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We have found 31 datasets for the keyword " overwintering". You can continue exploring the search results in the list below.
Datasets: 106,031
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31 Datasets, Page 1 of 4
Probability of frost for cool season/overwintering crops (<-2°C)
The Probability (likelihood) of frost occurring. The number of days in the forecast period with a minimum temperature below the frost temperature, the temperature at which frost damage occurs. This temperature is -2°C for cool season crops (ffd_cool_prob).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.Cool season crops require a relatively low temperature condition. Typical examples include wheat, barley, canola, oat, rye, pea, and potato. They normally grow in late spring and summer, and mature between the end of summer and early fall in the southern agricultural areas of Canada. The optimum temperature for such crops is 25°C.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.
Frost-free days for cool season/overwintering crops (>-2°C)
Frost free days are the number of days in the forecast period with a minimum temperature above the frost temperature; the temperature at which frost damage occurs. This temperature is -2°C for cool season crops (ffd_cool).Week 1 and week 2 forecasted index is available daily from April 1 to October 31.Week 3 and week 4 forecasted index is available weekly (Thursday) from April 1 to October 31.Cool season crops require a relatively low temperature condition. Typical examples include wheat, barley, canola, oat, rye, pea, and potato. They normally grow in late spring and summer, and mature between the end of summer and early fall in the southern agricultural areas of Canada. The optimum temperature for such crops is 25°C.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.
Probability of Cool wave days for cool season/overwintering crops (<5°C)
The Probability (likelihood) of cool wave days for cool season/overwintering crops occurring Cool Wave Days are the number of days in the forecast period with a minimum temperature below the cardinal minimum temperature, the lowest temperature at which crop growth will begin (dcw_cool_prob). This temperature is 5°C for cool season crops.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.Cool season crops require a relatively low temperature condition. Typical examples include wheat, barley, canola, oat, rye, pea, and potato. They normally grow in late spring and summer, and mature between the end of summer and early fall in the southern agricultural areas of Canada. The optimum temperature for such crops is 25°C.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.
Cool wave days for cool season/overwintering crops (< 5°C)
Cool Wave Days are the number of days in the forecast period with a minimum temperature below the cardinal minimum temperature, the lowest temperature at which crop growth will begin (dcw_cool). This temperature is 5°C for cool season crops.Week 1 and week 2 forecasted index is available daily from April 1 to October 31.Week 3 and week 4 forecasted index is available weekly (Thursday) from April 1 to October 31.Cool season crops require a relatively low temperature condition. Typical examples include wheat, barley, canola, oat, rye, pea, and potato. They normally grow in late spring and summer, and mature between the end of summer and early fall in the southern agricultural areas of Canada. The optimum temperature for such crops is 25°C.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.
California Sea Lion Haulout Counts in British Columbia
The United States population of California Sea Lions (Zalophus californianus) range from southeast Alaska to the Pacific coast of central Mexico. While this population does not breed in Canada, some sub-adult and adult males migrate northwards to British Columbia during the non-breeding season with an arrival in August-October and a departure in April-May. The population in coastal BC has not been fully assessed since 1985. However, opportunistic counts suggest that California Sea Lions overwintering in BC increased in abundance from approximately 1,000 animals in the mid-2000s to several thousand individuals in more recent years.The survey targeted Steller sea lions and sites were chosen based on knowledge of historically occupied rookeries and haul-out sites with nearby areas monitored for potential shifts in distribution. The presence of California Sea Lions are based on incidental observations while surveying sites for Steller sea lion counts. This dataset contains counts that have been collected from sightings of individuals in the 2016/2017 survey season.
Monthly Climate Observation Summaries
A cross-country summary of the averages and extremes for the month, including precipitation totals, max-min temperatures, and degree days. This data is available from stations that produce daily data.
Fire season length - Reference Period (1981-2010)
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: the fire season length across Canada for a reference period (1981-2010).
Statistically downscaled scenarios of projected maximum temperature change
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.
Trends of temperature change based on adjusted and homogenized climate station data
Monthly, seasonal and annual trends of daily minimum, mean and maximum surface air temperature change (degrees Celsius) based on homogenized station data (AHCCD) are available. Trends are calculated using the Theil-Sen method using the station’s full period of available data. The availability of temperature trends will vary by station; if more than 5 consecutive years are missing data or more than 10% of the data within the time series is missing, a trend was not calculated.
Maximum Temperature (°C)
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.
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