{ "count": 47, "next": null, "previous": null, "results": [ { "id": 5596, "url": "https://svs.gsfc.nasa.gov/5596/", "result_type": "Visualization", "release_date": "2026-01-27T17:00:00-05:00", "title": "Tracking Weather Extremes: December 2025 Pacific Northwest Flooding", "description": "Created with NASA's GEOS data, this visualization shows the December 2025 atmospheric river that brought extreme precipitation to the Pacific Northwest. The analysis displays total precipitable water from the Pacific Ocean and resulting precipitation across Washington, Oregon, British Columbia, and Montana. 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Five visualization assets show fire information, black carbon dispersal, air quality effects, weather conditions, and progression, demonstrating how technology helps understand wildfire dynamics.", "hits": 229 }, { "id": 5597, "url": "https://svs.gsfc.nasa.gov/5597/", "result_type": "Visualization", "release_date": "2025-12-30T17:18:00-05:00", "title": "Los Angeles Palisades and Eaton Wildfires: 2025 Year in Review", "description": "Part of our 2025 Year in Review series examining major wildfire events, this analysis of the January 2025 Los Angeles Palisades and Eaton wildfires leverages NASA's satellite data, models, and computing power to reveal fire behavior and impacts. Five visualization assets show fire information, black carbon dispersal, air quality effects, weather conditions, and progression, demonstrating how technology helps understand wildfire dynamics.", "hits": 547 }, { "id": 5595, "url": "https://svs.gsfc.nasa.gov/5595/", "result_type": "Visualization", "release_date": "2025-12-29T15:50:00-05:00", "title": "Tracking Weather Extremes: July 2025 Texas Precipitation and Guadalupe River Flooding", "description": "Created with NASA's GEOS-FP 2km replay data, this visualization shows extreme precipitation across Texas from June 30 - July 5, 2025. The Hunt City, marked on the visualization, experienced 6.5 inches of rain in three hours on July 4th, triggering catastrophic Guadalupe River flooding that reached record-breaking levels of 37.52 feet - the highest ever recorded at this location.", "hits": 203 }, { "id": 5594, "url": "https://svs.gsfc.nasa.gov/5594/", "result_type": "Visualization", "release_date": "2025-12-29T15:00:00-05:00", "title": "Los Angeles Palisades Wildfire, January 2025: Black Carbon, Weather, and Air Quality", "description": "NASA GEOS model visualization showing black carbon dispersal from the Palisades Fire overlaid with regional weather patterns and air quality indicators, January 2-14, 2025.", "hits": 456 }, { "id": 5593, "url": "https://svs.gsfc.nasa.gov/5593/", "result_type": "Visualization", "release_date": "2025-12-29T13:00:00-05:00", "title": "Tracking Weather Extremes: May 2025 Tornadoes and Flooding Across the Continental United States", "description": "Created with NASA's GEOS-FP 2km replay model, this visualization tracks May 2025's severe weather across the continental US. The visualization maps tornado paths and 24-hour precipitation data, revealing how tornadic activity and heavy rainfall combined to create compound disasters affecting communities from the Great Plains to the Southeast.", "hits": 283 }, { "id": 5424, "url": "https://svs.gsfc.nasa.gov/5424/", "result_type": "Visualization", "release_date": "2025-09-22T07:00:00-04:00", "title": "The Different Sources of Atmospheric Methane", "description": "This data visualization shows methane (CH₄) in the Earth’s atmosphere during 2021. The colors represent contributions from different sources: agriculture and waste (fuchsia), industry (blue), wetlands (green), wildfires and cropland fires (yellow), and other natural sources (gray).", "hits": 241 }, { "id": 5554, "url": "https://svs.gsfc.nasa.gov/5554/", "result_type": "Visualization", "release_date": "2025-07-11T12:25:00-04:00", "title": "Atmospheric Methane Tagged by Source for Science on a Sphere", "description": "This data visualization shows methane in Earth's atmosphere during 2021. The colors represent different sources: agriculture and waste (fuchsia), industry (blue), wetlands (green), burning forests and farmlands (yellow) and other natural (gray). Advanced computer modeling techniques at NASA's Global Modeling and Assimilation Office allow us to view the distribution of CH4 sources to better understand how methane moves through Earth’s systems.", "hits": 61 }, { "id": 5552, "url": "https://svs.gsfc.nasa.gov/5552/", "result_type": "Visualization", "release_date": "2025-06-23T09:00:00-04:00", "title": "Science On A Sphere: Aerosols in the Air", "description": "NASA merges observations, advanced models and computing power to monitor aerosols in the atmosphere. Aerosols are tiny invisible solid or liquid particles that float in the atmosphere and can travel long distances affecting air quality and visibility far from their source. These particles come from natural and human sources and include black carbon (orange/red), sea salt (cyan), dust (magenta) and sulfates (green).", "hits": 678 }, { "id": 5533, "url": "https://svs.gsfc.nasa.gov/5533/", "result_type": "Visualization", "release_date": "2025-05-05T12:30:00-04:00", "title": "Air Quality Model Runs", "description": "NASA utilizes satellite instruments and models to monitor sources of air pollutants and their movement through the atmosphere. This visualization shows concentrations of air pollutants, such as Particulate Matter (PM2.5, fine particles smaller than 2.5 micrometers), Ozone (O~3~), Carbon Monoxide (CO), and Nitrogen Oxides (NO~x~) as they are tracked from NASA's Goddard Earth Observing System Composition Forecasting (GEOS-CF) system.", "hits": 186 }, { "id": 5518, "url": "https://svs.gsfc.nasa.gov/5518/", "result_type": "Visualization", "release_date": "2025-05-05T11:30:00-04:00", "title": "Science On A Sphere: Air Quality Model Runs", "description": "NASA utilizes satellite instruments and models to monitor sources of air pollutants and their movement through the atmosphere. 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However, its increase in the atmosphere would be even more rapid without land and ocean carbon sinks, which collectively absorb about half of human emissions every year. Advanced computer modeling techniques in NASA's Global Modeling and Assimilation Office allow us to disentangle the influences of sources and sinks and to better understand where carbon is coming from and going to.", "hits": 179 }, { "id": 5147, "url": "https://svs.gsfc.nasa.gov/5147/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "GEOS-FP Near-Surface Temperature", "description": "Near-surface temperature is calculated by sampling 3-D atmospheric fields from NASA’s GEOS-FP system 3 meters above Earth’s surface. GEOS-FP combines millions of weather observations with a predictive model to create a global best estimate of weather conditions that are used to begin a forecast.", "hits": 0 }, { "id": 5148, "url": "https://svs.gsfc.nasa.gov/5148/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "GEOS-FP Near-Surface Wind Speed", "description": "Near-surface wind speed is calculated by sampling 3-D atmospheric fields from NASA’s GEOS-FP system 10 meters above Earth’s surface. GEOS-FP combines millions of weather observations with a predictive model to create a global best estimate of weather conditions that are used to begin a forecast.", "hits": 0 }, { "id": 5149, "url": "https://svs.gsfc.nasa.gov/5149/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "GEOS-FP Precipitation and Clouds", "description": "Precipitation and clouds are calculated using fields from NASA’s GEOS-FP system. GEOS-FP combines millions of weather observations with a predictive model to create a global best estimate of weather conditions, which can be used to estimate the formation of clouds along with rain and snowfall.", "hits": 0 }, { "id": 5150, "url": "https://svs.gsfc.nasa.gov/5150/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "GEOS-FP Near-Surface Humidity", "description": "Near-surface Humidity, also known as specific humidity (Q2M) from NASA’s GEOS-FP system. GEOS-FP combines millions of weather observations with a predictive model to create a global best estimate of weather conditions that are used to begin a forecast.", "hits": 0 }, { "id": 5151, "url": "https://svs.gsfc.nasa.gov/5151/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "Particulate Matter (PM) 2.5", "description": "Near surface concentration of fine particular matter (PM2.5) estimated from NASA’s aerosol and weather fields produced by NASA’s GEOS-CF model.", "hits": 0 }, { "id": 5152, "url": "https://svs.gsfc.nasa.gov/5152/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "Near surface Ozone (O3)", "description": "Near surface concentration of ozone (O3) estimated by NASA’s GEOS-CF model.", "hits": 0 }, { "id": 5153, "url": "https://svs.gsfc.nasa.gov/5153/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "Carbon Monoxide (CO)", "description": "Near surface concentration of carbon monoxide (CO) estimated by NASA’s GEOS-CF model.", "hits": 0 }, { "id": 5154, "url": "https://svs.gsfc.nasa.gov/5154/", "result_type": "Visualization", "release_date": "2023-09-26T17:00:00-04:00", "title": "Nitrogen Oxides (NOx)", "description": "Near surface concentration of Nitrogen Oxides (NOx) estimated from concentrations of nitrogen oxide and nitrogen dioxide produced by NASA’s GEOS-CF model.", "hits": 0 }, { "id": 31234, "url": "https://svs.gsfc.nasa.gov/31234/", "result_type": "Hyperwall Visual", "release_date": "2023-07-22T00:00:00-04:00", "title": "Column Carbon Monoxide (CO) from Canada Wildfires", "description": "Column CO from Canada Wildfires || goes-fp-cobbna-nam-jun2023_00000_print.jpg (1024x576) [154.9 KB] || goes-fp-cobbna-nam-jun2023_00000_searchweb.png (320x180) [85.6 KB] || goes-fp-cobbna-nam-jun2023_00000_thm.png (80x40) [6.3 KB] || goes-fp-cobbna-nam-jun2023_1080p30.mp4 (1920x1080) [11.6 MB] || goes-fp-cobbna-nam-jun2023_1080p30.webm (1920x1080) [2.4 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || goes-fp-cobbna-nam-jun2023_2160p30.mp4 (3840x2160) [35.4 MB] || earth_observations_5x3.hwshow [570 bytes] || ", "hits": 187 }, { "id": 5117, "url": "https://svs.gsfc.nasa.gov/5117/", "result_type": "Visualization", "release_date": "2023-06-20T21:00:00-04:00", "title": "Trends in atmospheric Nitrous Oxide (N₂O)", "description": "Global trends in atmospheric Nitrous Oxide (N₂O) for the period January 2001-December 2022. || N2OTrends_1920x1080p30.00900_print.jpg (1024x576) [60.7 KB] || N2OTrends_1920x1080p30.00900.png (1920x1080) [685.4 KB] || N2OTrends_1920x1080p30.00900_searchweb.png (320x180) [24.2 KB] || N2OTrends_1920x1080p30.00900_thm.png (80x40) [3.0 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || N2O_Trends_1920x1080p30.mp4 (1920x1080) [7.4 MB] || N2OTrends_1920x1080p30.00900.exr (1920x1080) [1.8 MB] || ", "hits": 80 }, { "id": 5116, "url": "https://svs.gsfc.nasa.gov/5116/", "result_type": "Visualization", "release_date": "2023-06-20T16:00:00-04:00", "title": "Global Atmospheric Methane (CH₄)", "description": "Volumetric visualization of the total Methane (CH₄) on a global scale added on Earth's atmosphere over the course of the year 2021. || TotalCH4_Comp_1920x19020p30_00080.png (1920x1920) [2.5 MB] || TotalCH4_Comp_1920x19020p30_00080_print.jpg (1024x1024) [114.9 KB] || VolumetricCH4_Composite (1920x1920) [0 Item(s)] || VolumetricCH4_Composite_1920x19020p30.mp4 (1920x1920) [353.5 MB] || ", "hits": 346 }, { "id": 5115, "url": "https://svs.gsfc.nasa.gov/5115/", "result_type": "Visualization", "release_date": "2023-06-20T15:00:00-04:00", "title": "Global Atmospheric Carbon Dioxide (CO₂)", "description": "Volumetric visualization of the total carbon dioxide (CO₂) on a global scale added on Earth's atmosphere over the course of the year 2021. || TotalCO2_Comp_1920x1920p30_00080.png (1920x1920) [3.2 MB] || TotalCO2_Comp_1920x1920p30_00080_print.jpg (1024x1024) [168.5 KB] || VolumetricCO2_Composite (1920x1920) [0 Item(s)] || VolumetricCO2_Composite_1920x1920p30.mp4 (1920x1920) [806.2 MB] || ", "hits": 579 }, { "id": 5110, "url": "https://svs.gsfc.nasa.gov/5110/", "result_type": "Visualization", "release_date": "2023-06-16T10:00:00-04:00", "title": "Atmospheric Carbon Dioxide Tagged by Source", "description": "Carbon dioxide (CO2) is the most prevalent greenhouse gas driving global climate change. However, its increase in the atmosphere would be even more rapid without land and ocean carbon sinks, which collectively absorb about half of human emissions every year. Advanced computer modeling techniques in NASA's Global Modeling and Assimilation Office allow us to disentangle the influences of sources and sinks and to better understand where carbon is coming from and going to. ||", "hits": 1097 }, { "id": 14177, "url": "https://svs.gsfc.nasa.gov/14177/", "result_type": "Produced Video", "release_date": "2022-07-19T11:00:00-04:00", "title": "How Climate Patterns Thousands of Miles Away Affect US Bird Migration", "description": "Stock footage: Pond5Radar video courtesy of Dr. Kyle Horton, Colorado State UniversityUniversal Production Music: “Two Ticks” by Michael Lesirge [PRS] and Tarek Christopher Modi [PRS]This video can be freely shared and downloaded. While the video in its entirety can be shared without permission, some individual imagery provided by pond5.com and CSU is obtained through permission and may not be excised or remixed in other products. For more information on NASA’s media guidelines, visit https://www.nasa.gov/multimedia/guidelines/index.htmlComplete transcript available. || 14177_BirdMigration_Thumb.jpg (1920x1080) [268.4 KB] || 14177_BirdMigration_Thumb_print.jpg (1024x576) [130.4 KB] || 14177_BirdMigration_Thumb_searchweb.png (320x180) [64.3 KB] || 14177_BirdMigration_Thumb_web.png (320x180) [64.3 KB] || 14177_BirdMigration_Thumb_thm.png (80x40) [6.5 KB] || BirdMigration.mov (1920x1080) [4.0 GB] || BirdMigration.webm (960x540) [50.2 MB] || BirdMigration.mp4 (1920x1080) [380.5 MB] || TWITTER_720_BirdMigration.mp4 (1280x720) [35.5 MB] || YOUTUBE_1080_BirdMigration.mp4 (1920x1080) [289.5 MB] || 14177_BirdMigration_EN.US.en_US.srt [3.9 KB] || 14177_BirdMigration_EN.US.en_US.vtt [3.7 KB] || ", "hits": 37 }, { "id": 4983, "url": "https://svs.gsfc.nasa.gov/4983/", "result_type": "Visualization", "release_date": "2022-04-11T12:00:00-04:00", "title": "Global Carbon Dioxide 2020-2021 for Hyperwalls", "description": "This webpage provides a wide aspect ratio version of: Global Carbon Dioxide 2020-2021, released on November 2, 2021. This version has been created for wide aspect ratio display systems with resolution up to 9600x3240. It is recommended to use content from this version for display systems with 16:9 aspect ratio. || ", "hits": 97 }, { "id": 4949, "url": "https://svs.gsfc.nasa.gov/4949/", "result_type": "Visualization", "release_date": "2021-11-02T00:00:00-04:00", "title": "Global Carbon Dioxide 2020-2021", "description": "Data visualization featuring volumetric carbon dioxide on a global scale for the period June 1, 2020 - July 31, 2021.Coming soon to our YouTube channel. || CO2Volumetric_1024x576_02582_print.jpg (1024x576) [90.6 KB] || CO2Volumetric_1024x576_02582.png (1024x576) [569.1 KB] || CO2Volumetric_1024x576_02582_searchweb.png (180x320) [60.0 KB] || CO2Volumetric_1024x576_02582_thm.png (80x40) [5.1 KB] || CO2Volumetric_1920x1080p30.mp4 (1920x1080) [65.3 MB] || CO2Volumetric_1920x1080p30.webm (1920x1080) [13.3 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || CO2Volumetric_3840x2160_30fps_02582.exr (3840x2160) [63.3 MB] || CO2Volumetric_3840x2160_30fps_02582.tif (3840x2160) [44.5 MB] || captions_silent.31831.en_US.srt [43 bytes] || CO2Volumetric_3840x2160p30.mp4 (3840x2160) [931.2 MB] || ", "hits": 160 }, { "id": 13567, "url": "https://svs.gsfc.nasa.gov/13567/", "result_type": "Produced Video", "release_date": "2020-03-06T09:00:00-05:00", "title": "How Does NASA Model Atmospheric Patterns?", "description": "Music: Favor by Victor Maitre [SACEM]Complete transcript available. || GMAOThumb.jpg (1920x1080) [251.3 KB] || GMAOThumb_print.jpg (1024x576) [131.2 KB] || GMAOThumb_searchweb.png (180x320) [82.2 KB] || GMAOThumb_web.png (320x180) [82.2 KB] || GMAOThumb_thm.png (80x40) [6.4 KB] || 13567_GMAO_Atmospheric_Model.mp4 (1920x1080) [88.5 MB] || 13567_GMAO_Atmospheric_Model.webm (1920x1080) [10.2 MB] || 13567_GMAO_Atmospheric_Model.mov (1920x1080) [673.0 MB] || captions.en_US.srt [1.3 KB] || captions.en_US.vtt [1.4 KB] || ", "hits": 48 }, { "id": 30910, "url": "https://svs.gsfc.nasa.gov/30910/", "result_type": "Hyperwall Visual", "release_date": "2017-11-13T00:00:00-05:00", "title": "Simulation of Aerosols During the 2017 North Atlantic Hurricane Season", "description": "This animation shows the effects of hurricanes on dust, smoke, and sea salt. || plot_aerosols-northamerica_F517R06K-GEOS_06KM-REPLAY-20170915_1200_print.jpg (1024x567) [160.5 KB] || plot_aerosols-northamerica_F517R06K-GEOS_06KM-REPLAY-20170915_1200.png (5760x3190) [18.1 MB] || plot_aerosols-northamerica_F517R06K-GEOS_06KM-REPLAY-20170915_1200_searchweb.png (320x180) [108.2 KB] || plot_aerosols-northamerica_F517R06K-GEOS_06KM-REPLAY-20170915_1200_thm.png (80x40) [8.2 KB] || plot_aerosols-northamerica_720p.webm (1280x720) [35.3 MB] || plot_aerosols-northamerica_720p.mp4 (1280x720) [191.7 MB] || plot_aerosols-northamerica_1080p.mp4 (1920x1080) [369.7 MB] || ", "hits": 53 }, { "id": 30911, "url": "https://svs.gsfc.nasa.gov/30911/", "result_type": "Hyperwall Visual", "release_date": "2017-11-13T00:00:00-05:00", "title": "2017 North Atlantic Hurricane Season Simulation", "description": "GEOs model run showing 2017 Atlantic hurricane season || plot_ir4-goeseast_proj_F517R06K-GEOS_06KM-REPLAY-20170905_1745_print.jpg (1024x576) [98.0 KB] || plot_ir4-goeseast_proj_F517R06K-GEOS_06KM-REPLAY-20170905_1745.png (5760x3240) [5.5 MB] || plot_ir4-goeseast_proj_F517R06K-GEOS_06KM-REPLAY-20170905_1745_searchweb.png (320x180) [44.2 KB] || plot_ir4-goeseast_proj_F517R06K-GEOS_06KM-REPLAY-20170905_1745_thm.png (80x40) [3.8 KB] || plot_ir4-goeseast_proj_720p.webm (1280x720) [49.6 MB] || plot_ir4-goeseast_proj_720p.mp4 (1280x720) [156.3 MB] || ", "hits": 32 }, { "id": 30912, "url": "https://svs.gsfc.nasa.gov/30912/", "result_type": "Hyperwall Visual", "release_date": "2017-11-13T00:00:00-05:00", "title": "2017 North Atlantic Hurricane Season Simulation Compared With Observations", "description": "A video comparing model output and satellite imagery. || ir_compare2m-globe_F517R06K-F517R06K_20170801_0000_print.jpg (1024x547) [132.7 KB] || ir_compare2m-globe_F517R06K-F517R06K_20170801_0000.png (5760x3081) [5.8 MB] || ir_compare2m-globe_F517R06K-F517R06K_20170801_0000_searchweb.png (320x180) [60.4 KB] || ir_compare2m-globe_F517R06K-F517R06K_20170801_0000_thm.png (80x40) [5.7 KB] || ir_compare2m-globe_720p.webm (1280x720) [16.1 MB] || ir_compare2m-globe_720p.mp4 (1280x720) [198.3 MB] || ", "hits": 15 }, { "id": 30913, "url": "https://svs.gsfc.nasa.gov/30913/", "result_type": "Hyperwall Visual", "release_date": "2017-11-13T00:00:00-05:00", "title": "SC17 North Atlantic Icelandic Low 1.5-km - Simulation", "description": "A video of a low pressure weather system shows which types of clouds the GEOS model can reproduce. || plot_ir4-northatlantic_map_G5ECMWF-GEOS_01KM-GEOS-20170427_1200_print.jpg (1024x576) [183.4 KB] || plot_ir4-northatlantic_map_G5ECMWF-GEOS_01KM-GEOS-20170427_1200.png (5760x3240) [12.6 MB] || plot_ir4-northatlantic_map_G5ECMWF-GEOS_01KM-GEOS-20170427_1200_searchweb.png (320x180) [81.4 KB] || plot_ir4-northatlantic_map_G5ECMWF-GEOS_01KM-GEOS-20170427_1200_thm.png (80x40) [7.0 KB] || plot_ir4-northatlantic_map_720p.mp4 (1280x720) [44.5 MB] || plot_ir4-northatlantic_map_720p.webm (1280x720) [1.8 MB] || ", "hits": 29 }, { "id": 4582, "url": "https://svs.gsfc.nasa.gov/4582/", "result_type": "Visualization", "release_date": "2017-07-27T18:00:00-04:00", "title": "Aerosol Optical Thickness Updating Forecast", "description": "The atmosphere is made up of gases like oxygen, nitrogen, and water vapor, but it also contains tiny particles called aerosols. Aerosols come from both natural and human sources and include things like sea salt, dust, soot, and sulfates. Aerosols often contribute to air pollution and poor visibility. Once they are in the atmosphere, they can travel long distances, affecting air quality far from their source. Aerosols also absorb or reflect energy (light), influencing temperatures in the atmosphere and on the ground. Satellites measure aerosols by how much light can pass through them. A thick layer of aerosols will block the ground from view, while a thin layer allows enough light through to see the ground. The measurement is called aerosol optical thickness.The GEOS model is built on satellite data and provides a forecast of aerosol optical thickness (among other things). This animation shows a daily updated 10-day forecast of aerosol optical thickness from GEOS. The date and timestamp are in the lower left corner. In general, brighter colors are thick aerosols, while dull darker colors are thin aerosols. Blue represents sea salt (sea salt extinction aerosol optical thickness, 550 nm). Winds blowing across the ocean kicks up ocean spray, which includes sea salt. In the animation, pale blue to white colors reflect stormy conditions. Individual large storms like tropical cyclones (hurricanes, typhoons) are visible as swirling circles of thick sea salt. Red represents dust (dust extinction aerosol optical thickness, 550 nm). The Saharan Desert of northern Africa is the largest source of dust, but dust can be seen across the globe. Saharan dust often interacts with tropical cyclones.Green represents the sum of aerosol optical thickness for organic carbon, black carbon, and sulfate. Organic and black carbon come from burning biomass or fossil fuels. Sources include fires, power plants, vehicles, and other combustion engines that run on fossil fuel. Sulfate particles come mostly from burning fossil fuels, but also from volcanoes. || gmao_aerosols_print.jpg (1024x576) [201.6 KB] || gmao_aerosols_searchweb.png (320x180) [108.3 KB] || gmao_aerosols.00001_thm.png (80x40) [7.0 KB] || gmao_aerosols.mp4 (1920x962) [16.2 MB] || gmao_aerosols.webm (1920x962) [1.5 MB] || latest-wdates (2239x1123) [0 Item(s)] || latest-nodates (2239x1123) [0 Item(s)] || gmao_aerosols.mp4.hwshow [191 bytes] || ", "hits": 75 }, { "id": 4544, "url": "https://svs.gsfc.nasa.gov/4544/", "result_type": "Visualization", "release_date": "2017-05-26T10:30:00-04:00", "title": "2015-2016 El Niño: Daily Sea Surface Temperature Anomaly and Ocean Currents", "description": "This visualization shows 2015-2016 El Nino through changes in sea surface temperature and ocean currents. Blue regions represent colder temperatures and red regions represent warmer temperatures when compared with normal conditions. Yellow arrows illustrate eastward currents and white arrows are westward currents. || GMAO_elNino_oceanTemperatureAnomaly_currents__1300_print.jpg (1024x576) [175.5 KB] || GMAO_elNino_oceanTemperatureAnomaly_currents__1300_searchweb.png (320x180) [97.1 KB] || GMAO_elNino_oceanTemperatureAnomaly_currents__1300_thm.png (80x40) [6.7 KB] || GMAO_elNino_oceanTemperatureAnomaly_currents_1080p.webm (1920x1080) [163.5 KB] || with_colorbar (3840x2160) [256.0 KB] || GMAO_elNino_oceanTemperatureAnomaly_currents_1080p.mp4 (1920x1080) [159.4 MB] || GMAO_oceanTemperatureAnomaly_withColorbar.mp4 (3840x2160) [166.0 MB] || ", "hits": 91 }, { "id": 4565, "url": "https://svs.gsfc.nasa.gov/4565/", "result_type": "Visualization", "release_date": "2017-05-04T19:00:00-04:00", "title": "Seasonal Changes in Carbon Dioxide", "description": "Narrated visualization showing seasonal drawdown in carbon dioxideThis video is also available on our YouTube channel. || co2_science_comp.0740_print.jpg (1024x576) [118.8 KB] || co2_science_comp.0740_searchweb.png (180x320) [75.9 KB] || co2_science_comp.0740_thm.png (80x40) [6.1 KB] || CO2_Science_001_DDMMYY.m4v (1280x720) [66.6 MB] || CO2_Science_001_DDMMYY.webmhd.webm (1080x606) [17.7 MB] || CO2_Science_001_MM.m4v (1280x720) [66.5 MB] || comp (1920x1080) [0 Item(s)] || CO2_Science_001_DDMMYY.mp4 (1920x1080) [147.8 MB] || CO2_Science_001_MM.mp4 (1920x1080) [147.9 MB] || CO2_Science.en_US.srt [1.7 KB] || CO2_Science.en_US.vtt [1.7 KB] || CO2_Science_001_DDMMYY.mov (1920x1080) [1.1 GB] || CO2_Science_001_MM.mov (1920x1080) [1.1 GB] || ", "hits": 557 }, { "id": 4514, "url": "https://svs.gsfc.nasa.gov/4514/", "result_type": "Visualization", "release_date": "2016-12-13T14:00:00-05:00", "title": "Carbon Dioxide from GMAO using Assimilated OCO-2 Data", "description": "Carbon Dioxide from the GEOS-5 modelThis video is also available on our YouTube channel. || co2_30.with_labels.2000_print.jpg (1024x576) [90.1 KB] || co2_30.with_labels.2000_searchweb.png (180x320) [64.0 KB] || co2_30.with_labels.2000_thm.png (80x40) [5.9 KB] || co2_30.with_labels_1080p30.mp4 (1920x1080) [75.6 MB] || co2_30.with_labels_1080p30.webm (1920x1080) [11.3 MB] || co2_30.with_labels_360p30.mp4 (640x360) [12.2 MB] || final_no_dates (3840x2160) [0 Item(s)] || final_with_labels (3840x2160) [0 Item(s)] || co2_30.with_labels.key [77.8 MB] || co2_30.with_labels.pptx [77.4 MB] || co2_30.with_labels_2160p30.mp4 (3840x2160) [306.7 MB] || co2_30.with_labels_1080p30.mp4.hwshow [192 bytes] || ", "hits": 84 }, { "id": 12370, "url": "https://svs.gsfc.nasa.gov/12370/", "result_type": "Produced Video", "release_date": "2016-09-13T11:00:00-04:00", "title": "Return To Normal in 2016, After Strong El Niño in 2015", "description": "Scientists at the Global Modeling and Assimilation Office of NASA's Goddard Space Flight Center regulary produce a forecast of sea surface temperatures in the equatorial Pacific ocean. The temperatures in this area are used to determine the conditions known as El Niño and La Niña. For several months, the NASA forecast has indicated the temperatures will be neutral over the next nine months. This indicates there will be no La Niña in 2016-2017, after the previous year's very strong El Niño.Music: Find The Answer, by Klangraum. Composers: Bernhard Hering [GEMA], Matthias Kruger [GEMA]Complete transcript available. || 12370_La_Nada_2016_MASTER_large.00090_print.jpg (1024x576) [106.7 KB] || 12370_La_Nada_2016_MASTER_large.00090_searchweb.png (320x180) [66.2 KB] || 12370_La_Nada_2016_MASTER_large.00090_thm.png (80x40) [5.0 KB] || 12370_La_Nada_2016_MASTER_V2_prores.mov (1280x720) [970.6 MB] || 12370_La_Nada_2016_MASTER_V2_youtube_hq.mov (1280x720) [196.0 MB] || 12370_La_Nada_2016_MASTER_V2_large.mp4 (1280x720) [70.8 MB] || 12370_La_Nada_2016_MASTER_V2_appletv.m4v (1280x720) [33.1 MB] || 12370_La_Nada_2016_MASTER_V2_appletv_subtitles.m4v (1280x720) [33.1 MB] || 12370_La_Nada_2016-captions.en_US.srt [970 bytes] || 12370_La_Nada_2016-captions.en_US.vtt [983 bytes] || 12370_La_Nada_2016_MASTER_V2_ipod_sm.mp4 (320x240) [11.2 MB] || 12370_La_Nada_2016_MASTER_V2_prores.webm [0 bytes] || ", "hits": 55 }, { "id": 12206, "url": "https://svs.gsfc.nasa.gov/12206/", "result_type": "Produced Video", "release_date": "2016-05-25T00:00:00-04:00", "title": "Hurricane Forecasts Rely on Modeling the Past", "description": "Complete transcript available.Music: Chris White, Afterglow || 12206_Hurricanes_youtube.00229_print.jpg (1024x576) [119.1 KB] || 12206_Hurricanes_youtube.00229_searchweb.png (180x320) [87.4 KB] || 12206_Hurricanes_youtube.00229_thm.png (80x40) [6.6 KB] || 12206_Hurricane_modeling_MASTER.webm (960x540) [72.0 MB] || Hurricane_modeling.webm (1080x606) [34.9 MB] || 12206_Hurricanes_youtube.mp4 (1920x1080) [190.4 MB] || 12206_Hurricane_modeling_MASTER.mpeg (1280x720) [610.1 MB] || 12206_Hurricanes.en_US.srt [3.8 KB] || 12206_Hurricanes.en_US.vtt [3.8 KB] || 12206_Hurricane_modeling_MASTER_ipod_sm.mp4 (320x240) [32.3 MB] || Hurricane_modeling_prores.mov (1920x1080) [2.5 GB] || ", "hits": 44 }, { "id": 4433, "url": "https://svs.gsfc.nasa.gov/4433/", "result_type": "Visualization", "release_date": "2016-02-25T20:00:00-05:00", "title": "El Niño: GMAO Daily Sea Surface Temperature Anomaly from 1997/1998 and 2015/2016", "description": "This visualization shows how the Sea Surface Temperature Anomaly (SSTA) data and subsurface Temperature Anomaly from the 1997 El Nino year compares to the 2015 El Nino year. The visualization shows how the 1997 event started from colder-than-average sea surface temperatures – but the 2015 event started with warmer-than-average temperatures not only in the Pacific but also in in the Atlantic and Indian Oceans.This video is also available on our YouTube channel. || SSTcompare1997_2015_0000_print.jpg (1024x576) [87.4 KB] || SSTcompare1997_2015_0000_searchweb.png (320x180) [53.0 KB] || SSTcompare1997_2015_0000_thm.png (80x40) [5.6 KB] || Compare1997_2015_SSTA.mp4 (1920x1080) [28.7 MB] || compare (1920x1080) [0 Item(s)] || Compare1997_2015_SSTA.webm (1920x1080) [1.5 MB] || Compare1997_2015_SSTA.m4v (640x360) [2.5 MB] || Compare1997_2015_SSTA.mp4.hwshow [187 bytes] || ", "hits": 120 }, { "id": 30590, "url": "https://svs.gsfc.nasa.gov/30590/", "result_type": "Hyperwall Visual", "release_date": "2015-05-07T10:00:00-04:00", "title": "From Observations to Models", "description": "NASA’s Global Modeling and Assimilation Office (GMAO) uses the Goddard Earth Observing System Model, Version 5 Data Assimilation System (GEOS­-5 DAS) to produce global numerical weather forecasts on a routine basis. GMAO forecasts play important roles in managing NASA’s fleet of science satellites and in researching the impact of new satellite observations. In order to provide timely information about the state of the atmosphere for NASA instrument teams and researchers, the GMAO runs the GEOS-­5 DAS four times each day in real time. For each forecast, it is necessary to provide accurate initial conditions that drive the GEOS-­5 forecasts. To do this, the best estimate of the full, three-dimensional atmospheric state is determined by combining the latest observations and a short-term, 6-­hour forecast—a process known as data assimilation. The GEOS-­5 DAS assimilates more than 5 million observations during each 6-hour assimilation period.These observations are assembled from a number of sources from around the globe, including NASA, NOAA, EUMETSAT (European Organization for the Exploitation of Meteorological Satellites), commercial airlines, the US Department of Defense, and many others. Similarly, each observation type has its own sampling characteristics. It can be seen in the animation how different observation types have different strategies. One of the main challenges of data assimilation is to understand how all these observations are alike, how they differ, and how they interact with each other.Funding for the development of the GEOS-5 model and data assimilation system development comes from NASA's Modeling, Analysis, and Prediction Program and the NASA Weather Focus Area's contribution to the Joint Center for Satellite Data Assimilation.The GEOS-5 DAS runs at the NASA Center for Climate Simulation, which is funded by NASA’s High-End Computing Program.For More Information:http://gmao.gsfc.nasa.gov/http://www.nccs.nasa.gov/images/data_assim_story_072815.pdf || ", "hits": 83 }, { "id": 10563, "url": "https://svs.gsfc.nasa.gov/10563/", "result_type": "Produced Video", "release_date": "2010-06-02T00:00:00-04:00", "title": "Supercomputing the Climate", "description": "Goddard Space Flight Center is the home of a state-of-the-art supercomputing facility called the NASA Center for Climate Simulation (NCCS) that is capable of running highly complex models to help scientists better understand Earth's climate. || ", "hits": 106 }, { "id": 10568, "url": "https://svs.gsfc.nasa.gov/10568/", "result_type": "Produced Video", "release_date": "2010-06-02T00:00:00-04:00", "title": "NCCS Video Files", "description": "These three clips show highlights of the NASA Center for Climate Simulation (NCCS) at Goddard Space Flight Center. || ", "hits": 53 } ] }