{ "count": 113, "next": "https://svs.gsfc.nasa.gov/api/search/?keywords=surface+water&limit=100&offset=100", "previous": null, "results": [ { "id": 5565, "url": "https://svs.gsfc.nasa.gov/5565/", "result_type": "Visualization", "release_date": "2025-06-26T00:00:00-04:00", "title": "Water Cycle Extremes 2002-2024: Droughts and Pluvials", "description": "In a study of 20 years of data from the NASA/German GRACE and GRACE-FO satellites, NASA scientists confirmed that major droughts and pluvials — periods of excessive precipitation and water storage on the landscape — have been occurring more often. They also found that the worldwide intensity of these extreme wet and dry events – a metric that combines extent, duration, and severity — is closely linked to global warming.", "hits": 305 }, { "id": 5409, "url": "https://svs.gsfc.nasa.gov/5409/", "result_type": "Visualization", "release_date": "2024-10-17T00:00:00-04:00", "title": "Slow Reveal Graphs: Water Cycle Extremes", "description": "In a study of 20 years of data from the NASA/German GRACE and GRACE-FO satellites, NASA scientists confirmed that major droughts and pluvials — periods of excessive precipitation and water storage on the landscape — have been occurring more often. They also found that the worldwide intensity of these extreme wet and dry events – a metric that combines extent, duration, and severity — is closely linked to global warming.", "hits": 38 }, { "id": 5392, "url": "https://svs.gsfc.nasa.gov/5392/", "result_type": "Visualization", "release_date": "2024-10-01T00:00:00-04:00", "title": "Water Cycle Extremes 2002-2023: Droughts and Pluvials", "description": "This visualization shows extremes of the water cycle — droughts and pluvials — over a twenty-year period (2002-2023) based on observations from the GRACE and GRACE-FO satellites. D. A total of 1,138 extreme wet and dry events are shown the visualization. The plots at the bottom of the figure show that the total intensity of extreme events increased as global temperatures increased. |", "hits": 136 }, { "id": 31247, "url": "https://svs.gsfc.nasa.gov/31247/", "result_type": "Hyperwall Visual", "release_date": "2023-09-27T00:00:00-04:00", "title": "SWOT Monitors Warming Waters Off California Coast \nFull Resolution", "description": "This data visualization image above shows sea surface heights off the northern California coast in August 2023 as measured by the Surface Water and Ocean Topography (SWOT) satellite. || SWOT_2023-08_ca_coast_PIA26091_print.jpg (1024x576) [81.4 KB] || SWOT_2023-08_ca_coast_PIA26091.png (3840x2160) [2.2 MB] || SWOT_2023-08_ca_coast_PIA26091_searchweb.png (320x180) [29.9 KB] || SWOT_2023-08_ca_coast_PIA26091_thm.png (80x40) [3.4 KB] || SWOT_2023-08_ca_coast_PIA26091.hwshow [109 bytes] || ", "hits": 51 }, { "id": 31240, "url": "https://svs.gsfc.nasa.gov/31240/", "result_type": "Hyperwall Visual", "release_date": "2023-09-15T00:00:00-04:00", "title": "SWOT Captures the Yukon River in Alaska", "description": "SWOT view of the Yukon River, August 30, 2023 || PIA25780_print.jpg (1024x576) [341.9 KB] || PIA25780.png (3840x2160) [11.4 MB] || PIA25780_searchweb.png (320x180) [99.9 KB] || PIA25780_thm.png (80x40) [6.6 KB] || swot-captures-the-yukon-river-in-alaska.hwshow [279 bytes] || ", "hits": 39 }, { "id": 31231, "url": "https://svs.gsfc.nasa.gov/31231/", "result_type": "Hyperwall Visual", "release_date": "2023-06-07T00:00:00-04:00", "title": "Monitoring California Groundwater", "description": "GRACE California Terrestrial Water Storage from 2002-04 to 2023-03. || grace_ca_water_black_v3_20230316_1200_print.jpg (1024x574) [149.5 KB] || grace_ca_water_black_v3_20230316_1200_searchweb.png (320x180) [66.6 KB] || grace_ca_water_black_v3_20230316_1200_thm.png (80x40) [12.5 KB] || grace_ca_water_2002-2023_seasonal_1080p.mp4 (1920x1080) [7.0 MB] || grace_ca_water_2002-2023_seasonal_1080p.webm (1920x1080) [4.2 MB] || grace_ca_water_2002-2023_seasonal_2160p.mp4 (3840x2160) [23.1 MB] || grace_ca_water_black_v3_20230316_1200.tif (4104x2304) [4.7 MB] || grace_ca_water_2002-2023 (4104x2304) [0 Item(s)] || grace_ca_water_2002-2023_seasonal_1080p.hwshow [112 bytes] || ", "hits": 51 }, { "id": 5087, "url": "https://svs.gsfc.nasa.gov/5087/", "result_type": "Visualization", "release_date": "2023-03-13T12:00:00-04:00", "title": "Water Cycle Extremes: Droughts and Pluvials", "description": "This visualization shows extremes of the water cycle — droughts and pluvials — over a twenty-year period (2002-2021) based on observations from the GRACE and GRACE-FO satellites. Dry events are shown as red spheres and wet events as blue spheres, with earlier years being shown as lighter shades and later years as darker shades. The volume of the sphere is proportional to the intensity of the event, a quantity measured in cubic kilometer months.", "hits": 119 }, { "id": 31212, "url": "https://svs.gsfc.nasa.gov/31212/", "result_type": "Hyperwall Visual", "release_date": "2022-12-28T00:00:00-05:00", "title": "Where There's Water...There's SWOT", "description": "SWOT launched at 3:46 a.m. PST on Friday Dec. 16, 2022, from Space Launch Complex 4E at Vandenberg Space Force Base in California || InternationalSWOTMissionLaunchesfromVandenbergSpaceForceBase.00001_print.jpg (1024x576) [83.6 KB] || InternationalSWOTMissionLaunchesfromVandenbergSpaceForceBase.00001_searchweb.png (320x180) [50.2 KB] || InternationalSWOTMissionLaunchesfromVandenbergSpaceForceBase.00001_thm.png (80x40) [5.0 KB] || InternationalSWOTMissionLaunchesfromVandenbergSpaceForceBase_1.mp4 (1920x1080) [77.0 MB] || InternationalSWOTMissionLaunchesfromVandenbergSpaceForceBase.webm (1920x1080) [13.3 MB] || where-theres-watertheres-swot-has-audio.hwshow [385 bytes] || ", "hits": 28 }, { "id": 31198, "url": "https://svs.gsfc.nasa.gov/31198/", "result_type": "Hyperwall Visual", "release_date": "2022-10-31T00:00:00-04:00", "title": "Surface Water and Ocean Topography (SWOT) for hyperwall", "description": "Images and videos prepared for hyperwall for SWOT. || SWOT title slide || SWOT_title_print.jpg (1024x576) [403.1 KB] || SWOT_title.jpg (5760x3240) [9.0 MB] || SWOT_title_searchweb.png (320x180) [86.2 KB] || SWOT_title_thm.png (80x40) [6.9 KB] || SWOT_title.hwshow || ", "hits": 26 }, { "id": 5017, "url": "https://svs.gsfc.nasa.gov/5017/", "result_type": "Visualization", "release_date": "2022-08-26T00:00:00-04:00", "title": "A Decade of Sea Surface Salinity", "description": "This data visualization shows sea surface salinity (i.e., ocean salt concentration) over a ten year period (2011 to 2021). Warm colors (orange to yellow) are areas of high salinity/hot tropics. Cooler colors (blue to violet) are fresher waters, many of which can be seen coming from rainy/river/wetter tropics. || salinity_v48_8k.4653_print.jpg (1024x512) [132.1 KB] || salinity_v48_8k.4653_searchweb.png (180x320) [80.5 KB] || salinity_v48_8k.4653_thm.png (80x40) [6.6 KB] || salinity_v49_1000p30.mp4 (2000x1000) [56.3 MB] || 2000x1000_2x1_60p (2000x1000) [0 Item(s)] || salinity_v49_1000p30.webm (2000x1000) [14.5 MB] || salinity_v49_1000p60.mp4 (2000x1000) [31.9 MB] || 8000x4000_2x1_60p (8000x4000) [0 Item(s)] || salinity_v49_8k_2000p30_h265.mp4 (4000x2000) [88.0 MB] || ", "hits": 355 }, { "id": 5020, "url": "https://svs.gsfc.nasa.gov/5020/", "result_type": "Visualization", "release_date": "2022-08-24T00:00:00-04:00", "title": "Sea Surface Salinity Trend", "description": "This data visualization shows the areas where sea surface salinity has increased (depicted in red) and descreased (depicted in blue) over ten years (2011 to 2021). || trend_2k.png (2000x1000) [870.4 KB] || trend_8k.png (8000x4000) [12.8 MB] || trend_4k.png (4000x2000) [3.3 MB] || trend_8k_print.jpg (1024x512) [169.6 KB] || trend_8k_searchweb.png (320x180) [88.8 KB] || trend_8k_thm.png (80x40) [8.2 KB] || trend_2k.tif (2000x1000) [50.0 MB] || trend_8k.tif (8000x4000) [94.0 MB] || trend_4k.tif (4000x2000) [193.2 MB] || sea-surface-salinity-trend.hwshow [258 bytes] || ", "hits": 60 }, { "id": 5014, "url": "https://svs.gsfc.nasa.gov/5014/", "result_type": "Visualization", "release_date": "2022-08-17T00:00:00-04:00", "title": "Drought in the Horn of Africa", "description": "According to a July 29 2022 report from the International Food Security and Nutrition Working Group, the worst drought conditions in 70 years across the Horn of Africa have more than 16 million people coping with a shortage of drinking water. Yields of key crops are down for the third year in a row, milk production is in decline, and more than 9 million livestock animals have been lost due to a lack of water and suitable forage land. At the same time, regional conflicts, COVID-19, locusts, and the Ukraine War have caused price spikes and shortages of basic commodities. An estimated 18 to 21 million people now \"face high levels of acute food insecurity\" in Ethiopia, Kenya, and Somalia.These animations depict root zone and surface soil moisture observations and forecasts from the NASA Hydrological Forecast and Analysis System (NHyFAS). Reds depict areas with soil moisture percentages below the average, while blues reflect areas that are above average (often due to passing storms). The first 27 seconds of the animation show soil moisture from August 2020 through June 2022. The final 10 seconds show forecasts for July through December 2022, including the next rainy season. Root zone moisture is critical for long term crop growth. New seedlings are mostly dependent on surface water, but then as plants grow and sink deeper roots, they are sustained by moisture in the top layer of the soil. || ", "hits": 151 }, { "id": 14094, "url": "https://svs.gsfc.nasa.gov/14094/", "result_type": "Produced Video", "release_date": "2022-02-09T00:00:00-05:00", "title": "NASA Earth Valentines", "description": "We've got that look of love! Earth-observing satellites and astronauts capture our planet’s beauty every day. Share a Valentine with the one you can’t keep your eyes off of, inspired by some of our NASA missions. || ", "hits": 41 }, { "id": 14066, "url": "https://svs.gsfc.nasa.gov/14066/", "result_type": "Produced Video", "release_date": "2022-01-13T11:00:00-05:00", "title": "Temperature Record 101: How We Know What We Know", "description": "2021 was tied for the sixth warmest year on NASA’s record, stretching more than a century. But, what is a temperature record?GISTEMP, NASA’s global temperature analysis, takes in millions of observations from instruments on weather stations, ships and ocean buoys, and Antarctic research stations, to determine how much warmer or cooler Earth is on average from year to year.Stretching back to 1880, NASA’s record shows a clear warming trend. However, individual weather events and La Niña — a pattern of cooler waters in the Pacific that was responsible for slightly cooling 2021’s average temperature — can affect individual years.Because the record is global, not every place on Earth experienced the sixth warmest year on record. Some places had record-high temperatures, and we saw record droughts, floods and fires around the globe. || ", "hits": 105 }, { "id": 14043, "url": "https://svs.gsfc.nasa.gov/14043/", "result_type": "Produced Video", "release_date": "2021-12-13T14:00:00-05:00", "title": "Tour 2022: NASA's Upcoming Earth Missions", "description": "NASA has a unique view of our planet from space. NASA’s fleet of Earth-observing satellites provide high quality data on different parts of Earth’s interconnected environment from air quality to sea ice. Take a tour of missions launching in 2022, including SWOT, TROPICS, EMIT, and JPSS-2. || ", "hits": 61 }, { "id": 13842, "url": "https://svs.gsfc.nasa.gov/13842/", "result_type": "Produced Video", "release_date": "2021-04-21T13:00:00-04:00", "title": "NASA Explores Earth’s Connections", "description": "Complete transcript available. || EarthDay2021Connectionsv1080.00750_print.jpg (1024x576) [126.5 KB] || EarthDay2021Connectionsv1080.00750_searchweb.png (320x180) [61.3 KB] || EarthDay2021Connectionsv1080.00750_web.png (320x180) [61.3 KB] || EarthDay2021Connectionsv1080.00750_thm.png (80x40) [5.9 KB] || EarthDay2021Connectionsv1080.mp4 (1920x1080) [426.0 MB] || EarthDay2021Connectionsv1080.webm (1920x1080) [34.3 MB] || EarthDay2021ConnectionsFinal.mp4 (3840x2160) [426.2 MB] || EarthDay2021ConnectionsFinal.en_US.srt [5.0 KB] || EarthDay2021ConnectionsFinal.en_US.vtt [5.0 KB] || ", "hits": 65 }, { "id": 4826, "url": "https://svs.gsfc.nasa.gov/4826/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Brazil and Novo Progresso Land Use Data Over Time", "description": "This animation begins by showing the similar sizes between the country of Brazil and the United States. It then cycles through over three decades of classification data for the entire Northern half of Brazil. We then zoom down to the town of Novo Progresso and compare its relative size to the San Francisco Bay region. Next we cycle through over three decades of transformation in the region showing how the north/south corridor of this region changed over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || novo_progressov_finalcomp.2009_print.jpg (1024x576) [287.1 KB] || novo_progressov_finalcomp.2009_searchweb.png (180x320) [105.7 KB] || novo_progressov_finalcomp.2009_thm.png (80x40) [7.3 KB] || novo_progressov_finalcomp_1080p30.mp4 (1920x1080) [48.9 MB] || example_composite (1920x1080) [0 Item(s)] || novo_progressov_finalcomp_1080p30.webm (1920x1080) [7.9 MB] || novo_progressov_finalcomp_1080p30.mp4.hwshow [199 bytes] || ", "hits": 66 }, { "id": 4827, "url": "https://svs.gsfc.nasa.gov/4827/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Novo Progresso Surrounding Region Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Novo Progresso and compare its relative size to the San Francisco Bay region. Next we cycle through over three decades of transformation in the region showing how the north/south corridor of this area opened up over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || novo_wide_finalcomp.2009_print.jpg (1024x576) [387.4 KB] || novo_wide_finalcomp.1116_print.jpg (1024x576) [221.0 KB] || novo_wide_finalcomp_1080p30_2.mp4 (1920x1080) [30.2 MB] || novo_wide_finalcomp_1080p30_2.webm (1920x1080) [3.7 MB] || Example_Composite (1920x1080) [0 Item(s)] || novo_wide_finalcomp_1080p30_2.mp4.hwshow [195 bytes] || ", "hits": 47 }, { "id": 4828, "url": "https://svs.gsfc.nasa.gov/4828/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Colider Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Colider and compares its relative size to Northern California. Next we cycle through over three decades of land use transformation showing cropland a pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || colider_finalcomp.2009_print.jpg (1024x576) [548.1 KB] || colider_finalcomp.2009_searchweb.png (320x180) [144.4 KB] || colider_finalcomp.2009_thm.png (80x40) [8.4 KB] || colider_finalcomp_1080p30.mp4 (1920x1080) [40.2 MB] || colider_finalcomp_1080p30.webm (1920x1080) [4.0 MB] || Example_Composite (1920x1080) [0 Item(s)] || colider_finalcomp_1080p30.mp4.hwshow [191 bytes] || ", "hits": 43 }, { "id": 4829, "url": "https://svs.gsfc.nasa.gov/4829/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Ji-Paraná Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Ji Parana and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing cropland a pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || ji_parana_finalcomp.2009_print.jpg (1024x576) [412.8 KB] || ji_parana_finalcomp.2009_searchweb.png (320x180) [133.8 KB] || ji_parana_finalcomp.2009_thm.png (80x40) [8.2 KB] || ji_parana_finalcomp_1080p30.mp4 (1920x1080) [34.0 MB] || Example_Composite (1920x1080) [0 Item(s)] || ji_parana_finalcomp_1080p30.webm (1920x1080) [3.8 MB] || ji_parana_finalcomp_1080p30.mp4.hwshow [193 bytes] || ", "hits": 54 }, { "id": 4830, "url": "https://svs.gsfc.nasa.gov/4830/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Rio Branco Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region surrounding the town of Rio Branco and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || rio_branco_finalcomp.2009_print.jpg (1024x576) [331.8 KB] || rio_branco_finalcomp.2009_searchweb.png (320x180) [108.8 KB] || rio_branco_finalcomp.2009_thm.png (80x40) [7.4 KB] || rio_branco_finalcomp_1080p30.mp4 (1920x1080) [24.0 MB] || rio_branco_finalcomp_1080p30.webm (1920x1080) [3.4 MB] || Example_Composite (1920x1080) [0 Item(s)] || rio_branco_finalcomp_1080p30.mp4.hwshow [194 bytes] || ", "hits": 42 }, { "id": 4831, "url": "https://svs.gsfc.nasa.gov/4831/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Uatumã Biological Reserve Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the Uatumã Biological Reserve and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation to show the lake formation over time as well as the increased pasture and croplands to the west of the lake. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || dam_finalcomp.2009_print.jpg (1024x576) [216.7 KB] || dam_finalcomp.2009_searchweb.png (320x180) [80.9 KB] || dam_finalcomp.2009_thm.png (80x40) [5.9 KB] || dam_finalcomp_1080p30.mp4 (1920x1080) [22.1 MB] || Example_Composite (1920x1080) [0 Item(s)] || dam_finalcomp_1080p30.webm (1920x1080) [3.3 MB] || dam_finalcomp_1080p30.mp4.hwshow [187 bytes] || ", "hits": 43 }, { "id": 4832, "url": "https://svs.gsfc.nasa.gov/4832/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Itaituba and Uruara Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. It then zooms down to the region between Itaituba and Uruara and compares its relative size to the San Francisco Bay area. Next we cycle through over three decades of land use transformation showing pasture expansion over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || ruropolis_finalcomp.2009_print.jpg (1024x576) [345.6 KB] || ruropolis_finalcomp.2009_searchweb.png (320x180) [116.9 KB] || ruropolis_finalcomp.2009_thm.png (80x40) [7.6 KB] || ruropolis_finalcomp_1080p30.mp4 (1920x1080) [29.5 MB] || Sample_Composite (1920x1080) [0 Item(s)] || ruropolis_finalcomp_1080p30.webm (1920x1080) [3.5 MB] || ruropolis_finalcomp_1080p30.mp4.hwshow [193 bytes] || ", "hits": 39 }, { "id": 4833, "url": "https://svs.gsfc.nasa.gov/4833/", "result_type": "Visualization", "release_date": "2021-04-19T12:00:00-04:00", "title": "Northern Brazil Land Use Data Over Time", "description": "This data visualization begins with a wide view of Northern Brazil. While zooming in a little closer an image of the United States fades in to get the relative size of the region. Next we cycle through over three decades of transformation in the region showing land use change over time. Lastly, we fade in 2019 fire data to indicate how the data will continue to change into the upcoming year. || brazil_wide_finalcomp.2009_print.jpg (1024x576) [451.8 KB] || brazil_wide_finalcomp.2009_searchweb.png (320x180) [128.6 KB] || brazil_wide_finalcomp.2009_thm.png (80x40) [8.1 KB] || brazil_wide_finalcomp_1080p30.mp4 (1920x1080) [31.3 MB] || Sample_Composite (1920x1080) [0 Item(s)] || brazil_wide_finalcomp_1080p30.webm (1920x1080) [3.8 MB] || brazil_wide_finalcomp_1080p30.mp4.hwshow [195 bytes] || ", "hits": 68 }, { "id": 4900, "url": "https://svs.gsfc.nasa.gov/4900/", "result_type": "Visualization", "release_date": "2021-04-19T00:00:00-04:00", "title": "Novo Progresso Deforestation Soccer Field Comparison", "description": "Animation begins with a stylized bright green soccer field. Soccer fields then fall into place over a recently deforested field showing the estimated size of the newly cleared field. The camera then pulls back to reveal all the recently deforested areas (shown in bright green) around Novo Progresso from 2017 to 2018. || soccer_comp.0700_print.jpg (1024x576) [161.5 KB] || soccer_comp.0700_searchweb.png (320x180) [85.8 KB] || soccer_comp.0700_thm.png (80x40) [14.1 KB] || soccer_2017_2018_1080p30.mp4 (1920x1080) [28.6 MB] || 2017_to_2018 (1920x1080) [0 Item(s)] || soccer_2017_2018_1080p30.webm (1920x1080) [5.7 MB] || soccer_2017_2018_1080p30.mp4.hwshow [190 bytes] || ", "hits": 59 }, { "id": 13824, "url": "https://svs.gsfc.nasa.gov/13824/", "result_type": "Produced Video", "release_date": "2021-03-03T09:00:00-05:00", "title": "NASA Satellite Measures the Human Impact in Water Storage", "description": "Music: \"Cycle of the Moon,\" \"Domestic Idyll,\" Universal Production MusicComplete transcript available.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 is obtained through permission and may not be excised or remixed in other products. Specific details on stock footage may be found here. For more information on NASA’s media guidelines, visit https://www.nasa.gov/multimedia/guidelines/index.html.Notes on footage:0:27-0:33; 0:57-1:06; 2:00-2:05; 2:14-2:45 provided by pond5. || reservoirthumb_print.jpg (1024x555) [244.0 KB] || reservoirthumb.png (3152x1710) [8.9 MB] || reservoirthumb_searchweb.png (320x180) [131.1 KB] || reservoirthumb_thm.png (80x40) [11.3 KB] || Reservoirs_prores.mov (1920x1080) [4.2 GB] || Reservoirs_3-2-v2.mp4 (1920x1080) [202.9 MB] || Reservoirs_prores.webm (1920x1080) [22.0 MB] || Reservoirs.en_US.srt [3.9 KB] || Reservoirs.en_US.vtt [3.9 KB] || ", "hits": 48 }, { "id": 13765, "url": "https://svs.gsfc.nasa.gov/13765/", "result_type": "Produced Video", "release_date": "2020-11-05T12:00:00-05:00", "title": "High Tide Flooding", "description": "Complete transcript available. || SLR_2020_High_Tide_Flooding_Final_1080.02397_print.jpg (1024x576) [140.1 KB] || SLR_2020_High_Tide_Flooding_Final_1080.02397_web.png (320x180) [86.8 KB] || SLR_2020_High_Tide_Flooding_Final_1080.02397_thm.png (80x40) [6.1 KB] || SLR_2020_High_Tide_Flooding_Final_1080.02397_searchweb.png (320x180) [86.8 KB] || SLR_2020_High_Tide_Flooding_Final_1080.mp4 (1920x1080) [670.8 MB] || SLR_2020_High_Tide_Flooding_Final_1080.webm (1920x1080) [57.4 MB] || SLR_2020_High_Tide_Flooding_Final.mp4 (3840x2160) [2.0 GB] || high_tide_flooding_12.en_US.srt [10.0 KB] || high_tide_flooding_12.en_US.vtt [10.0 KB] || ", "hits": 35 }, { "id": 4834, "url": "https://svs.gsfc.nasa.gov/4834/", "result_type": "Visualization", "release_date": "2020-08-31T11:00:00-04:00", "title": "First Global Survey of Glacial Lakes Shows 30-Years of Dramatic Growth", "description": "Data visualization featuring the glacier rich region of the Himalayas, along with many of Earth’s highest peaks. The visualization sequence starts with a wide view of the Tibetan plateau and moves along a hiking path highlighting Mt. Everest, Mt. Lhotse, Mt Nuptse, the Everest Base Camp, the Khumbhu glacier, all the way to Imja Lake. Moving to a top-down view of Imja Lake, a time series of Landsat data unveils its dramatic growth for the period 1989-2019.This video is also available on our YouTube channel. || imja_final_4k.4600_print.jpg (1024x576) [114.8 KB] || imja_final_4k.4600_searchweb.png (320x180) [101.5 KB] || imja_final_4k.4600_web.png (320x180) [101.5 KB] || imja_final_4k.4600_thm.png (80x40) [7.5 KB] || imja_final_HD_1080p60.mp4 (1920x1080) [72.9 MB] || 1920x1080_16x9_60p (1920x1080) [0 Item(s)] || imja_final_HD_1080p60.webm (1920x1080) [19.7 MB] || with_cities (3840x2160) [0 Item(s)] || captions_silent.30013.en_US.srt [43 bytes] || imja_final_4k_2160p60.mp4 (3840x2160) [215.1 MB] || imja_final_2160p60_prores.mov (3840x2160) [16.9 GB] || ", "hits": 108 }, { "id": 4842, "url": "https://svs.gsfc.nasa.gov/4842/", "result_type": "Visualization", "release_date": "2020-07-28T00:00:00-04:00", "title": "GPM observes Tropical Storm Cristobal drenching Louisiana and Mississippi", "description": "This data visualization shows Tropical Storm Cristobal on June 8th, 2020 after it had already made landfall and began moving northward up Louisiana and Alabama into Arkansas. GPM's GMI and DPR then sweep in to reveal the detailed surface precipitation and storm structure. || cam_cristobal_finalShape.4300_print.jpg (1024x576) [221.9 KB] || cam_cristobal_finalShape.4300_searchweb.png (320x180) [107.7 KB] || cam_cristobal_finalShape.4300_thm.png (80x40) [8.1 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || cam_cristobal_finalShape.webm (1920x1080) [10.5 MB] || cam_cristobal_finalShape.mp4 (1920x1080) [106.6 MB] || cam_cristobal_finalShape.mp4.hwshow [190 bytes] || ", "hits": 40 }, { "id": 4812, "url": "https://svs.gsfc.nasa.gov/4812/", "result_type": "Visualization", "release_date": "2020-04-09T00:00:00-04:00", "title": "GPM observes Cyclone Harold in the South Pacific", "description": "View of 3D precipitation from DPR and surface rain rates (mm/hr) from GMI of Cyclone Harold in the South Pacific on April 6 2020. The camera pushes in as a cutting plan reveals the inner precipitation rates of the storm. This video is also available on our YouTube channel. || harold_05.2400_print.jpg (1024x576) [159.2 KB] || harold_05.2400_searchweb.png (320x180) [121.3 KB] || harold_05.2400_thm.png (80x40) [8.9 KB] || harold (1920x1080) [0 Item(s)] || harold_05_1080p30.mp4 (1920x1080) [59.7 MB] || harold_05_1080p30.webm (1920x1080) [5.9 MB] || captions_silent.29226.en_US.srt [43 bytes] || harold_05_1080p30.mp4.hwshow [183 bytes] || ", "hits": 46 }, { "id": 13574, "url": "https://svs.gsfc.nasa.gov/13574/", "result_type": "Produced Video", "release_date": "2020-03-31T11:00:00-04:00", "title": "Global Maps of Dryness Help Prepare for Water Use around the Globe", "description": "Music: Lines of Enquiry by Theo Golding [PRS]Complete transcript available. || Still.png (1673x941) [936.4 KB] || Still_print.jpg (1024x575) [73.9 KB] || Still_searchweb.png (320x180) [44.5 KB] || Still_thm.png (80x40) [4.8 KB] || YOUTUBE_1080_13574_GRACEDryness_VX-1020457_youtube_1080.webm (1920x1080) [24.5 MB] || YOUTUBE_1080_13574_GRACEDryness_VX-1020457_youtube_1080.mp4 (1920x1080) [287.7 MB] || GRACEDryness.en_US.srt [4.4 KB] || GRACEDryness.en_US.vtt [4.4 KB] || ", "hits": 37 }, { "id": 4753, "url": "https://svs.gsfc.nasa.gov/4753/", "result_type": "Visualization", "release_date": "2019-09-06T09:00:00-04:00", "title": "GPM observes Hurricane Dorian lashing Florida", "description": "Snapshot view of 3D precipitation from DPR and surface rain rates (mm/hr) from GMI at 10:41 UTC (6:41 am EDT) 4 September 2019 when the center of Dorian was near the coast of central Florida about 90 miles due east of Daytona Beach.This video is also available on our YouTube channel. || dorian2__cam_dorianShape2_beauty.4300_print.jpg (1024x576) [187.7 KB] || dorian2__cam_dorianShape2_beauty.4300_searchweb.png (320x180) [116.1 KB] || dorian2__cam_dorianShape2_beauty.4300_thm.png (80x40) [8.3 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || dorian2__cam_dorianShape2_beauty.webm (1920x1080) [6.8 MB] || dorian2__cam_dorianShape2_beauty.mp4 (1920x1080) [123.3 MB] || captions_silent.27948.en_US.srt [43 bytes] || dorian2__cam_dorianShape2_beauty.mp4.hwshow [276 bytes] || ", "hits": 79 }, { "id": 4751, "url": "https://svs.gsfc.nasa.gov/4751/", "result_type": "Visualization", "release_date": "2019-09-03T00:00:00-04:00", "title": "GPM observes Hurricane Dorian over the Bahamas", "description": "Hurricane Dorian on September 1, 2019 (21:22 UTC) over Abaco Island in The BahamasThis video is also available on our YouTube channel. || dorian_08.2400_print.jpg (1024x576) [144.6 KB] || dorian_08.2400_searchweb.png (320x180) [121.2 KB] || dorian_08.2400_thm.png (80x40) [8.7 KB] || dorian (1920x1080) [0 Item(s)] || dorian_1080p30.mp4 (1920x1080) [72.2 MB] || dorian_1080p30.webm (1920x1080) [5.2 MB] || captions_silent.27911.en_US.srt [43 bytes] || dorian_1080p30.mp4.hwshow [180 bytes] || ", "hits": 96 }, { "id": 4740, "url": "https://svs.gsfc.nasa.gov/4740/", "result_type": "Visualization", "release_date": "2019-07-25T10:00:00-04:00", "title": "GPM observes Washington DC flooding", "description": "Animation that begins by showing IMERG precipitation across the eastern United States. GPM's DPR and GPROF data then wipe in. The camera then zooms into the Washington DC region to take a closer look at the precipitation centered over the DC area as the interior structure of the event is revealed. || dc_storm_HD.3600_print.jpg (1024x576) [140.6 KB] || dc_storm_HD.3600_searchweb.png (320x180) [99.3 KB] || dc_storm_HD.3600_thm.png (80x40) [7.1 KB] || dc_storm_HD_1080p30.mp4 (1920x1080) [67.8 MB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || dc_storm_HD_1080p30.webm (1920x1080) [5.4 MB] || 5760x3240_16x9_30p (5760x3240) [0 Item(s)] || dc_storm_HD_1080p30.mp4.hwshow [185 bytes] || ", "hits": 17 }, { "id": 13227, "url": "https://svs.gsfc.nasa.gov/13227/", "result_type": "Produced Video", "release_date": "2019-06-12T11:00:00-04:00", "title": "NASA Follows Changing Freshwater from Space", "description": "When we look into the vastness of space, our home planet stands out in many ways. One of the most crucial is the presence of abundant, accessible freshwater -- as a liquid, solid and gas. Water helps make our planet habitable. The first question NASA researchers studying freshwater on Earth ask is: Where is the water? As it constantly cycles between water vapor, rain and snow, and reservoirs above and below ground, water is tracked by a fleet of NASA satellites. Heat travels with that water, as energy from the Sun drives freshwater’s transformations between vapor, liquid water, and ice. As our planet warms due to greenhouse gases, scientists have a second pressing question: How is climate change affecting the distribution of water? || ", "hits": 68 }, { "id": 13216, "url": "https://svs.gsfc.nasa.gov/13216/", "result_type": "Produced Video", "release_date": "2019-06-03T12:00:00-04:00", "title": "NASA Has Eyes On The Atlantic Hurricane Season", "description": "NASA has a unique and important view of hurricanes around the planet. Satellites and aircraft watch as storms form, travel across the ocean and sometimes, make landfall. After the hurricanes have passed, the satellites and aircraft see the aftermath of hurricanes, from downed forests to mass power loss. || ", "hits": 67 }, { "id": 31033, "url": "https://svs.gsfc.nasa.gov/31033/", "result_type": "Hyperwall Visual", "release_date": "2019-04-22T00:00:00-04:00", "title": "Australia's Disappearing Lakes", "description": "Landsat imagery from 2017, 2018, and 2019 shows water level changes in Lake Menindee || lake_menindee_2019_print.jpg (1024x576) [195.6 KB] || lake_menindee_2019_searchweb.png (320x180) [114.1 KB] || lake_menindee_2019_thm.png (80x40) [7.1 KB] || lake_menindee_1080p.mp4 (1920x1080) [4.4 MB] || lake_menindee_720p.mp4 (1280x720) [2.0 MB] || lake_menindee_720p.webm (1280x720) [564.9 KB] || lake_menindee_2160p.mp4 (3840x2160) [17.4 MB] || lake_menindee_2019.tif (3840x2160) [23.7 MB] || lake_menindee.hwshow [81 bytes] || lake_menindee_1080p.hwshow [81 bytes] || ", "hits": 45 }, { "id": 4692, "url": "https://svs.gsfc.nasa.gov/4692/", "result_type": "Visualization", "release_date": "2018-10-11T00:00:00-04:00", "title": "Tropical Storm Michael Drenches the Carolinas", "description": "This data visualization shows Tropical Storm Michael over the Carolinas on October 11, 2018. Shades of green, yellow, and red are ground precipitation rates. Blue and purple indicate frozen precipitation. || michael3.4300_print.jpg (1024x576) [173.7 KB] || michael3.4300_searchweb.png (320x180) [123.0 KB] || michael3.4300_thm.png (80x40) [9.1 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || michael3.webm (1920x1080) [11.6 MB] || michael3.mp4 (1920x1080) [142.5 MB] || michael3.mp4.hwshow [174 bytes] || ", "hits": 36 }, { "id": 4687, "url": "https://svs.gsfc.nasa.gov/4687/", "result_type": "Visualization", "release_date": "2018-09-28T00:00:00-04:00", "title": "El Nino Fueled Rains Swamp South America", "description": "Since the middle of 2015, meteorologists have warned that El Niño could bring unusually wet weather to Paraguay, Uruguay, Argentina, and southern Brazil. The first image shows a view of this region before the flood and the second is after the December/January El Nino rains swamped this part of South America. || OneBeforeAfterFLoodSA-ArgentinaParaguay02.00001_print.jpg (1024x576) [252.4 KB] || OneBeforeAfterFLoodSA-ArgentinaParaguay02.00001_searchweb.png (320x180) [131.8 KB] || OneBeforeAfterFLoodSA-ArgentinaParaguay02.00001_thm.png (80x40) [7.7 KB] || OneBeforeAfterFLoodSA-ArgentinaParaguay02.mp4 (3840x2160) [71.7 MB] || ElNinoFlood (3240x3240) [0 Item(s)] || OneBeforeAfterFLoodSA-ArgentinaParaguay02.webm (3840x2160) [8.8 MB] || rioparaguay02.hwshow [207 bytes] || ", "hits": 85 }, { "id": 12932, "url": "https://svs.gsfc.nasa.gov/12932/", "result_type": "Produced Video", "release_date": "2018-06-08T14:00:00-04:00", "title": "Using Earth to Understand How Water May Have Affected Volcanoes on Mars", "description": "This scientific data visualization shows the evolution of the newly-erupted island in the Kingdom of Tonga. Results of this study can enhance our understanding of numerous small volcanic landforms on Mars whose formation may have been in shallow-water environments during epochs when persistent surface water was present.Learn more about the evolution of Earth's newest island and how it could reveal new infomration about the presence of water on Mars: Monitoring and Modeling the Rapid Evolution of EArth's Newest Volcanic Island: Hunga Tonga Hunga Ha'apai (Tonga) Using High Spatial Resolution Satellite Observations Authors: J.B. Garvin, D.A. Slayback, V. Ferrini, J. Frawley, C. Giguere, G.R. Asrar, K. AndersonPages: 3445-3452 l First Published: 26 March 2018- Volumetric erosion for new hydromagmatic island is approximately 0.0026km3/year- Demostrated first meter-scale documentation of landscapes and topography for a new volcanic island over its initial stages of evolution (approximately 3 years)- Satellite-based measurements of news island predict lifetime of up to approximately 42 years || ", "hits": 70 }, { "id": 12876, "url": "https://svs.gsfc.nasa.gov/12876/", "result_type": "Produced Video", "release_date": "2018-05-16T13:00:00-04:00", "title": "For 15 Years, GRACE Tracked Freshwater Movements Around the World", "description": "NASA scientists used GRACE data to identify regional trends of freshwater movement, and combined that information with data from other satellites, climate models and precipitation measurements to determine the causes of major regional trends in freshwater storage. || ", "hits": 49 }, { "id": 4587, "url": "https://svs.gsfc.nasa.gov/4587/", "result_type": "Visualization", "release_date": "2017-10-05T00:00:00-04:00", "title": "The Brown Ocean Effect", "description": "Before Tropical Storm Bill made landfall over Texas, eastern Texas experienced several days of rain that began flooding areas to the south east and northern parts of the state. As Tropical Storm Bill moved northward through Texas it is hypothesized that it fed off the highly saturated ground (as if it were still over the ocean) and can be seen slightly intensifying (via winds) as it moved into Oklahoma and progressed to the northeast. || brown_ocean_v3.1016_print.jpg (1024x576) [267.9 KB] || brown_ocean_v3.1016_searchweb.png (320x180) [127.0 KB] || brown_ocean_v3.1016_thm.png (80x40) [7.8 KB] || 1920x1080_16x9_30p (1920x1080) [0 Item(s)] || brown_ocean_v3.webm (1920x1080) [17.0 MB] || brown_ocean_v3.mp4 (1920x1080) [245.0 MB] || brown_ocean_v3.mp4.hwshow [180 bytes] || ", "hits": 124 }, { "id": 4585, "url": "https://svs.gsfc.nasa.gov/4585/", "result_type": "Visualization", "release_date": "2017-09-19T00:00:00-04:00", "title": "Hurricane Jose lingers in the Atlantic as Hurricane Maria approaches Puerto Rico", "description": "GPM passed over both Hurricane Maria and Hurricane Jose on September 18th, 2017. As the camera moves in on the Maria, DPR's volumetric view of the storm is revealed. A slicing plane moves across the volume to display precipitation rates throughout the storm. Shades of green to red represent liquid precipitation extending down to the ground. || JoseMaria_03.6000_print.jpg (576x1024) [192.4 KB] || JoseMaria_03.6000_searchweb.png (320x180) [112.5 KB] || JoseMaria_03.6000_thm.png (80x40) [7.7 KB] || JoseMaria_09-18 (1920x1080) [0 Item(s)] || JoseMaria_03_1080p30.webm (1920x1080) [4.8 MB] || JoseMaria_03_1080p30.mp4 (1920x1080) [81.8 MB] || JoseMaria_09-18 (3840x2160) [0 Item(s)] || JoseMaria_03_2160p30.mp4 (3840x2160) [232.0 MB] || JoseMaria_03_1080p30.mp4.hwshow [186 bytes] || ", "hits": 76 }, { "id": 4584, "url": "https://svs.gsfc.nasa.gov/4584/", "result_type": "Visualization", "release_date": "2017-09-10T12:00:00-04:00", "title": "GPM Examines Hurricane Irma", "description": "GPM scans Hurricane Irma on September 5th and again on September 7th as the storm approaches Puerto Rico, the Dominican Republic, and Haiti as a category 5 hurricane. This video is also available on our YouTube channel. || Irma_4k_with_dates.2670_print.jpg (1024x576) [158.4 KB] || Irma_4k_with_dates.2670_searchweb.png (320x180) [96.8 KB] || Irma_4k_with_dates.2670_thm.png (80x40) [7.6 KB] || irma_with_dates (1920x1080) [128.0 KB] || Irma_with_dates_1080p30.mp4 (1920x1080) [86.9 MB] || Irma_with_dates_1080p30.webm (1920x1080) [6.3 MB] || irma_with_dates (3840x2160) [128.0 KB] || Irma_4k_with_dates_2160p30.mp4 (3840x2160) [233.2 MB] || ", "hits": 71 }, { "id": 30895, "url": "https://svs.gsfc.nasa.gov/30895/", "result_type": "Hyperwall Visual", "release_date": "2017-09-08T00:00:00-04:00", "title": "Surface Flooding from Hurricane Harvey", "description": "Flooding around Houston, Tx after Hurricane Harvey || SMAP_Harvey_PIA21930_print.jpg (1024x574) [84.0 KB] || SMAP_Harvey_PIA21930.png (4104x2304) [1.9 MB] || SMAP_Harvey_PIA21930_searchweb.png (320x180) [59.1 KB] || SMAP_Harvey_PIA21930_thm.png (80x40) [6.0 KB] || SMAP_Harvey_PIA21930.hwshow [208 bytes] || ", "hits": 30 }, { "id": 4458, "url": "https://svs.gsfc.nasa.gov/4458/", "result_type": "Visualization", "release_date": "2017-08-31T17:00:00-04:00", "title": "Harvey Floods Texas and Threatens Louisiana (Final Tropical Storm Update)", "description": "GPM caught Tropical Storm Harvey twice on August 30th, 2017. This time the storm made landfall in Louisiana and moved up east of the Texas/Louisiana border pounding already drenched eastern Texas and western Louisiana with more rain. || harvey_v2.3400_print.jpg (1024x576) [163.6 KB] || harvey_v3.mp4 (1920x1080) [91.1 MB] || harvey_through_aug_30 (1920x1080) [128.0 KB] || harvey_v3.webm (1920x1080) [11.4 MB] || GSFC_20170830_GPM_m4458_Harvey.en_US.vtt [64 bytes] || harvey.mp4.hwshow [187 bytes] || ", "hits": 56 }, { "id": 12697, "url": "https://svs.gsfc.nasa.gov/12697/", "result_type": "Produced Video", "release_date": "2017-08-30T12:00:00-04:00", "title": "NASA Captures Hurricane Harvey's Rainfall", "description": "Music: \"Whirlpool,\" Michael Jan Levine, Killer Tracks || 4458_Hurricane_Harvey_final_large.00656_print.jpg (1024x576) [189.0 KB] || 4458_Hurricane_Harvey_final_large.00656_searchweb.png (320x180) [107.2 KB] || 4458_Hurricane_Harvey_final_large.00656_thm.png (80x40) [7.8 KB] || 12697_Hurricane_Harvey_MASTER.webm (960x540) [36.1 MB] || 12697_Hurricane_Harvey_MASTER_facebook_720.mp4 (1280x720) [95.2 MB] || 12697_Hurricane_Harvey_MASTER_youtube_1080.mp4 (1920x1080) [128.4 MB] || 12697_Hurricane_Harvey_prores.mov (1920x1080) [1.2 GB] || 12697_Harvey.en_US.srt [1.4 KB] || 12697_Harvey.en_US.vtt [1.4 KB] || ", "hits": 53 }, { "id": 12583, "url": "https://svs.gsfc.nasa.gov/12583/", "result_type": "Produced Video", "release_date": "2017-08-03T12:00:00-04:00", "title": "North American Monsoon", "description": "Music: \"Mesmerized Housewives,\" Donn WIlkersonComplete transcript available. || NAM_still_print.jpg (1024x578) [142.4 KB] || NAM_still_searchweb.png (320x180) [98.6 KB] || NAM_still_thm.png (80x40) [7.1 KB] || 12069_NAM_final_prores.mov (1920x1080) [2.7 GB] || 12069_NAM_final_1.mp4 (1920x1080) [160.4 MB] || 12069_NAM_final_large.mp4 (1920x1080) [108.5 MB] || 12069_NAM_final_appletv.m4v (1280x720) [68.8 MB] || 12069_NAM_final_prores.webm (1920x1080) [11.2 MB] || 12069_NAM_final_appletv_subtitles.m4v (1280x720) [68.8 MB] || 12069_NAM.en_US.srt [1.8 KB] || 12069_NAM.en_US.vtt [1.9 KB] || ", "hits": 23 }, { "id": 4575, "url": "https://svs.gsfc.nasa.gov/4575/", "result_type": "Visualization", "release_date": "2017-07-31T00:00:00-04:00", "title": "NASA Studies Hurricane Matthew", "description": "This data visualization follows Hurricane Matthew throughout its destructive run in the Caribbean and Southeast U.S. coast. By utilizing different data sets from NOAA's GOES satellite, NASA/JAXA's GPM, MERRA-2 model runs, IMERG, Goddard's soil moisture product, and sea surface temperatures, scientists are able to put together a clearer picture of how this hurricane quickly intensified and eventually weakened. || matthew_narrated_v106.5800_print.jpg (1024x576) [189.6 KB] || matthew_narrated_v106.5800_searchweb.png (320x180) [114.8 KB] || matthew_narrated_v106.5800_thm.png (80x40) [7.8 KB] || matthew (1920x1080) [0 Item(s)] || matthew_narrated_v106.webm (1920x1080) [22.0 MB] || matthew_narrated_v106.mp4 (1920x1080) [140.5 MB] || 3840x2160_16x9_30p (3840x2160) [0 Item(s)] || matthew_narrated_v106_4k.mp4 (3840x2160) [443.1 MB] || matthew_narrated_nosound.hwshow || ", "hits": 67 }, { "id": 12635, "url": "https://svs.gsfc.nasa.gov/12635/", "result_type": "Produced Video", "release_date": "2017-07-25T00:00:00-04:00", "title": "A New Multi-dimensional View of a Hurricane", "description": "Music: \"Buoys,\" Donn Wilkerson, Killer Tracks; \"Late Night Drive,\" Donn Wilkerson, Killer Tracks.Complete transcript available. || Matthew_screengrab_print.jpg (1024x574) [158.4 KB] || Matthew_screengrab_searchweb.png (320x180) [114.3 KB] || Matthew_screengrab_thm.png (80x40) [8.1 KB] || 12635_Hurricane_Matthew_prores.webm (1920x1080) [25.4 MB] || 12635_Hurricane_Matthew_twitter_720.mp4 (1280x720) [49.8 MB] || 12635_Hurricane_Matthew.mp4 (1920x1080) [236.9 MB] || 12635_Hurricane_Matthew_facebook_720.mp4 (1280x720) [271.2 MB] || 12635_Hurricane_Matthew_prores_youtube_720.mp4 (1280x720) [362.8 MB] || 12635_Hurricane_Matthew_youtube_1080.mp4 (1920x1080) [362.9 MB] || 12635_Hurricane_Matthew.en_US.srt [4.1 KB] || 12635_Hurricane_Matthew.en_US.vtt [4.1 KB] || 12635_Hurricane_Matthew_prores.mov (1920x1080) [3.0 GB] || ", "hits": 55 }, { "id": 30862, "url": "https://svs.gsfc.nasa.gov/30862/", "result_type": "Hyperwall Visual", "release_date": "2017-03-07T00:00:00-05:00", "title": "GRACE measures California water", "description": "Water storage from 2002-2017 as measured by gravity anomalies. || grace_ca_water_black_201701_print.jpg (1024x574) [119.7 KB] || grace_ca_water_black_201701_searchweb.png (320x180) [59.5 KB] || grace_ca_water_black_201701_thm.png (80x40) [4.9 KB] || grace_ca_water_black_1080p.mp4 (1920x1080) [7.3 MB] || grace_ca_water_black_720p.mp4 (1280x720) [3.6 MB] || grace_ca_water_black_720p.webm (1280x720) [5.9 MB] || grace_ca_water_black_201701.tif (4104x2304) [4.5 MB] || grace_ca_water_black_2304p.mp4 (4096x2304) [25.9 MB] || grace_ca_water_black_360p.mp4 (640x360) [1.1 MB] || ", "hits": 70 }, { "id": 4543, "url": "https://svs.gsfc.nasa.gov/4543/", "result_type": "Visualization", "release_date": "2017-01-23T00:00:00-05:00", "title": "Monitoring Hurricane Matthew", "description": "This example visualization shows how all of the below data visualizations could be arranged on NASA's 3x3 hyperwall display. || MatthewHyperwall9.01110_print.jpg (1024x576) [227.7 KB] || MatthewHyperwall9.01110_searchweb.png (320x180) [116.5 KB] || MatthewHyperwall9.01110_thm.png (80x40) [8.0 KB] || MatthewHyperwall9.mp4 (1920x1080) [61.9 MB] || MatthewHyperwall9.webm (1920x1080) [4.8 MB] || MatthewHyperwall9_4543.key [64.9 MB] || MatthewHyperwall9_4543.pptx [64.4 MB] || MatthewHyperwall9.mp4.hwshow [206 bytes] || ", "hits": 48 }, { "id": 4506, "url": "https://svs.gsfc.nasa.gov/4506/", "result_type": "Visualization", "release_date": "2016-11-30T13:00:00-05:00", "title": "The Rivers of Central California", "description": "The central California Watershed is the largest drainage basin in California.. The USGS has created a database of this area which indicates the direction of waterflow at each point. By assembling these directions into streamflows, it is possible to trace the path of water from every point of the area to the San Pablo Bay. This animation starts with the points furthest from the bay and reveals the streams and rivers as a steady progression towards the bay until all the major rivers are revealed. The speed of the reveal of the rivers is not dependent on the actual speed of the water flow. The reveal proceeds at a constant velocity along each river path, timed so that all reveals reach the bay at the same time. || ", "hits": 35 }, { "id": 4512, "url": "https://svs.gsfc.nasa.gov/4512/", "result_type": "Visualization", "release_date": "2016-10-11T17:00:00-04:00", "title": "GPM Monitors Hurricane Matthew Flooding the Carolinas", "description": "This data visualization resumes where the visualization \"GPM Captures Hurricane Matthew Nearing Florida\" leaves off. In this animation Hurricane Matthew travels up the east coast from Florida to the Carolinas. On October 8, 2016 Matthew (still a category 2 hurricane) dumps massive amounts of rain throughout the southeast dousing North and South Carolina. GPM then flies over the area revealing precipitation rates on the ground. As we zoom in closer, GPM's DPR sensor reveals a curtain of 3D rain rates within the massive weather system. || matthew_v4_annotated.4999_print.jpg (1024x576) [143.7 KB] || matthew_v4_annotated.4999_searchweb.png (320x180) [86.4 KB] || matthew_v4_annotated.4999_thm.png (80x40) [6.7 KB] || Matthew_with_annotations (1920x1080) [0 Item(s)] || matthew_v4_annotated_1080p30.mp4 (1920x1080) [20.0 MB] || matthew_v4_annotated_1080p30.webm (1920x1080) [4.0 MB] || matthew_v4_annotated_1080p30.mp4.hwshow [194 bytes] || ", "hits": 35 }, { "id": 4497, "url": "https://svs.gsfc.nasa.gov/4497/", "result_type": "Visualization", "release_date": "2016-09-27T13:00:00-04:00", "title": "GPM sees Louisiana Floods", "description": "This visualization begins with an overview of the United States showing the clouds and rainfall accumulation of the massive rain event over Louisiana beginning on August 11th, 2016 through August 13th, 2016. The camera then begins to zoom in as time resets to August 11th. Time then slows way down on August 12th to show the first of GPM's passes. In this close up of GPM's volumetric DPR data over Louisiana, a cutting plane materializes into view to show the inner structure of this giant storm system. From this view, one can clearly see the heavy amounts of rain in the center of the storm (depicted in yellow, orange, and red). The GPM data then dissolves away as time speeds up before slowing down again later on that same day. This time GPM captures a much larger swath of the storm. Dissolving in the cutting plane again reveals huge amounts of rainfall at this later time. As the GPM data dissolves away again, time speeds back up to show the rest of the rainfall accumulation partway through August 13. At this time, a large portion of Louisiana can be seen completely saturated with rainfall accumulations (depicted in shades of orange to red). || la_flood_rainaccum_w_dates.1190_print.jpg (1024x576) [106.8 KB] || la_flood_rainaccum_w_dates.1190_searchweb.png (320x180) [83.6 KB] || la_flood_rainaccum_w_dates.1190_thm.png (80x40) [6.6 KB] || la_flood_rainaccum_w_dates_1080p30_2.mp4 (1920x1080) [33.4 MB] || example_composite (1920x1080) [128.0 KB] || dates (1920x1080) [64.0 KB] || state_outlines (1920x1080) [128.0 KB] || dpr_clipped_1221Z (1920x1080) [64.0 KB] || dpr_1221Z (1920x1080) [64.0 KB] || dpr_clipped_0220Z (1920x1080) [64.0 KB] || dpr_0220Z (1920x1080) [64.0 KB] || rain_accumulation (1920x1080) [64.0 KB] || gpm_gprof (1920x1080) [128.0 KB] || cloudy_earth (1920x1080) [128.0 KB] || la_flood_rainaccum_w_dates_1080p30_2.webm (1920x1080) [5.7 MB] || la_flood_rainaccum_w_dates_1080p30_2.mp4.hwshow [244 bytes] || ", "hits": 35 }, { "id": 4493, "url": "https://svs.gsfc.nasa.gov/4493/", "result_type": "Visualization", "release_date": "2016-09-12T00:00:00-04:00", "title": "The Rivers of the Mississippi Watershed", "description": "The Mississippi Watershed is the largest drainage basin in North America at 3.2 million square kilometers in area. The USGS has created a database of this area which indicates the direction of waterflow at each point. By assembling these directions into streamflows, it is possible to trace the path of water from every point of the area to the mouth of the Mississippi in the Gulf of Mexico. This animation starts with the points furthest from the Gulf and reveals the streams and rivers as a steady progression towards the mouth of the Mississippi until all the major rivers are revealed. The speed of the reveal of the rivers is not dependent on the actual speed of the water flow. The reveal proceeds at a constant velocity along each river path, timed so that all reveals reach the mouth of the Mississippi at the same time. || ", "hits": 506 }, { "id": 4477, "url": "https://svs.gsfc.nasa.gov/4477/", "result_type": "Visualization", "release_date": "2016-07-28T18:00:00-04:00", "title": "GRACE over Brazil (March 2015 - March 2016)", "description": "Example animation showing significant ground water storage loss in the northern half of Brazil. This animation starts with a global view of the Americas, then zooms into the country of Brazil. Finally, monthly GRACE water storage anomaly data from March 2015 to March 2016 are shown. || grace2016.0598_print.jpg (1024x576) [81.8 KB] || grace2016.0598_thm.png (80x40) [5.9 KB] || grace2016.0598_searchweb.png (320x180) [63.1 KB] || grace2016_720p30.mp4 (1280x720) [2.8 MB] || Earth (1920x1080) [0 Item(s)] || Brazil_TWSA_data (1920x1080) [0 Item(s)] || Brazil_label (1920x1080) [0 Item(s)] || Brazil_outlines (1920x1080) [0 Item(s)] || Country_names (1920x1080) [0 Item(s)] || Brazil_mask (1920x1080) [0 Item(s)] || Country_borders (1920x1080) [0 Item(s)] || Example_edit (1920x1080) [0 Item(s)] || grace2016_1080p30.webm (1920x1080) [1.6 MB] || 4477_GRACE_Brazil_2016_youtube_hq.mov (1920x1080) [35.7 MB] || 4477_GRACE_Brazil_2016_appletv.m4v (1280x720) [11.0 MB] || grace2016_1080p30.mp4 (1920x1080) [5.1 MB] || 4477_GRACE_Brazil_2016.mpeg (1280x720) [100.5 MB] || 4477_GRACE_Brazil_2016_prores.mov (1280x720) [413.9 MB] || grace2016_360p30.mp4 (640x360) [1.0 MB] || 4477_GRACE_Brazil_2016_ipod_sm.mp4 (320x240) [3.0 MB] || grace2016_1080p30.mp4.hwshow [183 bytes] || ", "hits": 33 }, { "id": 12255, "url": "https://svs.gsfc.nasa.gov/12255/", "result_type": "Produced Video", "release_date": "2016-06-23T11:00:00-04:00", "title": "Monsoons: Wet, Dry, Repeat...", "description": "Complete transcript available.Music: Letting Go by Mario Lauer, 24 Dimensions by Christian Telford, David Travis Edwards, Matthew St. Laurent, and Robert Anthony Navarro || Monsoon_narrated_1080_30fps_youtube.00749_print.jpg (1024x576) [184.2 KB] || Monsoon_narrated_1080_30fps_youtube.00749_searchweb.png (180x320) [92.7 KB] || Monsoon_narrated_1080_30fps_youtube.00749_thm.png (80x40) [6.3 KB] || monsoonnarrfull.en_US.srt [4.9 KB] || monsoonnarrfull.en_US.vtt [4.9 KB] || 12255_Monsoons_1080_30fps.mp4 (1920x1080) [406.7 MB] || 12255_Monsoons_1080_60fps.mp4 (1920x1080) [409.0 MB] || 12255_Monsoons_4k_60fps_prores.mov (3840x2160) [27.8 GB] || 12255_Monsoons_4k30fps_youtube.mp4 (3840x2160) [1008.7 MB] || 12255_Monsoons_4k_60fps.webm (3840x2160) [131.9 MB] || ", "hits": 99 }, { "id": 4473, "url": "https://svs.gsfc.nasa.gov/4473/", "result_type": "Visualization", "release_date": "2016-06-17T15:00:00-04:00", "title": "IMERG Rainfall Accumulation over the United States for 5/27/2016-6/9/2016", "description": "A week-long series of heavy rain storms across Texas in late May to early June of 2016 led to flash floods from Houston to Dallas. This rain is captured in a rain accumulation visualization derived from the IMERG precipitation dataset. || ", "hits": 38 }, { "id": 12113, "url": "https://svs.gsfc.nasa.gov/12113/", "result_type": "Produced Video", "release_date": "2016-01-04T09:00:00-05:00", "title": "GPM 2015: One Year of Storms", "description": "A look back at the storms captured by GPM for 2015. || GPM_2015_Year_print.jpg (1024x576) [63.5 KB] || GPM_2015_Year_searchweb.png (320x180) [55.1 KB] || GPM_2015_Year_thm.png (80x40) [4.6 KB] || 12113_GPMYear2015_MASTER.mov (1280x720) [1.1 GB] || GPM_2015_Year.mp4 (1280x720) [163.0 MB] || 12113_GPMYear2015_MASTER.webm (1280x720) [17.2 MB] || 12113_GPMYear2015_MASTER.mpeg (1280x720) [539.6 MB] || 12113_GPMYear2015_MASTER_appletv.m4v (1280x720) [78.9 MB] || 12113_GPMYear2015_MASTER_large.mp4 (1280x720) [164.5 MB] || 12113_GPMYear2015_MASTER_appletv_subtitles.m4v (1280x720) [78.9 MB] || GPM_2015_Year.en_US.srt [1.3 KB] || GPM_2015_Year.en_US.vtt [1.4 KB] || ", "hits": 33 }, { "id": 4339, "url": "https://svs.gsfc.nasa.gov/4339/", "result_type": "Visualization", "release_date": "2015-10-30T09:00:00-04:00", "title": "GRACE Detects Brazil Drought", "description": "Example animation showing significant ground water storage loss around Brazil's most populated areas. This animation starts with a global view of the Americas, then zooms into the country of Brazil. The location of major reservoirs are revealed, followed by population data. Lastly, GRACE water storage anomaly data for the months of April, May, June is shown beginning in 2002 and going up to 2014. Finally, the region around São Paulo and Rio de Janeiro is highlighted to show the significant water storage loss in this highly populated region.This video is also available on our YouTube channel. || brazil_comp2.0760_print.jpg (1024x576) [101.6 KB] || brazil_comp2.0760_thm.png (80x40) [6.4 KB] || brazil_comp2.0760_searchweb.png (320x180) [72.9 KB] || brazil_comp2_1080p30.mp4 (1920x1080) [9.2 MB] || Population_Overlay (1920x1080) [0 Item(s)] || Country_boundaries (1920x1080) [0 Item(s)] || Brazil_boundary_mask (1920x1080) [0 Item(s)] || Reservoirs_solid_circle (1920x1080) [0 Item(s)] || Country_names (1920x1080) [0 Item(s)] || Year_Annotation (1920x1080) [0 Item(s)] || Brazil_mask (1920x1080) [0 Item(s)] || Background_Earth (1920x1080) [0 Item(s)] || Brazil_country_label (1920x1080) [0 Item(s)] || Brazil_state_boundaries (1920x1080) [0 Item(s)] || Reservoirs_hollow_circle (1920x1080) [0 Item(s)] || GRACE_Data_Overlay (1920x1080) [0 Item(s)] || Example_Composite (1920x1080) [0 Item(s)] || brazil_comp2_1080p30.webm (1920x1080) [3.1 MB] || brazil_comp2_1080p30.mp4.hwshow [186 bytes] || ", "hits": 51 }, { "id": 12013, "url": "https://svs.gsfc.nasa.gov/12013/", "result_type": "Produced Video", "release_date": "2015-09-24T11:00:00-04:00", "title": "Landsat Helps Feed the Birds", "description": "The BirdReturns program, created by The Nature Conservancy of California, is an effort to provide \"pop-up habitats\" for some of the millions of shorebirds, such as sandpipers and plovers, that migrate each year from their summer breeding grounds in Alaska and Canada to their winter habitats in California, Mexico, Central and South America. The route takes the birds along what’s called the Pacific Flyway, where they seek out the increasingly rare wetlands teeming with tasty insects to fuel their long-distance flights. The Nature Conservancy of California operates the BirdReturns program, with partners including Point Blue Conservation Science, Audubon California and the Cornell Lab of Ornithology. Over the last century, California's Central Valley has lost 95% of the wetlands habitat, which is needed for the shorebirds while on their migration. The solution involves big data, binoculars and rice paddies. The Cornell Lab of Ornithology’s eBird program collects on-the-ground observations, including species and date spotted, from bird watchers nationwide. With a recent NASA grant to Cornell, scientists created computer models to analyze that information and combine it with satellite remote sensing imagery from Landsat and the Moderate Resolution Imaging Spectroradiometer instruments on NASA’s Terra and Aqua satellites. With these models, they could identify areas in the Central Valley where birds flocked to during the spring and fall migrations, as well as estimate the number of birds making the journey.Some of his colleagues had been using Landsat images to look at where – and when – there was standing water, to assist with surveys of shorebirds.The nonprofit Point Blue, based in Petaluma, California, developed models that can classify habitats based on Landsat imagery. For the BirdReturns project, the team analyzed 1,500 Landsat scenes between 2000 and 2011, and then additional images from Landsat 8 after its 2013 launch. For each area not blocked by clouds, they classified whether there was surface water.Matching the location and timing of surface water from Landsat with the route and timing of migrating shorebirds from eBird, the BirdReturns program looks for those key sites where extra water would make a difference for the birds, which forage for food in the wetland areas. The Nature Conservancy then uses a reverse auction where farmers try to submit the lowest bid to turn their empty fields into a pop-up wetland for the few weeks the birds are stopping in the Central Valley while on their migration.We would like to thank the Point Blue and The Nature Conservancy for supplying Central Valley water data. Least sandpiper data courtesy of Cornell Lab of Ornithology, eBird Basic Dataset. Version: EBD_relMay-2013. Cornell Lab of Ornithology, Ithaca, New York. May 2013. || ", "hits": 44 }, { "id": 30599, "url": "https://svs.gsfc.nasa.gov/30599/", "result_type": "Hyperwall Visual", "release_date": "2015-05-17T00:00:00-04:00", "title": "Soil Moisture Maps and Australian Rainfall", "description": "A series of images shows soil moisture and flooding in Australia. || smap_rainfall_australia_april_2015_print.jpg (1024x574) [129.9 KB] || smap_rainfall_australia_april_2015.png (4104x2304) [1.6 MB] || smap_rainfall_australia_april_2015_searchweb.png (180x320) [62.4 KB] || smap_rainfall_australia_april_2015_thm.png (80x40) [6.9 KB] || smap_rainfall_australia_april_2015_30599.key [4.6 MB] || smap_rainfall_australia_april_2015_30599.pptx [2.0 MB] || smap_rainfall_australia_april_2015.hwshow [236 bytes] || ", "hits": 45 }, { "id": 11506, "url": "https://svs.gsfc.nasa.gov/11506/", "result_type": "Produced Video", "release_date": "2014-03-20T00:00:00-04:00", "title": "Tracking Urban Change With Landsat", "description": "For helping communities across the United States stay up-to-date on their flood risk, the NASA/USGS Landsat satellites can take a bow. The Federal Emergency Management Agency uses Landsat images, which can illustrate urban changes, as a key indicator of sites where the agency should further investigate the flooding potential. With its archive of images capturing sprawling cities and new developments, Landsat can help FEMA track how building and construction is impacting an area’s landscapeEarth-observing Landsat satellites have been capturing images of the planet’s surface since 1972. Landsat 8 is the newest satellite in the program, a joint effort between NASA and the U.S. Geological Survey. It launched Feb. 11, 2013, and collects more than 400 images per day. New and archived Landsat data are available free to the public over the internet – and researchers have put the data to a multitude of uses. One is called the National Urban Change Indicator, or NUCI, created by MacDonald, Dettwiler, and Associates, LTD. It’s the results from a process that mines Landsat images over a 27-year period to identify areas of “permanent change,” where soil has been paved over for parking lots or other concrete structures.NUCI results act as a red flag for FEMA, helping the agency focus its mapping efforts and budget. But if maps identify a high risk of floods for a certain community, residents can take action, including elevating houses, building flood barricades, and more. || ", "hits": 72 }, { "id": 30473, "url": "https://svs.gsfc.nasa.gov/30473/", "result_type": "Hyperwall Visual", "release_date": "2013-11-01T12:00:00-04:00", "title": "Observing Freshwater Losses in the Middle East", "description": "A study using data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites found that large parts of the arid Middle East region lost freshwater reserves rapidly during the past decade. Meanwhile, demand for freshwater continues to rise. The two natural-color images on the left were acquired by the Landsat 5 satellite and show the shrinking of the Qadisiyah Reservoir in Iraq between September 7, 2006 [top left] and September 15, 2009 [bottom left]. The graph below these two images shows the elevation of the water in that reservoir between January 2003 and December 2009. The elevation is a proxy measurement for the total volume of water stored there. The two regional images on the right were created with GRACE data and show total water storage in the Tigris and Euphrates river basins for September 2003 [top right] and September 2009 [bottom right]. The graph shows a decrease in water storage for the study area as measured by GRACE from January 2003 to December 2009. The gray line depicts total water storage—groundwater, surface water bodies, and soil moisture—while the green line depicts changes in surface water. The difference between those two lines reflects the change in water stored in underground aquifers. The total water storage shows a seasonal fluctuation, but also an overall downward trend, suggesting that groundwater is being pumped and used faster than natural processes can replenish it. Data from satellites such as GRACE are essential to providing a more complete global picture of water storage trends.Used in 2014 Calendar. || ", "hits": 103 }, { "id": 11221, "url": "https://svs.gsfc.nasa.gov/11221/", "result_type": "Produced Video", "release_date": "2013-04-12T00:00:00-04:00", "title": "GPM: Our Wet Wide World", "description": "The Global Precipitation Measurement (GPM) is an international satellite mission to provide next-generation observations of rain and snow worldwide every three hours. NASA and the Japan Aerospace Exploration Agency (JAXA) will launch a \"Core\" satellite carrying advanced instruments that will set a new standard for precipitation measurements from space. The data they provide will be used to unify precipitation measurements made by an international network of partner satellites to quantify when, where, and how much it rains or snows around the world.The GPM mission will help advance our understanding of Earth's water and energy cycles, improve the forecasting of extreme events that cause natural disasters, and extend current capabilities of using satellite precipitation information to directly benefit society. || ", "hits": 36 }, { "id": 30039, "url": "https://svs.gsfc.nasa.gov/30039/", "result_type": "Hyperwall Visual", "release_date": "2013-03-28T00:00:00-04:00", "title": "2010 Indus Floods", "description": "Some blamed La Niña, while others faulted inadequate flood-prevention plans for the devastation left behind by the 2010 Pakistan Floods. In either case, the coming together of international partners allowed rapid humanitarian response efforts to take place. The importance of international partnership lies within the craftsmanship of the middle map, a mosaic of shared satellite data pieced together by UNITAR’s Operational Satellite Application Programme (UNOSAT). The map provides flood analysis based on a time series of satellite data recorded between July 28-September 16, 2010. With the support from several other partners, UNOSAT was able to provide emergency response maps to humanitarian communities during the floods. Often times, those assessing flood extent on land are unable to map an entire area before water levels change again. Satellites, however, offer a unique perspective from space and provide data across large geographic areas nearly every day. || ", "hits": 38 }, { "id": 4047, "url": "https://svs.gsfc.nasa.gov/4047/", "result_type": "Visualization", "release_date": "2013-02-27T00:00:00-05:00", "title": "Collecting LIDAR data over the Ganges and Brahmaputra River Basin", "description": "Animation of a generic satellite taking digital elevation map measurements across the Ganges and Brahmaputra river basin. This animation was created for a NASA-funded educational movie as part of the Fulbright program. Terrain elevation is exaggerated 5 times. || ", "hits": 77 }, { "id": 11202, "url": "https://svs.gsfc.nasa.gov/11202/", "result_type": "Produced Video", "release_date": "2013-01-31T16:00:00-05:00", "title": "Monitoring Changes in the Chesapeake Bay Watershed", "description": "Landsat is a critical and invaluable tool for characterizing the landscape and mapping it over time. Landsat data provides a baseline of observations for science about how human activities on the land affect water quality, affect wildlife habitat, affect air quality. The satellite imagery covers the entire 64,000 square miles of the Chesapeake Bay watershed (spanning six states and the District of Columbia). Without it we wouldn't be able to really understand how sources of nutrients and sediment have changed and where they are in the Chesapeake Bay. The Landsat Program is a series of Earth-observing satellite missions jointly managed by NASA and the U.S. Geological Survey. The narration in this video is by Peter Claggett, a research geographer with the U.S. Geological Survey's Eastern Geographic Science Center. He has worked at the Chesapeake Bay Program Office since 2002, where he leads the Land Data Team that conducts research on land change characterization, analysis, and modeling in the Chesapeake Bay Watershed. The audio was adapted from a radio interview with EarthSky.org. || ", "hits": 51 }, { "id": 11091, "url": "https://svs.gsfc.nasa.gov/11091/", "result_type": "Produced Video", "release_date": "2012-08-27T13:00:00-04:00", "title": "GPM Applications", "description": "Water is fundamental to life on Earth. Knowing where and how much rain and snow falls globally is vital to understanding how weather and climate impact both our environment and Earth's water and energy cycles, including effects on agriculture, fresh water availability, and responses to natural disasters. Since rainfall and snowfall vary greatly from place to place and over time, satellites can provide more uniform observations of rain and snow around the globe than ground instruments, especially in areas where surface measurements are difficult. GPM's next-generation global precipitation data will lead to scientific advances and societal benefits in the following areas: Improved knowledge of the Earth's water cycle and its link to climate change New insights into precipitation microphysics, storm structures and large-scale atmospheric processes Better understanding of climate sensitivity and feedback processes Extended capabilities in monitoring and predicting hurricanes and other extreme weather events Improved forecasting capabilities for natural hazards, including floods, droughts and landslides. Enhanced numerical prediction skills for weather and climate Better agricultural crop forecasting and monitoring of freshwater resources.For more information and resources please visit the Precipitation Measurement Missions web site. || ", "hits": 40 }, { "id": 11054, "url": "https://svs.gsfc.nasa.gov/11054/", "result_type": "Produced Video", "release_date": "2012-08-02T12:00:00-04:00", "title": "Earth's Water Cycle", "description": "Water is the fundamental ingredient for life on Earth. Looking at our Earth from space, with its vast and deep ocean, it appears as though there is an abundance of water for our use. However, only a small portion of Earth's water is accessible for our needs. How much fresh water exists and where it is stored affects us all. This animation uses Earth science data from a variety of sensors on NASA Earth observing satellites as well as cartoons to describe Earth's water cycle and the continuous movement of water on, above and below the surface of the Earth. Sensors on a suite of NASA satellites observe and measure water on land, in the ocean and in the atmosphere. These measurements are important to understanding the availability and distribution of Earth's water — vital to life and vulnerable to the impacts of climate change on a growing world population.NASA Earth Observing System Data and Information Systems (EOSDIS) EOSDIS is a distributed system of twelve data centers and science investigator processing systems. EOSDIS processes, archives, and distributes data from Earth observing satellites, field campaigns, airborne sensors, and related Earth science programs. These data enable the study of Earth from space to advance scientific understanding.For questions, please contact eosdis-outreach@lists.nasa.gov || ", "hits": 114 }, { "id": 11042, "url": "https://svs.gsfc.nasa.gov/11042/", "result_type": "Produced Video", "release_date": "2012-07-23T00:00:00-04:00", "title": "Vermilion Parish, LA", "description": "Timelapse of six years in southern Vermilion Parish, Louisiana (1973, 1980, 1986, 1992, 2003, 2010) land being overtaken by water. In these images from Landsat data, red indicates healthy vegetation and shades of blue indicate water. || Pecan_Island_2011.jpg (1280x720) [349.5 KB] || Pecan_Island_2003.jpg (1280x720) [369.1 KB] || Pecan_Island_1992.jpg (1280x720) [335.4 KB] || Pecan_Island_1986.jpg (1280x720) [350.0 KB] || 7-Loveland-1-Pecan_series.00002_print.jpg (1024x576) [148.9 KB] || Pecan_Island_1980.jpg (1280x720) [464.4 KB] || Pecan_Island_1973.jpg (1280x720) [290.8 KB] || 7-Loveland-1-Pecan_series_web.png (320x180) [288.7 KB] || 7-Loveland-1-Pecan_series_thm.png (80x40) [17.6 KB] || 7-Loveland-1-Pecan_series_youtube_hq.mov (1280x720) [18.7 MB] || 7-Loveland-1-Pecan_series_appletv.m4v (960x540) [13.4 MB] || 7-Loveland-1-Pecan_series_1280x720.wmv (1280x720) [13.6 MB] || 7-Loveland-1-Pecan_series_720x480.webmhd.webm (960x540) [4.2 MB] || 7-Loveland-1-Pecan_series.mov (640x360) [9.9 MB] || 7-Loveland-1-Pecan_series_720x480.wmv (720x480) [7.7 MB] || 7-Loveland-1-Pecan_series_ipod_lg.m4v (640x360) [5.5 MB] || GSFC_20120723_Landsat_m11042_Vermilion.en_US.vtt [64 bytes] || 7-Loveland-1-Pecan_series_ipod_sm.mp4 (320x240) [2.1 MB] || 7-Loveland-1-Pecan_series_prores.mov (1280x720) [602.1 MB] || landsat_vermillion_parish_bigmovie.hwshow [57 bytes] || ", "hits": 59 }, { "id": 3850, "url": "https://svs.gsfc.nasa.gov/3850/", "result_type": "Visualization", "release_date": "2011-08-30T00:00:00-04:00", "title": "Extreme Russian Fires and Pakistan Floods Linked Meteorologically", "description": "In the summer of 2010, months of record-breaking drought and temperatures culminated with a rash of fires that ravaged western Russia for weeks. Temperatures in Moscow soared to an average of 104 °F (40 °C) during late July and early August — more than 18 °F (10 °C) above normal. Hundreds of fires broke out producing some $15 million in damages. The heat and smoke killed about 56,000 people, making the Russian wildfires fires one of the most lethal natural disasters of the year.Meanwhile, some 930 kilometers (1,500 miles) away, relentless rainfall was simultaneously pounding Pakistan and generating intense flooding. The Pakistan Meteorological Department reported nationwide rain totals 70 percent above normal in July and 102 percent above normal in August.New research conducted by William Lau, an atmospheric scientist at NASA's Goddard Space Flight Center in Greenbelt, Md., suggests the two seemingly disconnected events were actually closely linked.Under normal circumstances, the jet stream pushes weather fronts through Eurasia in four or five days, but something unusual happened in July of 2010. A large-scale, stagnant weather pattern — known as an Omega blocking event — slowed the Rossby wave over Russia and prevented the normal progression of weather systems from west to east.As a result, a large region of high-pressure formed over Russia trapping a hot, dry air mass over the area. As the high lingered, the land surface dried and the normal transfer of moisture from the soil to the atmosphere slowed. Precipitation ceased, vegetation dried out, and the region became a taiga tinderbox.Meanwhile, the blocking pattern created unusual downstream wind patterns over Pakistan. Areas of low pressure on the leading edge of the Rossby wave formed in response to the high, pulling cold, dry Siberian air into lower latitudes.This cold air from Siberia clashed with warm, moist air arriving over Pakistan from the Bay of Bengal as part of the monsoon. There's nothing unusual about moisture moving north over India toward the Himalayas. It's a normal part of the monsoon. However, in this case, the unusual wind patterns associated with the blocking high brought upper level air disturbances farther south than typical, which in effect helped shifted the entire monsoon system north and west.This brought heavy monsoon rains — centered over parts of India — squarely over the northern part of Pakistan, a region ill-prepared to handle large amounts of rain. || ", "hits": 72 }, { "id": 10773, "url": "https://svs.gsfc.nasa.gov/10773/", "result_type": "Produced Video", "release_date": "2011-05-19T11:00:00-04:00", "title": "Mississippi Flooding 2011", "description": "Heavy spring rains and snowmelt led to devastating floods along the Mississippi River in May 2011. Landsat 5 flew over the Mississippi River on May 10, 2011, giving a distinct view of the extraordinary extent of the flooding. This was only eight days after the Army Corps of Engineers began blasting holes in earthen levees near Cairo, Illinois, when the river reached a depth of 61 feet. The extent of the 2011 flooding is compared with the same locations in April 2010. || ", "hits": 113 }, { "id": 3719, "url": "https://svs.gsfc.nasa.gov/3719/", "result_type": "Visualization", "release_date": "2010-06-24T00:00:00-04:00", "title": "MERRA Specific Humidity", "description": "Retrospective-analyses (or reanalyses) have been a critical tool in studying weather and climate variability for the last 15 years. Reanalyses blend the continuity and breadth of output data of a numerical model with the constraint of vast quantities of observational data. The result is a long-term continuous data record. The Modern Era Retrospective-analysis for Research and Applications was developed to support NASA's Earth science objectives, by applying the state-of-the-art GMAO data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle.The time period covered by the visualization is the months of May, June, and July of 1988 and 1993, two years with contrasting extreme weather events during the summer: a drought through the midwestern states of the US in 1988, and heavy rains and flooding through the same region in 1993.This visualization shows the specific humidity dataset produced by MERRA, up to a geopotential height of 20 km. The height coordinate is greatly exaggerated. Both opacity and color are driven by the data value.This animation was created as part of a presentation for the Nasa Center for Climate Simulation (NCCS) hyperwall display. This is a set of tiled high definition displays consisting of 5 displays across by 3 displays down. The full resolution of all combined displays is 6840 pixels accross by 2304 pixels down. For the full presentation, see the link below. || ", "hits": 23 }, { "id": 3732, "url": "https://svs.gsfc.nasa.gov/3732/", "result_type": "Visualization", "release_date": "2010-06-24T00:00:00-04:00", "title": "MERRA Relative Humidity", "description": "Retrospective-analyses (or reanalyses) have been a critical tool in studying weather and climate variability for the last 15 years. Reanalyses blend the continuity and breadth of output data of a numerical model with the constraint of vast quantities of observational data. The result is a long-term continuous data record. The Modern Era Retrospective-analysis for Research and Applications was developed to support NASA's Earth science objectives, by applying the state-of-the-art GMAO data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle.The time period covered by the visualization is the months of May, June, and July of 1988 and 1993, two years with contrasting extreme weather events during the summer: a drought through the midwestern states of the US in 1988, and heavy rains and flooding through the same region in 1993.This visualization shows the relative humidity dataset produced by MERRA, up to a geopotential height of 20 km. The height coordinate is greatly exaggerated. Both opacity and color are driven by the data value.This animation was created as part of a presentation for the Nasa Center for Climate Simulation (NCCS) hyperwall display. This is a set of tiled high definition displays consisting of 5 displays across by 3 displays down. The full resolution of all combined displays is 6840 pixels accross by 2304 pixels down. For the full presentation, see the link below. || ", "hits": 38 }, { "id": 3733, "url": "https://svs.gsfc.nasa.gov/3733/", "result_type": "Visualization", "release_date": "2010-06-24T00:00:00-04:00", "title": "MERRA Wind", "description": "Retrospective-analyses (or reanalyses) have been a critical tool in studying weather and climate variability for the last 15 years. Reanalyses blend the continuity and breadth of output data of a numerical model with the constraint of vast quantities of observational data. The result is a long-term continuous data record. The Modern Era Retrospective-analysis for Research and Applications was developed to support NASA's Earth science objectives, by applying the state-of-the-art GMAO data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle.The time period covered by the visualization is the months of May, June, and July of 1988 and 1993, two years with contrasting extreme weather events during the summer: a drought through the midwestern states of the US in 1988, and heavy rains and flooding through the same region in 1993.This visualization shows the combined U and V components of wind at three different pressure levels: 850 mb, 500 mb, and 300 mb. The pressure coordinate is greatly exaggerated.This animation was created as part of a presentation for the Nasa Center for Climate Simulation (NCCS) hyperwall display. This is a set of tiled high definition displays consisting of 5 displays across by 3 displays down. The full resolution of all combined displays is 6840 pixels accross by 2304 pixels down. For the full presentation, see the link below. || ", "hits": 39 }, { "id": 3734, "url": "https://svs.gsfc.nasa.gov/3734/", "result_type": "Visualization", "release_date": "2010-06-24T00:00:00-04:00", "title": "MERRA Combined Liquid Water and Ice Mixing Ratios", "description": "Retrospective-analyses (or reanalyses) have been a critical tool in studying weather and climate variability for the last 15 years. Reanalyses blend the continuity and breadth of output data of a numerical model with the constraint of vast quantities of observational data. The result is a long-term continuous data record. The Modern Era Retrospective-analysis for Research and Applications was developed to support NASA's Earth science objectives, by applying the state-of-the-art GMAO data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle.The time period covered by the visualization is the months of May, June, and July of 1988 and 1993, two years with contrasting extreme weather events during the summer: a drought through the midwestern states of the US in 1988, and heavy rains and flooding through the same region in 1993.This visualization shows the combined liquid water and ice mixing ratio dataset produced by MERRA, roughly corresponding to cloud cover, up to an geopotential height of 20 km. The height coordinate is greatly exaggerated. Both opacity and color are driven by the data value.This animation was created as part of a presentation for the NASA Center for Climate Simulation (NCCS) hyperwall display. This is a set of tiled high definition displays consisting of 5 displays across by 3 displays down. The full resolution of all combined displays is 6840 pixels accross by 2304 pixels down. For the full presentation, see the link below. || ", "hits": 17 }, { "id": 3735, "url": "https://svs.gsfc.nasa.gov/3735/", "result_type": "Visualization", "release_date": "2010-06-24T00:00:00-04:00", "title": "MERRA Rate of Total Precipitation, 1988, 1993", "description": "Retrospective-analyses (or reanalyses) have been a critical tool in studying weather and climate variability for the last 15 years. Reanalyses blend the continuity and breadth of output data of a numerical model with the constraint of vast quantities of observational data. The result is a long-term continuous data record. The Modern Era Retrospective-analysis for Research and Applications was developed to support NASA's Earth science objectives, by applying the state-of-the-art GMAO data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle.The time period covered by the visualization is the months of May, June, and July of 1988 and 1993, two years with contrasting extreme weather events during the summer: a drought through the midwestern states of the US in 1988, and heavy rains and flooding through the same region in 1993.This visualization shows the total precipitation rate dataset produced by MERRA.This animation was created as part of a presentation for the NASA Center for Climate Simulation (NCCS) hyperwall display. This is a set of tiled high definition displays consisting of 5 displays across by 3 displays down. The full resolution of all combined displays is 6840 pixels accross by 2304 pixels down. For the full presentation, see the link below. || ", "hits": 17 }, { "id": 10512, "url": "https://svs.gsfc.nasa.gov/10512/", "result_type": "Produced Video", "release_date": "2009-10-27T00:00:00-04:00", "title": "Science for a Hungry World: Growing Water Problems", "description": "One of the biggest changes to global agriculture is less about the food itself as it is about the water we use to grow it. In some areas, farmers are using freshwater resources - including groundwater - at an alarming rate. The GRACE satellites enable scientists to discover changes to underground aquifers by monitoring changes in the Earth's gravity. In northern India, farmers rely heavily on irrigation to grow crops, and the resulting massive aquifer depletion creates an uncertain future for the region. For complete transcript, click here. || Agriculture_Episode_5_Water_512x288.05177_print.jpg (1024x576) [180.7 KB] || Agriculture_Episode_5_Water_512x288_web.png (320x180) [321.0 KB] || Agriculture_Episode_5_Water_512x288_thm.png (80x40) [18.0 KB] || Agriculture_Episode_5_Water_960x540_AppleTV.webmhd.webm (960x540) [72.9 MB] || Agriculture_Episode_5_Water_1280x720_Youtube.mov (1280x720) [76.1 MB] || Agriculture_Episode_5_Water_960x540_AppleTV.m4v (960x540) [176.9 MB] || Agriculture_Episode_5_Water_1280x720_H264.mov (1280x720) [135.9 MB] || Agriculture_Episode_5_Water_640x480_ipod.m4v (640x360) [52.9 MB] || Agriculture_Episode_5_Water_512x288.mpg (512x288) [159.1 MB] || Agriculture_Episode_5_Water_320x240.mp4 (320x180) [23.2 MB] || bigmovie-science_for_a_hungry_world_5-water_problems.hwshow || ", "hits": 28 }, { "id": 3477, "url": "https://svs.gsfc.nasa.gov/3477/", "result_type": "Visualization", "release_date": "2008-04-21T08:00:00-04:00", "title": "Chesapeake Bay Watershed Region (short version)", "description": "The watershed that drains into the Chesapeake Bay is a huge expanse that extends 64,000 miles into five states across North America (New York, Pensylvania, Maryland, Delaware, Virginia) and the District of Columbia. This visualization overlays the full watershed onto a Landsat satellite visualization of the Bay area. The eight different distinctly colored regions indicate the Chesapeake's major subwatersheds. These subwatershed regions are: Susquehanna, Potomac, Patuxent, MD West Shore, Rapahhannock, Eastern Shore, James and York. This visualization contains just the last part of the Chesapeake Bay Flyover and Watershed Region (#3472) animation and demonstrates the entire Watershed without the Chesapeake Bay flyover. This animation highlights and labels each subwatershed in turn. Data Notes:The mosaic was created by EarthSat under contract with NASA as part of the GeoCover 2000 product. All images used in GeoCover were acquired by Landsat-7 during the period of 1999-2002. The pixel size of the full resolution image represents 14.25 m on the ground. The Chesapeake Bay mosaic uses portions of eight Landsat-7 scenes. Below you will find a listing of the eight Landsat 7 images that were put together to create the composite image. Landsat scenes are organized by a Path and Row number according to the Worldwide Reference System. (To learn more about Landsat's Worldwide Reference System, please visit: http://landsat.gsfc.nasa.gov/about/wrs.html)Scenes used in the Chesapeake Bay mosaic: Landsat-7 WRS Path 15-Row 32 acquired on Oct. 05, 2001 Landsat-7 WRS Path 14-Row 32 acquired on Sept. 23, 1999 Landsat-7 WRS Path 15-Row 33 acquired on October 05, 2001 Landsat-7 WRS Path 14-Row 33 acquired on July 10, 2001Landsat-7 WRS Path 15-Row 34 acquired on Sept. 30, 1999 Landsat-7 WRS Path 14-Row 34 acquired on July 10, 2001 Landsat-7 WRS Path 15-Row 35 acquired on Sept. 30, 1999 Landsat-7 WRS Path 14-Row 35 acquired on Sept. 23, 1999 || ", "hits": 62 }, { "id": 10207, "url": "https://svs.gsfc.nasa.gov/10207/", "result_type": "Produced Video", "release_date": "2008-04-20T12:00:00-04:00", "title": "NASA Satellites Aid in Chesapeake Bay Recovery", "description": "From the distant reaches of the Universe, to black holes, and the Martian surface, NASA explores some of the most far out parts of space. But NASA also does research much closer to home. In fact, NASA Earth Science satellites are taking part in the management and recovery of an ecosystem right in our backyard, the Chesapeake Bay. || ", "hits": 19 }, { "id": 3433, "url": "https://svs.gsfc.nasa.gov/3433/", "result_type": "Visualization", "release_date": "2007-06-11T00:00:00-04:00", "title": "Rise of the Three Gorges Dam", "description": "Some call it the eighth wonder of world; others say it's the next Great Wall of China. Upon completion in 2009, the Three Gorges Dam will be the world's largest hydroelectric power generator. One of the few man-made structures so enormous that it's actually visible to the naked eye from space, NASA's Landsat satellite has had a closer look, providing detailed, vivid views of the dam since its inception in 1994. The dam is built along the Yangtze River, the third largest in the world, stretching more than 3,900 miles across China before reaching its mouth near Shanghai. Historically, the river has been prone to massive flooding, overflowing its banks about once every ten years. During the 20th century alone, Chinese authorities estimate that some 300,000 people were killed from Yangtze River floods. The dam is designed to greatly improve flood control on the river and protect the 15 million people and 3.7 million acres of farmland in the lower Yangtze flood plains. Observations from the NASA-built Landsat satellites provide an overview of the dam's construction. The earliest data set, from 1987, shows the region prior to start of construction. By 2000, construction along each riverbank was underway, but sediment-filled water still flowed through a narrow channel near the river's south bank. The 2004 data shows development of the main wall and the partial filling of the reservoir, including numerous side canyons. By mid-2006, construction of the main wall was completed and a reservoir more than 2 miles (3 kilometers) across had filled just upstream of the dam. To read more about the Three Gorges Dam, please click here. This animation was designed in three parts: Part 1: The first part of this animation zooms in to the Three Gorges Dam and travels backward and forward through time emphasizing the dam construction and filling of the reservoir. This animation then continues seemlessly into Part 2. Part 2: Starting where Part 1 leaves off, the camera flies up the 2006 data showing the high water levels that have already filled the multiple gorges upstream. Part 3: Identical to Part 2, except showing the 1987 data prior to the dam construction. || ", "hits": 582 }, { "id": 3352, "url": "https://svs.gsfc.nasa.gov/3352/", "result_type": "Visualization", "release_date": "2006-04-04T00:00:00-04:00", "title": "Before and During the Great Mississippi Flood of 1993", "description": "During the first half of 1993, heavy rains in the Midwest United States caused the greatest flood ever recorded on the Upper Mississippi. The Mississippi River remained above flood stage from April through September of that year, and many of the dykes and water control systems along the rivers in this region were overwhelmed. These images from the Landsat-5 Thematic Mapper clearly show the flooded regions near St. Louis. The pink areas near the flooded regions show the scoured land from which the flood waters have receded. A comparison of the image during the flood with an image from a year before clearly shows the preponderance of cultivated fields in the lowland flooded region, evidence that floods and river meanderings have deposited rich soil in these regions in the past. || ", "hits": 129 }, { "id": 3112, "url": "https://svs.gsfc.nasa.gov/3112/", "result_type": "Visualization", "release_date": "2005-02-15T12:00:00-05:00", "title": "Aral Sea Evaporation (WMS)", "description": "The Aral Sea is actually not a sea at all, but an immense fresh water lake. In the last thirty years, more than sixty percent of the lake has disappeared because much of the river flow feeding the lake was diverted to irrigate cotton fields and rice paddies. Concentrations of salts and minerals began to rise in the shrinking body of water, leading to staggering alterations in the lake's ecology and precipitous drops in the Aral's fish population. Powerful winds that blow across this part of Asia routinely pick up and deposit the now exposed lake bed soil. This has contributed to a significant reduction in breathable air quality, and crop yields have been appreciably affected due to heavily salt laden particles falling on arable land. This series of Landsat images taken in 1973, 1987 and 2000 show the profound reduction in overall area at the north end of the Aral, and a commensurate increase in land area as the floor of the sea now lies exposed. || ", "hits": 53 }, { "id": 2571, "url": "https://svs.gsfc.nasa.gov/2571/", "result_type": "Visualization", "release_date": "2002-10-07T12:00:00-04:00", "title": "Southeastern Texas Floods: 24 June 2002 (before)", "description": "Rivers near San Antonio, Texas are difficult to distinguish before the flooding of July 2002. After the floods, the swollen rivers are easy to discern. || Southeastern Texas before flood: 24 June 2002 || Texas.flood.beforeWide.jpg (1600x1080) [527.3 KB] || Texas.flood.beforeWide_web.jpg (320x216) [19.5 KB] || Texas.flood.beforeWide_thm.png (80x40) [6.6 KB] || Texas.flood.beforeWide_web_searchweb.jpg (320x180) [113.8 KB] || Texas.flood.beforeWide.tif (1600x1080) [3.5 MB] || ", "hits": 12 }, { "id": 2572, "url": "https://svs.gsfc.nasa.gov/2572/", "result_type": "Visualization", "release_date": "2002-10-07T12:00:00-04:00", "title": "Southeastern Texas Floods: 8 July 2002 (after)", "description": "Rivers near San Antonio, Texas are difficult to distinguish before the flooding of July 2002. After the floods, the swollen rivers are easy to discern. || Southeastern Texas after flood: 8 July 2002 || Texas.flood.afterWide.jpg (1600x1080) [695.8 KB] || Texas.flood.afterWide_web.jpg (320x216) [22.2 KB] || Texas.flood.afterWide_thm.png (80x40) [6.8 KB] || Texas.flood.afterWide_web_searchweb.jpg (320x180) [128.0 KB] || Texas.flood.afterWide.tif (1600x1080) [4.4 MB] || ", "hits": 21 }, { "id": 2560, "url": "https://svs.gsfc.nasa.gov/2560/", "result_type": "Visualization", "release_date": "2002-09-26T12:00:00-04:00", "title": "Flooding in China (Before and After)", "description": "Flooding in China which may be related to the weather effects of black carbon aerosols in the region. || Simple dissolve from pre-flood to post-flood view. || a002560.00100_print.png (720x480) [556.8 KB] || flood60_pre.jpg (320x240) [11.3 KB] || a002560.webmhd.webm (960x540) [1.5 MB] || a002560.dv (720x480) [27.2 MB] || flood60.mpg (320x240) [284.7 KB] || ", "hits": 12 }, { "id": 2499, "url": "https://svs.gsfc.nasa.gov/2499/", "result_type": "Visualization", "release_date": "2002-08-15T12:00:00-04:00", "title": "The First Day In The Life of Aqua/MODIS", "description": "In its first day of operations, June 24, 2002, Aqua/MODIS observed significant Earth events occurring all over the globe. As Super Typhoon Chataan was rapidly approaching Japan, there was severe flooding in southeast Texas and a vast, thick pall of smoke from Canadian wildfires blanketed almost the entire U.S. East Coast. MODIS collected and beamed to Earth these images in very near real-time. || ", "hits": 13 }, { "id": 2500, "url": "https://svs.gsfc.nasa.gov/2500/", "result_type": "Visualization", "release_date": "2002-08-15T12:00:00-04:00", "title": "Flooding in Southeast Texas", "description": "Southeast of San Antonio, Texas, rivers that were barely discernible in satellite imagery acquired in late June 2002 by Terra MODIS stand out clearly this Aqua MODIS image from July 24, 2002. Heavy rains during the first week of July brought as much as 2 feet of rain to some places in southeastern Texas, resulting in massive flooding of three major river systems along the Gulf of Mexico. Please note that this story is in relation to the 'Before the Flooding in Southeast Texas' story and is match-framed for dissolves in post production. || ", "hits": 7 }, { "id": 2501, "url": "https://svs.gsfc.nasa.gov/2501/", "result_type": "Visualization", "release_date": "2002-08-15T12:00:00-04:00", "title": "Before the Flooding in Southeast Texas", "description": "Southeast of San Antonio, Texas, rivers that were barely discernible in satellite imagery acquired in this late June 2002 by Terra MODIS stand out clearly in the congruent Aqua MODIS image from July 24, 2002. Heavy rains during the first week of July brought as much as 2 feet of rain to some places in southeastern Texas, resulting in massive flooding of three major river systems along the Gulf of Mexico. Please note that this story is in relation to the 'Flooding in Southeast Texas' story and is match-framed for dissolves in post production. || ", "hits": 28 }, { "id": 2030, "url": "https://svs.gsfc.nasa.gov/2030/", "result_type": "Visualization", "release_date": "2000-12-18T12:00:00-05:00", "title": "TRMM: Covering Mozambique Flooding Using Daily Rainfall Measurements.", "description": "Red indicates areas of high rainfall. Blue indicates areas of low rainfall. Mozambique underwent major flooding during this time period. || ", "hits": 11 }, { "id": 2026, "url": "https://svs.gsfc.nasa.gov/2026/", "result_type": "Visualization", "release_date": "2000-12-11T12:00:00-05:00", "title": "TRMM: Covers Hurricane Floyd over North Carolina Using Daily Rainfall Measurements", "description": "TRMM daily rainfall measurements over the east coast (i.e., North Carolina) during Hurricane Floyd from 2/19/99 through 9/17/99. Red indicates areas of high rainfall. Blue indicates areas of low rainfall. North Carolina experienced major flooding during this time period. || ", "hits": 38 }, { "id": 2027, "url": "https://svs.gsfc.nasa.gov/2027/", "result_type": "Visualization", "release_date": "2000-12-11T12:00:00-05:00", "title": "TRMM: Covering Hurricane Floyd over North Carolina Using Monthly Average Rainfall Measurements", "description": "Monthly average rainfall measurements covering the East Coast (especially North Carolina) during Hurricane Floyd, from October 1998 through September 1999. || ", "hits": 27 }, { "id": 2028, "url": "https://svs.gsfc.nasa.gov/2028/", "result_type": "Visualization", "release_date": "2000-12-11T12:00:00-05:00", "title": "TRMM: Covers Hurricane Mitch over Honduras Using Daily Rainfall Measurements", "description": "TRMM daily rainfall measurements covering Honduras during Hurricane Mitch, from 4/7/98 through 11/5/98. Red indicates areas of high rainfall. Blue indicates areas of low rainfall. Honduras experienced major flooding during this time period. || ", "hits": 16 }, { "id": 2029, "url": "https://svs.gsfc.nasa.gov/2029/", "result_type": "Visualization", "release_date": "2000-12-11T12:00:00-05:00", "title": "TRMM: Covers Hurricane Mitch over Honduras Using Monthly Average Rainfall Measurements", "description": "Monthly average rainfall measurements over Honduras during Hurricane Mitch, from January 1998 through October 1998. || ", "hits": 22 }, { "id": 2031, "url": "https://svs.gsfc.nasa.gov/2031/", "result_type": "Visualization", "release_date": "2000-12-11T12:00:00-05:00", "title": "TRMM: Covers Mozambique Flooding Using Monthly Moving Average Rainfall Measurements", "description": "Monthly average rainfall measurements covering the Mozambique floods, from March 1999 through February 2000. || ", "hits": 15 }, { "id": 2002, "url": "https://svs.gsfc.nasa.gov/2002/", "result_type": "Visualization", "release_date": "2000-10-10T12:00:00-04:00", "title": "Terra/MODIS Views Flooding in Vietnam", "description": "View from the Terra/MODIS instrument of the flooding in Vietnam, Summer 2000. Ground coloration in the image was altered to enhance visibility of flooding. || Movie showing the change in water coverage in Vietnam from June to September of 2000. || a002002.00005_print.png (720x480) [484.5 KB] || a002002_pre.jpg (320x242) [9.2 KB] || a002002.webmhd.webm (960x540) [1.1 MB] || a002002.dv (720x480) [27.4 MB] || a002002.mp4 (640x480) [1.4 MB] || a002002.mpg (352x240) [6.6 MB] || ", "hits": 13 }, { "id": 615, "url": "https://svs.gsfc.nasa.gov/615/", "result_type": "Visualization", "release_date": "1999-11-17T12:00:00-05:00", "title": "SeaWiFS - North Carolina Flooding after Hurricane Floyd\n(Sept. 23, 1999)", "description": "SeaWiFS - North Carolina Flooding after Hurricane Floyd(Sept. 23, 1999) || a000615.00005_print.png (720x480) [709.2 KB] || a000615_thm.png (80x40) [6.2 KB] || a000615_pre.jpg (320x242) [15.3 KB] || a000615_pre_searchweb.jpg (320x180) [92.5 KB] || a000615.webmhd.webm (960x540) [3.8 MB] || a000615.dv (720x480) [61.8 MB] || a000615.mp4 (640x480) [3.4 MB] || a000615.mpg (352x240) [2.4 MB] || ", "hits": 36 }, { "id": 597, "url": "https://svs.gsfc.nasa.gov/597/", "result_type": "Visualization", "release_date": "1999-04-22T12:00:00-04:00", "title": "North Carolina Floods from Landsat: September 23, 1999", "description": "North Carolina Floods September 23, 1999 || a000597.00005_print.png (720x480) [532.5 KB] || a000597_thm.png (80x40) [5.7 KB] || a000597_pre.jpg (320x242) [10.0 KB] || a000597_pre_searchweb.jpg (320x180) [68.2 KB] || a000597.webmhd.webm (960x540) [11.7 MB] || a000597.dv (720x480) [164.8 MB] || a000597.mp4 (640x480) [9.0 MB] || a000597.mpg (352x240) [6.2 MB] || ", "hits": 40 } ] }