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.

Data from the analysis of sea surface temperature, sea surface salinity, bottom temperature, and bottom salinity, over the Gulf of Maine and Scotian Shelf, for 23 CMIP6 models. The analysis includes an evaluation of CMIP6 model performance for the CMIP6 historical (1950-2014) experiment. Future projections are summarized for CMIP6 scenarios SSP245 and SSP370 with the calculation of relative annual and seasonal changes between the historical period (1950-2014) and three future periods (2030-2039, 2040-2049, 2030-2049).Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D., Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 models. Can. Tech. Rep. Hydrogr. Ocean. Sci. XXX: vii + XXXp.Cite this data as: Wang, Z., DeTracey, B., Maniar, A., Greenan, B., Gilbert, D. and Brickman, D. Future hydrographic state of the Scotian Shelf and Gulf of Maine from 23 CMIP6 Models. Published July 2022. Ocean Ecosystem Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/6247bb5a-14b3-461d-9ed3-b42553107bbc

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.

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

Gridded temperature and salinity of the Estuary and Gulf of St. Lawrence bottom waters including shallow waters. Data are a result of a 3D interpolation on a 1km x 1km x bottom depth grid. They mostly come from the 2 multidisciplinary surveys but all the available CTD data sampled in August and September were used. The dataset contains 24 layers: one layer per year per variable from 2014 to 2023, two layers of temperature and salinity climatologies and two layers of anomalies for the last year.PurposeSince 1990, the Department of Fisheries and Oceans has been conducting an annual multidisciplinary survey in the Estuary and northern Gulf of St. Lawrence using a standardized protocol. In the southern Gulf of St. Lawrence, these bottom trawl surveys has been carrying out each September since 1971. These missions are an important source of information about the status of the marine ressources.The objectives of the surveys are multiple: to estimate the abundance and biomass of groundfish and invertebrates, to identify the spatial distribution and biological characteristics of these species, to monitor the biodiversity of the Estuary and Gulf and finally, to describe the environmental conditions observed in the area at the moment of the sampling.The southern Gulf surveys are realized using the following standardized protocol:Hurlbut,T. and D.Clay (eds) 1990. Protocols for Research Vessel Cruises within the Gulf Region (Demersal Fish) (1970-1987). Can. MS Rep. Fish. Aquat. Sci. No. 2082: 143p.The sampling protocols used for the Estuary and northern Gulf surveys are described in details in the following publications:Bourdages, H., Archambault, D., Bernier, B., Fréchet, A., Gauthier, J., Grégoire, F., Lambert, J., et Savard, L. 2010. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2009 dans le nord du golfe du Saint-Laurent. Rapp. stat. can. sci. halieut. aquat. 1226 : xii+ 72 p. Bourdages, H., Archambault, D., Morin, B., Fréchet, A., Savard, L., Grégoire, F., et Bérubé, M. 2003. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2003 dans le nord du golfe du Saint-Laurent. Secr. can. consult. sci. du MPO. Doc. rech. 2003/078. vi + 68 p.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Bourdages, H., Brassard, C., Desgagnés, M., Galbraith, P., Gauthier, J., Légaré, B., Nozères, C. and Parent, E. 2017. Preliminary results from the groundfish and shrimp multidisciplinary survey in August 2016 in the Estuary and northern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/002. v + 87 p.

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 includes fifteen GeoTIFFs of Sea Surface Temperature (SST) organized into five distinct marine regions along Canada's Pacific coast, derived from Sentinel 3 satellite data for the period of April-September 2017. For each region, three GeoTIFFs are provided which represent the mean, maximum, and standard deviation values of SST (degrees Celcius). Jupyter notebooks with Python code used for data downloading and processing are also included for reference.The primary objective of this dataset is to provide detailed, regional spatial information on SST for key areas of Canada's Pacific coast, including the nearshore environment. The data can be used for various applications including species distribution modelling.This dataset is intended to fill the knowledge gap by providing high-resolution, spatially explicit regional SST data for Canada's Pacific coast. Existing datasets may not provide sufficient spatial resolution or may not include comprehensive statistical measures (mean, max, standard deviation) of SST for these specific areas.The dataset is structured by region. For each of the five regions, a set of three related GeoTIFFs is provided, representing the mean, max, and standard deviation of SST. Within each regional set, the three layers share the same spatial reference system, resolution, and extent, making them suitable for direct use in analytical stacks (e.g., for species distribution models).The Sentinel-3 satellites, part of the European Union's Copernicus Programme, are equipped with the Sea and Land Surface Temperature Radiometer (SLSTR) which measures SST among other parameters. The SST data products in this dataset are derived from Sentinel-3 satellite data.The intent of the data is to represent the marine environment and so a mask that excludes land was applied during data download and extraction. The SST data products have been resampled using a bilinear interpolation from their native resolution to a 20 m resolution to provide more detailed spatial information.

This dataset provides refined monthly climatological projections for six key ocean variables: surface and bottom temperature, surface and bottom salinity, mixed layer depth, and bottom current speed. The projections are provided for six Maritime Marine Protected Areas: the Gully, the Laurentian Channel, St. Anns Bank, Musquash Estuary, Banc-des-Américains, and Basin Head. These projections are based on downscaled outputs from 22 CMIP6 models under four emissions scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) for four 20-year periods spanning 2020 to 2099 (2020–2039, 2040–2059, 2060–2079, and 2080–2099).For each model and scenario, 20-year climatological means were computed for each future period. These climatologies were then aggregated to produce ensemble means and ensemble standard deviations for all variables. The released dataset includes only these ensemble summary fields and is provided as gridded data with dimensions longitude × latitude × scenario × time.Cite this data as: Wang., Z. Data of High-resolution climate projection data for Marine Protected Areas in the Maritimes. Published: May 2026. Ocean Ecosystems Science Division, Maritimes Region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/fb4b3212-bca3-4192-8401-687faccc534b

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.

The shallow substrate bottom type model was created to support near shore habitat modelling. Data sources include both available observations of bottom type and environmental predictor layers including oceanographic layers, fetch, and bathymetry and its derivatives. Using weighted random forest classification from the ranger R package, the relationship between observed bottom type and predictor layers can be determined, allowing bottom type to be classified across the study areas. The predicted raster files are classified as follows: 1) Rock, 2) Mixed, 3) Sand, 4) MudThe categorical substrate model domains are restricted to the extent of the input bathymetry layers (see data sources) which is 5 km from the 50 m depth contour.