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Climate change

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    The Government of Canada’s Fuel Life Cycle Assessment (LCA) Model is a tool to calculate the life cycle carbon intensity (CI) of fuels and energy sources used and produced in Canada.

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    This dataset contains blended (gauge and satellite estimates) pentad mean precipitation rates (unit: mm/day) at a one degree spatial resolution over Canada. The data can be used for hydrometeorological, agricultural, forestry modelling, for numerical weather model and climate model verification, and for climate impact studies.

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    The data consists of temperature indices based on homogenized daily maximum and minimum temperatures at 338 locations across Canada, and of precipitation indices based on adjusted daily rainfall, daily snowfall and daily precipitation amounts at 463 locations across the country. These indices were selected for their relevance to social and economic impact assessment in Canada and for the insights they could provide regarding changes in extreme climate conditions. Please refer to the papers below for detailed information regarding the adjustment procedures and the trends in the indices.

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    Humidex (Masterton and Richardson 1979) is an index developed by the Meteorological Service of Canada to describe how hot and humid the weather feels to the average person. In Canada, it is recommended that outdoor activities be moderated when the humidex exceeds 30, and that all unnecessary activities cease when it passes 40 (Mekis et al., 2015). With the increase in temperature projected by climate models over the coming decades over Canada, increases are also expected in the number of days with high-value Humidex across the country, which will have important consequences for human health. This dataset consists of a multi-model ensemble of statistically downscaled climate model projections for three humidex threshold indices (annual number of days when humidex exceeds 30, 35 and 40, noted HXmax30, HXmax35 and HXmax40 respectively) on a 0.1-degree latitude-longitude grid over Canada. The three indices (HXmax30, HXmax35 and HXmax40) are available for download at annual time step and 30-year averages from 1950 to 2100, for each of the 19 individual models and for the 10th, 50th, and 90th ensemble percentiles. The multi-model ensemble is using output from 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCM) that are available at the Earth System Grid Federation (ESGF) Data Nodes, for three emission scenarios called “Shared Socioeconomic Pathways” (SSPs) (Riahi et al. 2017): SSP126, SSP245 and SSP585. The GCM outputs were statistically downscaled and bias corrected using the N-dimensional probability density function transform multivariate quantile mapping method (Cannon, 2018) against ERA5-Land data (Muñoz, 2019), using a method described in Diaconescu et al. (2022). This method is based on the observation that the time when Humidex reaches its daily maximum coincide statistically with the time when temperature reaches its daily maximum and relative humidity reaches its daily minimum. In order to eliminate model biases and the errors in the adjustment method, the daily maximum temperature and daily minimum relative humidity from GCMs are statistically downscaled and bias corrected against the hourly temperature and relative humidity at the time of daily maximum humidex from ERA5-Land. The bias-corrected values are used to compute the daily maximum humidex and next the three threshold annual indices. These ensembles of indices are intended to enable users to better identify and reduce the susceptibility of vulnerable populations to illness and mortality due to increase in the frequency and intensity of extreme heat events due to climate change. References: Cannon, A. J. (2018). 'Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables', Climate Dynamics, 50(1-2), 31-49. Available at https://doi.org/10.1007/s00382-017-3580-6 Diaconescu, E. P. et al. (2022) ' A short note on the use of daily climate data to calculate Humidex heat-stress indices', International Journal of Climatology, 1– 13. https://doi.org/10.1002/joc.7833 Masterton, J. M., and Richardson, F. (1979) 'Humidex: a method of quantifying human discomfort due to excessive heat and humidity', Environment Canada, Atmospheric Environment, 45. Mekis, É., et al. (2015) 'Observed trends in severe weather conditions based on humidex, wind chill, and heavy rainfall events in Canada for 1953–2012', Atmosphere-Ocean, 53, 383-397. Available at https://doi.org/10.1080/07055900.2015.1086970, (Accessed: 19 April 2022). Muñoz Sabater, J., 2019: ERA5-Land hourly data from 1981 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on < 25-Jun-2021 >), https://doi.org/10.24381/cds.e2161bac Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O’Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Crespo Cuaresma, J., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Aleluia Da Silva, L., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., & Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An Overview. Global Environmental Change, 42, 153-168. https://doi.org/10.1016/j.gloenvcha.2016.05.009

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    Climate Data Products at Environment Canada comprise of four different datasets: Almanac Averages and Extremes, Monthly Climate Summaries, Canadian Climate Normals, and Canadian Historical Weather Radar. Almanac Averages and Extremes provides average and extreme temperature and precipitation values for a particular station over its entire period of record. Monthly Climate Summaries contains values of various climatic parameters, including monthly averages and extremes of temperature, precipitation amounts, degree days, sunshine hours, days without precipitation, etc. Canadian Climate Normals are used to summarize or describe the average climatic conditions of a particular location. Data is available for stations with at least 15 years of data between the periods of 1961-1990, 1971-2000 and 1981-2010. Canadian Historical Weather Radar compirses of historical images from the radar network providing a national overview of where percipitation is occuring.

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    This first version of the dataset (CanHoPmlyV1) contains homogenized time series of monthly total precipitation for 425 long-term stations in Canada. As detailed in Wang et al. (2023), it is based on the quality-controlled version 2020 of the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset (Wang et al. 2017; available at http://open.canada.ca/data/en/dataset/d8616c52-a812-44ad-8754-7bcc0d8de305), and on daily total precipitation data from automated gauges (including Belfort, Fisher & Porter, Nipher, Geonor, and Pluvio), with some records from neighbouring stations being joined to form long-term data series. Version 1 of ANUSPLIN surfaces of the adjusted monthly precipitation (MacDonald et al. 2021, available at https://open.canada.ca/data/en/dataset/779ea77a-0ad1-42f2-853e-833e1cbb9a13) was used to infill temporal data gaps in the 425 data series. A comprehensive semi-automatic data homogenization procedure was used to homogenize the data series. The aforementioned ANUSPLIN data and the Twentieth Century Reanalysis 20CRv3 ensemble-mean series of monthly precipitation (Slivinski et al., 2021) were used as reference in the homogeneity tests (Wang et al., 2023). The homogenized dataset provides more realistic trend estimates and shows better spatial consistency of trends than does the raw dataset (Wang et al. 2023). References: Wang, X.L, Y. Feng, V. Y. S. Cheng, H. Xu, 2023: Observed precipitation trends inferred from Canada’s homogenized monthly precipitation dataset, J. Clim., in press. DOI: 10.1175/JCLI-D-23-0193.1. Wang, X. L., H. Xu, B. Qian, Y. Feng, E. Mekis, 2017: The adjusted daily rainfall and snowfall data for Canada. Atmosphere-Ocean, 55:3, 155-168, DOI:10.1080/07055900.2017.1342163. MacDonald, H., D. W. McKenney, X. L. Wang, J. Pedlar, P. Papadopol, K. Lawrence, M. F. Hutchinson, 2021: Spatial Models of adjusted precipitation for Canada at varying time scales. J. Appl. Meteor. And Climatol., 60, 291-304. DOI: 10.1175/JAMC-D-20-0041.1. Slivinski, L. and coauthors, 2019: Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system. Q. J. R. Meteor. Soc., 2876-2908, https://doi.org/10.1002/qj.3598.

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    Black carbon is a short-lived, small aerosol (or airborne) particle linked to both climate warming and adverse health effects. It is emitted from incomplete combustion of carbon-based fuels (i.e., fossil fuels, biofuels, wood) in the form of very fine particulate matter. Black carbon is not emitted on its own, but as a component of particulate matter less than or equal to 2.5 micrometres in diameter (PM2.5). As a member of the Arctic Council, Canada has committed to producing an annual inventory of black carbon emissions. This data will serve to inform Canadians about black carbon emissions and provide valuable information for the development of air quality management strategies. The data used to compile the report originate from sections of the Air Pollutant Emission Inventory (APEI) specifically fine particulate matter (PM2.5) emissions from combustion-related sources.

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    "The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Temperature change in Canada indicators show the yearly and seasonal surface air temperature departures for the years 1948 to 2022. As well, they present a spatial distribution of surface air temperature departures for the year 2022. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators"

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    The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Greenhouse gas concentrations indicator shows the trends in concentrations for 2 greenhouse gases: carbon dioxide (CO2) and methane (CH4). It serves to identify trends and seasonal variability of carbon dioxide and methane concentrations in Canada. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators

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    "The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Snow cover indicators show how Canada's snow cover is changing from year-to-year and over time. Snow cover extent is expressed in millions of square kilometres and is presented for the spring months of April, May and June. Sixty-five (65) percent of Canada's land mass has annual snow cover for more than 6 months of the year. Changes in snow cover have important and far-reaching consequences for ecological and human systems. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Canadian Environmental Sustainability Indicators: https://www.canada.ca/environmental-indicators