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        {
            "id": 5574,
            "url": "https://svs.gsfc.nasa.gov/5574/",
            "result_type": "Visualization",
            "release_date": "2026-03-02T00:00:00-05:00",
            "title": "GRACE FO Soil Moisture Within Continental United States: Monitoring Drought",
            "description": "The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission  is a joint Earth-science project launched in 2018 by NASA and the German Research Centre for Geosciences to continue the work of the earlier GRACE mission. It consists of two satellites flying about 137 mi (220 km) apart in the same orbit around Earth, constantly measuring tiny changes in the distance between them. These variations occur because changes in Earth’s gravity, caused by shifting masses such as melting ice sheets, groundwater depletion, and ocean circulation, slightly alter the satellites’ speeds and separation. By precisely tracking these changes, GRACE FO allows scientists to map how water moves across the planet, improving our understanding of climate change, sea-level rise, and global water resources.This visualization uses data from GRACE FO to create an index based on percentile dryness, categorizing the dregree of wetness or dryness within three domains: groundwater storage, root zone soil moisture, and surface moisture. It updates weekly, and extends back over a period of a year from the current week.This visualization is created for use within the Earth Information Center (EIC). || ",
            "hits": 322
        },
        {
            "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": 412
        },
        {
            "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": 53
        },
        {
            "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": 202
        },
        {
            "id": 31280,
            "url": "https://svs.gsfc.nasa.gov/31280/",
            "result_type": "Hyperwall Visual",
            "release_date": "2024-04-24T00:00:00-04:00",
            "title": "A Rough Harvest for Kansas Wheat",
            "description": "This is a hyperwall-ready version of the image published at: https://earthobservatory.nasa.gov/images/151487 || ",
            "hits": 12
        },
        {
            "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": 218
        },
        {
            "id": 5051,
            "url": "https://svs.gsfc.nasa.gov/5051/",
            "result_type": "Visualization",
            "release_date": "2022-12-12T00:00:00-05:00",
            "title": "Drought conditions set the stage for an intense fire season in California in 2021",
            "description": "NASA’s Earth Information System (EIS) analysis captures the onset of drought and heightened fire conditions in mid-August 2021, with seasonal deficits of rainfall, exceptionally dry soils, onset of acute vegetation stress, and reduced plant growth. || fire_hyro_VIZ01_final_HD.02350_print.jpg (1024x576) [135.1 KB] || fire_hyro_VIZ01_final_HD.02350_searchweb.png (320x180) [73.4 KB] || fire_hyro_VIZ01_final_HD.02350_thm.png (80x40) [5.1 KB] || fire_hyro_VIZ01_final_HD_1080p59.94.mp4 (1920x1080) [20.6 MB] || 1920x1080_16x9_60p (1920x1080) [256.0 KB] || fire_hyro_VIZ01_final_HD_1080p59.94.webm (1920x1080) [6.7 MB] || fire_hyro_VIZ01_final_4k_2160p59.94.mp4 (3840x2160) [66.2 MB] || 3840x2160_16x9_60p (3840x2160) [256.0 KB] || 9600x3240_16x9_30p (9600x3240) [256.0 KB] || ",
            "hits": 44
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        {
            "id": 5052,
            "url": "https://svs.gsfc.nasa.gov/5052/",
            "result_type": "Visualization",
            "release_date": "2022-12-12T00:00:00-05:00",
            "title": "Post-Fire: Assessing Downstream Effects on Hydrology and Water Quality (Thomas Fire)",
            "description": "Tracing Hydrological impacts of wildfires to understand downstream landslide risks; an example of the 2017 Thomas Fire, Southern California. || thomas_fire_FINAL_035_HD.04500_print.jpg (1024x576) [211.6 KB] || thomas_fire_FINAL_035_HD.04500_searchweb.png (320x180) [81.0 KB] || thomas_fire_FINAL_035_HD.04500_thm.png (80x40) [6.0 KB] || thomas_fire_FINAL_035_HD_1080p59.94.mp4 (1920x1080) [28.5 MB] || 1920x1080_16x9_60p (1920x1080) [256.0 KB] || thomas_fire_FINAL_035_HD_1080p59.94.webm (1920x1080) [6.9 MB] || thomas_fire_FINAL_035_4k_2160p59.94.mp4 (3840x2160) [90.0 MB] || 9600x3240_16x9_30p (9600x3240) [128.0 KB] || 3840x2160_16x9_60p (3840x2160) [256.0 KB] || ",
            "hits": 37
        },
        {
            "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": 101
        },
        {
            "id": 13910,
            "url": "https://svs.gsfc.nasa.gov/13910/",
            "result_type": "Produced Video",
            "release_date": "2021-08-18T14:00:00-04:00",
            "title": "Snack Time with NASA",
            "description": "Snack Time with NASA digs into the science behind what’s on your plate from a tasty cheese board, to seafood, to fresh produce, to chips and dip.Food can bring us a sense of home, and it connects people all around the world. With observations from space and aircraft, combined with high-end computer modeling, NASA scientists work together with partner agencies, organizations, farmers, ranchers, fishermen, and decision makers to understand the relationship between the Earth system and the environments that provide us food. || ",
            "hits": 34
        },
        {
            "id": 13646,
            "url": "https://svs.gsfc.nasa.gov/13646/",
            "result_type": "Produced Video",
            "release_date": "2020-06-19T00:00:00-04:00",
            "title": "NASA Satellites Help Farmers in Central America's Dry Corridor",
            "description": "Music: \"Beautiful Serenity,\" Samuel Karl Bohn & Anthony Phillips, Universal Production Music.Complete transcript available. || Elsalvador_thumb_print.jpg (1024x570) [271.1 KB] || Elsalvador_thumb_searchweb.png (320x180) [151.0 KB] || Elsalvador_thumb_thm.png (80x40) [11.9 KB] || ElSalvador_Twitter.mp4 (1920x1080) [43.5 MB] || ElSalvador_prores.mov (1920x1080) [2.7 GB] || ElSalvador_YouTube.mp4 (1920x1080) [325.4 MB] || ElSalvador_prores.webm (1920x1080) [27.3 MB] || elsalvador.en_US.srt [3.6 KB] || elsalvador.en_US.vtt [3.6 KB] || ",
            "hits": 23
        },
        {
            "id": 4783,
            "url": "https://svs.gsfc.nasa.gov/4783/",
            "result_type": "Visualization",
            "release_date": "2020-02-27T00:00:00-05:00",
            "title": "Precipitation Anomaly and Rift Valley fever (RVF) outbreaks in South Africa: 2008-2011",
            "description": "This visualization with corresponding data dashboard shows the relationship between precipitation anomalies and outbreaks of Rift Valley fever (RVF) during 2008 and 2011 in the South Africa region. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa to take a closer look at the patterns between ENSO events (El Niño and La Niña), above normal precipitation over land (blue) and RVF outbreak locations (orange pins). || PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg (1024x576) [97.8 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_searchweb.png (320x180) [57.6 KB] || PrecipRVF_SAfrica_Composite_3840x2160_3422_thm.png (80x40) [5.2 KB] || PrecipRVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [31.5 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || PrecipRVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [68.2 MB] || PrecipRVF_SAfrica_Composite_3840x2160_3422.tif (3840x2160) [4.0 MB] || PrecipRVF_SAfrica_Composite_3840x2160_p30.webm (3840x2160) [14.1 MB] || ",
            "hits": 26
        },
        {
            "id": 4724,
            "url": "https://svs.gsfc.nasa.gov/4724/",
            "result_type": "Visualization",
            "release_date": "2020-02-21T00:00:00-05:00",
            "title": "Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in Africa and Middle East during 2000-2018",
            "description": "Data visualization featuring vegetation index anomalies over Africa and Middle East and locations of Rift Valley Fever (RVF) outbreaks (orange pins) during the period of 2000-2018. Frames are provided in 4K resolution. || Africa_NDVIRVF_2000_2018_3840x2160_2430_print.jpg (1024x576) [78.8 KB] || Africa_NDVIRVF_2000_2018_3840x2160_2430_searchweb.png (320x180) [48.8 KB] || Africa_NDVIRVF_2000_2018_3840x2160_2430_thm.png (80x40) [4.4 KB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_1080p30.mp4 (1920x1080) [88.7 MB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_1080p30.webm (1920x1080) [25.5 MB] || Africa_NDVIRVF_2000_2018_Composite (3840x2160) [0 Item(s)] || Africa_NDVIRVF_2000_2018_3840x2160_2430.tif (3840x2160) [6.0 MB] || Africa_NDVIRVFComposite_2000_2018_3840x2160_p30.mp4 (3840x2160) [283.2 MB] || ",
            "hits": 37
        },
        {
            "id": 4747,
            "url": "https://svs.gsfc.nasa.gov/4747/",
            "result_type": "Visualization",
            "release_date": "2020-02-21T00:00:00-05:00",
            "title": "Vegetation index anomalies and Rift Valley fever (RVF) outbreaks in South Africa during 2009-2011",
            "description": "This visualization shows the relationship between vegetation index anomalies (Normalized Difference Vegetation Index - NDVI) data and outbreak locations of Rift Valley fever (RVf) during 2008 and 2011. The sequence starts in 2007 looking at the entire continent of Africa and zooms in the region of South Africa slowly to take a closer look at the above normal vegetation (green) and RVF outbreak locations (orange pins). Frames are provided in 4K resolution. || SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg (1024x576) [86.2 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_searchweb.png (320x180) [56.0 KB] || SAfrica_NDVIRVFwDates_3840x2160_1263_thm.png (80x40) [4.5 KB] || SAfrica_NDVIRVFComposite_1080p30.mp4 (1920x1080) [31.6 MB] || SAfrica_NDVIRVFComposite_1080p30.webm (1920x1080) [7.0 MB] || Composite (3840x2160) [0 Item(s)] || SAfrica_NDVIRVFwDates_3840x2160_1263.tif (3840x2160) [7.6 MB] || SAfrica_NDVIRVFComposite_3840x2160_p30.mp4 (3840x2160) [96.4 MB] || ",
            "hits": 35
        },
        {
            "id": 4784,
            "url": "https://svs.gsfc.nasa.gov/4784/",
            "result_type": "Visualization",
            "release_date": "2020-02-21T00:00:00-05:00",
            "title": "ENSO Teleconnections and Rift Valley fever (RVF) Outbreaks",
            "description": "During the 2008-2011 period, ENSO events brought changes to weather conditions across the globe that triggered infectious disease outbreaks, such as mosquito-borne Rift Valley fever (RVF) in South Africa. This visualization with corresponding data dashboard shows how Sea Surface Temperature (SST) anomalies in the equatorial Pacific Ocean (left) gave rise to Precipitation (center) and Vegetation (right) Index Anomalies in South Africa. During La Niña events, Southern Africa receives persistent and above normal rainfall, which floods habitats of RVF mosquito vectors triggering hatching of RVF virus infected eggs. The above-normal rainfall is followed by an increase in vegetation creating appropriate habitats for the mosquito vectors setting the stage for RVF outbreak activity, which in simple terms means an uptick in mosquito populations that cause infections of domestic livestock and human populations with the RVF virus. However, in rare cases there is a departure from this canonical response, as we can observe in 2009-2010, when a mild El Niño event resulted in above normal vegetaton and a large RVF outbreak in  South Africa. || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960_print.jpg (1024x576) [107.8 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png (320x180) [63.0 KB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_thm.png (80x40) [6.5 KB] || ENSO_Teleconnections (1920x1080) [0 Item(s)] || SST_Precip_NDVI_Dashboard_2008_2011_1920x1080_p30.mp4 (1920x1080) [22.7 MB] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_Teleconnections (3840x2160) [0 Item(s)] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.mp4 (3840x2160) [56.0 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_p30.webm (3840x2160) [10.2 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_2960.tif (3840x2160) [3.4 MB] || ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525.tif (3840x2160) [3.4 MB] || ",
            "hits": 32
        },
        {
            "id": 4785,
            "url": "https://svs.gsfc.nasa.gov/4785/",
            "result_type": "Visualization",
            "release_date": "2020-01-09T00:00:00-05:00",
            "title": "Sea Surface Temperature Anomalies and Patterns of Global Disease Outbreaks: 2009-2018 (4K version)",
            "description": "This webpage provides the 4K version of: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated), released on January 6, 2020.Content has been created for 4K display systems that can handle finer resolution and details. It is recommended to use content from this version  for HD (1920x1080) and lower resolutions. || ",
            "hits": 69
        },
        {
            "id": 4781,
            "url": "https://svs.gsfc.nasa.gov/4781/",
            "result_type": "Visualization",
            "release_date": "2020-01-06T00:00:00-05:00",
            "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (updated)",
            "description": "This visualization shows the variability in global sea surface temperature anomalies, the associated ENSO index timeline and locations of infectious disease outbreaks over the global land surface. || CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg (1024x576) [135.9 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_searchweb.png (320x180) [82.6 KB] || CompositeWLabel_2009_2018_1920x108060fps_1705_thm.png (80x40) [7.1 KB] || Composite_StrongElNino (1920x1080) [0 Item(s)] || Composite_StrongElNino (1920x1080) [0 Item(s)] || CompositeWLabel_2009_2018_1920x1080_p30.mp4 (1920x1080) [22.1 MB] || CompositeWLabel_2009_2018_1920x108060fps_1705.tif (1920x1080) [1.3 MB] || CompositeWLabel_2009_2018_1920x1080_p30.webm (1920x1080) [4.6 MB] || CompositeWLabel_2009_2018_1920x1080_p30.mp4.hwshow [205 bytes] || ",
            "hits": 83
        },
        {
            "id": 4765,
            "url": "https://svs.gsfc.nasa.gov/4765/",
            "result_type": "Visualization",
            "release_date": "2019-12-10T00:00:00-05:00",
            "title": "Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018",
            "description": "El Niño is an irregularly recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions. This visualization captures monthly Sea Surface Temperature (SST) anomalies around the world from 2009-2018, along with locations of global disease outbreaks and a corresponding timeline showcasing the Niño 3.4 Index. The Niño 3.4 Index represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the above average El Niño years, in which sea surface temperature anomalies peaked during 2015-2016. || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg (1024x576) [130.6 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_searchweb.png (320x180) [79.7 KB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_thm.png (80x40) [7.0 KB] || Composite (1920x1080) [0 Item(s)] || Composite (1920x1080) [0 Item(s)] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4 (1920x1080) [23.0 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769.tif (1920x1080) [1.3 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.webm (1920x1080) [4.7 MB] || SSTENSO_Diseases_Comp_2009_2018_1920x1080_p30.mp4.hwshow [211 bytes] || ",
            "hits": 106
        },
        {
            "id": 13242,
            "url": "https://svs.gsfc.nasa.gov/13242/",
            "result_type": "Produced Video",
            "release_date": "2019-07-01T11:00:00-04:00",
            "title": "Using NASA Data to Monitor Drought and Food Insecurity",
            "description": "NASA’s satellite imagery and model forecasts play an important role in monitoring the performance of crops worldwide and preparing for food shortages. NASA's view from space helps government agencies forecast food insecurity, like during the drought in Southern Africa in 2018. || ",
            "hits": 25
        },
        {
            "id": 13198,
            "url": "https://svs.gsfc.nasa.gov/13198/",
            "result_type": "Produced Video",
            "release_date": "2019-05-01T13:00:00-04:00",
            "title": "Human Influence on Global Droughts Goes Back 100 Years",
            "description": "Music: In Light of Things by Matthew Charles Gilbert DavidsonComplete transcript available. || Hydroclimate_Thumbnail.png (1920x1080) [3.1 MB] || Hydroclimate_Thumbnail_print.jpg (1024x576) [166.5 KB] || Hydroclimate_Thumbnail_searchweb.png (320x180) [114.8 KB] || Hydroclimate_Thumbnail_thm.png (80x40) [7.6 KB] || Hydroclimate_highres.mp4 (1920x1080) [330.6 MB] || Hydroclimate_V4.en_US.srt [1.8 KB] || Hydroclimate_V4.en_US.vtt [1.8 KB] || Hydroclimate.webm [0 bytes] || Hydroclimate.mov (1920x1080) [2.5 GB] || ",
            "hits": 76
        },
        {
            "id": 4693,
            "url": "https://svs.gsfc.nasa.gov/4693/",
            "result_type": "Visualization",
            "release_date": "2019-02-28T09:00:00-05:00",
            "title": "Precipitation Anomaly and Dengue Outbreaks in South East Asia: 2015-2016",
            "description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between precipitation anomaly in Southeast Asia and dengue outbreaks. Drier than normal habitats drew mosquitoes into populated, urban areas containing the open water needed for laying eggs. As the air warmed, mosquitoes also grew hungrier and reached sexual maturity more quickly, resulting in an increase in mosquito bites. || SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg (1024x576) [75.8 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_searchweb.png (320x180) [52.9 KB] || SEAsia_PrecipDengueComposite_1920x1080_1211_thm.png (80x40) [5.4 KB] || SEAsia_PrecipDengueComposite_1920x1080_p30.webm (1920x1080) [6.4 MB] || SEAsia_PrecipDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_PrecipDengueComposite_1920x1080_p30.mp4 (1920x1080) [14.8 MB] || SEAsia_PrecipDengueComposite_1920x1080_1211.tif (1920x1080) [1.5 MB] || SEAsia_PrecipDengueComposite (3840x2160) [0 Item(s)] || ",
            "hits": 33
        },
        {
            "id": 4695,
            "url": "https://svs.gsfc.nasa.gov/4695/",
            "result_type": "Visualization",
            "release_date": "2019-02-28T09:00:00-05:00",
            "title": "Niño 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017",
            "description": "This visualization captures Sea Surface Temperature (SST) anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 SST Index region (5N-5S, 120W-170W), which represents average equatorial sea surface temperatures in the Pacific Ocean from about the International Date Line to the coast of South America. Highlighted in the timeline are the El Niño years, in which sea surface temperature anomalies peaked: 1982-1983, 1997-1998, and 2015-2016. || NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg (1024x576) [104.9 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_searchweb.png (320x180) [72.1 KB] || NINO3.4SST_FlatMapComposite_1920x1080_00932_thm.png (80x40) [6.8 KB] || SST_Nino3.4Index_1982_2017_Composite (1920x1080) [0 Item(s)] || NINO3.4SST_FlatMapComposite_1920x1080_p30.mp4 (1920x1080) [57.2 MB] || NINO3.4SST_FlatMapComposite_1920x1080_00932.tif (1920x1080) [1.4 MB] || NINO3.4SST_FlatMapComposite_1920x1080_p30.webm (1920x1080) [9.3 MB] || SSTNino3.4Index_1982_2017_Composite (3840x2160) [0 Item(s)] || ",
            "hits": 351
        },
        {
            "id": 4696,
            "url": "https://svs.gsfc.nasa.gov/4696/",
            "result_type": "Visualization",
            "release_date": "2019-02-28T09:00:00-05:00",
            "title": "Land Surface Temperature Anomaly and Dengue Outbreaks in South East Asia Region: 2015-2016",
            "description": "The 2015-2016 El Niño event brought changes to weather conditions across the globe that triggered regional disease outbreaks, including mosquito-borne dengue fever in Southeast Asia. This visualization with corresponding timeplot graph reveals the relationship between land surface temperature anomaly in Southeast Asia and dengue outbreaks. Higher than normal land surface temperatures results in an increase of dengue reported locations. || SEAsia_LSTDiseases_1920x1080_1730_print.jpg (1024x576) [85.1 KB] || SEAsia_LSTDiseases_1920x1080_1730_searchweb.png (320x180) [54.4 KB] || SEAsia_LSTDiseases_1920x1080_1730_thm.png (80x40) [5.3 KB] || SEAsia_LSTDengue_Composite (1920x1080) [0 Item(s)] || SEAsia_LSTDiseases_1920x1080_p30.mp4 (1920x1080) [33.8 MB] || SEAsia_LSTDiseases_1920x1080_1730.tif (1920x1080) [1.7 MB] || SEAsia_LSTDiseases_1920x1080_p30.webm (1920x1080) [6.2 MB] || SEAsia_LSTDengue_Composite (3840x2160) [0 Item(s)] || ",
            "hits": 25
        },
        {
            "id": 4697,
            "url": "https://svs.gsfc.nasa.gov/4697/",
            "result_type": "Visualization",
            "release_date": "2019-02-28T09:00:00-05:00",
            "title": "ENSO teleconnections in South East Asia for the period of 2015-2016",
            "description": "The 2015-2016 strong El Niño event brought changes to weather conditions across the globe that triggered regional infectious disease outbreaks, including mosquito-borne dengue fever in South East Asia. This visualization with corresponding multi-plot graph shows how Sea Surface Temperature anomalies in the equatorial Pacific Ocean (left), resulted in anomalous drought conditions (center) and increase in land surface temperatures (right) in South East Asia.  During the 2015-2016 El Niño event, the South East Asia region received below than normal precipitation resulting in drier and warner than normal conditions, which increased the populations of mosquito vectors in urban areas, where there are open water storage containers providing ideal habitats for mosquito production. In addition, the higher than normal temperature on land shortens the maturation time of larvae to adult mosquitos and induces frequent blood feeding/biting of humans by mosquito vectors resulting in the amplification of dengue disease outbreaks over the South East Asia region. || SST_LST_Precip_2014_2016_Comp_print.jpg (1024x576) [82.9 KB] || SST_LST_Precip_2014_2016_Comp_searchweb.png (320x180) [51.5 KB] || SST_LST_Precip_2014_2016_Comp_thm.png (80x40) [6.0 KB] || SST_Precip_LST_Plot_Composite (1920x1080) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4 (1920x1080) [9.7 MB] || SST_LST_Precip_2014_2016_Comp.tif (1920x1080) [1.1 MB] || SST_LST_Precip_2014_2016_Comp_1080p30.webm (1920x1080) [4.2 MB] || TeleconnectionsSEAsia (3840x2160) [0 Item(s)] || SST_LST_Precip_2014_2016_Comp_1080p30.mp4.hwshow [203 bytes] || ",
            "hits": 80
        },
        {
            "id": 4634,
            "url": "https://svs.gsfc.nasa.gov/4634/",
            "result_type": "Visualization",
            "release_date": "2018-06-28T09:00:00-04:00",
            "title": "Global Fire Weather Database",
            "description": "The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, which tracks the dryness of three general fuel classes, and the potential behavior of a fire if it were to start. Each day, FWI values are calculated from global weather data, including satellite rainfall data from the Global Precipitation Measurement (GPM) mission.The FWI System is the most widely used fire danger rating system in the world, and has been adopted for different boreal, temperate and tropical fire environments. GFWED provides a globally consistent fire weather dataset for fire researchers and managers to apply locally. The Fire Weather Index component is suitable as a general index of fire danger. Globally, shifts in continental-scale fire activity follow seasonal changes in the FWI. Over South America and Africa, regions of high FWI and active agricultural burning shift with the tropical rain belts, seen in the GPM precipitation overlay. Over North America and Eurasia, the FWI will ‘activate’ in the spring, and shows how week-to-week surges in fire activity can be driven by high FWI values. || ",
            "hits": 99
        },
        {
            "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": 22
        },
        {
            "id": 30730,
            "url": "https://svs.gsfc.nasa.gov/30730/",
            "result_type": "Hyperwall Visual",
            "release_date": "2015-12-16T12:00:00-05:00",
            "title": "High-Resolution Soil Moisture Maps",
            "description": "These maps combine data from the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) with other satellite and ground-based measurements to model the relative amount of water stored at two different levels: at plant root level and underground. The wetness, or water content, of each layer is compared to the average between 1948 and 2009. The darkest red regions represent dry conditions that should occur only 2 percent of the time (about once every 50 years). All of the maps are experimental products funded by NASA’s Applied Sciences Program and developed by scientists at NASA’s Goddard Space Flight Center and the National Drought Mitigation Center. The maps do not attempt to represent human consumption of water; but rather, they show changes in water storage related to weather, climate, and seasonal patterns. || ",
            "hits": 76
        },
        {
            "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": 25
        },
        {
            "id": 4338,
            "url": "https://svs.gsfc.nasa.gov/4338/",
            "result_type": "Visualization",
            "release_date": "2015-07-30T17:00:00-04:00",
            "title": "Global Terrestrial Water Storage Anomaly",
            "description": "Slow zoom out starting over the United States revealing the rest of the world. || grace_world_anom.6000_print.jpg (1024x576) [118.7 KB] || grace_world_anom.6.mp4 (1920x1080) [3.7 MB] || 1920x1080_16x9_30p (1920x1080) [32.0 KB] || grace_world_anom.6.webm (1920x1080) [896.4 KB] || grace_world_anom.6.mp4.hwshow [45 bytes] || ",
            "hits": 38
        },
        {
            "id": 4270,
            "url": "https://svs.gsfc.nasa.gov/4270/",
            "result_type": "Visualization",
            "release_date": "2015-02-12T13:30:00-05:00",
            "title": "Megadroughts in U.S. West Projected to be Worst of the Millennium",
            "description": "Soil moisture (surface down to 30cm) from 1950 to 2095 based on a 10 year moving average of 17 CMIP5 models using a high future emissions scenario (RCP 8.5).  The year shown is the middle of the 10-year moving average.This video is also available on our YouTube channel. || print10yr_-3to3_rcp85_1700_print.jpg (1024x576) [75.8 KB] || print10yr_-3to3_rcp85_1700.png (5760x3240) [10.6 MB] || 10yr_-3to3_rcp85_1700_searchweb.png (320x180) [48.3 KB] || 10yr_-3to3_rcp85_1700_thm.png (80x40) [4.8 KB] || 10yr_-3to3_rcp85.webm (1920x1080) [1.7 MB] || 10yr_-3to3_rcp85.mp4 (1920x1080) [3.3 MB] || 10yr_-3to3_rcp85 (1920x1080) [32.0 KB] || 10yr_-3to3_rcp85_comp_1080p30.mp4 (1920x1080) [3.6 MB] || comp_rcp85 (1920x1080) [32.0 KB] || 10yr_-3to3_rcp85.m4v (640x360) [2.0 MB] || 10yr_-3to3_rcp85.hwshow [195 bytes] || print10yr_-3to3_rcp85_1700.hwshow [205 bytes] || ",
            "hits": 238
        },
        {
            "id": 30177,
            "url": "https://svs.gsfc.nasa.gov/30177/",
            "result_type": "Hyperwall Visual",
            "release_date": "2013-10-17T12:00:00-04:00",
            "title": "Measuring Soil Moisture from Space",
            "description": "These maps combine data from the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) with other satellite and ground-based measurements to model the relative amount of water stored at three different levels: at the surface, at plant root level and underground from January 2003 to December 2014. The wetness, or water content, of each layer is compared to the average between 1948 and 2009. The darkest red regions represent dry conditions that should occur only 2 percent of the time (about once every 50 years). All of the maps are experimental products funded by NASA’s Applied Sciences Program and developed by scientists at NASA’s Goddard Space Flight Center and the National Drought Mitigation Center. The maps do not attempt to represent human consumption of water; but rather, they show changes in water storage related to weather, climate, and seasonal patterns. || ",
            "hits": 33
        },
        {
            "id": 3764,
            "url": "https://svs.gsfc.nasa.gov/3764/",
            "result_type": "Visualization",
            "release_date": "2010-08-19T14:00:00-04:00",
            "title": "How Much Carbon do Plants Take from the Atmosphere?",
            "description": "Plant life converts atmospheric carbon dioxide into biomass through photosynthesis, a process called 'fixing'. This is one of the main ways in which carbon dioxide is removed from the atmosphere and is a major part of the carbon cycle. The amount of carbon removed is called the gross primary productivity (GPP), and the change in GPP due to rising global temperatures is very important factor in the response of the Earth to climate change.Data from the MODIS instrument on NASA's Terra satellite has been recently used to calculate the GPP for the whole world for the last 10 years. This animation shows a time sequence of GPP on land as measured by MODIS during the years 2000 through 2009. Two things to note are the year-long productivity of the tropical regions and the large seasonal productivity in the northern hemisphere. A close look at the animation also reveals major urban areas for which the productivity is negligible.For a look at why the decade from 2000 through 2009 meant lower productivity, see the page 'How has the Atmospheric Carbon Uptake from Plants Changed in the Last Decade?' || ",
            "hits": 107
        },
        {
            "id": 3765,
            "url": "https://svs.gsfc.nasa.gov/3765/",
            "result_type": "Visualization",
            "release_date": "2010-08-19T14:00:00-04:00",
            "title": "How has the Atmospheric Carbon Uptake from Plants Changed in the Last Decade?",
            "description": "Plant life converts atmospheric carbon dioxide into biomass through photosynthesis. This process, called fixing, is one of the main ways in which carbon dioxide is removed from the atmosphere and is a major part of the carbon cycle. Plants release a fraction of this fixed carbon by respiration in order to get energy to live and to move carbon to other organs. The amount of carbon removed minus the amount of carbon respired is called the net primary productivity (NPP) and is the amount of carbon turned into biomass.The change in NPP due to rising global temperatures is a very important factor in the response of the Earth to climate change. Measurements of radiation and leaf area from the MODIS instrument on NASA's Terra satellite have recently been used to calculate the change in NPP for the whole world for the last 10 years. This animation shows a time sequence of annual NPP deviation from normal (or 'anomaly') on land as measured by MODIS during the years 2000 through 2009. Annual NPP, especially its departures from a long-term mean condition, will demonstrate the effects of environmental drivers such as ENSO (El Niño) events, climate change, droughts, pollution episodes, land degradation, and agricultural expansion.Earlier studies of productivity between 1982 and 1999 showed that prouctivity went up as global temperatures rose, because longer, warmer growing seasons were better for plant growth. This new study indicates that this is still true in the northern hemisphere, but that increased temperatures have meant increased drought and dryness in the tropics and the southern hemisphere. As a result, the global net productivity has actually decreased in the period from 2000 through 2009.Regionally, negative annual NPP anomalies were mainly caused by large-scale droughts. In 2000, droughts reduced NPP in North America and China; in 2002, droughts reduced NPP in North America and Australia; in 2003, drought caused by a major heat wave reduced NPP in Europe; in 2005, severe droughts in the Amazon, Africa, and Australia greatly reduced both regional and global NPP; from 2007 through 2009 over large parts of Australia, continuous droughts reduced continental NPP.For an animation of daily productivity, see the page How Much Carbon do Plants Take from the Atmosphere?. || ",
            "hits": 112
        },
        {
            "id": 3651,
            "url": "https://svs.gsfc.nasa.gov/3651/",
            "result_type": "Visualization",
            "release_date": "2009-10-07T12:00:00-04:00",
            "title": "World Droughts From 2005 to 2009 Versus Where Crops are Grown",
            "description": "The Global Inventory Monitoring and Modeling Studies (GIMMS) group at NASA Goddard Space Flight Center (NASA/GSFC) provides United States Department of Agriculture/Foreign Agricultural Service (USDA/FAS) with global data stream of NDVI that spans over two decades (1981-present). The GIMMS NDVI is derived from measurements made by the Advanced Very High Resolution Radiometer (AVHRR), Global Area Coverage (GAC) data from the National Atmospheric Oceanic Administration (NOAA) polar orbiting series of satellites. GIMMS has inter-calibrated the data from the NOAA-AVHRR satellite series and performed atmospheric correction to minimize the effects of volcanic aerosols to produce and maintain a consistent NDVI archive. The NDVI archive from GIMMS provides the historic database for monitoring the response of vegetation to climatic conditions.Linking the MODIS data to the long-term GIMMS AVHRR/NDVI, archive and SPOT Vegetation sensor data is a critical component of this project providing a consistent multi-source long-term data record for agricultural monitoring. This allows FAS analysts to compare current data with the spatial extent and severity of NDVI anomalies associated with heat stress, droughts and floods associated with crop failures. || ",
            "hits": 14
        }
    ]
}