The Regional Ice Ocean Prediction System (RIOPS) provides ice and ocean forecasts up to 84 hours, four times per day on a 1/12° resolution grid (3-8 km). RIOPS is initialized using analyses from the Global Ice-Ocean Prediction System (GIOPS). Atmospheric fluxes up to 84 hours forecasts are calculated using fields from a component of the Global Deterministic Prediction System (GDPS) at 10km horizontal resolution

This polygon layer reflects short-range (up to 84 hours) accumulated precipitation forecasts from the Regional Deterministic Prediction System (RDPS), a high-resolution (~10 km) weather model developed by Environment and Climate Change Canada (ECCC). It supports flood forecasting, hydrological modeling, and operational planning by providing refined, near-real-time precipitation guidance for Canada and surrounding areas.Short-Range Forecasts: RDPS runs multiple times per day, offering precipitation outlooks for days 0–3.5 with updates every six hours. High Resolution: At ~10 km, RDPS captures critical mesoscale phenomena like localized downpours, lake-effect snow, and terrain-driven precipitation. Hydrological Utility: Especially valuable for sub-basin-level flood risk assessment and water resource management in near-term scenarios. Technical Basis: The RDPS is a limited-area configuration of the GEM model, using initial/boundary conditions from ECCC’s Global Deterministic Prediction System (GDPS).

This polygon layer displays 84-hour accumulated precipitation forecasts from the Regional Deterministic Prediction System (RDPS), aggregated at the sub-basin level. This layer helps hydrologists, water resource managers, and emergency responders identify watersheds with potentially higher rainfall or snowfall, facilitating short-term flood risk analysis and operational planning.Model & Domain: The RDPS is Environment and Climate Change Canada’s regional numerical weather prediction model, running at ~10 km resolution to capture mesoscale weather patterns over Canada and adjacent regions. Forecast Integration: It produces short-range forecasts (up to 84 hours), updated 4 times daily with boundary conditions from the global GEM model (GDPS). Sub-Basin Aggregation: This layer averages forecasted precipitation across each sub-basin polygon, providing a convenient snapshot of expected accumulations for hydrological modeling and water management. Key Applications:Flood Forecasting – Identifying basins at risk of heavy runoff. Resource Allocation – Positioning crews and equipment in vulnerable watersheds. Planning – Adapting reservoir release schedules, urban drainage controls, and agricultural activities

Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.

The Regional Deterministic Prediction System (RDPS) carries out physics calculations to arrive at deterministic predictions of atmospheric elements from the current day out to 84 hours into the future. Atmospheric elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage includes Canada and the United States. Data is available at horizontal resolution of about 10 km up to 33 vertical levels. Predictions are performed four times a day.Note: The Regional Deterministic Prediction System is now a component of the Global Deterministic Prediction System (GDPS) at 10 km resolution, over a North American domain.

This GIS dataset depicts the surficial geology of the NTS map area 84K northeast (point features). The data are created in ArcInfo format and output for public distribution in Arc export (E00) and shapefile formats.

This dataset represents abundance data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey. Data is binned into 5-mm shell height bins, is prorated to an 800 m tow length and 17.5 feet (5.334 m) drag width (i.e., representing an area swept of 4267 m2), and was collected using unlined dredge gear. Each row represents a tow and contains information such as tow date, cruise name, gear type, 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 Commercial Size Abundance Data. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ecc09d98-56ed-4a27-ad62-5c3714a1d9b4

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

This GIS dataset depicts the surficial geology of the NTS map area 84K northeast ( line features). The data are created in ArcInfo format and output for public distribution in Arc export (E00) and shapefile formats.

The Canadian Precipitation Analysis System (CaPA) produces a best estimate of 6 and 24 hour precipitation amounts. This objective estimate integrates data from in situ precipitation gauge measurements, radar QPEs and a trial field generated by a numerical weather prediction system. In order to produce the High Resolution Deterministic Precipitation Analysis (HRDPA) at a resolution of 2.5 km, CaPA is connected to the continental HRDPS for its trial field. CaPA-HRDPA produces four analyses of 6 hour amounts per day, valid at synoptic hours (00, 06, 12 and 18 UTC) and two 24 hour analysis valid at 06 and 12 UTC. A preliminary production is started 1 hour after valid time and a final one is launched 7 hours later. This translates into a production of 12 analyses per day.