RI_623
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Formats
Representation types
Update frequencies
status
Scale
-
Each pixel value corresponds to the quality control, cloud cover and snow fraction value for each pixel in the Best-Quality Max-NDVI product.
-
Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.
-
An archive of 2D regional seismic and long period magnetotelluric data collected during 20 years of work under the LITHOPROBE project. Data are primarily onshore and cover widespread regions of Canada. Available data types include raw digital data, processed sections, and images of final sections, as well as auxiliary information required for analysis of the data.
-
Precipitation Percentiles represents the accumulated precipitation (mm) for the time period compared to historical information for the same time period. This comparison ranks the current precipitation amount and assigns it a percentile value based on a historic record. Products are produced for the following timeframes: Agricultural Year, Growing Season and Winter Season as well as rolling products for 30, 60, 90 and 180 days
-
The ‘Land use allocation to Soils and Landforms by year’ dataset links agricultural land use activities to soils and landscapes within Soil Landscapes of Canada (SLC) polygons. The land use allocations to soils area datasets were generated on an annual time step (1971-2015). Agricultural land use is categorized and allocated based on the following general land use types: Annual cropland, Perennial cropland, Specialty Crops, Improved pasture and Unimproved Pasture.
-
The Grain Elevators in Canada dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada.
-
The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.
-
The Coastal Environmental Baseline Program is a multi-year Fisheries and Oceans Canada initiative designed to work with Indigenous and local communities and other key parties to collect coastal environmental data at six unique sites across Canada, including the Port of Saint John (New Brunswick). The overall purpose of the Program is to collect localized ecological data in these areas to build a better baseline understanding of marine ecological conditions. The Maritimes region has developed a physical oceanography project to align with the interests and data needs of local communities and stakeholders. Starting in 2020, data describing the depth and temperature of tidal flood waters have been collected at a series of intertidal locations in the Port of Saint John vicinity, to characterize high marsh flood tides and water level fluctuations near the Courtenay Bay causeway. Inundation by marine waters in high marsh areas is typically limited to spring tides, while the water level in Courtenay Bay is influenced by anthropogenic infrastructure (e.g. causeway, tide gates). The resulting data can enhance studies ranging from coastal vulnerability and resilience to salt marsh morphodynamics, by quantifying the frequency, amplitude and duration of tidal inundation. Data were collected using Hobo U20-001-02 water level loggers, which were deployed inside stilling wells constructed from 15-inch lengths of perforated ABS pipe (2¼” diameter). The stilling wells were sunk to a depth of 6 inches below ground, with the water level logger suspended inside the well from a bolt near the top. The logger was positioned with a rigid wire such that the measurement volume was equal to ground level, while allowing the logger to be easily removed for downloading and precisely replaced at the measurement location. Loggers were accessed 2-3 times per year to download, and were removed during the winter months. Data have been compensated for changing atmospheric pressure using the Barometric Compensation Tool in HobowarePro (version 3.7.21) and barometric pressure data collected from a dry location during the study period. The resulting water level is reported in meters, and is relative to the elevation of the water level logger (e.g. above ground level). Citation: Port of Saint John intertidal water level and temperature (2020-2022). Coastal Environmental Baseline Program. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, St. Andrews, N.B. XX-XX-2024
-
The objectives of the fish component of the integrated oil sands monitoring program are to provide the necessary data/information to address key questions related to both environmental health of fish populations and fish health issues that can be used to inform human use and consumption. The questions underlying the fish monitoring design are related to the status and health of wild fish populations in the Lower Athabasca River including and in an expanded geographical extent. Data is being collected to provide a baseline against which future changes in fish populations will be evaluated, and compared to data from historical studies to assess change over time to the current state. Data is also being collected in areas of new oil sands development, to develop baseline data for future site-specific comparisons, contribute to an expanded geographic basis of the overall monitoring plan, and contribute to an improved ability to examine cumulative effects.
-
Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). Historical gridded minimum and maximum temperature datasets of Canada (ANUSPLIN) were used as the respective downscaling targets. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected mean temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of mean temperature change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled minimum mean temperature (°C) 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 downscaled 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.
Arctic SDI catalogue