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We have found 2,352 datasets for the keyword "high resolution". You can continue exploring the search results in the list below.
Datasets: 104,029
Contributors: 42
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2,352 Datasets, Page 1 of 236
Forecasted Basin-Average Accumulated Precipitation (HRDPS - 24 & 48 hrs)
This polygon layer shows sub-basin averages of HRDPS (High Resolution Deterministic Prediction System) precipitation. Ideal for capturing short-range (0–48h) high-resolution precipitation forecasts aggregated at the watershed scale.The HRDPS is a 2.5 km resolution model used for short-range, convection-permitting forecasts in Canada. This layer takes HRDPS precipitation totals and aggregates them by each sub-basin polygon, revealing how localized rain or snow could impact individual watersheds. Useful for near-term flood or flash-flood risk, as well as local water management during intense weather.
Canada's surface water frequency
Data represents surface water occurrence frequency (percentage), which describes the frequency for each grid appeared as water in the 30 years time period of 1991 to 2020. The data covers Canada’s entire landmass including all transboundary watersheds, and is at 30-meter spatial resolution. The surface water occurrence frequency is derived using the surface water model of Wang et al. (2023) from all-available monthly water data observed by the Landsat satellites (Pekel et al., 2016). Here, permanent waters are represented by 100%, and permanent land surfaces by 0%, of water occurrence for a 30-meter by 30-meter grid.References:Pekel, J.-F., A. Cottam, N. Gorelick, A.S. Belward, 2016, High-resolution mapping of global surface water and its long-term changes. Nature, 540, 418-422.Wang, S., J. Li, and H. A. J. Russell, 2023, Methods for Estimating Surface Water Storage Changes and Their Evaluations. Journal of Hydrometeorology, DOI: https://doi.org/10.1175/JHM-D-22-0098.1.
Collection - Mosaic of High Resolution Digital Elevation Model (HRDEM) at 1m
The High Resolution Digital Elevation Model (HRDEM) Mosaic represents the current and continous coverage of high-resolution elevation data available in Canada. This version of the mosaic, available at a spatial resolution of 1 meter, is a combination of DEM data generated from airborne LiDAR data and available at this resolution. This data collection includes a digital terrain model (DTM) and a digital surface model (DSM) for the entire coverage. The mosaic product is referenced to the Canadian Geodetic Vertical Datum 2013 (CGVD2013). The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). In case of overlap between data sources, pixel values are set according to the most recent source. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
Weather Elements on Grid based on the High Resolution Deterministic Prediction System
Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).
High Resolution Digital Elevation Model Mosaic (HRDEM Mosaic) - CanElevation Series
The High Resolution Digital Elevation Model Mosaic provides a unique and continuous representation of the high resolution elevation data available across the country. The High Resolution Digital Elevation Model (HRDEM) product used is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The mosaic is available for both the Digital Terrain Model (DTM) and the Digital Surface Model (DSM) from web mapping services. It is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan. This strategy aims to increase Canada's coverage of high-resolution elevation data and increase the accessibility of the products.Unlike the HRDEM product in the same series, which is distributed by acquisition project without integration between projects, the mosaic is created to provide a single, continuous representation of strategy data. The most recent datasets for a given territory are used to generate the mosaic. This mosaic is disseminated through the Data Cube Platform, implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The mosaic is available from Web Map Services (WMS), Web Coverage Services (WCS) and SpatioTemporal Asset Catalog (STAC) collections. Accessible data includes the Digital Terrain Model (DTM), the Digital Surface Model (DSM) and derived products such as shaded relief and slope.The mosaic is referenced to the Canadian Height Reference System 2013 (CGVD2013) which is the reference standard for orthometric heights across Canada.Source data for HRDEM datasets used to create the mosaic is acquired through multiple projects with different partners.Collaboration is a key factor to the success of the National Elevation Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.
Yukon High Resolution Satellite Imagery
Yukon highresolution satellite imagery is distributed from the Government of Yukonimagery repository. This is a dynamic service containing satellite imagery forlocations in the Yukon, Canada.This data is hostedin Yukon Albers equal area projection. It can be viewed and queried in theGeoYukon application: [https://mapservices.gov.yk.ca/GeoYukon](https://mapservices.gov.yk.ca/GeoYukon).For more informationcontact geomatics.help@yukon.ca.
Northeast Pacific Monthly Mean Ocean Current Climatology (October - March)
This dataset provides 1/36-degree monthly mean ocean current climatology (October - March) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the perid from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).
Observed Basin-Average Accumulated Precipitation (HRDPA - Past 1 day, 3 days & 7 days)
This polygon layer depicts sub-basin average observed precipitation from the High Resolution Deterministic Precipitation Analysis (HRDPA). Offers insight into how much rain/snow actually fell across each watershed in the past observation period. Observation periods we are interested are for past 1 day, 3 days and 7 days.HRDPA is ECCC’s high-resolution precipitation analysis, merging gauge, radar, and HRDPS model data. This layer aggregates the final (or preliminary) HRDPA accumulations to sub-basin polygons. Each record indicates the average precipitation that truly occurred over each watershed, vital for verifying model forecasts, calibrating hydrological models, and conducting post-event analyses of flood or drought severity.
Northeast Pacific Monthly-Mean Ocean Current Climatology (April - September)
This dataset provides 1/36-degree monthly-mean ocean current climatology (April - September) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the period from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).
Canadian Land Data Assimilation System in the National Surface and River Prediction System [experimental]
CaLDAS-NSRPS was installed as an experimental system within the National Surface and River Prediction System (NSRPS) at Environment and Climate Change Canada's (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP) in July 2019. CaLDAS-NSRPS is a continuous offline land-surface assimilation system, which provides analyses of the land surface every 3 h over the domain of the High-Resolution Deterministic Prediction System (HRDPS) at a 2.5 km grid spacing. The emphasis in CaLDAS-NSRPS is to focus upon the assimilation of satellite based remote sensing observations to provide the optimal initial conditions for the predictive components of the NSRPS, the High Resolution Deterministic/Ensemble Land Surface Prediction System (HRDLPS/HRELPS) and the Deterministic/Ensemble Hydrological Prediction Systems (DHPS/EHPS). CaLDAS-NSRPS is launched 4 times per day, at 0000, 0600, 1200, and 1800 UTC.
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