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Temperature is a key factor affecting the physiological development of field crops as well as crop yield and agricultural product quality achieved during the growing season. Crop responses to the temperature are characterized by three important cardinal temperature indices; the cardinal minimum temperature, maximum cardinal temperature, and optimum temperature for field crop production at which the plant growth and development can start, stop, and proceed at the maximum rate 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 probability of effective growing season degree days above 100 for cool season crops. This condition must be maintained for at least 5 consecutive days in order for EGDD to be accumulated (egdd_cool_100prob). Week 1 and week 2 forecasted probability is available daily from April 1 to October 31. Week 3 and week 4 forecasted probability is available weekly (Thursday) from April 1 to October 31. Cumulative heat-energy satisfies the essential requirement of field crop growth and development towards a high yield and good quality of agricultural crop products. 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.

Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in sea ice concentration based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Sea ice concentration is represented as the percentage (%) of grid cell area. Therefore, projected change in sea ice concentration is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensembles of sea ice concentration change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in sea ice concentration (%) 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.

Snow survey administrative basin areas, which are components of the BC snow survey network. Basin codes are used as basis of snow survey station names, and for some reporting purposes.

This file contains output from ensemble. Contains vertical profiles and cross sections.

Multi-model ensembles of sea ice concentration based on projections from twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of sea ice concentration as represented as the percentage (%) of grid cell area, are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. 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.

A database of verified tornado tracks across Canada has been created covering the 30-year period from 1980 to 2009. The tornado data have undergone a number of quality control checks and represent the most current knowledge of past tornado events over the period. However, updates may be made to the database as new or more accurate information becomes available. The data have been converted to a geo-referenced mapping file that can be viewed and manipulated using GIS software.

Difference from normal soil moisture is the modelled amount of plant available water (mm) in the root zone of the soil, minus 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 and by the amount of water (mm). Values are computed using the Versatile Soil Moisture Budget (VSMB)

The Agri-Environmental Indicator Residual Soil Nitrogen (RSN) dataset estimates the amount of nitrogen remaining in the soil at the end of the growing season (after harvest) on Canadian agricultural lands annually.