" in %; and "\\u1D29" is the rock density. Heat production constants of the natural radio-elements U, Th, K are 9.525x10 -5 , 2.561x10 -5 and 3.477x10 -9 W/kg, respectively.Data and Methods:Geochemical data from \~1760 samples of plutonic rocks from Yukon are used to calculate potential heat production. The calculated values for radiogenic heat production (A) are plotted over the mapped distribution of Paleozoic and younger plutonic rocks and major crustal faults are also shown for reference.

Geochronology is a discipline of geoscience which measures the age of earth materials and provides the temporal framework in which other geoscience data can be interpreted in the context of Earth history. This knowledge helps to answer questions such as when did a volcano last erupt, what is the rate of crustal uplift in a specific area, are rocks at one gold prospect the same age as those at another.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Locations of automated snow weather stations, active and inactive. Automated snow weather stations are components of the BC snow survey network.

High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**