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.

This polygon layer visualizes actual observed precipitation polygons (classed by amounts) from the HRDPA product, offering a clear map-based depiction of recent rainfall or snowfall distribution. Observation periods depicted are past 1 day, past 3 days and past 7 days.This polygon layer is generated by taking HRDPA’s gridded precipitation data (6h, 24h, or multi-day accumulations) and grouping them into precipitation ranges, then polygonizing. Each feature shows how much precipitation truly fell in that zone. This is essential for event verification against forecasts, analyzing localized extremes, and updating water resource or flood models with real observed input.

This polygon layer presents the spatial distribution of forecasted accumulated precipitation from the Global Forecast System (GFS) over watershed sub‑basins. GFS APCP raster data are overlaid with global watershed boundaries, and zonal statistics are computed to derive average precipitation per sub‑basin over a 7‑day (168‑hour) period. This product aids in global disaster preparedness and water management planning.GFS model output is processed into APCP rasters that capture accumulated precipitation over a 7‑day forecast period. These rasters are then combined with watershed boundary data, and zonal statistics are applied to compute average precipitation for each sub‑basin. The final polygon features provide a clear depiction of global rainfall and snowfall patterns, offering critical information for disaster risk management and international water resource planning.

Accumulated Precipitation represents the amount of total precipitation in mm (solid and/or liquid) which has been recorded over a given month or ISO week.Accumulation of precipitation values serve to inform users about the total amount of precipitation that has fallen in a specific region during a set time period. The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

Difference from Average Precipitation represents the accumulated precipitation value for a location, subtracted by the long-term average value. A negative value indicates that the location has received less than the normal amount of precipitation (mm) for that timeframe. A positive value indicates that the location has received more than the normal amount of precipitation (mm).Time periods calculated for difference from average precipitation are 1, 2, 3, 6, 9, 12, 18, 24 months.Long-term average is 1991-2020. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

The Adjusted Precipitation data consist of monthly, seasonal and annual totals of daily adjusted rain, snow and total precipitation (millimetres) for 464 locations in Canada. Adjusted precipitation data incorporate adjustments (derived from comparison of instruments) to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The time periods of the data vary by location, with the oldest data available from the early 1880s at some stations to the most recent update in 2017. Observations at co-located sites were sometimes joined in order to create longer time series. Data availability over most of the Canadian Arctic is restricted to the mid-1940s to present.

Monthly, seasonal and annual trends of total precipitation change (millimetres) based on adjusted station data (AHCCD) are available. Trends are calculated using the Theil-Sen method using the station’s full period of available data. The availability of precipitation trends will vary by station; if more than 5 consecutive years are missing data or more than 10% of the data within the time series is missing, a trend was not calculated.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in total precipitation are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily precipitation (mm/day) from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded precipitation dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected relative change in total precipitation is with respect to the reference period of 1986-2005 and expressed as a percentage (%). Seasonal and annual averages of projected precipitation change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of projected precipitation change are available for the historical time period, 1901-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in statistically downscaled total precipitation (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of downscaled CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.

This polygon layer depicts sub-basin average observed precipitation from the High Resolution Deterministic Precipitation Analysis (HRDPA). Offers insight into how much rain/snow actually fell across each watershed in the past observation period. Observation periods we are interested are for past 1 day, 3 days and 7 days.HRDPA is ECCC’s high-resolution precipitation analysis, merging gauge, radar, and HRDPS model data. This layer aggregates the final (or preliminary) HRDPA accumulations to sub-basin polygons. Each record indicates the average precipitation that truly occurred over each watershed, vital for verifying model forecasts, calibrating hydrological models, and conducting post-event analyses of flood or drought severity.

Statistically downscaled multi-model ensembles of total precipitation are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily precipitation (mm/day) from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded precipitation dataset of Canada (ANUSPLIN) was used as the downscaling target. The 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of downscaled total precipitation (mm/day) are available for the historical time period, 1951-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.