The Global Deterministic Prediction System (GDPS) is a coupled atmosphere (GEM), ocean and sea ice (NEMO-CICE) deterministic numerical weather prediction model. Forecasts are carried out twice a day for 10 days lead time. The geographical coverage is global at 15 km horizontal resolution. Data is available on some thirty vertical levels and interpolated on a global latitude-longitude uniform grid with 0.15 degree horizontal resolution. Variables availability in number and time frequency is a function of forecast lead time.

Winds can significantly influence crop growth and yield mainly due to mechanical damage of plant vegetative and reproductive organs, an imbalance of plant-soil-atmosphere water relationships such as evapotranspiration, and pest and disease distributions in agricultural fields. The maximum wind speed and the number of strong wind days over the forecast period represent short term and extended strong wind events respectively.Agriculture is an important primary production sector in Canada. Agricultural production, profitability, sustainability and food security depend on many agrometeorological factors. Extreme weather events in Canada, such as drought, floods, heat waves, frosts and high intensity storms, have the ability to significantly impact field crop production. Agriculture and Agri-Food Canada (AAFC) and Environment and Climate Change Canada (ECCC) have together developed a suite of extreme agrometeorological indices based on four main categories of weather factors: temperature, precipitation, heat, and wind. The extreme weather indices are intended as short-term prediction tools and generated using ECCC’s medium range forecasts to create a weekly index product on a daily basis.

Annual and five-year (5YA) average wet deposition maps for the ammonium ion are available. The file formats include geodatabase files (*.gdb) compatible with geospatial software (e.g. ESRI ArcGIS) and KMZ files compatible with virtual globe software (e.g. Google Earth™). Maps can also be viewed online via Open Maps and the ArcGIS online viewer. Annual deposition from each site was screened for completeness using the following criteria: (1) precipitation amounts were recorded for >90% of the year and >60% of each quarter, and (2) ammonium concentrations were reported for >70% of the precipitation measured over the year and for >60% of each quarter. Five-year average wet deposition values are averaged annual deposition values with a completeness criterion >60% for the five-year period. Units for wet deposition fluxes are in kg of NH4 per hectare per year (kg ha-1 y-1). Sources of measurement data and spatial interpolation method are described here: https://doi.org/10.18164/e8896575-1fb8-4e53-8acd-8579c3c055c2. Recommended citation: Environment and Climate Change Canada, [year published]. NH4 Wet Deposition Maps. Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada. [URL/DOI], accessed [date].Recommended acknowledgement: The author(s) acknowledge Environment and Climate Change Canada for the provision of Canada-U.S. wet deposition kriging maps accessed from the Government of Canada Open Government Portal at open.canada.ca, and the data providers referenced therein.

Annual and five-year (5YA) average wet deposition maps for the nitrate ion are available. The file formats include geodatabase files (*.gdb) compatible with geospatial software (e.g. ESRI ArcGIS) and KMZ files compatible with virtual globe software (e.g. Google Earth™). Maps can also be viewed online via Open Maps and the ArcGIS online viewer. Annual deposition from each site was screened for completeness using the following criteria: (1) precipitation amounts were recorded for >90% of the year and >60% of each quarter, and (2) nitrate concentrations were reported for >70% of the precipitation measured over the year and for >60% of each quarter. Five-year average wet deposition values are averaged annual deposition values with a completeness criterion >60% for the five-year period. Units for wet deposition fluxes are in kg of NO3 per hectare per year (kg ha-1 y-1). Sources of measurement data and spatial interpolation method are described here: https://doi.org/10.18164/e8896575-1fb8-4e53-8acd-8579c3c055c2.Recommended citation: Environment and Climate Change Canada, [year published]. NO3 Wet Deposition Maps. Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada. [URL/DOI], accessed [date].Recommended acknowledgement: The author(s) acknowledge Environment and Climate Change Canada for the provision of Canada-U.S. wet deposition kriging maps accessed from the Government of Canada Open Government Portal at open.canada.ca, and the data providers referenced therein.

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.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in mean temperature (°C) 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). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). Historical gridded minimum and maximum temperature datasets of Canada (ANUSPLIN) were used as the respective downscaling targets. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected mean temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of 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 statistically downscaled minimum 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 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.

Deep water (> 200 m) dissolved oxygen interpolated on a grid cell of 10 km x10 km in the Estuary and Gulf of St. Lawrence. Input data are from the annual August multidisciplinary survey hold in 2014 to 2023.PurposeSince 1990, the Department of Fisheries and Oceans has been conducting an annual multidisciplinary survey in the Estuary and northern Gulf of St. Lawrence using a standardized protocol. These surveys are an important source of information about the status of the marine ressources. The objectives of the survey are multiple: to estimate the abundance and biomass of groundfish and invertebrates, to identify the spatial distribution and biological characteristics of these species, to monitor the biodiversity of the Estuary and the northern Gulf and finally, to describe the environmental conditions observed in August in the sampling area.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Bourdages, H., Brassard, C., Desgagnés, M., Galbraith, P., Gauthier, J., Légaré, B., Nozères, C. and Parent, E. 2017. Preliminary results from the groundfish and shrimp multidisciplinary survey in August 2016 in the Estuary and northern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/002. v + 87 p.Supplemental InformationThe bottom dissolved oxygen is determined from a CTD profile in the water column according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in maximum temperature (°C) 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 maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. Projected change in maximum temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected maximum temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of maximum 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 statistically downscaled maximum 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 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.

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.

Statistically downscaled multi-model ensembles of minimum temperature 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 minimum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded minimum temperature 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 minimum temperature (°C) 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.