644 datasets of Typical Meteorological Years (TMY) created by joining twelve Typical Meteorological Months selected from a database of up to 20 years of CWEEDS hourly data. The months are chosen by statistically comparing individual monthly means with long-term monthly means for daily total global solar irradiance, mean, minimum and maximum dry bulb temperature, mean, minimum and maximum dew point temperature, and mean and maximum wind speed. These hourly datasets are used by the engineering and scientific community mainly as inputs for solar system design and analysis and building energy systems analysis tools. This dataset has been updated with the most recent changes made in March 2023. The solar values in these files are based on 0.1° x 0.1° (11 km x 11 km grid) for all of Canada. Refer to Data Resources below for additional information on the TMY file format.

Towers -- structures or buildings that are typically higher than their diameter and high relative to their surroundings -- are shown in this data set. They include: * communication towers * fire towers * microwave towers * radio towers * navigation beacons * lighthouses * lightning locators * meteorological towers

Estimates of wind-driven upwelling of colder water on the Scotian Shelf along the Nova Scotia coastline from 1993 to 2022 (inclusive) are presented, calculated using surface and 55m-depth water temperatures from the Global Ocean Physics Reanalysis (GLORYS12v1) product, and also ERA5 surface winds. GLORYS12v1 is a 1/12o data-assimilative reanalysis modelling product from Mercator Ocean International, implemented by the Copernicus Marine Environment Monitoring Service (CMEMS; (https://doi.org/10.48670/moi-00021). ERA5 is a weather forecast produced by the European Centre for Medium-Range Weather Forecasts (ECMWF; https://doi.org/10.24381/cds.adbb2d47). Daily estimates are given of upwelling area and intensity (temperature anomaly between upwelled and non-upwelled water), calculated over the area of interest (AOI) on the Scotian Shelf. Yearly estimates are given of total upwelling duration and cumulative area for the year in question, further broken down into seasons: Spring (March-May), Summer (June-August), and Fall (September-November). Lastly, estimates of the yearly start/end dates of the cold-water upwelling season (lasting generally from March to November) are estimated. The sea surface temperature (SST) data from GLORYS were validated against in-situ buoy observations (https://www.meds-sdmm.dfo-mpo.gc.ca/alphapro/wave/waveshare/metaData/meta_c44258.csv) and satellite-derived SST produced by Canadian Meteorological Centre (https://doi.org/10.5067/GHCMC-4FM02 and https://doi.org/10.5067/GHCMC-4FM03. These products may be used to gain knowledge of interannual variability of coastal upwelling on the ScS over the past 30 years.Cite this data as: Tao, J., Casey, M., Lu, Y., and Shen, H. Upwelling indices derived from GLORYS12 Model and ERA5 surface wind on the Scotian Shelf during 1993-2022.Published: December 2024. Ecosystems and Oceans Science, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS. https://open.canada.ca/data/en/dataset/a2da6bfd-92e3-434e-b9bd-456b7fc9e92b

For nearly three decades, the SCRIBE system has been used to assist meteorologists in preparing weather reports. The philosophy behind SCRIBE is that a set of weather element matrices are generated for selected stations or sample points and then transmitted to regional weather centers. The matrices are then decoded by SCRIBE and can be modified via the graphical interface by the users. The resulting data is then provided to a text generator, which produces bilingual public forecasts in plain language.The various rules related to the Scribe matrices hinder scientific innovation, do not exploit the richness of the Numerical Weather Prediction (NWP), reduce the comprehension of meteorological forecasts, and and may require frequent interventions from forecasters.As part of a larger modernization plan for the Meteorological Service of Canada (MSC), in which the role of the forecaster is evolving, the goal is to replace the Scribe matrices, available on the MSC Datamart, and their limited number of points across Canada with Weather Elements on the Grid ("WEonG").Weather Elements on Grid (WEonG) based on the Regional Deterministic Prediction System (RDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the Regional Deterministic Prediction System (RDPS).

644 datasets of hourly meteorological data for all of Canada from various periods (1998 to 2020). The values of the records for solar irradiance are primarily based on satellite-derived solar estimates. This dataset has been updated with the most recent changes made in March 2023. The solar values in these files are based on 0.1° x 0.1° (11 km x 11 km grid) for all of Canada. Refer to Data Resources below for additional information on the CWEEDS file format and revision history.

Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).

Anomalous weather resulting in Temperature and Precipitation extremes occurs almost every day somewhere in Canada. For the purpose of identifying and tabulating daily extremes of record for temperature, precipitation and snowfall, the Meteorological Service of Canada has threaded or put together data from closely related stations to compile a long time series of data for about 750 locations in Canada to monitor for record-breaking weather. Virtual Climate stations correspond with the city pages of weather.gc.ca. This data provides the daily extremes of record for Temperature for each day of the year. Daily elements include: High Maximum, Low Maximum, High Minimum, Low Minimum.

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.

The Standardized Precipitation Index (SPI) has been recognized as the most accessible index for quantifying and reporting meteorological drought. On short timescales, the SPI is closely related to soil moisture, while at longer timescales, the SPI can be related to groundwater and reservoir storage. The model uses observed historical precipitation amounts to compute probability distributions which are then normalized using an incomplete gamma function over a range of timescales. The values can be interpreted as the number of standard deviations by which the observed anomaly deviates from the long-term mean. where positive values (greater than zero) result from above average conditions.

This dataset is a locational record of the meteorological input files publically available on Saskatchewan GeoHub that can be used with the Environmental Protection Agency approved Regulatory Model (AERMOD). Each file represents the meteorology over an area of the province while minimizing the influences of local terrain on air flow. Additional attribute information for each location includes coordinates and a link to download the AERMOD data as a zip file.The Air Quality Section of the Ministry of Environment uses air quality modelling to simulate how air pollutants disperse in the ambient atmosphere in order to help manage the air quality in the province. The models are used to estimate the impact of air pollutants emitted from emission sources, and are typically employed to determine whether existing or new proposed industrial facilities are or will be in compliance with the ambient air quality standards outlined in Table 20 of the province's Environmental Code, June 1, 2015 under The Environmental Management and Protection Act, 2010.  The information needed to run dispersion models consists primarily of emissions and meteorological data. Five years (2012-2016) of preprocessed meteorological datasets in an AERMOD ready format is publicly available. This file is contained in the downloadable zipped file. The zipped file contains five files: the SFC and PFL files are the AERMOD ready files required to run AERMOD (i.e., data, sensible heat flux, frictional velocity, potential temperature gradient, vertical velocity, mixing height, monin-obukhov length, surface roughness, Bowen ratio, albedo, scalar wind speed, wind direction, ambient temperature, precipitation, precipitation rate, relative humidity, surface pressure, and total cloud amounts); the DAT file contains the land use information (i.e., Surface roughness, Bowen ratio and albedo) chosen for each month in the SFC file; the KMZ file contains the wind rose for that location which can be used on Google Earth; and the PNG file contains various graphs of monthly or diurnal meteorological distribution (i.e., temperature, wind speed, daytime mixing heights and sensible heat flux, and stability) which can be used to help determine if that location is representative of the area proposed for modelling.  Please note: Since this data is newly developed, it is possible there may be issues with the data as it gets used in more applications. Ongoing changes, edits and updates may be made by the Air Quality Section of the Ministry of Environment. Is is recommended for any future modelling to download the latest version of the input files and not archive any input files on your own server for future use, unless this notification no longer exists. If there are any issues discovered with data in the zipped file, please contact Dennis Fudge at dennis.fudge@gov.sk.ca or at 306-519-7105. Your support will be greatly appreciated.  There may be times you feel that the input files are not representative of the proposed modelling domain due to the surrounding features (i.e., forest/agricultural or rural/urban) being different than those used to generate the input files. If that is the case, the modeler can generate the input modelling files themselves. The relevant files to generate these input files are available upon request. Please contact Dennis Fudge at dennis.fudge@gov.sk.ca or at 306-519-7105.