Contained within 3rd Edition (1957) of the Atlas of Canada is a map that shows the division of Canada into climatic regions according to the classification of the climates of the world developed by W. Koppen. Koppen first divided the world into five major divisions to which he assigned the letters A, B, C, D, and E. The letters represent the range of divisions from tropical climate (A) to polar climate (E). There are no A climates in Canada. The descriptions of the four remaining major divisions are given in the map legend. Koppen then divided the large divisions into a number of climatic types in accordance with temperature differences and variations in the amounts and distribution of precipitation, on the basis of which he added certain letters to the initial letter denoting the major division. The definitions of the additional letters which apply in Canada are also given when they first appear in the map legend. Thus b is defined under Csb and the definition is, therefore, not repeated under Cfb, Dfb or Dsb. For this map, the temperature and precipitation criteria established by Koppen have been applied to Canadian data for a standard thirty year period (1921 to 1950 inclusive).

The HOT2000 software contains monthly and annual climate data for 403 locations in Canada. Boundary lines for HOT2000 climate zones were defined through spatial interpolation of the annual Celsius heating degree-days for each weather station. In a number of instances, the positions of boundary lines may not be representative of the local climate conditions due to lack of appropriate climate data. Each HOT2000 climate zone contains one weather station to be used for all locations within the zone. Climate data represent 20-year averaged data from 1998 to 2017 for locations south of 58° latitude and 13-year averaged data from 2005 to 2017 for locations north of 58° latitude. Note that Whistler, BC uses 13 years of data. The following information is available in the climate map: o Location: the name of the weather station. o Region: the provincial or territorial location of the weather station. o Latitude: measured in degrees north of the equator. o Annual heating degree-days using a base of 18 °C. o Design heating dry bulb temperature (°C): the 2.5% January design temperature used to calculate the design heat loss for the house. o Design cooling dry bulb temperature (°C): the 2.5% July design temperature used to calculate the design cooling load for the house. o Design cooling wet bulb temperature (°C): the 2.5% July design temperature used to calculate the design cooling load for the house. The climate map is intended to be used by all users of the HOT2000 software under the EnerGuide Rating System, including energy advisors, service organizations, regulatory agencies, builders, utilities, and all levels of government. The weather locations and climate data are based on Environment and Climate Change Canada data, specifically the Canadian Weather Energy and Engineering Datasets (CWEEDS).

The North American Climate Zones map shows the distribution of climate types across Canada, Mexico, and the United States based on the Köppen-Geiger climate classification. This map is derived from the global climate zones presented by Beck et al. (2018), “Present and future Köppen-Geiger climate classification maps at 1-km resolution,” and represents the spatial distribution in vector format of 29 climate zones (out of 30 global climate zones) present in North America. This map was produced by resampling the original input data spatial resolution of 0.0083 degrees to 0.016 degrees and cropping the global data to the North American region. The map was used to meet the needs of the CEC project “Improving the effectiveness of early warning systems for drought” in assessing the effectiveness of available drought indicators and indices in climate zones of North America. Reference: Beck, H., Zimmermann, N., McVicar, T. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci Data 5, 180214 (2018). https://doi.org/10.1038/sdata.2018.214 Files Download

The map title is Climate Regions. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into eight categories: Arctic, Taiga, Cordilleran, Pacific Maritime, Boreal, Prairie, Southeastern, Atlantic Maritime. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

Local climate zones have been developed in the climatology field to characterize the landscape surrounding climate monitoring stations, toward adjusting for local landscape influences on measured temperature trends. For example, a station surrounded by tall buildings may be influenced by the urban heat island effect compared to a station in an agricultural area. The local climate zone classification system was developed by Iain Stewart and Tim Oke at the University of British Columbia. The classification scheme has been adopted by the World Urban Database Access and Tools Portal (WUDAPT) project, which aims to produce local climate zone maps for the entire world at a scale of ~ 100m. Local climate zones take building and vegetation type and height into account, and therefore serve as indicators of urban form, from dense urban (high building with little vegetation) to industrial/commercial (large lowrise buildings with paved areas) and natural (dense trees, low plants, water). How local climate zones are related to human health is a new area of research.CANUE staff and students worked in collaboratation with WUDAPT researchers to map local climate zones for Canada, using scripts developed in Google Earth Engine and applied to LandSat imagery for key time periods. Each postal code has been assigned to one of 14 local climate zone classes. In adition, seven groups have been created by aggregating similar local climate zones, and the percentage of group in the neighbourhood (1km2) around each postal code has been calculated.

The map title is Climate Regions. Map scale. North arrow pointing to the north. Map projection is Hammer-Aitoff. Border of Canada. Great Lakes Border for each theme category within Canada. Neat line around the map. Each theme category is identified by a number that corresponds to the legend. Legend is divided into eight categories: Arctic, Taiga, Cordilleran, Pacific Maritime, Boreal, Prairie, Southeastern, Atlantic Maritime. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

"Vegetation Zones of Canada: a Biogeoclimatic Perspective" maps Canadian geography in relation to gradients of regional climate, as expressed by potential vegetation on zonal sites. Compared to previous similar national-scale products, "Vegetation Zones of Canada" benefits from the work of provincial and territorial ecological classification programs over the last 30+ years, incorporating this regional knowledge of ecologically significant climatic gradients into a harmonized national map. This new map, reflecting vegetation and soils adapted to climates prior to approximately 1960, can serve as a broad-scale (approximately 1:5 M to 1:10 M) geospatial reference for monitoring and modeling effects of climate changes on Canadian ecosystems. "Vegetation Zones of Canada: a Biogeoclimatic Perspective" employs a two-level hierarchical legend. Level 1 vegetation zones reflect the global-scale latitudinal gradient of annual net radiation, as well as the effects of high elevation and west to east climatic and biogeographic variation across Canada. Within the level 1 vegetation zones, level 2 zones distinguish finer scale variation in zonal vegetation, especially in response to elevational and arctic climatic gradients, climate-related floristics and physiognomic diversity in the Great Plains, and maritime climatic influences on the east and west coasts. Thirty-three level 2 vegetation zones are recognized: High Arctic Sparse Tundra Mid-Arctic Dwarf Shrub Tundra Low Arctic Shrub Tundra Subarctic Alpine Tundra Western Boreal Alpine Tundra Cordilleran Alpine Tundra Pacific Alpine Tundra Eastern Alpine Tundra Subarctic Woodland-Tundra Northern Boreal Woodland Northwestern Boreal Forest West-Central Boreal Forest Eastern Boreal Forest Atlantic Maritime Heathland Pacific Maritime Rainforest Pacific Dry Forest Pacific Montane Forest Cordilleran Subboreal Forest Cordilleran Montane Forest Cordilleran Rainforest Cordilleran Dry Forest Eastern Temperate Mixed Forest Eastern Temperate Deciduous Forest Acadian Temperate Forest Rocky Mountains Foothills Parkland Great Plains Parkland Intermontane Shrub-Steppe Rocky Mountains Foothills Fescue Grassland Great Plains Fescue Grassland Great Plains Mixedgrass Grassland Central Tallgrass Grassland Cypress Hills Glaciers Please cite this dataset as: Baldwin, K.; Allen, L.; Basquill, S.; Chapman, K.; Downing, D.; Flynn, N.; MacKenzie, W.; Major, M.; Meades, W.; Meidinger, D.; Morneau, C.; Saucier, J-P.; Thorpe, J.; Uhlig, P. 2019. Vegetation Zones of Canada: a Biogeoclimatic Perspective. [Map] Scale 1:5,000,000. Natural Resources Canada, Canadian Forest Service. Great Lake Forestry Center, Sault Ste. Marie, ON, Canada.

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows the distribution for the two moisture aspects of Thornthwaite's climate classification system. The moisture regions are shown as coloured areas representing six moist and three dry climates; and seasonal variation of effective moisture shown as linework indicating dry periods in moist climates and moist periods in dry climates.

Data Sources:CanCoast Coastal Sensitivity Index 2090s, CanCoast Coastal Sensitivity Index 2020s, CanCoast Ground Ice, CanCoast Sea Level Change 2006 to 2099, CanCoast Sea Level Change 2006 to 2020, CanCoast Mean Wave Height with Sea Ice 1996-2005, CanCoast Mean Wave Height with Sea Ice 2090-2099Manson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669Natural Resources of Canada:Permafrost Atlas of Canada: https://maps-cartes.services.geo.ca/server_serveur/services/NRCan/permafrost_atlas_of_canada_en/MapServer/WMSServer?request=GetCapabilities&service=WMS Esri:basemap: https://basemaps.arcgis.com/arcgis/rest/services/World_Basemap_v2/VectorTileServerArctic Sea Ice Extent: https://www.arcgis.com/home/item.html?id=d1fb8225058e4a0d96ead7b9a574a652

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows the distribution for the two thermal aspects of Thornthwaite's climate classification system. There is thermal efficiency (a measure of heat received at the ground) shown as coloured areas in five classes and summer concentration of thermal efficiency shown by linework separating the eight classes. The climatic data for 1941 to 1970 is used for both aspects.

These rasters provide the local mean annual extreme low temperature from 1976 to 2005 in an 800m x 800m grid covering the USA (including Puerto Rico) based on interpolation of data from more than a thousand weather stations. Each location's Plant Hardiness Zone is calculated based on classifying that temperature into 5 degree bands. The classified rasters are then used to create print and interactive maps. A complex algorithm was used for this edition of the USDA Plant Hardiness Zone Map (PHZM) to enable more accurate interpolation between weather reporting stations. This new method takes into account factors such as elevation changes and proximity to bodies of water, which enabled mapping of more accurate zones.Temperature station data for this edition of the USDA PHZM came from several different sources. In the eastern and central United States, Puerto Rico, and Hawaii, nearly all the data came from weather stations of the National Weather Service. In the western United States and Alaska, data from stations maintained by USDA Natural Resources Conservation Service, USDA Forest Service, U.S. Department of the Interior (DOI) Bureau of Reclamation, and DOI Bureau of Land Management also helped to better define hardiness zones in mountainous areas. Environment Canada provided data from Canadian stations, and data from Mexican stations came from the Global Historical Climate Network.All of these data were carefully examined to ensure that only the most reliable were used in the mapping. In the end, data from a total of 7,983 stations were incorporated into the maps. The USDA PHZM was produced with the latest version of PRISM, a highly sophisticated climate mapping technology developed at Oregon State University. The map was produced from a digital computer grid, with each cell measuring about a half a mile on a side. PRISM estimated the mean annual extreme minimum temperature for each grid cell (or pixel on the map) by examining data from nearby stations; determining how the temperature changed with elevation; and accounting for possible coastal effects, temperature inversions, and the type of topography (ridge top, hill slope, or valley bottom).Information on PRISM can be obtained from the PRISM Climate Group website (http://prism.oregonstate.edu).Once a draft of the map was completed, it was reviewed by a team of climatologists, agricultural meteorologists, and horticultural experts. If the zone for an area appeared anomalous to these expert reviewers, experts doublechecked for errors or biases.For example, zones along the Canadian border in the Northern Plains initially appeared slightly too warm to several members of the review team who are experts in this region. It was found that there were very few weather reporting stations along the border in the United States in that area. Data from Canadian reporting stations were added, and the zones in that region are now more accurately represented. In another example, a reviewer noted that areas along the relatively mild New Jersey coastline that were distant from observing stations appeared to be too cold. This was remedied by increasing the PRISM algorithm’s sensitivity to coastal proximity, resulting in a mild coastal strip that is more consistently delineated up and down along the shoreline.On the other hand, a reviewer familiar with Maryland’s Eastern Shore thought the zones there seemed too warm. The data were doublechecked and no biases were found; the zone designations remained unchanged.The zones in this edition were calculated based on 1976-2005 temperature data. Each zone represents the average annual extreme minimum temperature for an area, reflecting the temperatures recorded for each of the years 1976-2005. This does not represent the coldest it has ever been or ever will be in an area, but it reflects the average lowest winter temperature for a given geographic area for this time period. This average value became the standard for assigning zones in the 1960s. The previous edition of the USDA Plant Hardiness Zone Map, which was revised and published in 1990, was drawn from weather data from 1974 to 1986.A detailed explanation of the mapmaking process and a discussion of the horticultural applications of the new PHZM are available from the articles listed below.Daly, C., M.P. Widrlechner, M.D. Halbleib, J.I. Smith, and W.P. Gibson. 2012. Development of a new USDA Plant Hardiness Zone Map for the United States. Journal of Applied Meteorology and Climatology, 51: 242-264. Link to articleWidrlechner, M.P., C. Daly, M. Keller, and K. Kaplan. 2012. Horticultural Applications of a Newly Revised USDA Plant Hardiness Zone Map. HortTechnology, 22: 6-19. Link to article

Data Sources:CanCoast_12_nautical_mile_zone_OGC Feature Layer: Manson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669Government of Canada:CanVec Series - Transport, Resources and Man-Made Features https://maps.geogratis.gc.ca/wms/canvec_en?request=getcapabilities&service=wms&layers=transport&version=1.3.0&legend_format=image/png&feature_info_type=text/htmlthumbnail:https://www.theglobeandmail.com/politics/article-northern-premiers-say-canada-cant-have-arctic-security-without/

The most sensitive river regions include the Atlantic coast, the Great Lakes-St. Lawrence Valley regions, the Rocky Mountains and the Prairies. The sensitivity projection for Canada's river regions in response to climate warming was derived based on an examination of the effects of projected precipitation changes on landscapes. Climate warming has the potential to cause substantial changes to flow in rivers. The most direct effects of projected climate change would be an increase in floods and river erosion.

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. The files below contain a map of Canada showing the locations of all facilities that reported to the NPRI in the most recent reporting year. The map is available in both ESRI REST (to use with ARC GIS) and WMS (open source) formats. For more information about the individual reporting facilities, datasets are available in either CSV or XLS formats. Please consult the following resources to enhance your analysis: - Guide on using and Interpreting NPRI Data: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/using-interpreting-data.html - Access additional data from the NPRI, including datasets and mapping products: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/tools-resources-data/exploredata.html

Context

The need to adapt to climate change is present in a growing number of fields, leading to an increase in the demand for climate scenarios for often interrelated sectors of activity. In order to meet this growing demand and to ensure the availability of climate scenarios responding to numerous vulnerability, impact, and adaptation (VIA) studies, Ouranos is working to create a set of operational multipurpose climate scenarios. The initial version of “Scénarios Génériques” (generic scenarios, acronym cb-oura-1.0) is used mainly in Ouranos’ work to provide a consistent image of the changing climate over the North East of North America, principally the province of Québec. Cb-oura-1.0 was produced in 2016 by downscaling and bias-adjusting a selection of global climate model simulations available through the CMIP5 program.

Climate simulations

Climate simulations in the ensemble


    Modeling center
    Acronym
    Model
    RCP
    Status*




    College of Global Change and Earth System Science, Beijing Normal University
    GCESS
    BNU-ESM
    4.5
    s





    8.5
    s


    Canadian Centre for Climate Modelling and Analysis
    CCCMA
    CanESM2
    4.5
    a





    8.5
    s


    Centro Euro-Mediterraneo per I Cambiamenti Climatici
    CMCC
    CMCC-CMS
    4.5
    a





    8.5
    s


    Commonwealth Scientific and Industrial Research Organization (CSIRO) and Bureau of Meteorology (BOM), Australia
    CSIRO-BOM
    ACCESS1.3
    4.5
    s





    8.5
    a


    Institute for Numerical Mathematics
    INM
    INM-CM4
    4.5
    s





    8.5
    a


    Institut Pierre-Simon Laplace
    IPSL
    IPSL-CM5A-LR
    4.5
    a





    8.5
    s




    IPSL-CM5B-LR
    4.5
    s





    8.5
    s


    Met Office Hadley Centre
    MOHC
    HadGem2
    4.5
    s





    8.5
    s


    Max-Planck-Institut für Meteorologie (Max Planck Institute for Meteorology)
    MPI-M
    MPI-ESM
    4.5
    s





    8.5
    s


    Norwegian Climate Centre
    NCC
    NorESM
    4.5
    a





    8.5
    s


    NOAA Geophysical Fluid Dynamics Laboratory
    NOAA-GFDL
    GFDL-ESM2M
    4.5
    s





    8.5
    s

From the complete ensemble of RCP 4.5 and 8.5 driven CMIP5 climate simulations, a selection of 22 simulations (11 per RCP) was made using a clustering ensemble reduction methodology (Casajus et al. 2016). This objective selection method identifies a reduced number of simulations that best represent the overall ensemble. Input criteria for the reduction were the monthly changes between the present (1981-2010) and two future horizons (2041-2070 and 2071-2100), at 15 regions distributed across Canada, for three variables (mean daily maximum temperature, mean daily minimum temperature and total precipitation). An initial selection of 16 simulations shows a distribution projected changes for the 12 (months) x 2 (horizons) x 15 (regions) x 3 (variables) indices that is not statistically different from the complete ensemble. A small number of simulations were subsequently added to have a complete set with both RCPs represented equally (11 members for each emission scenario).

Reference dataset

The bias-adjustment reference (or target) is a gridded observation dataset produced by Natural Resources Canada (McKenney et al., 2011; et Hutchinson et al. ,2009). It uses the ANUSPLIN interpolation method over station observations to derive daily grids of minimum and maximum temperature, as well as total precipitation for the Canadian landmass. The grid has a resolution of 10 km x 10 km and cover the time period from 1950 to 2013.

As this dataset is not available over the United States, it was merged with another observation interpolation dataset produced by Livneh et al. (2015) in order to enable the production of bias-corrected climate scenarios covering a portion of the northern United States.

Coverage

The final version of this dataset covers a region covering the Atlantic provinces, Québec, Ontario, Manitoba and Saskatchewan and part of the northern United States: From 120°W to 54°W and from 40°N to 62°N.

It contains the daily minimum temperature, daily maximum temperature and daily precipitation flux, covering the period 1950 to 2100.

Bias-adjustment

The global simulations where downscaled to the reference grid using bilinear interpolation and then bias-adjusted with a 1-D quantile mapping method, as described by Gennaretti et al. (2015). A moving window of 31 days was used to adjust each day of the year, using 50 quantiles to define the statistical distributions to match. The long-term linear trends of the temperature variables were preserved explicitly.

Climate indicators

This dataset is used to in the first versions (up to 1.3) of Ouranos’ Climate Portraits website. A selection of 26 seasonal and annual climate indicators were computed from the daily scenarios, using the xclim software package (Logan et al. 2022). The "virtual indicator module" used for the computation is made available here in the "indicators.yml" file.

On the Climate Portraits website, the information is presented from three aspects: spatial, temporal and summary. This repository stores the reduced ensemble data as shown on the website. Filenames are constructed as "{aspect}_{indicator}_{season}.nc".

Maps (files "spatial_*") : Climate indicators for each bias-adjusted climate simulation and for a given RCP emission scenario are averaged over 30-year horizons. Ensemble percentiles are computed in order to summarize climate model uncertainty. In particular the 10, 25, 50, 75 and 90th percentiles over the 11 members are calculated for each RCP.

Timeseries (files "temporal_*") : Climate indicators for each bias-adjusted simulation are averaged spatially over each region for every time step (annual or seasonal). The ensemble statistics are computed by first pooling all regional average values for the 11 members using within a centred 30-year window and then calculating percentile values (same as above) on the pooled data.

Summary (files "summary_*") : The indicators are averaged over each region and then over 30-year horizons. The ensemble statistics (same as above) are then computed.

In versions 2.x of the app, this data will be presented as "CMIP5".

Data availability

This repository stores the climate indicator ensemble statistics as shown on the Climate Portraits website and described above. The complete daily dataset is too large for this platform.

The complete daily dataset is available through the public THREDDS server of the PAVICS platform maintained by Ouranos. This data might be removed in the future. When this is the case, please contact us for data requests. https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/datasets/simulations/bias_adjusted/cmip5/ouranos/cb-oura-1.0/catalog.html

The annual and season indicators of the Climate Portraits website are available on the same server, along with a few more indicators not shown on the app. https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/catalog/birdhouse/ouranos/portraits-clim-1.3/catalog.html

Terms of use: Use of this dataset should be acknowledged as 'Data produced and provided by the Ouranos Consortium on Regional Climatology and Adaptation to Climate Change'. Furthermore, the modeling groups from which the bias-adjusted climate scenarios were constructed must also be acknowledged, please refer to: The Coupled Model Intercomparison Project https://pcmdi.llnl.gov/mips/cmip5/citation.html.

Wind erosion risk for unprotected soils in areas sensitive to climatic change is shown on this map. The regions that would have the highest sensitivity to a warming climate are likely to occur in the southern and central Prairies and in the southernmost part of Ontario. This risk of wind erosion is based on the nature of local climate and vegetation. Areas with dryer, warmer climates and with sparse vegetation cover are more vulnerable to wind erosion. The levels of climate sensitivity were derived by comparing present and future ecoclimatic regions of Canada, based on the assumption of a doubling of atmospheric carbon dioxide concentrations over pre-industrial levels.

Data Sources:CanCoast 2.0 Arctic Shoreline, Backshore Slope, Coastal Materials, Tidal Range, and 12 NM Coastal ZoneManson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669Esri World Topographic Basemap:

https://basemaps.arcgis.com/arcgis/rest/services/World_Basemap_v2/VectorTileServerEsri World Imagery Basemap:

https://services.arcgisonline.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0/WMTSCapabilities.xmlthumbnail:https://deeply.thenewhumanitarian.org/arctic/articles/2017/01/25/going-going-gone-canadian-arctic-faces-threat-of-coastal-erosion

This map showcases a 2D sea level change feature layer can be transformed to 3D with the sea level increase value extruded to the average elevation of each line segment. The original CanCoast 2099 sea level change polyline is divided into segments of ~300 meters from the longer segments. 200 meters landward buffer was created from the modified polyline feature. Sea level increase value is extruded to the 2D polygon to the lowest elevation. This map is for demonstration rather than scientific research purposes. Data Sources:coastline 200m buffer minHeightmodified from Manson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669EsriOpenStreet 3D buildings: https://www.arcgis.com/home/item.html?id=ca0470dbbddb4db28bad74ed39949e25WorldElevation3D/Terrain3D https://elevation3d.arcgis.com/arcgis/rest/services/WorldElevation3D/Terrain3D/ImageServer Topographic basemapthumbnail image: https://irc.inuvialuit.com/about-irc/community/tuktoyaktuk

Data Sources:CanCoast 12 Nautical Mile ZoneManson, G.K., Couture, N.J., and James, T.S., 2019. CanCoast Version 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate; Geological Survey of Canada, Open File 8551, 1 .zip file. https://doi.org/10.4095/314669Government of Canada:First Nationshttps://data.aadnc-aandc.gc.ca/geomatics/services/Donnees_Ouvertes-Open_Data/Premiere_Nation_First_Nation/MapServer/WFSServer?request=GetCapabilities&service=WFSCensus Subdivisions 2016

https://maps-cartes.services.geo.ca/server2_serveur2/services/StatCan/census_subdivisions_2016_en/MapServer/WMSServer?layers=0&legend_format=image%252Fpng&feature_info_type=text%252FhtmlMan-Made Features

https://maps.geogratis.gc.ca/wms/canvec_en?request=getcapabilities&service=wms&layers=transport&version=1.3.0&legend_format=image/png&feature_info_type=text/htmlthumbnail:https://www.centrostudi-italiacanada.it/articles/sovereignty-arctic-indigenous-peoples-canada

The EOS-WEBSTER VEMAP2 Data Collection contains several datasets which provide historical and future climate variables, and monthly and annual biogeochemical model outputs.

Two Tclimate + TScenario Datasets provide annual mean historical and model-predicted climate data from 1895 to 2100 for a subset of the variable available in the monthly dataset. These variables include Tmin, Tmax, Precipitation and Solar Radiation.

A dataset is provided for each GCM climate model scenarios:

1) TClimate + TScenario-CGCM1 - historical climate (1895 - 1993) + Canadian Climate Center (see above) predicted future values (1994 - 2100).

Canadian Climate Center -- Model Name: CCCma -CGCM1; Experiment: GHG+A 1; 1% per year compounded increase in equivalent CO2 plus IS92A sulphate aerosols; Ensemble 1.1994-2100. Release: r4.

2) TClimate + TScenario-HadCM2 - historical climate (1895 - 1993) + UKMO/Hadley predicted future values (1994 - 2099)

UKMO/Hadley -- Model Name: HadCM2; Experiment: HadCM2GSa1; 1% per year compounded increase in equivalent CO2 plus IS92A sulphate aerosols; Ensemble 1. 1994 - 2099. Release: r3.

Data provided by the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) at the National Center for Atmospheric Research (NCAR) are gridded monthly time series climate data for the Conterminous United States at 0.5 x 0.5 degree spatial resolution. Visit the VEMAP2 website for complete information about the VEMAP2 project and datasets.

The VEMAP2 Collection contains the following dataset groups.

1) TClimate - monthly historical climate dataset from 1895 to 1993. Release: r3.

2) TScenario - monthly climate data of possible future values based on different model scenarios.

3) TClimate + TScenario - annual historical climate data + possible future values based on the above different model scenarios.

4) TResults - annual biogeography/biogeochemical model estimates of ecosystem response from 1895 to 2100.

Please see the individual dataset group DIFs, for more detailed information.