The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.

In the hydrogeological unit, quantity of water that replenishes groundwater beneath the water table, expressed in mm/yr. Recharge is usually calculated using hydrology balance, integrating information from precipitation, hydrology data, drainage, soil properties, evapotranspiration, etc. The result is a raster dataset in which each cell has a given value for the recharge of the aquifer. It can be calculate using HELP software, developed by the US EPA. The methods used to create the dataset are described in the metadata associated with the dataset. The dataset represent a raster in which each cell has a mean value describing the global annual recharge of the hydrogeological unit.

The Versatile Soil Moisture Budget (VSMB) is a soil water budget model that is continuous and deterministic in nature and was developed by AAFC. It is based on the premise that the water available for plant growth is gained by precipitation or irrigation, and lost through evapotranspiration and runoff as well as lateral and deep drainage. The daily net loss or gain is added or subtracted from the water already present in the rooting zone. Water is withdrawn simultaneously, but at different rates, from different soil depths, depending on the potential evapotranspiration, the stage of crop development, the water release characteristics of each soil layer and the available water.

The datasets contain water surface evaporation (PET, in mm of H2O) over Canada's landmass at a spatial resolution of 10-km and temporal intervals of a month and a year over a 24-year period of 2000-2023. The PET was produced by the Land Surface Model EALCO (Ecological Assimilation of Land and Climate Observations) developed at Natural Resources Canada. The PET algorithm in EALCO integrates the dynamic surface evolutions of liquid water, ice, and snow-on-ice for a waterbody into the Penman Equation. The PET was simulated at a daily time step. The monthly (or annual) PET in the datasets is the sum of the daily PET values in a month (or a year). Dew and frost formations simulated by EALCO are included in the PET as negative values, so the PET represents the net water flux between water surface and the atmosphere. Details of the dataset and the EALCO PET modelling algorithms can be found in Li, Wang, and Li (2020, Spatial variations and long‑term trends of potential evaporation in Canada. Scientific Reports, 10: 22089, doi.org/10.1038/s41598-020-78994-9).

The datasets contain land surface evapotranspiration (ET, in mm of H2O) for Canada's landmass at a spatial resolution of 5-km and temporal intervals of a month and a year over a 24-year period of 2000-2023. The ET was produced by the Land Surface Model EALCO (Ecological Assimilation of Land and Climate Observations) developed at Natural Resources Canada. The EALCO model was run at a 30-minute time step. The monthly (or annual) ET in the datasets is the sum of the 30-minute ET values in a month (or a year). Dew and frost formations simulated by EALCO are included in the ET as negative values, so the ET represents the net water flux between land surface and the atmosphere. Details of the datasets and the EALCO ET modelling algorithms can be found in Wang (2007, Simulation of Evapotranspiration and Its Response to Plant Water and CO2 Transfer Dynamics. J. Hydrometeorology, 9, 426-443, doi: 10.1175/2007JHM918.1) and Wang et al. (2013, Spatial and seasonal variations in evapotranspiration over Canada’s landmass. Hydrol. Earth Syst. Sci., 17, 3561–3575, doi:10.5194/hess-17-3561-2013).

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 maximum temperature layer shows the modeled maximum temperature [°C] at a height of 100 m above ground level, at each grid point, over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 1.5 °C each. Further details including data for individual years can be obtained by clicking on the dot representing the grid point location.

The minimum temperature layer shows the modeled minimum temperature [°C] at a height of 100 m above ground level, at each grid point, over the three year period from January 1, 2008 to December 31, 2010. Values are presented in bins with ranges of 1.5 °C each. Further details including data for individual years can be obtained by clicking on the dot representing the grid point location.

Mean 2013 to 2022 summer surface conditions in the Estuary and Gulf of St. Lawrence. Data come from the August and the September multidisciplinary surveys. Surface conditions are described by temperature, salinity and nutrient concentration (mmol/m³) interpolated on a 10 km x 10 km grid.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. In the southern Gulf of St. Lawrence, these bottom trawl surveys has been carrying out each September since 1971. These missions are an important source of information about the status of the marine ressources.The objectives of the surveys 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 Gulf and finally, to describe the environmental conditions observed in the area at the moment of the sampling.The southern Gulf surveys are realized using the following standardized protocol:Hurlbut,T. and D.Clay (eds) 1990. Protocols for Research Vessel Cruises within the Gulf Region (Demersal Fish) (1970-1987). Can. MS Rep. Fish. Aquat. Sci. No. 2082: 143p.The sampling protocols used for the Estuary and northern Gulf surveys are described in details in the following publications:Bourdages, H., Archambault, D., Bernier, B., Fréchet, A., Gauthier, J., Grégoire, F., Lambert, J., et Savard, L. 2010. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2009 dans le nord du golfe du Saint-Laurent. Rapp. stat. can. sci. halieut. aquat. 1226 : xii+ 72 p. Bourdages, H., Archambault, D., Morin, B., Fréchet, A., Savard, L., Grégoire, F., et Bérubé, M. 2003. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2003 dans le nord du golfe du Saint-Laurent. Secr. can. consult. sci. du MPO. Doc. rech. 2003/078. vi + 68 p.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.

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.