Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.

Gridded monthly, seasonal and annual mean temperature anomalies derived from daily minimum, maximum and mean surface air temperatures (degrees Celsius) is available at a 50km resolution across Canada. The Canadian gridded data (CANGRD) are interpolated from homogenized temperature (i.e., AHCCD datasets). Homogenized temperatures incorporate adjustments to the original station data to account for discontinuities from non-climatic factors, such as instrument changes or station relocation. The anomalies are the difference between the temperature for a given year or season and a baseline value (defined as the average over 1961-1990 as the reference period). The yearly and seasonal temperature anomalies were computed for the years 1948 to 2017. The data will continue to be updated every year.

Drought is a deficiency in precipitation over an extended period, usually a season or more, resulting in a water shortage that has adverse impacts on vegetation, animals and/or people. The Climate Moisture Index (CMI) was calculated as the difference between annual precipitation and potential evapotranspiration (PET) – the potential loss of water vapour from a landscape covered by vegetation. Positive CMI values indicate wet or moist conditions and show that precipitation is sufficient to sustain a closed-canopy forest. Negative CMI values indicate dry conditions that, at best, can support discontinuous parkland-type forests. The CMI is well suited to evaluating moisture conditions in dry regions such as the Prairie Provinces and has been used for other ecological studies.Mean annual potential evapotranspiration (PET) was estimated for 30-year periods using the modified Penman-Monteith formulation of Hogg (1997), based on monthly 10-km gridded temperature data. Data shown on maps are 30-year averages. Historical values of CMI (1981-2010) were created by averaging annual CMI calculated from interpolated monthly temperature and precipitation data produced from climate station records. Future values of CMI were projected from downscaled monthly values of temperature and precipitation simulated using the Canadian Earth System Model version 2 (CanESM2) 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 mean annual Climate Moisture Index across Canada for the medium-term (2041-2070) under the RCP 8.5 (continued emissions increases).Reference: Hogg, E.H. 1997. Temporal scaling of moisture and the forest-grassland boundary in western Canada. Agricultural and Forest Meteorology 84,115–122.

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.

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.

This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58

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.Provided layer: difference in projected fire season length for the short-term (2011-2040) under the RCP 8.5 (continued emissions increases) compared to reference period across Canada.

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 annual maximum and minimum daily data are the maximum and minimum daily mean values for a given year.

Mean Temperature Difference From Normal values are computed by subtracting the normal monthly average temperature from the average monthly temperature of the month. The average monthly temperature is computed by obtaining the mean value of average daily temperatures for a month. If the month was colder than normal the value computed will be negative and if it was warmer the value will be positive.