Below is a library of all variables available within ClimateData.ca. Use the filter to limit your search to specific types of data.
Initiatives and measures to reduce the vulnerability of natural and human systems against actual or expected climate change impacts.
A system’s ability to implement adaptation measures to climate change (including climate variability and extremes).
Value that represents the difference between the value for a given year or season from the normal of the reference period.
Long-term continuous increase or decrease of any of the statistics over 30 years (mean, variability, extreme) of climatic variables such as temperature and precipitation.
A description of the evolution in the climate for a given time period in the future, using a specific modelling technique and under specific assumptions about the evolution of greenhouse gas emissions and other factors that may influence the climate in the future. Climate projections from climate models often serve as the raw material for constructing climate scenarios in the most widely-used method of climate scenario construction.
Refer to climatic data that describe either past conditions, obtained from meteorological observations (stations, satellites, radars), or the future, obtained from the outputs of climate models.
A numerical representation of the climate system based on the physical, chemical, and biological properties of its components, their interactions and feedback processes, and accounting for most of its known properties.
The average of weather conditions as obtained from observations for a historical 30-year time interval defines “typical” conditions for a given area. Note that according to the rules of the World Meteorological Organization (WMO), 30-year reference periods are updated at the start of each decade.
An organization that supplies climate information to users. The roles of these organizations may include providing historical climate data, running climate simulations, and tailoring their outputs to suit the needs of individual users.
The variations above or below a long-term mean state of the climate. This variability can be due to natural internal processes within the climate system (internal variability) or to variations in anthropogenic external forcing (external variability).
Coupled Model Intercomparison Project, Phase 5. CMIP5 is a coordinated climate modeling exercise involving 20 climate-modeling groups from around the world. It has provided a standard experimental protocol for producing and studying the output of many different global climate models. The output from CMIP5 ensemble experiments is used to inform international climate assessment reports, such as those from the IPCC.
Difference between the future value and the reference period (or baseline) value of a climate variable, as simulated by a climate model.
A method that can provide climate model outputs at a finer resolution than their original resolution. Two different approaches are prioritized: statistical downscaling and dynamical downscaling.
A plausible representation of the future development of emission of substances that are potentially radiatively active in the atmosphere, such as greenhouse gases and aerosols. They are based on assumptions regarding driving forces like demographic and socioeconomic development, or technological change.
Term used to refer to the complete set of climate simulations or climate scenarios used for a given study. Because no one model can be considered best, it is standard practice in climate change studies to use the outputs of many models when studying the projected changes. Consequently, ensemble is usually a synonym for the term multimodel ensemble. Note, however, that other, more restrictive, definitions exist for ensembles designed to study very specific scientific questions (for example, an ensemble could represent a set of simulations made with the same climate model, using the same emissions scenario, but initialized using different starting conditions).
The Humidex was 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.
To learn more: ECCC Glossary
Computer model that is a mathematical representation of the climate system, based on equations that drive the physical processes governing the climate, including the role of the atmosphere, hydrosphere, biosphere, etc. It represents a unique tool that helps reproduce a complex ensemble of processes relevant for climate evolution. Note the term Global (or General) Circulation Model is often used as a synonym.
Gaseous constituents of the atmosphere, both natural and anthropogenic, that absorb and emit radiation at specific wavelengths and that cause the greenhouse effect. These are gases that can absorb and emit thermal infrared (heat) energy. Primary greenhouse gases include water vapour (H2O), carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4) and ozone (O3). Without any greenhouse gases in its atmosphere, Earth would be too cold to support life as we know it. However, too high a concentration of greenhouse gases in the atmosphere can result in a dangerous level of planetary warming.
Climate Normals 1981-2010 are used to summarize or describe the average climatic conditions of a particular location. At the completion of each decade, Environment and Climate Change Canada updates its climate normals for as many locations and as many climatic characteristics as possible. The climate normals offered here are based on Canadian climate stations with at least 15 years of data between 1981 to 2010.
Discrete model “cells” which represent computational units of a climate model. The simplest model grids typically divide the globe (or model domain) into constant angular grid spacing (i.e. a latitude / longitude grid). A climate model’s horizontal resolution is often expressed as the size of a single grid cell (e.g. 1° x 1° grid or 10 km by 10 km grid).
This scenario assumes that greenhouse gas concentrations will continue to increase at approximately the same rate as they are increasing today. Under this scenario, the planet’s radiative forcing will have increased by 8.5 W/m2 by the year 2100, relative to 1750 (and continues to rise well after 2100). In the scientific literature, this scenario is referred to as “RCP8.5.” Of the four greenhouse gas pathways (RCP8.5, RCP6.0, RCP4.5, RCP2.6) used by the IPCC for its 5th Assessment Report, this pathway results in the most severe global warming and climate change.
A future time period of interest over which the outputs of climate simulations are examined or for which future scenarios are produced. The climate science community tends to converge on common time horizons that are recommended by the World Meteorological Organization (WMO). The horizons typically encompass a 30- or 20- year period. For example, horizon 2050 often corresponds to the years 2041-2070.
Term used to refer to properties of the climate that are not measured in the field or calculated by climate models but rather that are calculated or derived from climate variables such as temperature and precipitation. Examples include the number of growing degree-days, freeze-thaw cycles, and the drought code index. (see variable)
Weather station data comes from the Meteorological Service of Canada (MSC). This dataset is composed of weather observations from 325 high-quality weather stations located across Canada. Active stations are updated in near real-time and the oldest data is from 1840.
Intergovernmental Panel on Climate Change
The IPCC is an international body administered by the United Nations. It was created to assess climate science research, and it regularly issues authoritative assessment reports about the science of climate change, climate change impacts, and policy options for adaptation and mitigation.
Cooling degree days give an indication of the amount of air conditioning that may be required to maintain comfortable conditions in a building during warmer months. A threshold temperature of 18°C is used and for any day when the mean temperature exceeds this value, cooling degree days are accrued. So, if the daily mean temperature on a given day is 24°C, then 6 cooling degree days are accrued for this day. Cooling degree days values are totalled over the year; the larger the cooling degree days value the greater the requirement for air conditioning.
This scenario assumes that greenhouse gas emissions will continue to increase until mid-century and then decline significantly. The IPCC refers to this scenario as a ‘’peak and decline’’ scenario that increased the planet’s radiative forcing to 2.6W/m2 by year 2100, relative to 1750.In the scientific literature, this scenario is referred to as “RCP2.6.” Of the four greenhouse gas pathways (RCP8.5, RCP6.0, RCP4.5, RCP2.6) used by the IPCC for its 5th Assessment Report, this RCP results in the lowest level of global warming and climate change. This scenario is the only one that can ensure the success of the Paris Agreement.
This type of downscaling relies on the use of regional climate models that are driven at their boundaries by global climate models.
Number of days between the first occurrence of at least six consecutive days with mean daily temperature greater than 5°C and, after July 1st, the first occurrence of at least 6 consecutive days with mean daily temperature below 5℃.
The Canadian Centre for Climate Services (CCCS) is the federal source for credible, useful and timely climate information, data, and tools. The goal of CCCS is to help all Canadians – from individual homeowners to municipal planners – to have the climate data and information they need to understand the climate-related risks they face and be able to pursue effective ways to address them.
Annual average precipitation rate for days with daily precipitation over 1 mm, i.e., it is the average amount of precipitation that falls on wet days in a year.
GeoMet provides access to the Meteorological Service of Canada’s (part of Environment and Climate Change Canada) open data, including raw station data, output from raw numerical weather prediction model data layers and the weather radar mosaic.
ECCC informs Canadians about protecting and conserving our natural heritage, and ensuring a clean, safe and sustainable environment for present and future generations.
This scenario assumes that greenhouse gas emissions will continue to increase (but more slowly than they are today) until mid-century and then stabilize until the end of the century. However, carbon dioxide concentrations will still end up being much higher than they are today. The IPCC describes this scenario as a “stabilization pathway” that increases the planet’s radiative forcing by 4.5 W/m2 by the year 2100, relative to 1750. In the scientific literature, this scenario is referred to as “RCP4.5.” Of the four greenhouse gas pathways (RCP8.5, RCP6.0, RCP4.5, RCP2.6) used by the IPCC for its 5th Assessment Report, this RCP results in the second-lowest level of global warming and climate change.
Variability that describes short-term changes in that take place over months, seasons and years. It is due to natural variations in external forces such as changes in the sun’s radiation or volcanoes, as well variations in internal processes, such as those related to the interactions of the oceans and the atmosphere, that occur for example in the Pacific Ocean during an El Niño event.
Consortium on regional climatology and adaptation to climate change, based in Montreal.
Prairie Climate Centre. The PCC is a climate change research, communication, and policy centre based at the University of Winnipeg.
Pacific Climate Impacts Consortium. Based at the University of Victoria, the PCIC is a regional climate services centre that does statistical and scientific research on climate change and climate variability.
Projections represent the future portion of climate model simulations that take into account an emissions scenario. Consequently, a projection is based on assumptions such as those concerning future socioeconomic and technological developments that may or may not be realized and thus are subject to uncertainty.
The change in the net irradiance (downward minus upward ; expressed in Watts per square metre) at the top of the atmosphere (TOA) due to a change in an external driver of the climate system; for example, a change in the concentration of carbon dioxide or the radiation from the sun.
The term range is used to represent the spectrum of output data from an ensemble of simulations or scenarios.
In practice, it often refers to a period of time from the recent past used in the production of climate scenarios. Future period values produced by climate models are compared with those from this period to evaluate changes. The WMO recommends 30-year intervals as reference periods, such as 1971-2000; however there are exceptions. For example, the current reference period used by the IPCC is 1985-2005. A synonymous term is baseline period. Accordingly, the terms ‘reference scenario’ or ‘baseline scenario’ are used to refer to climate scenarios for a reference period.
Just like a GCM, the regional climate model is a mathematical representation of the climate system, based on equations describing the physical processes governing the climate. RCMs have a finer resolution than GCMs and therefore contain a better representation of topography and can include processes and features, such as lakes, which are too small to resolve in GCMs. As a consequence they are more expensive to run and typically operate as ‘limited domain’ models, meaning that they cover only a portion of the globe.
Time series of emissions and concentrations of the full suite of greenhouse gases and aerosols as well as chemically active gases, and land use. The word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing characteristics. Four RCPs were selected as the basis for the climate projections used in the Fifth Assessment Report published by the IPCC. RCP2.6 leads to the least warming, and reflects a future shaped by aggressive and immediate efforts to drastically reduce greenhouse gas emissions. RCP4.5 and RCP6.0 lie between the extreme low and high scenarios, and model futures in which some mitigation of emissions prevents the extreme warming projected by RCP8.5.
In climate models, this term refers to the physical distance (kilometres or degrees) between each point on the grid used to compute the equations. Temporal resolution refers to the time step or time elapsed between each model computation of the equations. See Grid
Climate simulations represent the outcome of running a climate model for a certain period of time. The time span of a simulation can range from a few years to thousands of years and will iteratively be computed at intervals of a few minutes. They are run for both the past and the future.
CRIM is an applied research and expertise centre in information technology, dedicated to making organizations more effective and competitive through the development of innovative technology and the transfer of leading edge know-how, while contributing to scientific advancement.
This type of downscaling relies on the use of statistical relationship that relate large scale climate features, named predictors, to local climate variables (predictants).
The term climate variable is used to refer to a variable that can be measured directly in the field (at meteorological stations for example) or that is calculated by climate models. (See Index)
The degree to which a system is susceptible to, and unable to cope with, adverse effects of climate change. It is a function of the character, magnitude and rate of change to which a system is exposed and the sensitivity and adaptive capacity of that system.
BCCAQ is a method developed at the Pacific Climate Impacts Consortium for downscaling daily climate model projections of temperature and precipitation, including indices of extremes. This methodology, a hybrid of BCCA (Maurer et al. 2010) and QMAP (Gudmundsson et al. 2012), combines quantile-mapping bias correction with a constructed analogues approach using daily large-scale temperature and precipitation fields. The method was developed to correct the bias in daily precipitation series from climate models so that the distributional properties, e.g., means, variances and quantiles, more closely match those of the historical observations (provided in this case by the ANUSPLIN dataset). The robustness of the methodology was tested by examining three criteria: the day-to-day sequencing of precipitation events, the distribution characteristics, and spatial correlation. BCCAQv2 is a modification of BCCAQ which preserves the coarse-scale projected changes at each quantile during the quantile mapping step, which other quantile mapping methods have a tendency to amplify (the “inflation” problem), including the method used in BCCAQv1. Preserving the precipitation change signal is important for maintaining the physical scaling relationships with model-projected temperature changes.
For more information see Cannon, A.J., S.R. Sobie, and T.Q. Murdock, 2015: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28(17), 6938-6959, doi:10.1175/JCLI-D-14-00754.1.
Additional references: Gudmundsson, L., J. Bremnes, J. Haugen and T. Engen-Skaugen, 2012: Technical note: Downscaling RCM precipitation to the station scale using statistical transformations – A comparison of methods. Hydrol. Earth Syst. Sci., 16, 3383-3390, doi:10.5194/hess-16-3383-2012.
Maurer, E.P., H. Hidalgo, T. Das, M. Dettinger and D. Cayan, 2010: The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrol. Earth Syst. Sci., 14, 1125-1138, doi:10.5194/hess-14-1125-2010.
Gridded observational dataset produced by Natural Resources Canada (NRCan), available at 300 arc second spatial resolution (1/12° grids, ~10 km) over Canada. The bulk of the daily minimum and maximum temperature, and precipitation amounts for the period 1950-2012 were produced circa 2011 by Hopkinson et al. (2011) and McKenney et al. (2011) on behalf of the Canadian Forest Service (CFS), NRCan. The dataset was updated in 2013 to correct for issues in the Churchill River area. Gridding was accomplished with the Australian National University Spline (ANUSPLIN) implementation of the trivariate thin plate splines interpolation method (Hutchinson et al., 2009) with latitude, longitude and elevation as predictors. Precipitation occurrence and square-root transformed precipitation amounts were interpolated separately on each day, combined, and transformed back to original units.
Quality-controlled, but unadjusted, station data from the National Climate Data Archive (NCDA) of Environment and Climate Change Canada data (Hutchinson et al., 2009) were interpolated onto the high-resolution grid using thin plate splines. Station density varies over time with changes in station availability, peaking in the 1970s with a general decrease towards the present day (Hutchinson et al., 2009). Thus, the number of stations active across Canada between 1950 and 2011 ranged from 2000 to 3000 for precipitation and 1500 to 3000 for air temperature (Hopkinson et al., 2011).
Intensity-Duration-Frequency curves relate short-duration rainfall intensity with its frequency of occurrence and are often used for flood forecasting and urban drainage design.
Degree Days form the basis for a number of climate indices which are used in agriculture, energy, transport and human health. The threshold temperature is core to the degree day index and, as with other climate indices, some specific temperature threshold values are associated with particular degree day indices, e.g., growing degree days, heating degree days and cooling degree days.
The degree day index generally provides information about heat energy that is available (e.g., in agriculture), or is required (e.g., for space heating in buildings), although there are other applications. Degree days can be calculated above, or below, the threshold temperature.
Degree days above particular threshold temperatures provide information about heat energy available and are often used in agriculture to determine if there is sufficient heat energy at a particular location to allow crops or pest species to mature, or to reach certain points in their lifecycles. Growing Degree Days and Cooling Degree Days are in this category.
In this case, if you want to calculate the number of degree days above a threshold temperature of, say, 14°C, then for any day when the mean (average) temperature is greater than this value, degree days are calculated. So, if the daily mean temperature on a given day is 24°C, then there are 10 DDs (24-14=10) for this day. If the daily mean temperature on the next day is 18°C, then the number of degree days on that day is 4 DDs (18-14=4). This value is then added to the total from the previous day to give a sum of 14 DDs over these two days. This process is repeated over a specific time period, e.g., the summer or winter season or the whole year. If, on a particular day in this time period, the mean temperature is below the threshold value, then there are zero degree days on this day and no change is made to the accumulated total. The larger the degree day total, the more energy available in the time period considered.
Degree days below particular threshold temperatures can provide information about heat energy required, often for the space heating of buildings. Heating Degree Days are in this category.
In this case, if you want to calculate the number of degree days below a threshold temperature of, say, 18°C, then for any day when the mean (average) temperature is less than this value, degree days are calculated. So, if the daily mean temperature on a given day is 15°C, then there are 3 DDs (18-15=3) for this day. If the daily mean temperature on the next day is 10°C, then the number of degree days on that day is 8 (18-10=8). This value is then added to the total from the previous day to give a sum of 11 DDs over these two days. This process is repeated over a specific time period, e.g., the winter season or the whole year. If, on a particular day in this time period, the mean temperature is above the threshold value, then there are zero degree days on this day and no change is made to the accumulated total. In this case, the larger the degree day total the more energy is required.