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We have found 3,567 datasets for the keyword "température de l'eau". You can continue exploring the search results in the list below.
Datasets: 104,592
Contributors: 42
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3,567 Datasets, Page 1 of 357
Margaree River and Tributaries Water Temperatures
PURPOSE:To record hourly water temperatures throughout the Margaree watershed.DESCRIPTION:The Department of Fisheries and Oceans (DFO) has been deploying water temperature monitoring equipment since spring 1993 in the Margaree River watershed. Coverage has changed throughout the time series and there is little documentation regarding equipment used. In recent years data have been collected using VEMCOs. USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.
Mean Temperature Difference From Normal
Mean Temperature Difference From Normal values are computed by subtracting the normal monthly average temperature from the average monthly temperature of the month. The average monthly temperature is computed by obtaining the mean value of average daily temperatures for a month. If the month was colder than normal the value computed will be negative and if it was warmer the value will be positive.
Crop (corn) heat units
Crop Heat Units (CHU) are calculated on a daily basis, using the maximum and minimum temperatures in order to account for a crop’s negative response to higher temperatures.The formula used to calculate the CHU value for a day is: (1.8 × (Minimum Temperature − 4.4) + 3.33 × (Maximum Temperature − 10) − 0.084 × (Maximum Temperature − 10)²) ÷ 2.0CHU values are only accumulated during the Growing Season, April 1 through October 31.
Maximum Temperature (°C)
Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.
CMIP5 Multi-model Ensembles of Temperature projections
Multi-model ensembles of mean temperature based on projections from twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of mean temperature (°C) are available for the historical time period, 1901-2005, 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.
Geothermal Thermal Springs
The THERMAL SPRINGS layer represents a compilation of available data from thermal springs throughout the Yukon and near the Yukon border. Spring data points include information on the name of the thermal springs, the measured temperature, the water chemistry, geothermometer results and references where more data may be found.
Projected Temperature change based on CMIP5 multi-model ensembles
Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of projected change in 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 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 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.
Ocean Bottom Temperature Variations from CIOPS-E and GLORYS12 Models at St. Anns Bank
These are derived products of ocean bottom temperature at St. Anns Bank Marine Protected Area (MPA), utilizing outputs from two numerical models: 1) Pseudo-analysis from the Coastal Ice-Ocean Prediction System for the East Coast of Canada (CIOPS-E v2.0.0) at 1/36° horizontal grid developed and implemented operationally at Environment and Climate Change Canada, covering 2016-2023 through combining research and operational runs from this system (https://eccc-msc.github.io/open-data/msc-data/nwp_ciops/readme_ciops_en/); 2) The Global Ocean Physics Reanalysis (GLORYS12v1), a 1/12° data assimilative reanalysis product produced by the Mercator Ocean International and implemented by the CMEMS, spanning from 1993 to 2023 ( https://doi.org/10.48670/moi-00021). The daily bottom temperature data presented here are calculated as daily area averages. The ocean bottom temperature data from the model available here are validated against in-situ observations from the open data (https://open.canada.ca/data/en/dataset/910b8e22-2fd1-4ba1-8db6-d16763c7a625). These products may be used to gain knowledge of ocean bottom temperature changes in the MPA over the past 8 and 30 years.Cite this data as: Casey, M., Hu, X, Tao, J., and Shen, H. Ocean Bottom Temperature Variations from CIOPS-E and GLORYS12 Models at St. Anns Bank. Published: August 2024. Ecosystems and Oceans Science, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/019f9138-6e3c-4f0e-997e-879e1ec2c42d
Beluga Calves Relative Summer Density in the St. Lawrence Estuary
This layer represents the relative summer density of beluga calves in the St. Lawrence Estuary based on 35 aerial surveys carried out from 1990 to 2009. The boundaries of the areas were determined by combining the highest densities until the desired proportion of the population was obtained using kernel density estimation in order to obtain a smooth and continuous density distribution.Within Fisheries and Oceans Canada (DFO), the ecosystem approach is considered as a tool for operational planning, project implementation and preparation of advisory reports. In response to this strategic direction, the DFO science division is committed to implement the ecosystem approach in its activities as Ecosystem Research Initiatives (ERI) in each of the six administrative regions of DFO. In the Quebec region, two pilot projects were implemented, of which one aimed to define and characterize the habitat of the St. Lawrence beluga (Delphinapterus leucas).Data sources and references:DFO. 2016. Ecosystem Research Initiative (ERI): Integrated Advice on the Summer Habitat of the St. Lawrence Estuary Beluga (Delphinapterus leucas). DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2016/030. Mosnier, A., R. Larocque, M. Lebeuf, J.-F. Gosselin, S. Dubé, V. Lapointe, V. Lesage, V., H. Bourdages, D. Lefaivre, S. Senneville and C. Chion. 2016. Définition et caractérisation de l'habitat du béluga (Delphinapterus leucas) de l'estuaire du Saint-Laurent selon une approche écosystémique. Secr. can. de consult. sci. du MPO. Doc. de rech. 2016/052. vi + 93 p.
Moisture Anomaly Index
The Moisture Anomaly Index (Palmer-Z) is an estimate of the moisture difference from normal (a 30-year mean). It attempts to express conditions for the current month regardless of what may have occurred before the month in question.
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