The probability of maximum wind above 70km/h (mdws70_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. 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, 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 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.

Habitat suitability was assessed for the Bay of Quinte Area of Concern, at a 3 m grid resolution, using the Habitat Ecosystem Assessment Tool (HEAT), temperature algorithms, vegetation models, and water level input. Habitat classifications were based on three variables: depth (elevation), vegetation, and substrate; and modified by temperature suitabilities. The final suitability maps were based on documented habitat and temperature associations for the fish in the area. Different life stages (spawning requirements, nursery habitat, adult habitat) were modeled for the years of 1972-2011. Suitability values were scaled from 0 (not suitable) to 1 (highly suitable) and converted to suitability classes of very low, low, medium, and high. The final maps for each guild – life stage combination are maximum suitability values from the 39-year period modelled.

Fish Habitat Assessment Output: 7 of 16 High Water Level (75.4m ASL) - Juvenile/Adult Habitat - Low Vegetation Association Species (Coolwater Guild) Habitat suitability was assessed for the Bay of Quinte Area of Concern, at a 3 m grid resolution, using the Habitat Ecosystem Assessment Tool (HEAT), temperature algorithms, vegetation models, and water level input. Habitat classifications were based on three variables: depth (elevation), vegetation, and substrate; and modified by temperature suitabilities. The final suitability maps were based on documented habitat and temperature associations for the fish in the area. Different life stages (spawning requirements, nursery habitat, adult habitat) were modeled for the years of 1972-2011. Suitability values were scaled from 0 (not suitable) to 1 (highly suitable) and converted to suitability classes of very low, low, medium, and high. The final maps for each guild – life stage combination are maximum suitability values from the 39-year period modelled.

Fish Habitat Assessment Output: 13 of 16 Average Water Level (75.0m ASL) - Juvenile/Adult Habitat - High Vegetation Association Species (All Thermal Guilds) Habitat suitability was assessed for the Bay of Quinte Area of Concern, at a 3 m grid resolution, using the Habitat Ecosystem Assessment Tool (HEAT), temperature algorithms, vegetation models, and water level input. Habitat classifications were based on three variables: depth (elevation), vegetation, and substrate; and modified by temperature suitabilities. The final suitability maps were based on documented habitat and temperature associations for the fish in the area. Different life stages (spawning requirements, nursery habitat, adult habitat) were modeled for the years of 1972-2011. Suitability values were scaled from 0 (not suitable) to 1 (highly suitable) and converted to suitability classes of very low, low, medium, and high. The final maps for each guild – life stage combination are maximum suitability values from the 39-year period modelled.

The number of days during the forecast period with an average wind speed greater than 30 km/h (nswd). Week 1 and week 2 forecasted index is available daily from September 1 to August 31. Week 3 and week 4 forecasted index is available weekly (Thursday) from September 1 to August 31. 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, 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 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.

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 0°C for warm season crops (ffd_warm_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. Warm season crops require a relatively warm temperature condition. Typical examples include bean, soybean, corn and sweet potato. They normally grow during the summer season and early fall, then ripen in late fall in southern Canada only. Other agricultural regions in Canada do not always experience sufficiently long growing seasons for these plants to achieve maturity. The optimum temperature for such crops is 30°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.

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east/vertical 2D decomposition is approximate and assumes constant viewing geometry and the absence of horizontal-north deformation. In the line-of-sight (LOS) map computed from ascending orbit data, a negative signal approximately corresponds to either subsidence or eastward motion, while a positive signal corresponds to uplift or westward motion. In the LOS map computed from descending orbit data, a negative signal approximately corresponds to either subsidence or westward motion, while a positive signal corresponds to uplift or eastward motion. In the horizontal-east map, a negative signal corresponds to westward motion, while a positive signal corresponds to eastward motion. In the vertical map, a negative signal indicates subsidence, while a positive signal indicates uplift. The maps were calculated from Sentinel-1 Synthetic Aperture Radar data collected between 2017 and 2024 during the snow-free season. Interferometric analysis of Sentinel-1 data was performed using GAMMA Software (https://www.gamma-rs.ch), and the long-term deformation rate was computed with the Multidimensional Small Baseline Subset (MSBAS) Software Version 10 (https://doi.org/10.1080/07038992.2024.2424753) at the Canada Centre for Mapping and Earth Observation, Natural Resources Canada. Long-wavelength signals caused by postglacial rebound and tectonic motion were filtered to enhance the visibility of small-scale deformation processes, such as those originating from landslides and mining. Field studies have confirmed only a few of these processes to date. The maps are expected to contain processing artifacts, which will be addressed in future work. References: Samsonov, S. V., & Feng, W. (2023). Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges. Canadian Journal of Remote Sensing, 49(1). https://doi.org/10.1080/07038992.2023.2247095 Samsonov, S. V. (2024). Multidimensional Small Baseline Subset (MSBAS) Software for Constrained and Unconstrained Deformation Analysis of Partially Coherent DInSAR and Speckle Offset Data. Canadian Journal of Remote Sensing, 50(1). https://doi.org/10.1080/07038992.2024.2424753 Limitation of Liability : The information contained on this website is provided on an “as is” basis and Natural Resources Canada makes no representations or warranties respecting the information, either expressed or implied, arising by law or otherwise, including but not limited to, effectiveness, completeness, accuracy or fitness for a particular purpose. Natural Resources Canada does not assume any liability in respect of any damage or loss based on the use of this website. In no event shall Natural Resources Canada be liable in any way for any direct, indirect, special, incidental, consequential, or other damages based on any use of this website or any other website to which this site is linked, including, without limitation, any lost profits or revenue or business interruption.

The number of days during the forecast period with an average wind speed greater than 30 km/h (nswd_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. 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, 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 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.

The Probability (likelihood) of heat wave days for cool season crops occurring Heat wave days: The number of days in the forecast period with a maximum temperature above the cardinal maximum temperature, the temperature at which crop growth ceases. This temperature is 30°C for cool season crops (dhw_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.