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Weather changes associated with the ENSO phenomenon result in climate anomalies related to each other, such as rainfall (increase or lack of thereof) and land surface temperature anomaly conditions that trigger outbreaks of infectious diseases of public health concern in different regions around the world. These distant weather effects are called teleconnections. Therefore, the effects of ENSO are called ENSO teleconnections, highlighting that warmer or colder than usual ocean temperatures in the equatorial Pacific Ocean with extents (5N-5S, 120W-170W) affect areas far from the source typically 2-3 months after.

During the last 20 years NASA scientist Dr. Assaf Anyamba and colleagues have been tracking ENSO events (please see: Niño 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017) and studying associated teleconnections by monitoring various climate datasets, among them Sea Surface Temperature, Precipitation and Land Surface Anomaly datasets from NASA and National Oceanic and Atmospheric Administration (NOAA). At the same time, the science team has been collecting, cataloguing and analyzing patterns and sources of infectious disease outbreaks worldwide.

Dr. Anyamba and colleagues conducted a scientific study - the first one to comprehensively assess the public health impacts of the major climate event on a global scale - that was open access published in the journal Nature Scientific Reports, with the title Global Disease Outbreaks Associated with the 2015-2016 El Niño event. According to the study, the 2015-2016 El Niño event brought weather conditions that triggered infectious disease outbreaks in ENSO teleconnected regions around the world, such as plague and hantavirus in Colorado and New Mexico (in 2015), cholera in East Africa’s Tanzania (during 2015- 2016), and dengue fever in Brazil and Southeast Asia (during 2015) among others. These outbreaks have been visualized with data in web entry: Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018 (4K version)).

The data visualization featured on this page with corresponding multiplot graph illustrates the relationship between the 2015-2016 El Niño event and the amplification of dengue outbreaks over the region of South East Asia for the same period. The visualization comprises of two parts:

Top:\r
On the top part we can see three separate representations of Earth (spheres) with three distinct datasets. On the left sphere Sea Surface Temperature (SST) anomaly data are mapped over water and our planet is rotated so that we can observe changes of temperature (increase/red hues, decrease/blue hues) over the equatorial Pacific Ocean. The strong ENSO (El Niño) event during May 2015-May 2016 is manifested in the visualization as increased temperature over water (red hues) in the equatorial Pacific Ocean, where the Nino 3.4 Index SST region (5N-5S, 120W-170W) is located. In the middle sphere, our planet is rotated so that we can see Precipitation anomaly data (dry/brown to wet/teal) over land in the South East Asia region. On the right sphere, Land Surface Temperature (LST) anomaly data (low/blue to high/red) are mapped on land.\r
\r
The three distinct representations of each dataset are accompanied right below each sphere with the corresponding colorbar information (for example, Sea Surface Temperature colorbar, Precipitation Anomaly colorbar and Land Surface Temperature Anomaly colorbar)\r

Bottom:\r
On the bottom, a synchronized multiplot of Precipitation Anomaly (mm) and Temperature Anomaly (Co ) for the same period, tracks and visualizes indicators from three sources represented in the top part of the visualization. The three indicators are:\r


The multiplot references both temperature-related anomaly datasets: Sea Surface Temperature (SST) Anomaly and Land Surface Temperature (LST) Anomaly data to the right axis of the multiplot. Temperature Anomaly values are referenced to the left axis of the multiplot. The overall design of this data visualization was chosen in an effort to make visible the relationships between the three datasets and their indicators concurrently. As time progresses, labels and visual cues in the multiplot guide the viewer about the occurrence and duration of the El Niño event, its different phases (Moderate, Strong, Very Strong) and the Dengue Amplification Period.

To explain a bit further the weather patterns and teleconnections, lets take a closer look at the sequence of events and their timelines. The El Niño event (May 2015-May 2016) is manifested over the equatorial Pacific Ocean, as increased temperature (left sphere, red hues) on the top part of the visualization and with the orange area graph on the bottom. During the same period, the South East Asia region receives below than normal precipitation (middle sphere, brown hues) resulting in drier than usual conditions, which in turn caused an anomalous increase in land surface temperature (left sphere, red hues). The dry and hot conditions in the South East Asia region were conducive for the upsurge in 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 Dengue Amplification Period (July 2015-March 2016) over the South East Asia region. Dengue fever is a painful, debilitating disease and is transmitted between people by mosquito vectors. It is a predominantly tropical disease affecting approximately 400 million people annually in many areas of the global tropics including South America and South East Asia. Dengue epidemics worldwide occur in urban areas where there is a coincidence of large numbers of dengue vectors (Aedes aegypti) and people with no immunity to one of the virus types.

The impact of precipitation and land surface temperature anomalies on the dengue outbreaks over the South East Asia region have been visualized with data on the following two web entries:

The strong relationship between ENSO events and disease outbreaks underscores the importance of seasonal forecasts. Since disease outbreaks typically manifest 2-3 months after the start of El Niño and La Nina events, early and regular climate monitoring, paired with the use of monthly and seasonal climate forecasts become significant tools for disease control and prevention. Findings of the scientific study by Dr. Assaf Anyamba and colleagues, suggests that by monitoring monthly climate datasets, country public health agencies such as CDC and international organizations such as the United Nations' World Health Organization and Food and Agriculture Organizations, can utilize early warning forecasts to undertake preventive measures to minimize the spread of ecologically coupled diseases.\r

Data Sources


Supported with funding from the Defense Threat Reduction Agency's (DTRA) Joint Science and Technology Office for Chemical and Biological Defense (JSTO-CBD) Biosurveillance Ecosystem (BSVE) Program (HDTRA1-16-C-0045) and the Defense Health Agency-Armed Forces Health Surveillance Branch (AFHSB) Global Emerging Infections Surveillance and Response System (GEIS) under Project # P0072_19_NS.

The rest of this webpage offers additional versions, frames, layers and colorbar information associated with the development of this data-driven visualization.", "items": [], "extra_data": {} }, { "id": 324208, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324208", "widget": "Video player", "title": "", "caption": "", "description": "This visualization is similar to the one above, except the timeplot graph is unveiled for the entire period 2015-2016.

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. 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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.", "width": 1920, "height": 1080, "pixels": 2073600 } }, { "id": 240957, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398289, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_30p/TeleconnectionsSEAsia_PlotOn/", "filename": "TeleconnectionsSEAsia_PlotOn", "media_type": "Frames", "alt_text": "This visualization is similar to the one above, except the timeplot graph is unveiled for the entire period 2015-2016. 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.", "width": 3840, "height": 2160, "pixels": 8294400 } }, { "id": 438275, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 1100018, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/SST_LST_Precip_2014_2016_GraphOn_Comp_1080p30.mp4.hwshow", "filename": "SST_LST_Precip_2014_2016_GraphOn_Comp_1080p30.mp4.hwshow", "media_type": "HyperwallShow", "alt_text": "", "width": 0, "height": 0, "pixels": null } } ], "extra_data": {} }, { "id": 324209, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324209", "widget": "Single image", "title": "", "caption": "", "description": "This set of frames provides the Sea Surface Temperature Anomaly layer for the period 2014-2016, with alpha channel.", "items": [ { "id": 240964, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398291, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/SSTAnomaly_wAlpha_2014_2016.0000_print.jpg", "filename": "SSTAnomaly_wAlpha_2014_2016.0000_print.jpg", "media_type": "Image", "alt_text": "This set of frames provides the Sea Surface Temperature Anomaly layer for the period 2014-2016, with alpha channel.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 240963, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398290, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_60p/SSTAnomaly_wAlpha/", "filename": "SSTAnomaly_wAlpha", "media_type": "Frames", "alt_text": "This set of frames provides the Sea Surface Temperature Anomaly layer for the period 2014-2016, with alpha channel.", "width": 3840, "height": 2160, "pixels": 8294400 } } ], "extra_data": {} }, { "id": 324210, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324210", "widget": "Single image", "title": "", "caption": "", "description": "This set of frames provides the dates layer for the Sea Surface Temperature Anomaly visuals. ", "items": [ { "id": 240966, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398293, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/SSTAnomalyDates2014_2016.0000_print.jpg", "filename": "SSTAnomalyDates2014_2016.0000_print.jpg", "media_type": "Image", "alt_text": "This set of frames provides the dates layer for the Sea Surface Temperature Anomaly visuals. ", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 240965, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398292, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_60p/SSTAnomaly_Dates/", "filename": "SSTAnomaly_Dates", "media_type": "Frames", "alt_text": "This set of frames provides the dates layer for the Sea Surface Temperature Anomaly visuals. ", "width": 3840, "height": 2160, "pixels": 8294400 } } ], "extra_data": {} }, { "id": 324211, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324211", "widget": "Single image", "title": "", "caption": "", "description": "Colorbar for sea surface temperature anomaly.", "items": [ { "id": 240967, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398294, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/SST_anomaly.png", "filename": "SST_anomaly.png", "media_type": "Image", "alt_text": "Colorbar for sea surface temperature anomaly.", "width": 640, "height": 180, "pixels": 115200 } } ], "extra_data": {} }, { "id": 324212, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324212", "widget": "Single image", "title": "", "caption": "", "description": "Monthly preicipitation anomaly in the Asia Region for the period of 2014-2016. This set of frames are provided with alpha channel.", "items": [ { "id": 240969, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398296, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/PrecipAnomalySEAsia2014_2016.0000_print.jpg", "filename": "PrecipAnomalySEAsia2014_2016.0000_print.jpg", "media_type": "Image", "alt_text": "Monthly preicipitation anomaly in the Asia Region for the period of 2014-2016. This set of frames are provided with alpha channel.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 240968, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398295, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_60p/PrecipAnomaly_wAlpha/", "filename": "PrecipAnomaly_wAlpha", "media_type": "Frames", "alt_text": "Monthly preicipitation anomaly in the Asia Region for the period of 2014-2016. This set of frames are provided with alpha channel.", "width": 3840, "height": 2160, "pixels": 8294400 } } ], "extra_data": {} }, { "id": 324213, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324213", "widget": "Single image", "title": "", "caption": "", "description": "Colorbar for precipitation anomaly.", "items": [ { "id": 240970, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398297, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/Precipitation_Anomaly.png", "filename": "Precipitation_Anomaly.png", "media_type": "Image", "alt_text": "Colorbar for precipitation anomaly.", "width": 640, "height": 180, "pixels": 115200 } } ], "extra_data": {} }, { "id": 324214, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324214", "widget": "Single image", "title": "", "caption": "", "description": "Monthly Land Surface Temperature Anomaly data in the Asia region during 2014-2016. This set of frames is provided with alpha channel.", "items": [ { "id": 240972, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398299, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/LSTAnomalySEAsia2014_2016.0000_print.jpg", "filename": "LSTAnomalySEAsia2014_2016.0000_print.jpg", "media_type": "Image", "alt_text": "Monthly Land Surface Temperature Anomaly data in the Asia region during 2014-2016. This set of frames is provided with alpha channel.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 240971, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398298, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_60p/LSTAnomaly_wAlpha/", "filename": "LSTAnomaly_wAlpha", "media_type": "Frames", "alt_text": "Monthly Land Surface Temperature Anomaly data in the Asia region during 2014-2016. This set of frames is provided with alpha channel.", "width": 3840, "height": 2160, "pixels": 8294400 } } ], "extra_data": {} }, { "id": 324215, "url": "https://svs.gsfc.nasa.gov/4697/#media_group_324215", "widget": "Single image", "title": "", "caption": "", "description": "This set of frames provides the dates layer for the Land Surface Temperature Anomaly visuals. Frames are provided with alpha channel.", "items": [ { "id": 240974, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398301, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/LSTAnomalySEAsiaDates2014_2016.0000_print.jpg", "filename": "LSTAnomalySEAsiaDates2014_2016.0000_print.jpg", "media_type": "Image", "alt_text": "This set of frames provides the dates layer for the Land Surface Temperature Anomaly visuals. Frames are provided with alpha channel.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 240973, "type": "media", "extra_data": null, "title": null, "caption": null, "instance": { "id": 398300, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004697/frames/3840x2160_16x9_60p/LSTAnomaly_Dates/", "filename": "LSTAnomaly_Dates", "media_type": "Frames", "alt_text": "This set of frames provides the dates layer for the Land Surface Temperature Anomaly visuals. 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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 vegetaion over land (green) and RVF outbreak locations (orange pins). || NDVI_RVF_SAfrica_Composite_3840x2160_2657_print.jpg (1024x576) [102.7 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_searchweb.png (320x180) [57.8 KB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657_thm.png (80x40) [5.0 KB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.mp4 (1920x1080) [35.6 MB] || NDVI_RVF_SAfrica_Composite_1920x1080p30.webm (1920x1080) [7.1 MB] || Composite (3840x2160) [0 Item(s)] || Composite (3840x2160) [0 Item(s)] || NDVI_RVF_SAfrica_Composite_3840x2160_p30.mp4 (3840x2160) [72.6 MB] || NDVI_RVF_SAfrica_Composite_3840x2160_2657.tif (3840x2160) [31.6 MB] || ", "release_date": "2020-03-04T00:00:00-05:00", "update_date": "2025-02-02T00:13:09.426850-05:00", "main_image": { "id": 386751, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004782/NDVI_RVF_SAfrica_Composite_3840x2160_2657_print.jpg", "filename": "NDVI_RVF_SAfrica_Composite_3840x2160_2657_print.jpg", "media_type": "Image", "alt_text": "This visualization with corresponding data dashboard shows the relationship between vegetation index 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 vegetaion over land (green) and RVF outbreak locations (orange pins).", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4783, "url": "https://svs.gsfc.nasa.gov/4783/", "page_type": "Visualization", "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] || ", "release_date": "2020-02-27T00:00:00-05:00", "update_date": "2025-02-02T22:45:20.294104-05:00", "main_image": { "id": 386570, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004783/PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg", "filename": "PrecipRVF_SAfrica_Composite_3840x2160_3422_print.jpg", "media_type": "Image", "alt_text": "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). ", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4724, "url": "https://svs.gsfc.nasa.gov/4724/", "page_type": "Visualization", "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] || ", "release_date": "2020-02-21T00:00:00-05:00", "update_date": "2025-02-02T00:12:08.568503-05:00", "main_image": { "id": 392091, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004724/Africa_NDVIRVF_2000_2018_3840x2160_2430_print.jpg", "filename": "Africa_NDVIRVF_2000_2018_3840x2160_2430_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4747, "url": "https://svs.gsfc.nasa.gov/4747/", "page_type": "Visualization", "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] || ", "release_date": "2020-02-21T00:00:00-05:00", "update_date": "2025-02-02T00:12:35.273066-05:00", "main_image": { "id": 392107, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004747/SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg", "filename": "SAfrica_NDVIRVFwDates_3840x2160_1263_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4784, "url": "https://svs.gsfc.nasa.gov/4784/", "page_type": "Visualization", "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] || ", "release_date": "2020-02-21T00:00:00-05:00", "update_date": "2025-02-02T00:13:13.644499-05:00", "main_image": { "id": 386811, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004784/ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png", "filename": "ENSO_TeleconnectionsRVF_2008_2011_3840x2160_3525_searchweb.png", "media_type": "Image", "alt_text": "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.", "width": 320, "height": 180, "pixels": 57600 } }, { "id": 4785, "url": "https://svs.gsfc.nasa.gov/4785/", "page_type": "Visualization", "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. || ", "release_date": "2020-01-09T00:00:00-05:00", "update_date": "2025-02-02T00:13:15.129941-05:00", "main_image": { "id": 388258, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004785/CompositeWLabel_2009_2018_3840x2160_30fps_0852_print.jpg", "filename": "CompositeWLabel_2009_2018_3840x2160_30fps_0852_print.jpg", "media_type": "Image", "alt_text": "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. Content is available in 4K resolution.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4781, "url": "https://svs.gsfc.nasa.gov/4781/", "page_type": "Visualization", "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] || ", "release_date": "2020-01-06T00:00:00-05:00", "update_date": "2025-02-02T00:13:06.818408-05:00", "main_image": { "id": 388349, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004781/CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg", "filename": "CompositeWLabel_2009_2018_1920x108060fps_1705_print.jpg", "media_type": "Image", "alt_text": "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. ", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4765, "url": "https://svs.gsfc.nasa.gov/4765/", "page_type": "Visualization", "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] || ", "release_date": "2019-12-10T00:00:00-05:00", "update_date": "2025-02-02T00:12:46.498564-05:00", "main_image": { "id": 388873, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004765/SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg", "filename": "SSTENSO_Diseases_Comp_2009_2018_1920x1080_0769_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4693, "url": "https://svs.gsfc.nasa.gov/4693/", "page_type": "Visualization", "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)] || ", "release_date": "2019-02-28T09:00:00-05:00", "update_date": "2025-02-02T00:11:30.105895-05:00", "main_image": { "id": 397408, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004693/SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg", "filename": "SEAsia_PrecipDengueComposite_1920x1080_1211_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4695, "url": "https://svs.gsfc.nasa.gov/4695/", "page_type": "Visualization", "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)] || ", "release_date": "2019-02-28T09:00:00-05:00", "update_date": "2025-02-02T22:39:44.671922-05:00", "main_image": { "id": 398258, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004695/NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg", "filename": "NINO3.4SST_FlatMapComposite_1920x1080_00932_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } }, { "id": 4696, "url": "https://svs.gsfc.nasa.gov/4696/", "page_type": "Visualization", "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)] || ", "release_date": "2019-02-28T09:00:00-05:00", "update_date": "2025-02-02T00:11:33.263475-05:00", "main_image": { "id": 397244, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004600/a004696/SEAsia_LSTDiseases_1920x1080_1730_print.jpg", "filename": "SEAsia_LSTDiseases_1920x1080_1730_print.jpg", "media_type": "Image", "alt_text": "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.", "width": 1024, "height": 576, "pixels": 589824 } } ], "sources": [], "products": [ { "id": 4742, "url": "https://svs.gsfc.nasa.gov/4742/", "page_type": "Visualization", "title": "SVS Demo Reel", "description": "This is the SVS Demo Reel presented at SIGGRAPH 2019 in Los Angeles, CA. || svs_siggraphreel2019_print.jpg (1920x1080) [319.8 KB] || svs_siggraphreel2019_print_searchweb.png (320x180) [36.2 KB] || svs_siggraphreel2019_print_thm.png (80x40) [3.3 KB] || svs_siggraphreel2019.mp4 (1920x1080) [298.4 MB] || svs_siggraphreel2019.webm (1920x1080) [18.6 MB] || svs_siggraphreel2019.en_US.srt [38 bytes] || svs_siggraphreel2019.en_US.vtt [51 bytes] || ", "release_date": "2019-07-25T15:00:00-04:00", "update_date": "2023-05-03T13:45:46.534851-04:00", "main_image": { "id": 394300, "url": "https://svs.gsfc.nasa.gov/vis/a000000/a004700/a004742/svs_siggraphreel2019_print.jpg", "filename": "svs_siggraphreel2019_print.jpg", "media_type": "Image", "alt_text": "This is the SVS Demo Reel presented at SIGGRAPH 2019 in Los Angeles, CA.", "width": 1920, "height": 1080, "pixels": 2073600 } }, { "id": 13152, "url": "https://svs.gsfc.nasa.gov/13152/", "page_type": "Produced Video", "title": "2015-2016 El Niño Triggered Disease Outbreaks Across the Globe", "description": "Music: Under Offer by Peter Keith Yelland-BrownComplete transcript available. || ENSO_Dengue_Thumbnail.png (1920x1080) [3.2 MB] || ENSO_Dengue_Thumbnail_print.jpg (1024x576) [143.5 KB] || ENSO_Dengue_Thumbnail_searchweb.png (320x180) [88.1 KB] || ENSO_Dengue_Thumbnail_thm.png (80x40) [6.2 KB] || ENSO_Dengue_FINAL_lowres.mp4 (1280x720) [39.4 MB] || ENSO_Dengue_FINAL_lowres.webm (1280x720) [16.2 MB] || ENSO_Dengue_Captions.en_US.srt [2.6 KB] || ENSO_Dengue_Captions.en_US.vtt [2.6 KB] || ENSO_Dengue_FINAL.mov (1920x1080) [3.9 GB] || ", "release_date": "2019-02-28T12:30:00-05:00", "update_date": "2023-05-03T13:46:06.104651-04:00", "main_image": { "id": 397228, "url": "https://svs.gsfc.nasa.gov/vis/a010000/a013100/a013152/ENSO_Dengue_Thumbnail.png", "filename": "ENSO_Dengue_Thumbnail.png", "media_type": "Image", "alt_text": "Music: Under Offer by Peter Keith Yelland-BrownComplete transcript available.", "width": 1920, "height": 1080, "pixels": 2073600 } } ], "newer_versions": [], "older_versions": [], "alternate_versions": [] }