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We have found 33 datasets for the keyword " skidoo". You can continue exploring the search results in the list below.
Datasets: 106,579
Contributors: 42
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33 Datasets, Page 1 of 4
Global Ice-Ocean Prediction System
The Global Ice-Ocean Prediction System (GIOPS) produces global sea ice and ocean analyses and 10 day forecasts daily. This product contains time-mean sea ice and ocean forecast fields interpolated to two grids. One of the grids is a 0.2° resolution regular latitude-longitude grid covering the global ocean (north of 80° S). The other grid is in north-polar stereographic projection with a 5-km spacing at the standard parallel 60° N and covers the Arctic Ocean and the neighbouring sub-polar seas. Data is available for 50 depths. The data files are in netCDF format and comply with the Climate and Forecast Conventions.
Snowmobile Areas in Parks within the Cariboo Region
Designated play areas for snowmobiles in Tweedsmuir and Itcha-Ilgachuz Provincial Parks. [__Tweedsmuir Provincial Park Master Plan__](https://bcparks.ca/planning/mgmtplns/tweedsmuir/tweeds_mp.pdf?v=1618329316506) [__Itcha Ilgachuz Provincial Park Management Plan__](https://bcparks.ca/planning/mgmtplns/itcha_il/itcha_ilgachuz_mp.pdf?v=1618329451240) [__Itcha Ilgachuz Provincial Park Winter Recreation Areas Map (PDF)__](https://bcparks.ca/planning/mgmtplns/itcha_il/rec_winmap.PDF)
Ski Resorts
Ski Resorts is a point dataset identifying the location of ski resorts in British Columbia.
CMIP5 Multi-Model Ensembles of Snow Depth projections
Multi-model ensembles of snow depth based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of snow depth (m) are available for the historical time period, 1900-2005, 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.
Search Service
Search Services: General place names, Populated Places and geonames
Regional Ice-Ocean Prediction System
The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution
Surface hydrography
Surface hydrographic network of the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Cobb Seamount Visual Survey 2012 (ROV)
This dataset contains observations of species occurrences from seafloor imagery collected by the remotely operated underwater vehicle (ROV) during the 2012 Expedition to Cobb Seamount. The ROV operated by Fisheries and Oceans Canada was a customized Deep Ocean Engineering Phantom HD2+2 which collected photographic images from 12 transects ranging from 35 m to 211 m in depth.
Ice and Snow - 1M
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)
Annual 30 m snow dynamics (2018-2019 to 2023-2024) – Canada
This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u].
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