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We have found 947 datasets for the keyword "étude à long terme". You can continue exploring the search results in the list below.
Datasets: 104,591
Contributors: 42
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947 Datasets, Page 1 of 95
Long-Term Tenure Map 2020 (Managed Forest Code 11)
Long-term tenure map (managed forest code 11) used in the Forest Management in Canada, 2020 story map.Long-term tenure map (managed forest code 11) with lands having more than five years volume- or area-based tenure or effectively having the equivalent, such as consistently recurrent commercial forest tenure with associated forest management activity. The Long-term tenure map is used in the Story Map of Forest Management in Canada, 2020 (Aménagement des forêts au Canada, 2020) and includes the following tiled layer:Tile Layer of Long-Term Tenure Managed Forest Code 11: 2020
Long Term Water Chemistry
Digitization of long-term water chemistry data collected between 1920's - 1990's from lakes across Saskatchewan by the Saskatchewan Fisheries Research Laboratory. Samples were collected using methods from the Standard Methods for the Examination of Water and Wastewater (APHA, AWWA and WPCF). This data serves as a baseline for water quality.This dataset is a digitization from paper records of water chemistry data across Saskatchewan collected by the Saskatchewan Fisheries Research Laboratory. Data ranges from the 1920's to the 1990's and were sampled using methodes from the Standard Methods for the Examination of Water and Wastewater (American Public Health Association, American Water Works Association and Water Pollution Control Facility) This long-term water chemistry data serves as a baseline for water quality. Different variables of water chemistry are organized into individual fields. The units of measurement appear at the end of each field name. Due to the historical nature of the data some uncertainty exist in values. Additonal notes on data: ND: no detection Trace: trace amounts Nil: zero NA: no data
Percent of Average Precipitation
Percent of Average Precipitation represents the accumulation of precipitation for a location, divided by the long term average value. The long term average value is defined as the average amount over the 1981 – 2010 period. Products are produced for the following timeframes: Agricultural Year, Growing Season, Winter Season, as well as rolling products for 30, 60, 90, 180, 270, 365, 730, 1095, 1460 and 1825 days.
Long Term Climate Extremes, Daily Extremes of Records – Precipitation
The daily climate records database, also known as Long Term Climate Extremes (LTCE), was developed to address the fragmentation of climate information due to station changes (opening, closing, relocation, etc.) over time. For approximately 750 locations in Canada, "virtual" climate stations have been developed by joining (threading) climate data for an urban location, from nearby stations to make long-term records. Each long-term record consists of the extremes (record values) of daily maximum/minimum temperatures, total precipitation and snowfall for each day of the year. Many of the longest data sets of extremes date as far back as the 1800s. This data provides the daily extremes of record for Precipitation for each day of the year. Daily elements include: Greatest Precipitation.
Blended Index – Long Term
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.
Long Term Climate Extremes, Virtual Climate Stations
A Virtual Climate station is the result of threading together climate data from proximate current and historical stations to construct a long term threaded data set. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. The length of the time series of virtual stations is often greater than 100 years. A Virtual Climate station is always named for an “Area” rather than a point, e.g. Winnipeg Area, to indicate that the data are drawn from that area (within a 20km radius from the urban center) rather than a single precise location.
Long Term Climate Extremes, Daily Extremes of Records – Temperature
Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Temperature for each day of the year. Daily elements include: High Maximum, Low Maximum, High Minimum, Low Minimum.
Departure from Average Precipitation (mm)
Departure from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long term average value. The long term average value is defined as the average amount over the 1981 – 2010 period. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm). Products are produced for the following timeframes: Agricultural Year, Growing Season, Winter Season as well as rolling products for 30, 60, 90, 180, 270, 365, 730, 1095, 1460 and 1825 days.
National Long-term Water Quality Monitoring Data
Long-term freshwater quality data from federal and federal-provincial sampling sites throughout Canada's aquatic ecosystems are included in this dataset. Measurements regularly include physical-chemical parameters such as temperature, pH, alkalinity, major ions, nutrients and metals. Collection includes data from active sites, as well as historical sites that have a period of record suitable for trend analysis. Sampling frequencies vary according to monitoring objectives. The number of sites in the network varies slightly from year-to-year, as sites are adjusted according to a risk-based adaptive management framework. The Great Lakes are sampled on a rotation basis and not all sites are sampled every year. Data are collected to meet federal commitments related to transboundary watersheds (rivers and lakes crossing international, inter-provincial and territorial borders) or under authorities such as the Department of the Environment Act, the Canada Water Act, the Canadian Environmental Protection Act, 1999, the Federal Sustainable Development Strategy, or to meet Canada's commitments under the 1969 Master Agreement on Apportionment.
Long Term Climate Extremes, Daily Extremes of Records – Snowfall
The daily climate records database, also known as Long Term Climate Extremes (LTCE), was developed to address the fragmentation of climate information due to station changes (opening, closing, relocation, etc.) over time. For approximately 750 locations in Canada, "virtual" climate stations have been developed by joining (threading) climate data for an urban location, from nearby stations to make long-term records. Each long-term record consists of the extremes (record values) of daily maximum/minimum temperatures, total precipitation and snowfall for each day of the year. Many of the longest data sets of extremes date as far back as the 1800s. This data provides the daily extremes of record for Snowfall for each day of the year. Daily elements include: Greatest Snowfall.
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