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We have found 356 datasets for the keyword " température océanique". You can continue exploring the search results in the list below.
Datasets: 103,401
Contributors: 42
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356 Datasets, Page 1 of 36
CCSM4-projected ocean temperature and salinity in the Northwest Atlantic under a high emission scenario RCP8.5
This dataset provides projected sea surface temperature and salinity as well as projected ocean bottom temperature and salinity in the Northwest Atlantic under a high emission scenario Representative Concentration Pathway (RCP) 8.5. The results are generated by a North Atlantic Ocean-ice Downsling System (NAODS) that downscales the global Climate Change System Model Version 4 (CCSM4) output. NAODS couples 1/12-degree model for the northwest Atlantic with a 1/4-degree model for the North Atlantic (Han et al., 2025). Bi-decadal means are included for 1986-2005, 2006-2025, 2026-2045, 2046-2065, 2066-2085, and 2080-2099, respectively.
Line P Climatology (1956-2012)
Climatological monthly-mean temperature and salinity data were computed for each of the 27 Line P stations (https://www.dfo-mpo.gc.ca/science/data-donnees/line-p/index-eng.html). For any particular station, data were accepted as belonging to that station if the location was within 10 km of the intended station (or 24km at Ocean Station Papa, P26). Data were binned by month/year over all available data for each station up to and including 2012. Hence the time interval that the mean state was computed from starts between 1956 and 1960 and ends at the end of 2012. Standard deviations were computed for each month independently and at each 5-m depth bin and were estimated as the variability between different years for the month in question.
HadGEM2-projected ocean temperature and salinity in the Northwest Atlantic under an intermediate emission scenario RCP4.5
This dataset provides projected sea surface temperature and salinity as well as projected ocean bottom temperature and salinity in the Northwest Atlantic under an intermediate emission scenario Representative Concentration Pathway (RCP) 4.5. The results are generated by a North Atlantic Ocean-ice Downscaling System (NAODS) that downscales the global Hedley Centre Global Environmental Model Version 2 with an Earth System component (HadGEM2-ES) output. NAODS couples a 1/12 ^o model for the northwest Atlantic with a 1/4 ^o model for the North Atlantic (Han et al., 2025). Bi-decadal means are included for 1986-2005, 2006-2025, 2026-2045, 2046-2065, 2066-2085, and 2080-2099, respectively.
Seasonal temperature and salinity of Petite baie Saint-Nicolas (Godbout) in Gulf of St Lawrence from August 2019 to October 2021
This data report provides information on temperature and salinity in the Godbout region of the St. Lawrence Estuary. Sampling was carried out from 2019 to 2021 over an area of <5 km2. The databases provide information on temperature and salinity at an hourly rate for 2 years. The aim of this project is to analyze telemetry data from sea urchins (Strongylocentrotus droebachiensis), snow crabs (Chionoecetes opilio), rock crabs (Cancer irroratus), spider crabs (Hyas spp.) and whelks (Buccinum undatum). This report focuses on the presentation of benthic environmental data collected throughout the study with high spatial and temporal resolution. All reported variables were collected at the seafloor, as the aim of the project was to study the movement of epibenthic species. Temperature data were collected from three devices: telemetry receivers with integrated temperature sensors (InnovaseaTM), HoboTM and Star-OddiTM probes. Temperature data processing involved cleaning up extreme values (below 2°C and above 20°C) and homogenizing the data to fit the bathymetry matrix (1m x 1m cells) of the study site. Temperature data are provided in a NetCDF file with a matrix of the entire study site, where there is a stratum for each hour between August 2019 and October 2021 and in each file, a temperature value for each pixel of the raster. Salinity data were collected from Star-OddiTM probes only. Salinity values were averaged hourly for the entire study area. Salinity data is provided as a CSV file with one salinity value per hour for the entire study area.
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
Heat Wave
Heat Wave represents the consecutive number of days (April 1 – October 31) where the maximum daily temperature is greater than 25 or 30 degrees respectively. Heat wave products are only generated during the Growing Season, April 1 through October 31.
British Columbia Lightstation Sea-Surface Temperature and Salinity Data (Pacific), 1914-present
Daily sea surface temperature and salinity observations have been carried out at several locations on the coast of British Columbia since the early part of the 20th century. Observations started at the Pacific Biological Station (Departure Bay) in 1914; 11 stations were added in the mid-1930s and several more in the 1960s. The number of stations reporting at any given time has varied as sampling has been discontinued at some stations and started or resumed at others.Presently termed the British Columbia Shore Station Oceanographic Program (BCSOP), there are 12 active participating stations. Most of the stations are at lighthouses staffed by Fisheries and Oceans Canada, but three (Race Rocks, Amphitrite Point, and Active Pass) are sampled by contracted observers.Observations are made daily using seawater collected in a bucket lowered into the surface water at or near the daytime high tide. This sampling method was designed long ago by Dr. John P. Tully and has not been changed in the interests of a homogeneous data set. This means, for example, that if an observer starts sampling one day at 6 a.m., and continues to sample at the daytime high tide on the second day the sample will be taken at about 06:50 the next day, 07:40 the day after etc. When the daytime high-tide gets close to 6 p.m. the observer will then begin again to sample early in the morning, and the cycle continues. Since there is a day/night variation in the sea surface temperatures the daily time series will show a signal that varies with the14-day tidal cycle. This artifact does not affect the monthly sea surface temperature data.
Bottom temperature at the Atlantic Zone Monitoring Program (AZMP)-Quebec’s stations
Bottom temperature time series at the 3 fixed stations and 46 stations, grouped into transects, of the Atlantic Zonal Monitoring Program (AZMP) under the Quebec region responsibility.The mean bottom temperature of the last ten years are displayed as 2 layers, one for the June survey (2014-2023, 2020 not sampled), another for the autumn survey (2014-2023). A third layer shows the positions of the fixed stations of the program (Anticosti Gyre, Gaspé Current and Rimouski).Each station is linked with a .png file showing the bottom temperature time series and with a .csv file containing all the bottom temperature data acquired at those stations since the beginning of the program sampling (columns : Station, Latitude, Longitude, Date(UTC), Sounding(m), Depth/Profondeur(m), Temperature/Température(ºC)).PurposeThe Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment.The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties.In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period.Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp.Supplemental InformationThe bottom temperature is determined from CTD profile in the water column according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.
Coastal Temperature Monitoring Program in the Southern Gulf of St. Lawrence
PURPOSE:The objective of the program is to gather environmental coastal data to better understand fluctuations in water temperature and its effect on coastal marine species.DESCRIPTION:Bottom and surface water temperatures are monitored in coastal waters of the southern Gulf of St. Lawrence using electronic recording devices attached to navigational buoys or moorings and set to record every two hours. PARAMETERS COLLECTED:Temperature (environmental); point (spatial).NOTES ON QUALITY CONTROL:Data are checked for irregularities.SAMPLING METHODS:Temperature recording devices are installed by fishermen, DFO staff and, since 2000, by the Canadian Coast Guard staff.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.
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.
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