30-year Average Dry Day Count is defined as the count of the average number of climate days which received less than 0.5 mm of precipitation during the calendar month. These values are calculated across Canada in 10x10 km cells, and are based on average precipitation amounts over a 30-year period (1961-1990, 1971-2000, 1981-2010, 1991-2020). These values are calculated across Canada in 10x10 km cells.

In 1997, a magnitude 4.6 earthquake occurred 3 to 4 km beneath the Strait of Georgia, near Vancouver. This scenario visualizes the effects of that event if it occurred today with a magnitude of 4.9. A magnitude 7.0 Georgia Strait scenario is also provided, and represents a less likely but more consequential case for comparison.

Bay Scale Assessment of Habitat in Bras d'Or Lake - River Denys 2005 - 2009 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - River Denys 2005 - 2009. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.

This is a magnitude 5.0 earthquake scenario along the Burlington Toronto Structural Zone — a fault near Toronto and its surrounding region. This fault is not known to be active but demonstrates a plausible earthquake scenario for the Toronto region.

A magnitude 5.6 rupture scenario near Ottawa along the Gloucester Fault in the south of the city. This fault is not known to be active, but this scenario is representative of seismicity in the Ottawa Valley.

Series of Panchromatic orthophotos for 4 reservoir areas, Duncairn, LaFleche, Moosomin, Gouverneur taken in 2005. The photos were meant to coincide at a time when the reservoirs where at high flood supply levels (FSL).

This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u].

This series of datasets has been created by AAFC’s National Agroclimate Information Service (NAIS) of the Agro-Climate, Geomatics and Earth Observations (ACGEO) Division of the Science and Technology Branch. The Canadian Drought Monitor (CDM) is a composite product developed from a wide assortment of information such as the Normalized Difference Vegetation Index (NDVI), streamflow values, Palmer Drought Index, and drought indicators used by the agriculture, forest and water management sectors. Drought prone regions are analyzed based on precipitation, temperature, drought model index maps, and climate data and are interpreted by federal, provincial and academic scientists. Once a consensus is reached, a monthly map showing drought designations for Canada is digitized. AAFC’s National Agroclimate Information Service (NAIS) updates this dataset on a monthly basis, usually by the 10th of every month to correspond to the end of the previous month, and subsequent Canadian input into the larger North American Drought Monitor (NA-DM). The drought areas are classified as follows: D0 (Abnormally Dry) – represents an event that occurs once every 3-5 years; D1 (Moderate Drought) – represents an event that occurs every 5-10 years; D2 (Severe Drought) – represents an event that occurs every 10-20 years; D3 (Extreme Drought) – represents an event that occurs every 20-25 years; and D4 (Exceptional Drought) – represents an event that occurs every 50 years. Impact lines highlight areas that have been physically impacted by drought. Impact labels specify the longitude and magnitude of impacts. The impact labels are classified as follows: S – Short-Term, typically less than 6 months (e.g. agriculture, grasslands). L – Long-Term, typically more than 6 months (e.g. hydrology, ecology).