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

The Ocean Data Inventory database is an inventory of all of the oceanographic time series data held by the Ocean Science Division at the Bedford Institute of Oceanography. The data archive includes about 5800 current meter and acoustic doppler time series, 4500 coastal temperature time series from thermographs, as well as a small number (200) of tide gauges. Many of the current meters also have temperature and salinity sensors. The area for which there are data is roughly defined as the North Atlantic and Arctic from 30° - 82° N, although there are some minor amounts of data from other parts of the world. The time period is from 1960 to present. The database is updated on a regular basis.

This dataset contains the modelled and observed data used in the publication "Fjord circulation permits persistent subsurface water mass in a long, deep mid-latitude inlet" by Laura Bianucci et al., DFO Ocean Sciences Division, Pacific Region (published in the journal Ocean Science in 2024). An application of the Finite Volume Community Ocean Model (FVCOM v4.1) was run from May 24 to June 27, 2019 in the Discovery Islands region of British Columbia, Canada. Observed temperature and salinity profiles available in this area during this time period are included in the dataset, along with the modelled values at the same times and locations.

Description:Seasonal temperature climatology of the Northeast Pacific Ocean was computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period. Methods:Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal temperature climatology for the Canadian Pacific Exclusive Economic Zone (EEZ), a subset of seasonal climatology of the Northeast Pacific Ocean, in high spatial resolution of 1/300 degree.References:Foreman, M. G. G., W. R. Crawford, J. Y. Cherniawsky, and J. Galbraith (2008). Dynamic ocean topography for the northeast Pacific and its continental margins, Geophys. Res. Lett., 35, L22606, doi: 10.1029/2008GL035152.Data Sources:NOAA, MEDS and IOS observational dataUncertainties:Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

This dataset contains the surface temperature and salinity data of the enlarged coastal thermograph network of the St. Lawrence river, estuary and gulf system. It includes data from the Canadian Hydrographic Service water level network (SINECO), the Department of Fisheries and Oceans (DFO)-Quebec long-termed thermograph monitoring program network and the oceanographic buoy network.Each station is linked with a .png file showing the temperature and salinity time series and with a .csv file containing the surface temperature and salinity data themselves (columns : Station,Latitude,Longitude,Date(UTC),Depth/Profondeur(m),Temperature/Température(ºC),Salinity/Salinité(psu)).Supplemental InformationA detailed description of the networks (SINECO, oceanographic buoys and the DFO-Quebec thermograph monitoring program) is available at the St. Lawrence Global Observatory (SLGO) portal :SINECO : https://ogsl.ca/en/tide-gauges-dfo-chs/Oceanographic buoys : https://ogsl.ca/en/marine-conditions-buoys-dfo/Thermographs: https://ogsl.ca/en/marine-conditions-thermographs-dfo/Technical Reports related to the Thermograph Network (the last one is also available at the same hypertext link mentionned above) :Pettigrew, B., Gilbert, D. and Desmarais R. 2016. Thermograph network in the Gulf of St. Lawrence. Can. Tech. Rep. Hydrogr. Ocean Sci. 311: vi + 77 p.Pettigrew, B., Gilbert, D. and Desmarais R. 2017. Thermograph network in the Gulf of St. Lawrence: 2014-2016 update. Can. Tech. Rep. Hydrogr. Ocean Sci. 317: vii + 54 p.

Description:Seasonal climatologies (temperature, salinity, and sigma-t) of the Northeast Pacific Ocean were computed from historical observations including all available conductivity-temperature-depth (CTD), bottle, expendable bathy-thermograph (XBT), and Argo data in NOAA (http://www.argo.ucsd.edu/), Marine Environmental Data Service (MEDS), and Institute of Ocean Sciences archives over 1980 to 2010 period in spatial resolution ranging from approximately 100m to 70km.Methods:Calculations, including smooth and interpolation, were carried out in sixty-five subregions and up to fifty-two vertical levels from surface to 5000m. Seasonal averages were computed as the median of yearly seasonal values. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March.Uncertainties:Uncertainties are introduced when quality controlled observational data are spatially interpolated to varying distances from the observation point. Climatological averages are calculated from these interpolated values.

Monthly mean temperature from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request.The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process.When using data please cite following:Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p

Wang, Z., Greenan, B.J.W., Hannah, C.G., and Layton, C. 2025. Past and future sea surface temperature changes in the oceans surrounding Canada. Can. Tech. Rep. Hydrogr. Ocean. Sci. 404: v + 44 pThis study presents changes in the sea surface temperature (SST) in the oceans surrounding Canada using past observations and model projections of future scenarios. The past changes are derived using an SST product, HadISST, in which a recent period (2012-2022) was referenced to a 26-year climatology (1955-1980). The future changes in SST are estimated using a 22-member ensemble of CMIP6 models. The SST changes for overlapping periods from the CMIP6 ensemble and the HadISST in the 10 regions of the Canadianshelf waters are in general agreement, although the CMIP6 results tend to overestimate the observed changes by about 0.1 oC. One exception to this is the Scotian Shelf where the CMIP6 models underestimate the observed SST change. The Gulf of Maine, Scotian Shelf, Gulf of St. Lawrence and southern Newfoundland shelf are the regions with the largest observed SST increases around Canada. The Gulf of St. Lawrence has the highest correlation (r=0.65) with the Atlantic Multi-decadal Oscillation (AMO) among the subregions in the North Atlantic Ocean, and the British Columbia Shelf is correlated with the Pacific Decadal Oscillation (r=0.58). Under the four climate scenarios (SSP1-2.6 to SSP5-8.5), among the mid-century (2040-2059) annual mean SST changes (reference period of 1990-2014) in the 10 regions, the Gulf of St. Lawrence is projected to have the largest increases in temperature (1.8 – 2.5oC), and Baffin Bay has the smallest increases (0.5 – 0.9oC), However, for the summer means, the southern Beaufort Sea has the largest SST increase (2.4 -3.1oC) with Baffin Bay having the smallest changes (1.3-2.1oC).Cite this data as: Wang, Z., Greenan, B.J.W., Hannah, C.G., and Layton, C. (2025) Data of:Past and Future Sea Surface Temperature Changes in the Oceans Surrounding Canada.Published: October 2025. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.https://open.canada.ca/data/en/dataset/3c336e55-4266-406a-922d-bbf8e717558c

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).

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).