<DIV STYLE="text-align:Left;"><DIV><P><SPAN>CCMEO is currently testing Pinkmatter’s FarEarth Observer Real-time Fire Detection Plugin for LANDSAT-8 for low latency hot spot fire warnings. Due to of its higher resolution resolution to the typical space-borne sensors used for fire detection (i.e. MODIS, VIIRS, etc), LANDSAT is a potential tool for the detection of small fires and the monitoring of a fire front. Hot Spot detection is done in Near Real Time during live receptions at the Prince Albert Satellite Station.</SPAN></P><P><SPAN STYLE="font-weight:bold;">*****DISCLAIMER*****</SPAN></P><P><SPAN>NRCan acknowledges that the Landsat 8 hotspot alerts are not error-free. While the hotspot detection from real-time Landsat 8 data received at the Prince Albert Satellite Station is based on a published hotspot detection algorithm, the algorithm hasn’t been optimized for Canadian wild fires. Also there is an inherent positional error of up to several hundred metres based on the real-time data processing. The hotspot alerts are supplied "as is", without any warranty of any kind, express or implied. NRCan can not be held liable for direct, indirect, special, incidental, or consequential damages arising out of the use of the hotspot alert data.</SPAN></P></DIV></DIV>

"The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem. The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications. Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century. Provided layer: projected number of large fires (>200 ha) across Canada for the short-term (2011-2040) under the RCP 8.5 (continued emissions increases)."

The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem. Annual area burned is the average surface area burned annually in Canada by large fires (greater than 200 hectares (ha)). Changes in annual area burned were estimated using Homogeneous Fire Regime (HFR) zones. These zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications. Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century. Multiple layers are provided. First, the annual area burned by large fires (>200 ha) is shown across Canada for a reference period (1981-2010). Projected annual area burned layers are available for the short- (2011-2040), medium- (2041-2070), and long-term (2071-2100) under the RCP 8.5 (continued emissions increases) and, for the long-term (2071-2100), under RCP 2.6 (rapid emissions reductions).

Fire weather refers to weather conditions that are conducive to fire. These conditions determine the fire season, which is the period(s) of the year during which fires are likely to start, spread and do sufficient damage to warrant organized fire suppression. The length of fire season is the difference between the start- and end-of-fire-season dates. These are defined by the Canadian Forest Fire Weather Index (FWI; http://cwfis.cfs.nrcan.gc.ca/) start-up and end dates. Start-up occurs when the station has been snow-free for 3 consecutive days, with noon temperatures of at least 12°C. For stations that do not report significant snow cover during the winter (i.e., less than 10 cm or snow-free for 75% of the days in January and February), start-up occurs when the mean daily temperature has been 6°C or higher for 3 consecutive days. The fire season ends with the onset of winter, generally following 7 consecutive days of snow cover. If there are no snow data, shutdown occurs following 7 consecutive days with noon temperatures lower than or equal to 5°C. Historical climate conditions were derived from the 1981–2010 Canadian Climate Normals. Future projections were computed using two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century. Multiple layers are provided. First, the fire season length is shown across Canada for a reference period (1981-2010). Projected fire season length layers are available for the short- (2011-2040), medium- (2041-2070), and long-term (2071-2100) under the RCP 8.5 (continued emissions increases) and, for the long-term (2071-2100), under RCP 2.6 (rapid emissions reductions).

Fire weather refers to weather conditions that are conducive to fire. These conditions determine the fire season, which is the period(s) of the year during which fires are likely to start, spread and do sufficient damage to warrant organized fire suppression. The length of fire season is the difference between the start- and end-of-fire-season dates. These are defined by the Canadian Forest Fire Weather Index (FWI; http://cwfis.cfs.nrcan.gc.ca/) start-up and end dates. Start-up occurs when the station has been snow-free for 3 consecutive days, with noon temperatures of at least 12°C. For stations that do not report significant snow cover during the winter (i.e., less than 10 cm or snow-free for 75% of the days in January and February), start-up occurs when the mean daily temperature has been 6°C or higher for 3 consecutive days. The fire season ends with the onset of winter, generally following 7 consecutive days of snow cover. If there are no snow data, shutdown occurs following 7 consecutive days with noon temperatures lower than or equal to 5°C. Historical climate conditions were derived from the 1981–2010 Canadian Climate Normals. Future projections were computed using two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century. Multiple layers are provided. First, the fire season length is shown across Canada for a reference period (1981-2010). Projected fire season length layers are available for the short- (2011-2040), medium- (2041-2070), and long-term (2071-2100) under the RCP 8.5 (continued emissions increases) and, for the long-term (2071-2100), under RCP 2.6 (rapid emissions reductions).

Environment and Climate Change Canada (ECCC) developed the ADAGIO (Atmospheric Deposition Analysis Generated by Interpolation of model and Observations) product, which provides maps of optimized wet, dry and total annual deposition of nitrogen, sulphur, and ozone in Canada and the United States by combining observed and modelled data. Ground-based measurements provide the most accurate data near measurement sites, but cannot provide reliable large-scale estimates of deposition where sites are sparse. Chemical transport models provide improved spatial coverage, but often have biases and uncertainties related to model parameterization. In the ADAGIO product, observational data are collected from precipitation chemistry and air monitoring networks comprising a few hundred stations across North America. Modelling data are obtained from ECCC’s GEM-MACH (Global Environmental Multiscale - Modeling Air Quality and CHemistry) model. If available, model versions that include wildfire emissions are used. The model and observational data are statistically combined using the Optimal Interpolation technique (Robichaud et al., 2025, 2026). ADAGIO provides continuous total deposition fluxes across North America, which can be used to evaluate the impacts of anthropogenic activities on ecosystem health, such as acidification and eutrophication. ADAGIO data from developmental (research) and operational runs are provided in the subfolder collections. The developmental runs were performed for the years 2010, 2013-2016, and 2019 and are provided here in support of the papers describing the method (Robichaud et al., 2025, 2026). Moving forward, ADAGIO data from using revised emissions and updated model runs operational runs will be provided on an ongoing basis as operational outputs. The data are available in geospatial formats (e.g. NetCDF, GeoTiff) and image formats (PNG). Please consult the README files for descriptions, updates, and recommended data citation and acknowledgement. Contact natchem@ec.gc.ca for more information. Acknowledgements: Measurement data for ADAGIO were provided by the Canadian Air and Precipitation Monitoring Network (CAPMoN), National Air Pollution Surveillance (NAPS) Program, the Governments of Alberta and New Brunswick, the National Atmospheric Deposition Program National Trends Network and Ammonia Monitoring Network, U.S. Environmental Protection Agency Clean Air Status and Trends Network (CASTNET) and Air Quality System. Model data were provided by the Air Quality Issues Response (AQIR) group of the Canadian Centre for Meteorological and Environmental Predictions at ECCC (operational product) or the Air Quality Research Division at ECCC (developmental product). Additional details, including data links, are provided in the README files. Robichaud, A., Cole, A., Cheng, I., Cathcart, H., Feng, J., and Hou, A. (2025). Data fusion of modelled and measured deposition in the U.S. and Canada, part I: Description of methodology and validation of wet deposition of sulfur and nitrogen. Atmos. Environ., 347, 121074, https://doi.org/10.1016/j.atmosenv.2025.121074. Robichaud, A., Cole, A., Cheng, I., Cathcart, H., Feng, J., Hou, A., Griffin, D., and Shephard, M. W. (2026). Data fusion of modelled and measured deposition in the U.S. and Canada, part II: Dry deposition of sulfur, nitrogen and ozone. Atmos. Environ., 364, 121656, https://doi.org/10.1016/j.atmosenv.2025.121656.