The mapping depicts the relative abundance of segregated ice in upper permafrost at a national scale. The mapping is based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019). The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.

The mapping depicts a first-order estimate of the combined volumetric percentage of excess ice in the top 5 m of permafrost from segregated, wedge, and relict ice. The estimates for the three ice types are based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019), and informed by available published values of ground ice content and expert knowledge. The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.

In 2018, Fisheries and Oceans Canada initiated the Multidisciplinary Arctic Program (MAP) – Last Ice, the first ecosystem study of the poorly characterized region of Tuvaijuittuq, where multiyear ice still resides in the Arctic Ocean. The program MAP-Last Ice takes a coordinated approach to integrate the physical, biochemical, and ecological components of the sea ice-ocean connected ecosystem and its response to climate and ocean forcings. This program provides baseline ecological knowledge for Tuvaijuittuq and, in particular, for its unique multiyear ice ecosystem. The database provides baseline data on fatty acid composition and stable isotopes signatures of sea ice communities in multi- and first-year ice in Tuvaijuittuq. The data were collected during the 2018 spring field campaign of the MAP-Last Ice Program, offshore of Canadian Forces Station (CFS) Alert, in the Lincoln Sea.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in sea ice concentration based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Sea ice concentration is represented as the percentage (%) of grid cell area. Therefore, projected change in sea ice concentration is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of sea ice concentration change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in sea ice concentration (%) 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 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.

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.

Icefields captured at 1:1,000,000 scale from Digital Chart of the World data for the Yukon and surrounding area.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)

Hydro Features is composed of the network of Canadian surface waters. Hydro Features entities are: Watercourse, Water Linear Flow, Hydro Obstacle (falls, rapids\...), Waterbody (lake, watercourse\...), Permanent Snow and Ice, Water Well, and Spring. CanVec is a digital cartographic reference product of Natural Resources Canada (NRCan). It originates from the best available data sources covering Canadian territory, offers quality topographical information in vector format, and complies with international geomatics standards. CanVec is a multi-source product coming mainly from the National Topographic Data Base (NTDB), the Mapping the North process conducted by the Canada Center for Mapping and Earth Observation (CCMEO), the Atlas of Canada data, the GeoBase initiative, and the data update using satellite imagery coverage (e.g. Landsat 7, Spot, Radarsat, etc.).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)

This dataset uses RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) satellite images to identify open water regions within ice-covered rivers during winter, with the aim to assess hydrokinetic resources near remote communities reliant on diesel fuel for electricity generation. The data is processed with the HyRASS, a machine learning-based SAR image processing and classification algorithm.Disclaimer:This dataset was designed to identify open water regions within ice-covered rivers for assessing hydrokinetic resources near remote communities reliant on diesel fuel for electricity generation and is subject to the following limitations: • This dataset was derived from RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) satellite images. While these images are generally reliable, they are subject to inherent limitations, including resolution constraints, potential distortion, and occasional inaccuracies in real-time conditions capture. • The HyRASS algorithm is designed to pinpoint open water areas using satellite images, with a particular emphasis on RCM quad polarization (QP) imagery. This specialization means that its effectiveness depends on the accessibility of this specific type of imagery. Consequently, the data it produces might not cover a broad spectrum of time periods. For more reliable results, it's essential to classify areas more regularly, ensuring that detected open water regions are consistent over time.This dataset is intended for preliminary assessment and should not be the sole basis for making critical decisions or investments related to hydrokinetic energy projects. Further validation and in-depth analysis are strongly recommended, and users should conduct their own due diligence and additional research to verify the data accuracy and relevance for specific applications. By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.

In 2018, Fisheries and Oceans Canada initiated the Multidisciplinary Arctic Program (MAP) – Last Ice, the first ecosystem study of the poorly characterized region of the Lincoln Sea in the Marine Protected Area of Tuvaijuittuq, where multiyear ice still resides in the Arctic Ocean. MAP-Last Ice takes a coordinated approach to integrate the physical, biochemical, and ecological components of the sea ice-ocean connected ecosystem and its response to climate and ocean forcings. The cross-disciplinary program establishes baseline ecological knowledge for Tuvaijuittuq and, in particular, for its unique multiyear ice ecosystem. The database provides baseline data on the abundance of bacteria and viruses in multi- and first-year ice and in surface waters of the Lincoln Sea in Tuvaijuittuq, and their relation to bio-physical conditions. The data were collected during the 2018 spring field campaign of the MAP-Last Ice Program, at an ice camp offshore of Canadian Forces Station (CFS) Alert.

The mapping depicts the relative abundance of wedge ice in upper permafrost at a national scale. The mapping is based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019). The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.