The Regional Ensemble storm Surge Prediction System (RESPS) produces storm surge forecasts using the DalCoast ocean model. DalCoast (Bernier and Thompson 2015) is a storm surge forecast system for the east coast of Canada based on the depth-integrated, barotropic and linearized form of the Princeton Ocean Model. The model is forced by the 10 meters winds and sea level pressure from the Global Ensemble Prediction System (GEPS).

Sea level rise increases coastal flooding in many areas of Canada. The Canadian Extreme Water Level Adaptation tool has been developed to accommodate sea level rise. The infrastructure needs to be built higher in order to reduce the risk of flooding. The vertical allowance is the recommended height that the infrastructure to be raised in future years relative to year 2010. The vertical allowance depends on (1) statistics of historical storm surge and tides, and (2) the best estimate and associated uncertainty of future sea level rise. The vertical allowance preserves the frequency of flooding events at some future time under uncertain sea level rise. Vertical allowances are provided for scenarios based on the fifth assessment report (AR5) of IPCC for the period of 2020-2100 and the sixth assessment report (AR6) of IPCC for the period of 2020-2150.Cite this data as: Zhai, L., Greenan, B., Perrie, W. Data of:Vertical allowance gridded dataset for Canada.Published: February 2024. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.https://open.canada.ca/data/en/dataset/5c164079-9785-42fa-8fa5-d886ccbae3b3

Representation of the causes of flooding events in the form of multiple points. The point groupings correspond to the set of locations that were affected by the same event. The inventory of past flooding events was compiled from various public sources and standardized into a common data model. Sources used are included in the data. Event locations have been extensively revised to have one location per location reported as affected by the flood. Flood events for which no location was included in the sources used are positioned on the place name of the location affected by the flood. The event positions do not indicate where the flooding occurred. Flood events that affected more than one locality are represented by a multipoint.For each event after January 1, 1980 caused by a heavy rainfall or a coastal storm , a precipitation analysis document, a precipitation animation and the precipitation data are available. These documents are the result of a collaboration with Environment and Climate Change Canada.Disclaimer:It should be noted that no consultation was conducted with the various providers and stakeholders of the historic flood data. Disparities in content among the various sources result in an incomlete product. No warranty is given as to the accuracy or completeness of the information provided. The absence of information does not mean that no flooding has occurred.

Extreme water level along the marine coastline is a result of a combination of storm surge, tides, and ocean waves. Future projections of climate change in the marine environment indicate that rising sea level and declining sea ice will cause changes in extreme water levels, which will impact Canada's coastlines and the infrastructure in these areas. Understanding these changes is essential for developing adaptation strategies that can minimize the harmful effects that may result.CAN-EWLAT is a science-based planning tool for climate change adaptation of coastal infrastructure related to future water-level extremes and changes in wave climate. The tool includes two main components: 1) vertical allowance and 2) wave climate. CAN-EWLAT was developed primarily for DFO Small Craft Harbours (SCH) locations, but it should prove useful for coastal planners dealing with infrastructure along Canada’s ocean coastlines.Cite this data as: Greenan B. Canadian Extreme Water Level Adaptation Tool (CAN-EWLAT) Published June 2022. Oceans Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

The Global Deterministic storm Surge Prediction System (GDSPS) produces water level forecasts using a modified version of the NEMO ocean model (Wang et al. 2021, 2022, 2023). It provides 240 hours forecasts twice per day on a 1/12° resolution grid (3-9 km). The model is forced by the 10 meters winds, sea level pressure, ice concentration, ice velocity and surface currents from the Global Deterministic Prediction System (GDPS). The three dimensionnal ocean temperature and salinity fields of the model are nudged to values provided by the Global Ice-Ocean Prediction System (GIOPS) and the GDPS. During the post-processing phase, storm surge elevation (ETAS) is derived from total water level (SSH) by harmonic analysis using t_tide (Foreman et al. 2009).

The Steller sea lion (Eumetopias jubatus) is the largest species of sea lion with males weighing as much as 1,100 kg and females as much as 350 kg. In Canada, the Steller can be spotted along the rocky coast of British Columbia (BC). These highly mobile marine mammals typically travel alone or in small groups, but they congregate in large numbers at traditional rookeries and haul-outs during the mating and pupping season. Females generally live longer (up to 30 years) than males (usually up to 20 years). The population was severely depleted in Canada but following its protection in 1970, the size of the adult population has more than doubled.Trends in the abundance of Steller sea lions in BC have been assessed based on a series of standardized, province-wide aerial surveys conducted during the breeding season (27-June to 06-July) between 1971 and 2021. Additional ad-hoc surveys during the fall, winter, and spring periods were completed to assess sea lion distribution outside of the breeding season. Surveys targeted historically occupied rookeries and haul-out sites with nearby areas also monitored for potential shifts in distribution.Both datasets contain counts that have been collected from sightings of individuals from 1971 through 2021. The updated standard breeding season survey counts data file consolidates and extends two previous datasets – one covering 1971 through 2013 and the other covering the summer portion of the 2016/2017 surveys. The non-breeding season count data was previously limited to the fall-winter portion of the 2016/2017 surveys and the updated data covers the entire study period to date.

"Fall" missions occur primarily in October and November, but sets from September and December are also present in the data. Collected data includes total catch in numbers and weights by species. Length frequency data is available for most species, as are the age, sex, maturity and weight information for a subset of the individual animals. Other data such as ageing material, genetic material, and stomach contents are often also collected, but are stored elsewhere."Fall" cruises occur in September, October, November and December.Cite this data as: Clark, D., Emberley, J. Data of Maritimes Fall Research Vessel Survey. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/5f82b379-c1e5-4a02-b825-f34fc645a529

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.

Food Banks is a point dataset identifying food banks in British Columbia.

This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58