Description:Seasonal climatologies for salinity of the Northeast Pacific Ocean were computed to cover the period 2001 to 2020. Historibal observations included all available conductivity-temperature_depth (CTD), bottle and profiling floats in the NODC World Ocean Database, Marine Environmental Data Services (MEDS), Institute of Ocean Sciences Water Properties website and the Canadian Integrated Ocean Observing System (CIOOS Pacific).Methods:Interpolation was carried out in up to fifty-two vertical levels from surface to 5000m. Data-Interpolating Variational Analysis (DIVA) was used for spatial interpolation for all years within each season and estimates projected onto a consistent grid. The average of the grid nodes was calculated to obtain the seasonal climatology. DIVA was used again on the final climatology followed by a median filter and a 5-point smoother. 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 salinity climatology for the Canadian Pacific Exclusive Economic Zone (EEZ), a subset of seasonal climatology of the Northeast Pacific Ocean, with high spatial resolution of 1/300 degree.Data Sources:NODC, MEDS, IOS and CIOOS Pacific Data.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.

This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer (<5 cm). The data is created daily and is averaged for the ISO standard week and month. The data is produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 6.20 of the SMOS soil moisture processor.The data are produced by the European Space Agency and obtained under a Category 1 proposal for Level 2 soil moisture data. The data are gridded to a resolution of 0.25 degrees. Data quality flags have been applied to remove areas where rainfall is present during the acquisition, where snow cover is detected and when Radio Frequency Interference (RFI) is above an acceptable threshold.

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.

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.

This inventory, conducted from September 26th to October 3th, 2019, aimed to describe the community structure of macroalgae and benthic macroinvertebrates of five small estuaries of the Upper North Shore of Quebec, namely Barthélemy Bay and the Colombier, Mistassini, Franquelin and Saint-Nicolas rivers. This inventory is part of a doctoral study of Valentine Loiseau on the global changes in the St. Lawrence system, mainly the study of marine benthic communities in response to changes of salinity, to ensure proper management of the environment in the face of future changes. The main objective is to describe the structure and the levels of specific diversities of mediolittoral communities of benthic macroinvertebrates and macroalgae along a salinity gradient. These five small estuaries were selected because of their similar size, hard substrates and easy access. Three levels of hypoosmotic stress (low, medium, high) and one control level (seawater) were used for each of the selected estuaries, with eight quadrats per stress level. Quadrat positions were randomly selected but had to meet two criteria: (1) regular height in the foreshore to control the influence of other stresses (temperature, exposure); and (2) presence of at least one macroalga to maintain homogeneity. A percentage cover by macroalgal and macroinvertebrate species was estimated, and then all organisms were weighed by species and size group. The salinity of the nearest water point was measured at mid-tide with a portable refractometer and a Castaway-type CTD (Conductivity-Temperature-Density) probe. The inventory was done using a stratified random sampling design and the sampling unit was a quadrat measuring 25 x 25 cm. The three files provided (DarwinCore format) are complementary and are linked by the "eventID" key. The "event_information" file includes the generic information of the quadrat, including date and location. The "additional_information_event_and_occurrence" file includes salinity and substrate type of the quadrat, as well as the total weight of all individuals of the same species caught in the quadrat extrapolated to one square metre of surface. For nudibranchs and barnacles, weight was estimated from the size of the individuals so that they were not removed from the environment. The "taxon_occurrence" file includes the taxonomic inventory of macroalgal and benthic macroinvertebrate species observed in the quadrat, identified to the lowest possible species or taxonomic level and biomass by identified species.For quality control, organisms were identified on the field using the following guide: Chabot, Robert et Anne Rossignol. 2003. Algues et faune du littoral du Saint-Laurent maritime : Guide d'identification. Institut des Sciences de la mer de Rimouski, Rimouski ; Pêches et Océans Canada (Institut Maurice-Lamontagne), Mont-Joli. 113 pages. The taxonomy was checked against the World Register of Marine Species (WoRMS) to match recognized standards and using the R obistools and worrms libraries. The WoRMS match was placed in the "scientificNameID" field of the occurrence file. All sample locations were spatially validated. This project was funded by DFO Coastal Environmental Baseline Program under Canada’s Oceans Protection Plan. This initiative aims to acquire environmental baseline data contributing to the characterization of important coastal areas and to support evidence-based assessments and management decisions for preserving marine ecosystems.

11 tagged Blue whales (Balaenoptera musculus) were tracked during the daytime movements as well as the feeding behaviour in the St. Lawrence River estuary. Kernel density was applied to derminate the high density feeding areas of all individuals combined (30, 40, 50, 60, 75, 95 %).Doniol-Valcroze T, Lesage V, Giard J, Michaud R, 2012. Challenges in marine mammal habitat modelling: evidence of multiple foraging habitats from the identification of feeding events in blue whales. Endang Species Res, Vol. 17 : 255–268, doi : 10.3354/esr00427(English version only)

Description:Seasonal mean salinity from the British Columbia continental margin model (BCCM) were averaged over the 1993 to 2020 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone.Methods:Salinities at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. 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 salinity climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.Uncertainties:Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

Description:Seasonal mean salinity from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone.Methods:Salinities at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. 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 salinity climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.Uncertainties:Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

1999 to 2023 surface temperature and salinity measured along the track of commercial ships, mostly between Montreal (Quebec) and St. John's (Newfoundland).Monitoring of surface water conditions in the Estuary and Gulf of St. Lawrence is carried out with different complementary methods such as thermosalinographs (TSG) installed on commercial ships. These ships are sailing all year long from Montreal to St. John’s, one round trip per week, and are sampling water near the surface (3 to 8 meters deep) to determine the temperature and salinity all along the route.PurposeThe recorded data are used as input to numerical forecasting models for sea ice conditions and as a monitoring tool for the Gulf of St. Lawrence.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm). Galbraith, P.S., Chassé, J., Caverhill, C., Nicot, P., Gilbert, D., Lefaivre, D. and Lafleur, C. 2018. Physical Oceanographic Conditions in the Gulf of St. Lawrence during 2017. DFO Can. Sci. Advis. Sec. Res. Doc. 2018/050. v + 79 p.

The wind power density layer shows the modeled wind power density [W/m2] at a height of 100 m above ground level, at each grid point, averaged over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 0.5 W/m2 each. Further details including data at different heights, and for individual years, can be obtained by clicking on the dot representing the grid point location.