The dataset shows the distribution and spatial extent of the 3D models that were created in the context of Canadian aquifers mapping projects from the Geological Survey of Canada.

To support improved groundwater geoscience knowledge for southern Ontario, a regional 3-D model of the surficial geology of southern Ontario has been developed as a part of a collaboration between the Ontario Geological Survey and the Geological Survey of Canada. Covering approximately 66,870 km2 in area, the model is a synthesis of existing geological models, surficial geology mapping, and subsurface data. The model is a simplified 9-layer reclassification of numerous mapped local surficial sediment formations in places over 200 m thick with a total volume of approximately 2,455 km3. The model integrates 1:50,000 scale surficial geology mapping with 90 m bathymetrically corrected topographic digital elevation model (DEM) and 8 existing local 3-D models. Archival subsurface data include 10,237 geotechnical and stratigraphic boreholes, 3,312 picks from geophysical surveys, 15,902 field mapping sites and sections, 537 monitoring and water supply wells and 282,995 water well records. Roughly corresponding to regional aquifer and aquitard layers, primary model layers are (from oldest to youngest): Bedrock, Basal Aquifer, Lower Sediment, Regional Till, Post Regional Till Channel Fill, Glaciofluvial Sediment, Post Regional Till Mud, Glaciolacustrine Sand and Recent Sediment / Organics. Modelling was completed using an implicit modelling application (LeapFrog®) complemented by an expert knowledge approach to data classification and rules-based Expert System procedure for data interpretation and validation. An iterative cycle of automated data coding, intermediate model construction and manual data corrections, expert evaluations, and revisions lead to the final 3-D model. A semi-quantitative confidence assessment has been made for each model layer surface based on data quality, distribution and density. This surficial geology model completes the development of a series of regional 3-D geological and hydrogeological models for southern Ontario.

Digital terrain models offer a representation of the relief south of the 52nd parallel, in the form of an elevation matrix. This matrix makes it possible to visualize the territory in perspective and to perform three-dimensional spatial analyses, using appropriate software.A module specialized in three-dimensional data processing, such as 3D Analyst or Spatial Analyst, is required to visualize the digital altitude model in three dimensions.This digital altitude model (10-meter pixel matrix) is obtained by processing altimeter data (level curves and elevation points) from ** [topographic databases on a scale of 1/20,000] (https://www.donneesquebec.ca/recherche/fr/dataset/cartes-topographiques-a-l-echelle-de-1-20-000) **.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Digital model of 3D LOD2 buildings with textures in CityGML, 3DM and GDB format and in DWG format without textures of some Montreal boroughs.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Digital model of 3D LOD2 buildings with textures in CityGML and 3DM format of some boroughs of Montreal.The [digital terrain model (MNT)] (https://donnees.montreal.ca/dataset/modele-numerique-de-terrain-mnt) of these districts is also available to present the complete digital model of the territory.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Digital model of 3D LOD2 buildings with textures of the Le Sud-Ouest and Ville-Marie borough in CityGML and 3DM format.The [digital terrain model (MNT)] (/city-of-montreal/model-numerique-de-terrain-mnt) of the borough is also available to present the complete digital model of the territory.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Digital model of 3D LOD2 buildings with textures in CityGML, 3DM and GDB format and in DWG format without textures of some Montreal boroughs.[The digital terrain model (MNT)] (https://donnees.montreal.ca/ville-de-montreal/modele-numerique-de-terrain-mnt) of some districts is also available to present the complete digital model of the territory.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The numerical canopy model (MNC) is a representation of the altitude of the canopy. This 3D representation of the arboreal vegetation corresponds to the 2015 2D canopy.If necessary, the MNC can be coupled with the [Numerical Surface Model (MNS)] (/city-of-montreal/numeric-surface-model) 2015 in order to obtain more detailed coverage.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Multi-model ensembles for a suite of variables based on projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs) are available for 1850-2100 on a common 1x1 degree global grid. Climate projections vary across GCMs due to differences in the representation and approximation of earth systems and processes, and natural variability and uncertainty regarding future climate drivers. Thus, there is no single best climate model. Rather, using results from an ensemble of models (e.g., taking the average) is best practice, as an ensemble takes model uncertainty into account and provides more reliable climate projections.Provided on Canadian Climate Data and Scenarios (CCDS) are four types of products based on the CMIP6 multi-model ensembles: time series datasets and plots, maps and associated datasets, tabular datasets, and global gridded datasets. Monthly, seasonal, and annual ensembles are available for up to six Shared Socioeconomic Pathways (SSPs) (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-6.0, and SSP5-8.5), four future periods (near-term (2021-2040), mid-term (2041-2060 and 2061-2080), end of century (2081-2100)), and up to five percentiles (5th, 25th, 50th (median), 75th, and 95th) of the CMIP6 ensemble distribution. The number of models in each ensemble differs according to model availability for each SSP and variable, see the model list resource for details on the models included in each ensemble. The majority of products show projected changes expressed as anomalies according to a historical reference period of 1995-2014. The products provided include global, national, and provincial/territorial datasets and graphics. For more information on the CMIP6 multi-model ensembles, see the technical documentation resource.

Data from the analysis of sea surface temperature, sea surface salinity, bottom temperature, and bottom salinity, over the Gulf of Maine and Scotian Shelf, for 23 CMIP6 models. The analysis includes an evaluation of CMIP6 model performance for the CMIP6 historical (1950-2014) experiment. Future projections are summarized for CMIP6 scenarios SSP245 and SSP370 with the calculation of relative annual and seasonal changes between the historical period (1950-2014) and three future periods (2030-2039, 2040-2049, 2030-2049).Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D., Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 models. Can. Tech. Rep. Hydrogr. Ocean. Sci. XXX: vii + XXXp.Cite this data as: Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D. Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 Models. Published July 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6247bb5a-14b3-461d-9ed3-b42553107bbc