This polygon layer shows the spatial distribution of forecasted accumulated precipitation across watershed sub‑basins using data derived from the Regional Ensemble Prediction System (REPS). In other words, it aggregates precipitation amounts—computed from processed REPS forecast output (converted from GRIB2 files into raster [TIF] format)—over defined watershed boundaries to provide a detailed view of expected rainfall over a typical 72‑hour forecast period. This information supports regional hydrological forecasting, flood risk analysis, and water resource management. REPS forecast data are first processed to extract the accumulated precipitation field (APCP) and converted into high‑resolution raster images. These “REPS APCP rasters” represent the spatial distribution of forecast precipitation (in millimeters) over the region. Next, using pre‑defined watershed or sub‑basin boundaries, zonal statistics are applied to compute the average precipitation for each sub‑basin. The final layer displays these averaged values as polygon features, highlighting variations in forecasted rainfall across different drainage areas. This approach helps users pinpoint regions that may receive higher or lower rainfall, thereby enhancing hydrological assessments and emergency planning.

The Regional Air Quality Deterministic Prediction System FireWork (RAQDPS-FW) carries out physics and chemistry calculations, including emissions from active wildfires, to arrive at deterministic predictions of chemical species concentration of interest to air quality, such as fine particulate matter PM2.5 (2.5 micrometers in diameter or less). Geographical coverage is Canada and the United States. Data is available at a horizontal resolution of 10 km. While the system encompasses more than 80 vertical levels, data is available only for the surface level. The products are presented as historical, annual or monthly, averages which highlight long-term trends in cumulative effects on the environment.

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).

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).

This feature layer showcases ultra-fine (2.5 km) short-range precipitation forecasts from the High Resolution Deterministic Prediction System (HRDPS), a convection-permitting model by Environment and Climate Change Canada. It identifies local-scale rainfall or snowfall patterns up to 48 hours, supporting urban flood forecasting, severe weather response, and detailed water resource planning. Convection-Permitting: The HRDPS can explicitly resolve thunderstorms and other small-scale weather events by running at ~2.5 km. Short-Range Focus: Typically provides forecasts out to 36–48 hours, updated several times daily. Local Impact: Valuable for pinpointing high-impact precipitation in complex terrain or urban environments, aiding emergency managers and hydrologists in short-lead-time decisions. Nested Model: Receives lateral boundary conditions from RDPS, maintaining consistency with regional forecasts while refining detail in local domains.

This polygon layer showcases ultra-fine (2.5 km) short-range precipitation forecasts from the High Resolution Deterministic Prediction System (HRDPS), a convection-permitting model by Environment and Climate Change Canada. It identifies local-scale rainfall or snowfall patterns up to 48 hours, supporting urban flood forecasting, severe weather response, and detailed water resource planning. Convection-Permitting: The HRDPS can explicitly resolve thunderstorms and other small-scale weather events by running at ~2.5 km. Short-Range Focus: Typically provides forecasts out to 36–48 hours, updated several times daily. Local Impact: Valuable for pinpointing high-impact precipitation in complex terrain or urban environments, aiding emergency managers and hydrologists in short-lead-time decisions. Nested Model: Receives lateral boundary conditions from RDPS, maintaining consistency with regional forecasts while refining detail in local domains.

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

This polygon layer represents accumulated precipitation forecasts from the Regional Ensemble Prediction System (REPS), a regional probabilistic model. It delivers ensemble‑based, short‑range precipitation forecasts—typically a 72‑hour accumulation—that aid in assessing the risk and spatial distribution of rainfall events, supporting hydrological analysis, flood forecasting, and water resource management. This polygon layer is produced by processing REPS GRIB2 files. The workflow involves extracting the precipitation field, converting it to a TIF raster, and then applying resampling, smoothing, and classification to create polygon features. These features represent forecasted rainfall totals over a 72‑hour period and are updated with each model run to maintain current predictive information. Source: Environment & Climate Change Canada

This is the web experience created using ArcGIS Web Experience Builder to portray the dynamic precipitation maps derived using various weather model data published by the Environment Canada, National Oceanic and Atmospheric Administration and European Centre for Medium-Range Weather Forecasts. It contains various precipitation layers for each of the models depicting various forecast periods / observation periods. The underlying data is updated regularly as the data gets published by ECCC/NOAA/ECMWF as per the publishing frequency. Following are the forecast weather models depicted in this Web Experience : HRDPS Model (High Resolution Deterministic Prediction System - Continental) for 24 and 48 hours of forecast periods. Regional Ensemble Prediction System (REPS) for 72 hours of forecast period hour. Regional Deterministic Prediction System (RDPS) for 84 hours of forecast period hour. Global Deterministic Prediction System (GDPS) for 168 and 240 hours of forecast periods. Global Forecast System (GFS) for 168 hours of forecast period. Global Ensemble Prediction System (GEPS) for 384 hours of forecast period. European Centre for Medium-Range Weather Forecasts for 168 hours of forecast periodAnd following are the observed weather models depicted in this Web Experience :High Resolution Deterministic Precipitation Analysis (HRDPA) with observation periods of the past 1 day, 3 days and 7 days.Special Thanks to Environment and Climate Change Canada, NOAA’s National Centers for Environmental Prediction, European Centre for Medium-Range Weather Forecasts