The HOT2000 software contains monthly and annual climate data for 403 locations in Canada. Boundary lines for HOT2000 climate zones were defined through spatial interpolation of the annual Celsius heating degree-days for each weather station. In a number of instances, the positions of boundary lines may not be representative of the local climate conditions due to lack of appropriate climate data. Each HOT2000 climate zone contains one weather station to be used for all locations within the zone. Climate data represent 20-year averaged data from 1998 to 2017 for locations south of 58° latitude and 13-year averaged data from 2005 to 2017 for locations north of 58° latitude. Note that Whistler, BC uses 13 years of data.The following information is available in the climate map:o Location: the name of the weather station.o Region: the provincial or territorial location of the weather station.o Latitude: measured in degrees north of the equator.o Annual heating degree-days using a base of 18 °C.o Design heating dry bulb temperature (°C): the 2.5% January design temperature used to calculate the design heat loss for the house.o Design cooling dry bulb temperature (°C): the 2.5% July design temperature used to calculate the design cooling load for the house.o Design cooling wet bulb temperature (°C): the 2.5% July design temperature used to calculate the design cooling load for the house.The climate map is intended to be used by all users of the HOT2000 software under the EnerGuide Rating System, including energy advisors, service organizations, regulatory agencies, builders, utilities, and all levels of government.The weather locations and climate data are based on Environment and Climate Change Canada data, specifically the Canadian Weather Energy and Engineering Datasets (CWEEDS).

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.

Climate observations are derived from two sources of data. The first are Daily Climate Stations producing one or two observations per day of temperature, precipitation. The second are hourly stations that typically produce more weather elements e.g. wind or snow on ground.

Leaf area index (LAI) quantifies the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of time series of LAI observed between 2016 and 2025 over reclamation sites in Alberta, Canada May and October. The temporal frequency depends on cloud cover.

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.

644 datasets of Typical Meteorological Years (TMY) created by joining twelve Typical Meteorological Months selected from a database of up to 20 years of CWEEDS hourly data. The months are chosen by statistically comparing individual monthly means with long-term monthly means for daily total global solar irradiance, mean, minimum and maximum dry bulb temperature, mean, minimum and maximum dew point temperature, and mean and maximum wind speed. These hourly datasets are used by the engineering and scientific community mainly as inputs for solar system design and analysis and building energy systems analysis tools. This dataset has been updated with the most recent changes made in March 2023. The solar values in these files are based on 0.1° x 0.1° (11 km x 11 km grid) for all of Canada. Refer to Data Resources below for additional information on the TMY file format.

Environment and Climate Change Canada’s (ECCC) Climate Research Division (CRD) and the Pacific Climate Impacts Consortium (PCIC) previously produced statistically downscaled climate scenarios based on simulations from climate models that participated in the Coupled Model Intercomparison Project phase 5 (CMIP5) in 2015. ECCC and PCIC have now updated the CMIP5-based downscaled scenarios with two new sets of downscaled scenarios based on the next generation of climate projections from the Coupled Model Intercomparison Project phase 6 (CMIP6). The scenarios are named Canadian Downscaled Climate Scenarios–Univariate method from CMIP6 (CanDCS-U6) and Canadian Downscaled Climate Scenarios–Multivariate method from CMIP6 (CanDCS-M6).CMIP6 climate projections are based on both updated global climate models and new emissions scenarios called “Shared Socioeconomic Pathways” (SSPs). Statistically downscaled datasets have been produced from 26 CMIP6 global climate models (GCMs) under three different emission scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5), with PCIC later adding SSP3-7.0 to the CanDCS-M6 dataset. The CanDCS-U6 was downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2) procedure, and CanDCS-M6 was downscaled using the N-dimensional Multivariate Bias Correction (MBCn) method. The CanDCS-U6 dataset was produced using the same downscaling target data (NRCANmet) as the CMIP5-based downscaled scenarios, while the CanDCS-M6 dataset implements a new target dataset (ANUSPLIN and PNWNAmet blended dataset).Statistically downscaled individual model output and ensembles are available for download. Downscaled climate indices are available across Canada at 10km grid spatial resolution for the 1950-2014 historical period and for the 2015-2100 period following each of the three emission scenarios.Note: projected future changes by statistically downscaled products are not necessarily more credible than those by the underlying climate model outputs. In many cases, especially for absolute threshold-based indices, projections based on downscaled data have a smaller spread because of the removal of model biases. However, this is not the case for all indices. Downscaling from GCM resolution to the fine resolution needed for impacts assessment increases the level of spatial detail and temporal variability to better match observations. Since these adjustments are GCM dependent, the resulting indices could have a wider spread when computed from downscaled data as compared to those directly computed from GCM output. In the latter case, it is not the downscaling procedure that makes future projection more uncertain; rather, it is indicative of higher variability associated with finer spatial scale.Individual model datasets and all related derived products are subject to the terms of use (https://pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-1.html) of the source organization.

Point locations of water and weather monitoring stations used by the [Surface Water Monitoring Centre](http://www.ontario.ca/page/surface-water-monitoring-centre) to assess flood and drought conditions across Ontario. Monitoring station types include: * streamflow gauge stations * Environment and Climate Change Canada climate stations * Ministry of Transportation road weather stations * Ministry of Natural Resources (MNR) fire weather stations * MNR snow network stations (wildlife) * MNR snow survey stations (weather) * Ontario Power Generation snow survey stations (weather)

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) based on an ensemble of twenty-nine Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1901-2100. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of projected change in mean temperature 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 mean temperature (°C) 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 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.

Daily climate observations are derived from two sources of data. The first are Daily Climate Stations producing one or two observations per day of temperature, precipitation. The second are hourly stations that typically produce more weather elements e.g. wind or snow on ground. Only a subset of the total stations is shown due to size limitations. The criteria for station selection are listed as below. The priorities for inclusion are as follows: (1) Station is currently operational, (2) Stations with long periods of record, (3) Stations that are co-located with the categories above and supplement the period of record.