Data on traffic obstacles (street closures, roadworks, storms...)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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.

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.

Most of these events involved community evacuations, significant structural loss and/or involvement of a Ministry of Natural Resources (MNR) Emergency Response Officer. Events include those assigned to MNR by an Order-In-Council under the Emergency Management and Civil Protection Act as well as events where MNR provided requested emergency response assistance. These events fall into one of ten type categories: * dam failure * drought /low water * erosion * flood * forest fire * soil and bedrock instability * Petroleum Resource Center event * EMO requested assistance * continuity of operations event * other requested assistance This product requires the use of geographic information system (GIS) software.

Flood extent polygons from the last three days in selected Canadian regions that have been designated for observation, monitored by Natural Resources Canada using satellite imagery for emergency response. Coverage is not comprehensive nationwide. In response to large flood events, Natural Resources Canada (NRCan), for the provision of emergency geomatics services, may be activated by Canada’s emergency management protocols. As new satellite imagery becomes available, NRCan will extract flood extent polygons and update the dataset in near real time (4 hours). This item contains the latest flood products generated in the past three days. For any data older than 72 hours, please refer to the [Floods in Canada - Current Year](https://open.canada.ca/data/en/dataset/b1afd8d2-6e14-4ec4-9a09-652221a6cb71) entry. Note that the web mapping service may not display data if flood polygons have not been published by the EGS in the past three days. The flood products generated are validated on a best effort basis. Various factors may affect the quality of the flood polygons. These factors include, but are not limited to, sensor type, image resolution, cloud cover or limitations of the flood polygon extraction method. In this layer, where possible, a symbology is applied to the flood polygons based on the underlying land use classification, or is simply unclassified and shows the raw flood extent. When using Web mapping services, to display a specific product, filter by date (UTC Date) and area of interest (AOI). Also, a link to download each product directly is available in the Resources section. This prepackaged and compressed product contains a Shape file, a PDF file and a KMZ file. Disclaimer: Emergency response authorities are the primary users of these satellite-derived open water flood extent map products. These products are generated to provide analysis and emergency response situational awareness and to facilitate decision-making during major flood events. The open water flood extent products are generated rapidly and limited time is available for editing and validation. The flood products reflect the open water flood conditions at the date/time of acquisition. While efforts are made to produce high quality products, near-real time products may contain errors due to the limited time available for vector editing and validation. Please note that current algorithms do not map flooded areas under the forest canopy and are not optimized for urban flood mapping. Limitation of Liability: Accordingly, 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. Parent Collection:- **[Floods in Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/08b810c2-7c81-40f1-adb1-c32c8a2c9f50)**

Statistically downscaled multi-model ensembles of projected change (also known as anomalies) in mean 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). Downscaled daily mean temperature was calculated by averaging downscaled daily minimum and maximum temperature. Daily minimum and maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). Historical gridded minimum and maximum temperature datasets of Canada (ANUSPLIN) were used as the respective downscaling targets. Projected change in mean temperature (°C) is with respect to the reference period of 1986-2005. Seasonal and annual averages of projected mean temperature change to 1986-2005 are provided. Specifically, the 5th, 25th, 50th, 75th and 95th percentiles of the downscaled ensembles of mean 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 minimum mean 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.

A Storm Sewer is an enclosed system of pipes or drains that divert water away from the road and/or right of way. Also includes culverts that run under enclosed ditches. It is a Linear feature

Gridded temperature and salinity of the Estuary and Gulf of St. Lawrence bottom waters including shallow waters. Data are a result of a 3D interpolation on a 1km x 1km x bottom depth grid. They mostly come from the 2 multidisciplinary surveys but all the available CTD data sampled in August and September were used. The dataset contains 24 layers: one layer per year per variable from 2014 to 2023, two layers of temperature and salinity climatologies and two layers of anomalies for the last year.PurposeSince 1990, the Department of Fisheries and Oceans has been conducting an annual multidisciplinary survey in the Estuary and northern Gulf of St. Lawrence using a standardized protocol. In the southern Gulf of St. Lawrence, these bottom trawl surveys has been carrying out each September since 1971. These missions are an important source of information about the status of the marine ressources.The objectives of the surveys are multiple: to estimate the abundance and biomass of groundfish and invertebrates, to identify the spatial distribution and biological characteristics of these species, to monitor the biodiversity of the Estuary and Gulf and finally, to describe the environmental conditions observed in the area at the moment of the sampling.The southern Gulf surveys are realized using the following standardized protocol:Hurlbut,T. and D.Clay (eds) 1990. Protocols for Research Vessel Cruises within the Gulf Region (Demersal Fish) (1970-1987). Can. MS Rep. Fish. Aquat. Sci. No. 2082: 143p.The sampling protocols used for the Estuary and northern Gulf surveys are described in details in the following publications:Bourdages, H., Archambault, D., Bernier, B., Fréchet, A., Gauthier, J., Grégoire, F., Lambert, J., et Savard, L. 2010. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2009 dans le nord du golfe du Saint-Laurent. Rapp. stat. can. sci. halieut. aquat. 1226 : xii+ 72 p. Bourdages, H., Archambault, D., Morin, B., Fréchet, A., Savard, L., Grégoire, F., et Bérubé, M. 2003. Résultats préliminaires du relevé multidisciplinaire de poissons de fond et de crevette d’août 2003 dans le nord du golfe du Saint-Laurent. Secr. can. consult. sci. du MPO. Doc. rech. 2003/078. vi + 68 p.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Bourdages, H., Brassard, C., Desgagnés, M., Galbraith, P., Gauthier, J., Légaré, B., Nozères, C. and Parent, E. 2017. Preliminary results from the groundfish and shrimp multidisciplinary survey in August 2016 in the Estuary and northern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/002. v + 87 p.

The purpose of this feature layer is to provide the 2009 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 20 09 . Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery. The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas. When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

A magnitude 5 earthquake scenario along an unnamed fault located about 15 km north-northeast of Burnaby City Hall and directly south of Mt Elsay. This fault is not known to be active, but this scenario represents a small but damaging event in the North Shore Mountains.