WMS GeoMet-Weather provides public access to the Meteorological Service of Canada (MSC) and Environment and Climate Change Canada (ECCC) data via interoperable web services and application programming interfaces (API). Through open standards, users can freely and quickly access thousands of real-time and archived weather, climate and water datasets and products and integrate them in their domain-specific applications and decision support systems. Users can build mobile apps, create interactive web maps, and display and animate MSC data in desktop software. MSC GeoMet also enables on demand raw data clipping and reprojection, on demand format conversion and custom visualization. Weather Meteorology Climate Forecasting Floods Weather alerts Storms Wind Temperature Precipitations Snow Ice National Inquiry Response Team Government of Canada, Environment and Climate Change Canada, Meteorological Service of Canada Service Channel postal

77 Westmorland Street, Suite 260

Fredericton New Brunswick E3B 6Z3 Canada None +01-506-451-6010 ecweather-meteo@ec.gc.ca None None 16384 16384 text/xml image/png image/jpeg image/webp text/plain application/json application/vnd.ogc.gml text/xml image/png image/jpeg image/png; mode=8bit image/vnd.jpeg-png image/vnd.jpeg-png8 text/xml XML INIMAGE BLANK GeoMet-Weather provides public access to the Meteorological Service of Canada (MSC) and Environment and Climate Change Canada (ECCC) data via interoperable web services and application programming interfaces (API). Through open standards, users can freely and quickly access thousands of real-time and archived weather, climate and water datasets and products and integrate them in their domain-specific applications and decision support systems. Users can build mobile apps, create interactive web maps, and display and animate MSC data in desktop software. MSC GeoMet also enables on demand raw data clipping and reprojection, on demand format conversion and custom visualization. Weather Meteorology Climate Forecasting Floods Weather alerts Storms Wind Temperature Precipitations Snow Ice EPSG:4326 EPSG:2294 EPSG:2295 EPSG:2950 EPSG:3005 EPSG:3408 EPSG:3410 EPSG:3571 EPSG:3572 EPSG:3573 EPSG:3574 EPSG:3575 EPSG:3576 EPSG:3776 EPSG:3857 EPSG:3978 EPSG:3995 EPSG:4267 EPSG:4269 EPSG:26707 EPSG:26708 EPSG:26709 EPSG:26710 EPSG:26711 EPSG:26712 EPSG:26713 EPSG:26714 EPSG:26715 EPSG:26716 EPSG:26717 EPSG:26718 EPSG:26719 EPSG:26720 EPSG:26721 EPSG:26722 EPSG:26907 EPSG:26908 EPSG:26909 EPSG:26910 EPSG:26911 EPSG:26912 EPSG:26913 EPSG:26914 EPSG:26915 EPSG:26916 EPSG:26917 EPSG:26918 EPSG:26919 EPSG:26920 EPSG:26921 EPSG:26922 EPSG:32187 EPSG:32188 EPSG:32198 EPSG:32661 EPSG:42101 EPSG:42102 EPSG:42304 EPSG:102100 EPSG:102185 EPSG:900913 AUTO2:42003 -180.000000 180.000000 -90.000000 90.000000 image/jpeg Weather Radar North American radar composite [1 km] RADAR_COVERAGE_RRAI.INV.EPSG3978 Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_COVERAGE_RRAI Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_COVERAGE_RRAI.INV Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_COVERAGE_RSNO Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_COVERAGE_RSNO.INV Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_COVERAGE_RSNO.INV.EPSG3978 Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -89.999000 90.000000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite.coverage text/xml RADAR_1KM_RRAI This mosaic is calculated over the North American domain with a horizontal spatial resolution of 1 km. This mosaic therefore includes all the Canadian and American radars available in the network and which can reach a maximum of 180 contributing radars. To better represent precipitation over the different seasons, this mosaic renders in mm/h to represent rain and in cm/h to represent snow. For the two precipitation types (rain and snow), we use two different mathematical relationships to convert the reflectivity by rainfall rates (mm/h rain cm/h for snow). This mosaic is based on the DPQPE (Dual-Pol Quantitative Precipitation Estimation) product for S-Band radars. For the US Nexrad radars, ECCC uses the most similar product from the US Meteorological Service (NOAA). This product displays radar reflectivity converted into precipitation rates, using the same formulas as the Canadian radars. Atmospheric conditions Meteorology Weather Radar Remote sensing Weather -170.320000 -50.000000 16.930000 67.190000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite text/xml RADAR_1KM_RSNO This mosaic is calculated over the North American domain with a horizontal spatial resolution of 1 km. This mosaic therefore includes all the Canadian and American radars available in the network and which can reach a maximum of 180 contributing radars. To better represent precipitation over the different seasons, this mosaic renders in mm/h to represent rain and in cm/h to represent snow. For the two precipitation types (rain and snow), we use two different mathematical relationships to convert the reflectivity by rainfall rates (mm/h rain cm/h for snow). This mosaic is based on the DPQPE (Dual-Pol Quantitative Precipitation Estimation) product for S-Band radars. For the US Nexrad radars, ECCC uses the most similar product from the US Meteorological Service (NOAA). This product displays radar reflectivity converted into precipitation rates, using the same formulas as the Canadian radars. Atmospheric conditions Meteorology Weather Radar Remote sensing Weather -170.320000 -50.000000 16.930000 67.190000 2026-06-15T01:12:00Z/2026-06-15T04:12:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.composite text/xml North American radar surface precipitation type [1 km] Radar_1km_SfcPrecipType This product is a composite at 1 km resolution over the North American domain, which, for areas with radar coverage, can distinguish occurrence and type of precipitation and can recognize several levels of precipitation intensity. This product uses as input two high-resolution radar composites namely a North American composite cleaned using dual-polarization technology, another radar composite of particle (precipitation) classification as well as the surface temperature from the CMC High Regional Deterministic Prediction System (HRDPS) model. The SPTP product is produced every 6 minutes. Atmospheric conditions Meteorology Weather Radar Remote sensing Weather EPSG:102979 -180.000000 180.000000 18.354306 90.000000 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.sfcpreciptype text/xml Radar-Coverage_SfcPrecipType Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -85.060000 85.060000 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.sfcpreciptype.coverage text/xml Radar-Coverage_SfcPrecipType-Inverted Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -85.060000 85.060000 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.sfcpreciptype.coverage text/xml Radar-Coverage_SfcPrecipType-LCC Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap. Atmospheric conditions Meteorology Radar coverage Radar Remote sensing Weather -180.000000 180.000000 -85.060000 85.060000 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.sfcpreciptype.coverage text/xml North American radar extrapolation [1 km] Radar_1km_RainPrecipRate-Extrapolation This product is the Radar Extrapolation Composite at 1 km resolution over the North American domain. It uses only the 6-minute high-resolution (1 km) radar composite (the one displayed on the different government public platforms) as input. Using a modification of the open source PySTEPS library, a motion field is computed, and radar echoes are projected forward in time. The motion is based on similarities between radar reflectivity in a time sequence at multiple spatial scales. Future radar reflectivity is extrapolated, followed by conversion to precipitation rates of MM/HR (Rain) or CM/HR (Snow). An output sequence of future radar is generated every 6 minutes. It is important to note that this output is only a projection of existing echoes with no account for the growth and decay that is expected in a real radar sequence. Errors will exist, especially near the edges of radar coverage, or near geographic features. Therefore, the product should be used with caution considering that no perfect solution can exist given the limits of predictability. Atmospheric conditions Meteorology Radar extrapolation Radar Remote sensing Weather -170.320000 -50.000000 16.930000 67.190000 2026-06-15T04:06:00Z/2026-06-15T05:06:00Z/PT6M 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.extrapolation text/xml Radar_1km_SnowPrecipRate-Extrapolation This product is the Radar Extrapolation Composite at 1 km resolution over the North American domain. It uses only the 6-minute high-resolution (1 km) radar composite (the one displayed on the different government public platforms) as input. Using a modification of the open source PySTEPS library, a motion field is computed, and radar echoes are projected forward in time. The motion is based on similarities between radar reflectivity in a time sequence at multiple spatial scales. Future radar reflectivity is extrapolated, followed by conversion to precipitation rates of MM/HR (Rain) or CM/HR (Snow). An output sequence of future radar is generated every 6 minutes. It is important to note that this output is only a projection of existing echoes with no account for the growth and decay that is expected in a real radar sequence. Errors will exist, especially near the edges of radar coverage, or near geographic features. Therefore, the product should be used with caution considering that no perfect solution can exist given the limits of predictability. Atmospheric conditions Meteorology Radar extrapolation Radar Remote sensing Weather -170.320000 -50.000000 16.930000 67.190000 2026-06-15T04:06:00Z/2026-06-15T05:06:00Z/PT6M 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.extrapolation text/xml Radar_1km_dBZ-Extrapolation This product is the Radar Extrapolation Composite at 1 km resolution over the North American domain. It uses only the 6-minute high-resolution (1 km) radar composite (the one displayed on the different government public platforms) as input. Using a modification of the open source PySTEPS library, a motion field is computed, and radar echoes are projected forward in time. The motion is based on similarities between radar reflectivity in a time sequence at multiple spatial scales. Future radar reflectivity is extrapolated, followed by conversion to precipitation rates of MM/HR (Rain) or CM/HR (Snow). An output sequence of future radar is generated every 6 minutes. It is important to note that this output is only a projection of existing echoes with no account for the growth and decay that is expected in a real radar sequence. Errors will exist, especially near the edges of radar coverage, or near geographic features. Therefore, the product should be used with caution considering that no perfect solution can exist given the limits of predictability. Atmospheric conditions Meteorology Radar extrapolation Radar Remote sensing Weather -170.320000 -50.000000 16.930000 67.190000 2026-06-15T04:06:00Z/2026-06-15T05:06:00Z/PT6M 2026-06-15T01:06:00Z/2026-06-15T04:06:00Z/PT6M urn:x-msc-smc:md:weather-meteo::radar.extrapolation text/xml Canadian Weather Lightning_2.5km_Density The Canadian Lightning Detection Network (CLDN) provides lightning monitoring across most of Canada. The data distributed here represents a spatio-temporal aggregation of the observations of this network available with an accuracy of a few hundred meters. More precisely, every 10 minutes, the reported observations are processed in the following way: The location of observed lightning (cloud-to-ground and intra-cloud) in the last 10 minutes is extracted. Using a regular horizontal grid of about 2.5km by 2.5km, the number of observed lightning flashes within each grid cell is calculated. These grid data are normalized by the exact area of each cell (in km2) and by the accumulation period (10min) to obtain an observed flash density expressed in km-2 and min-1. A mask is applied to remove data located more than 250km from Canadian land or sea borders. Lightning Real-time Thunderstorm Storms Weather Detection -156.145350 -38.694350 31.541389 73.723389 2026-06-15T01:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::lightning text/xml Satellite Imagery Geostationary Operational Environmental Satellite (GOES) East GOES-East_1km_DayVis These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T19:50:00Z/2026-06-15T01:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_NaturalColor These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T19:50:00Z/2026-06-15T01:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_2km_NightIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_2km_NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_FireTemperature-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_2km_Ash These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_2km_SO2 These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_2km_Dust These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_DayCloudType-NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_DayVis-NightIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_VisibleIRSandwich-NightMicrophysicsIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_SnowFog-NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_SmokeABIband1-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml GOES-East_1km_DayLandCloudFire-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -152.800553 2.800553 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.east text/xml West GOES-West_1km_DayVis These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_NaturalColor These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_2km_NightIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_2km_NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_FireTemperature-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_2km_Ash These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_2km_SO2 These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_2km_Dust These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_DayCloudType-NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_DayVis-NightIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_VisibleIRSandwich-NightMicrophysicsIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_SnowFog-NightMicrophysics These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T21:50:00Z/2026-06-15T03:50:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_SmokeABIband1-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml GOES-West_1km_DayLandCloudFire-SWIR These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases. Atmospheric conditions Visible Infrared Clouds and weather Aviation weather Convective weather Fire weather Fog and low stratus Snow and ice Earth observation Satellite images Remote sensing Meteorology -214.800553 -59.199447 -44.372890 44.372890 2026-06-12T22:00:00Z/2026-06-15T04:00:00Z/PT10M urn:x-msc-smc:md:weather-meteo::satellite.goes.west text/xml