RI_623
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The “Soil Landscapes of Canada (SLC) Version 2.2” dataset series provides a set of geo-referenced soil areas (polygons) that are linked to attribute data found in the associated Component Table (CMP), Landscape Table (LAT), Carbon Layer Table (CLYR), and Dom/Sub File (DOM_SUB). Together, these datasets describe the spatial distribution of soils and associated landscapes for Canada.
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Description: Seasonal mean temperature from the British Columbia continental margin model (BCCM) were averaged over the 1993 to 2020 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone. Methods: Temperatures at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal temperature climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels. Uncertainties: Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.
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30-year Average Number of Days with Temperature above 25 °C are defined as the count of the number of climate days during the month where the maximum daily temperature was greater than 25 °C. These values are calculated across Canada in 10x10 km cells.
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Growing Degree Days (GDDs) are used to estimate the growth and development of plants and insects during the growing season. Insect and plant development are very dependent on temperature and the daily accumulation of heat. The amount of heat required to move a plant or pest to the next development stage remains constant from year to year. However, the actual amount of time (days) can vary considerably from year to year because of weather conditions. Base temperatures are a point below which development does not occur for the organism in question. Base 0 temperatures are commonly used for cereals. These values are calculated across Canada in 10x10 km cells.
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The Crop Stress Index is the ratio of actual evapotranspiration (AET) to potential evapotranspiration (PET) express as: CSI = 1-(AET/PET) AET and PET are calculated within the Versatile Soil Moisture Budget (VSMB) model using temperature and precipitation data and a crop-specific biometeorological time scale model to estimate growth stage (Robertson, 1968), with crop specific phenological and crop water extraction coefficients taken from Chipanshi et al 2013. The WDI ranges between 0 and 1, with a value closer to 1 indicating higher stress Crop Stress Index is modelled for each climate station using measured precipitation and temperature
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This data series was compiled by AAFC and Statistics Canada using a combination of agroclimate data and satellite-derived Normalized Difference Vegetation Index (NDVI) data for the current growing season. The forecast is made based on a statistical model using historical yield, climate and NDVI data.
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In 1949 a magnitude 8.1 earthquake occurred on the Queen Charlotte Fault, off the west coast of the Haida Gwaii archipelago. This magnitude 7.7 scenario along the Queen Charlotte Fault is slightly different and closer to population centres than the magnitude 7.8 earthquake that occurred in 2012.
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Monthly mean salinity from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request. The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process. When using data please cite following: Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p
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In 1949 a magnitude 8.1 earthquake occurred on the Queen Charlotte Fault, off the west coast of the Haida Gwaii archipelago. This magnitude 8.0 scenario along the Queen Charlotte Fault is slightly different and closer to population centres than the magnitude 7.8 earthquake that occurred in 2012.
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Magnitude 5.7 earthquake scenario located directly southeast of Ladysmith Town Centre. This fault is not known to be active, but this scenario represents a small but damaging event near Ladysmith and Burleith Arm.
Arctic SDI catalogue