Home /Search
Search datasets
We have found 44 datasets for the keyword " solaire". You can continue exploring the search results in the list below.
Datasets: 103,380
Contributors: 42
Results
44 Datasets, Page 1 of 5
Daily average solar irradiance on tilted surfaces for all of Canada
This dataset includes daily averages of solar irradiance on tilted surfaces for all of Canada based on the period of 1998 - 2022.Daily averages of solar irradiance are displayed on both a monthly and annual basis for ten different tilt and tracking methods relative to the ground (horizontal) and latitude of the location. The daily averages were derived from multi-year satellite-derived solar resource datasets at an hourly temporal resolution and gridded geospatial resolution of approximately 10 km by 10 km.The data can be used to further assess the potential of solar energy technologies in Canada, including solar photovoltaics (PV) for electricity and solar thermal for domestic hot water and space heating. Maps of solar resource potential in Canada – Data Format The data stored in these files includes the daily-average insolation on tilted surfaces in units of kW·hr/m² for a given period. Each band represents period, numbered in order: band 1 = Annual, band 2 = January, band 3 = February, ..., band 13 = December.The period of averaging is the year 1998-2022, inclusive.Four fixed tilted surfaces of 0° (horizontal), 30°, 60°, and 90° (vertical) relative to the horizontal plane:- fixed tilted surfaces of 0° (vertical) relative to the horizontal plane (H+ 00 S+00)- fixed tilted surfaces of 30° (vertical) relative to the horizontal plane (H+ 30 S+00)- fixed tilted surfaces of 60° (vertical) relative to the horizontal plane (H+ 60 S+00)- fixed tilted surfaces of 90° (vertical) relative to the horizontal plan (H+ 90 S+00)Three fixed tilted surfaces of 0°, +15°, and -15°, relative to the local latitude:- fixed tilted surfaces of 0° relative to the local latitude (L+00 S+00)- fixed tilted surfaces of +15°, relative to the local latitude (L+00 S+00)- fixed tilted surfaces of -15°, relative to the local latitude (L+00 S+00)- A two-axis tracking surface that follows the sun throughout the day (T+00 T+00)- A single-axis tracking surface with the axis aligned north-south, tracking the sun east to west (A+00_S+90)- A single-axis tracking surface with the axis aligned east-west, tracking the sun's elevation (A+00_S+00)
Annual Solar Radiation 1971-2000
The data represents the annual solar radiation in Alberta over the 30-year period from 1971 to 2000. A 30-year period is use to describe the present climate since it is enough time to filter out short-term fluctuation by is not dominated by any long-term trend in the climate. Daily total incoming solar radiation is measured in megajoules per square metre (MJ/m2). Southern Alberta receives the greatest amount of annual global solar radiation with the amount gradually decreasing as you move farther north. However, cropping is successful in the northern (Peace River) area of Alberta because the longer summer day length helps compensate for the less intense solar radiation. Cloud cover in the mountains will reduce the amount of solar radiation received there.The amount of solar radiation received at the earth's surface varies with two factors that depend on latitude: the angle of the sun's rays and the hours of daylight. The distance from the equator, and therefore the intensity of the sun's radiation has the greatest effect on climate. Canada's position in the northern portion of the earth's northern hemisphere means that it receives less solar radiation compared to countries near the equator. The northward decrease in solar radiation is also noticeable within Alberta. Temperatures are generally higher in southern Alberta in comparison to northern Alberta because the south receives more solar radiation. This resource was created using ArcGIS.
Solar Resource, NSRDB PSM Direct Normal Irradiance (DNI) - North American Cooperation on Energy Information
Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.
Solar Resource, NSRDB PSM Global Horizontal Irradiance (GHI) - North American Cooperation on Energy Information
Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.
Clean power generating stations by type in megawatts (MW)
This Web Map Service depicts the location of clean electricity generating facilities by type of clean energy source and power generation capacity. Clean energy sources shown on the map include biomass, hydro, nuclear, solar, tidal and wind. The data comes from the provinces and territories, other federal departments and clean energy associations in Canada. The service is one of many themes mapped in the web mapping application Map of Clean Energy Resources and Projects (CERP) in Canada.
MODIS 10-daily composite surface albedo time series of Canada - Revision 0
The MODIS surface albedo dataset was produced by the Canada Center for Remote Sensing (CCRS), Natural Resources Canada. The dataset represents the solar shortwave broadband surface albedo and it is at a 10-day interval covering the entire Canadian landmass as well as northern USA, Alaska, and the Greenland. The dataset was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the TERRA satellite which provides a global coverage every 1-2 days in 36 spectral bands ranging from visible to infrared and to thermal wavelengths between 405 and 14,385 nm, and was available since 2000. For the estimation of surface albedo, the first seven spectral bands of B1 to B7 ranging from 459 nm to 2155 nm were used. B1 and B2 have a 250 meter resolution and B3 to B7 have a 500 meter resolution. A downscaling method using a regression and normalization scheme was employed to downscale the bands B3 to B7 to 250 meter resolution while preserving radiometric properties of the original data. To obtain clear-sky observations from MODIS, composite images for a 10 day period were generated by using a series of advanced algorithms (Luo et al., 2008). The 10-day composites of B1-B7 reflectance were then used to retrieve spatially continuous spectral albedo by using a combined land/snow BRDF (Bi-directional Reflectance Distribution Function) model. In that method, the modified RossThick-LiSparse BRDF model (Maignan et al., 2004) for land and Kokhanovsky and Zege’s model (2004) for snow are linearly combined for mixed surface conditions. They are weighted by snow fraction (0.0 ~ 1.0). The seven spectral albedo were then converted into the shortwave broadband surface albedo using the empirical MODIS polynomial conversion equation of Liang et al. (1999). The data product is in LCC (Lambert Conformal Conic) projection with a 250m pixel resolution. There are 36 albedo images per year. A dataset representing the pixel state (e.g. cloud/shadow, snow/ice, water, land, et al.) was also generated for each 10-day corresponding to the surface albedo product. References: Kokhanovsky, A. A. and Zege, E. P., 2004, Scattering Optics of Snow, Applied Optics, 43, 1589-1602, doi:10.1364/AO.43.001589, 20. Liang, S., Strahler, A.H., Walthall, C., 1999. Retrieval of land surface albedo from satellite observations: a simulation study. J. Appl. Meteorol. 38, 712–725. Luo, Y., Trishchenko, A.P., Khlopenkov, K.V., 2008. Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America. Remote Sens. Environ. 112, 4167–4185. Maignan, F., F.M. Bréon and R. Lacaze, 2004, Bidirectional reflectance of Earth targets : evaluation of analytical models using a large set of spaceborne measurements with emphasis with the hot spot, Remote Sens. Environ., 90, 210-220.
Dynamic Habitat Index (2000-2006)
Dynamic Habitat Index. (2000-2005) Satellite derived estimates of photosynthetically active radiation can be obtained from satellites such as MODIS. Knowledge of the land cover allows for calculation the fraction of incoming solar radiation that is absorbed by vegetation. This fraction of photosynthetically active radiation (fPAR) absorbed by vegetation describes rate at which carbon dioxide and energy from sunlight are assimilated into carbohydrates during photosynthesis of plant tissues. The summation of carbon assimilated by the vegetation canopy over time yields the landscape's gross primary productivity. Daily MODIS imagery is the basis for periodic composites and monthly data products. Over the 6 year period from 2000-2005, we calculate the annual average cumulative total of 72 monthly fPAR measurements, to describe the integrated annual vegetative production of the landscape, the integrated average annual minimum monthly fPAR measurement, which describes the annual minimum green cover of the observed landscape, and the integrated average of the annual covariance of fPAR, which describes the seasonality of the observed landscape. We also share the combination of the annual integrated values for visualization and analysis as the Dynamic Habitat Index (with additional information in Coops et al. 2008). When using this data, please cite as: Coops, N.C., Wulder, M.A., Duro, D.C., Han, T. and Berry, S., 2008. The development of a Canadian dynamic habitat index using multi-temporal satellite estimates of canopy light absorbance. Ecological Indicators, 8(5), pp.754-766. ( Coops et al. 2008).
Canadian Weather Energy and Engineering Datasets (CWEEDS)
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.
Canadian Weather Year for Energy Calculation (CWEC)
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.
North American Cooperation on Energy Information, Mapping Data
Mapping Resources on energy infrastructure and potential implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.[Natural Gas Processing Plants](https://open.canada.ca/data/en/dataset/636b9550-3700-4e66-8259-5cfc8159a784): Facilities designed to recover natural gas liquids from a stream of natural gas. These facilities control the quality of the natural gas to be marketed.[Refineries](https://open.canada.ca/data/en/dataset/57e7bc4c-680b-4640-9fa1-ded7ce186fab): Facilities that separate and convert crude oil or other feedstock into liquid petroleum products, including upgraders and asphalt refineries.[Liquefied Natural Gas Terminals](https://open.canada.ca/data/en/dataset/e08eec16-7c7a-4253-9bee-ea640d400a54): Natural gas onshore facilities used to receive, unload, load, store, gasify, liquefy, process and transport by ship, natural gas that is imported from a foreign country, exported to a foreign country, or for interior commerce.[Power Plants, 100 MW or more](https://open.canada.ca/data/en/dataset/40fbe40c-01cd-49d3-8add-0d20ed64c90d): Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical, and/or fission energy into electric energy with an installed capacity of 100 megawatts or more.[Renewable Power Plants, 1 MW or more](https://open.canada.ca/data/en/dataset/490db619-ab58-4a2a-a245-2376ce1840de): Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical into electric energy with an installed capacity of 1 Megawatt or more generated from renewable energy, including biomass, hydroelectric, pumped-storage hydroelectric, geothermal, solar, and wind. [Natural Gas Underground Storage](https://open.canada.ca/data/en/dataset/07b63e0e-09bb-4c4f-b057-63a58d40553a): Sub-surface facilities used for storing natural gas. The facilities are usually hollowed-out salt domes, geological reservoirs (depleted oil or gas field) or water bearing sands (called aquifers) topped by an impermeable cap rock.Border Crossings: [Electric transmission lines](https://open.canada.ca/data/en/dataset/35c51098-5cd8-44b0-b1cd-c8ce2f5dae89), [liquids pipelines](https://open.canada.ca/data/en/dataset/82053097-6b4f-44d9-a750-549df44b36b4) and [gas pipelines](https://open.canada.ca/data/en/dataset/e313db89-4219-4a5e-a543-772a86068710).[Solar Resource, NSRDB PSM Global Horizontal Irradiance (GHI)](https://open.canada.ca/data/en/dataset/9554ed18-6ab2-477f-9545-da091eba762f): Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").[Solar Resource, NSRDB PSM Direct Normal Irradiance (DNI)](https://open.canada.ca/data/en/dataset/a2dd0554-03f8-4edc-a3b3-67b47c5c9d6d): Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and topics that matter to you.
Please send us your feedback