Gögnin innhalda staðsetningu veðurstöðva sem eru í eigu Vegagerðarinnar og staðsettar eru við þjóðvegi en einnig veðurstöðvar í eigu Veðurstofunnar og annarra.

Percent of normal soil moisture is the modelled amount of plant available water (mm) in the root zone of the soil, divided by the average amount that has historically been available on that day. This value is intended to provide users with a representation of conditions above or below normal as a percentage. Values are computed using the Versatile Soil Moisture Budget (VSMB)

For nearly three decades, the SCRIBE system has been used to assist meteorologists in preparing weather reports. The philosophy behind SCRIBE is that a set of weather element matrices are generated for selected stations or sample points and then transmitted to regional weather centers. The matrices are then decoded by SCRIBE and can be modified via the graphical interface by the users. The resulting data is then provided to a text generator, which produces bilingual public forecasts in plain language. The various rules related to the Scribe matrices hinder scientific innovation, do not exploit the richness of the Numerical Weather Prediction (NWP), reduce the understanding of weather forecasts, and and may require frequent interventions from forecasters. As part of a larger modernization plan for the Meteorological Service of Canada (MSC), in which the role of the forecaster is evolving, the goal is to replace the Scribe matrices, available on the MSC Datamart, and their limited number of points across Canada with Weather Elements on the Grid ("WEonG"). Weather Elements on Grid (WEonG) based on the Global Deterministic Prediction System (GDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the Global Deterministic Prediction System (GDPS).

Precipitation (moisture availability) establishes the economic yield potential and product quality of field crops. Both dry and wet precipitation extremes have the ability to inhibit proper crop growth. The maximum daily precipitation index covers the risk of excessive precipitation in the short term, while the other indices pertain to longer term moisture availability. 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.

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.

The Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants which combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) and hourly observational data from monitoring surface networks over North America in order to produce a better description of the air quality at every hour. Chemical constituents include 03, SO2, and NO2 gases, as well as fine particulate matter PM2.5 (2.5 micrometers in diameter or less) and coarse particulate matter PM10 (10 micrometers in diameter or less). Geographical coverage is Canada and the United States. Data is available only for the surface level, at a horizontal resolution of 10 km. The products are presented as historical, annual or monthly, averages which highlight long-term trends in cumulative effects on the environment.

The Regional Air Quality Deterministic Prediction System (RAQDPS) takes into account physical and chemical processes to produce deterministic forecasts of the concentration of chemical species of interest to air quality. These chemical constituents include gases such as O3, SO2, NO, and NO2, in addition to fine particles PM2.5 (diameter of 2.5 micrometers or less) and coarse particles PM10 (diameter of 10 micrometers or less). The PM2.5 and PM10 now include the contribution of wildfire emissions as well as anthropogenic and biogenic emission sources. The forecasts are available for the present up to 72 hours in the future twice a day (run 00 UTC and 12 UTC). The geographic domain of the RAQDPS covers most of North America with a horizontal resolution of 10km.

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.

Probability of total precipitation above 100mm over the forecast period (pweek100_prob) Week 1 and week 2 forecasted probability is available daily from September 1 to August 31. Week 3 and week 4 forecasted probability is available weekly (Thursday) from September 1 to August 31. Precipitation (moisture availability) establishes the economic yield potential and product quality of field crops. Both dry and wet precipitation extremes have the ability to inhibit proper crop growth. The greatest daily precipitation index covers the risk of excessive precipitation in the short term, while the other indices pertain to longer term moisture availability. 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 and weekly basis.

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. Multiple layers are provided. First, the mean annual Climate Moisture Index is shown across Canada for a reference period (1981-2010). Projected mean annual Climate Moisture Index is available for the short- (2011-2040), medium- (2041-2070), and long-term (2071-2100) under the RCP 8.5 (continued emissions increases) and, for the long-term (2071-2100), under RCP 2.6 (rapid emissions reductions). Reference: Hogg, E.H. 1997. Temporal scaling of moisture and the forest-grassland boundary in western Canada. Agricultural and Forest Meteorology 84,115–122.