What's New with Earth Today

Explore the latest visualizations of NASA's Earth Observing satellites and the data they collect. NASA researchers are constantly tracking remote-sensing data and modeling processes to better understand our home planet.

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Latest Earth Visuals

  • NASA/JAXA GPM Satellite Captures Hurricane Delta on Approach to the Gulf Coast
    2020.10.09
    GPM passed over Hurricane Delta Thursday October 8, 2020 at appproximately 7:40pm Central Time (UTC time: 10/9/2020 00:40Z) as it approached the Gulf coast. Hurricane Delta is the 25th named Atlantic storm of the 2020 hurricane season. After exhausting a list of prepared names, the World Meteorological Organization turns to the Greek alphabet to name storms. Delta marked the strongest Greek-named storm on record. Hurricanes typically get a massive boost of energy when they pass over warm waters. Hurricane Delta rapidly intensified from a tropical depression to Category 4 storm in about 30 hours. GPM data is archived at https://pps.gsfc.nasa.gov/
  • Annual Arctic Sea Ice Minimum 1979-2020 with Area Graph
    2020.10.16
    Satellite-based passive microwave images of the sea ice have provided a reliable tool for continuously monitoring changes in the Arctic ice since 1979. Every summer the Arctic ice cap melts down to what scientists call its "minimum" before colder weather begins to cause ice cover to increase. This graph displays the area of the minimum sea ice coverage each year from 1979 through 2020. In 2020, the Arctic minimum sea ice covered an area of 3.36 million square kilometers. This visualization shows the expanse of the annual minimum Arctic sea ice for each year from 1979 through 2020 as derived from passive microwave data. A graph overlay shows the area in million square kilometers for each year's minimum day.
  • Arctic Sea Ice Minimum 2020
    2020.09.21
    Satellite-based passive microwave images of the sea ice have provided a reliable tool for continuously monitoring changes in the Arctic ice since 1979. Every summer the Arctic ice cap melts down to what scientists call its "minimum" before colder weather begins to cause ice cover to increase. The extent of Arctic sea ice at the end of this summer was the second lowest since satellite monitoring began. An analysis of satellite data by NASA and the National Snow and Ice Data Center (NSIDC) at the University of Colorado Boulder shows that the 2020 minimum extent, which was likely reached on Sept. 15, measured 1.44 million square miles (3.74 million square kilometers). The Japan Aerospace Exploration Agency (JAXA) provides many water-related products derived from data acquired by the Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument aboard the Global Change Observation Mission 1st-Water "SHIZUKU" (GCOM-W1) satellite. Two JAXA datasets used in this animation are the 10-km daily sea ice concentration and the 10 km daily 89 GHz Brightness Temperature. In this animation, the daily Arctic sea ice and seasonal land cover change progress through time, from the yearly maximum ice extent on March 5 2020, through its minimum on September 15 2020. Over the water, Arctic sea ice changes from day to day showing a running 3-day minimum sea ice concentration in the region where the concentration is greater than 15%. The blueish white color of the sea ice is derived from a 3-day running minimum of the AMSR2 89 GHz brightness temperature. The red boundary shows the minimum extent averaged over the 30-year period from 1981 to 2010. Over the terrain, monthly data from the seasonal Blue Marble Next Generation fades slowly from month to month. The faint circle that appears periodically close to the pole is an artifact of the visualization process, and does not represent a real feature.
  • Air Quality - Global View of COVID-19 Impacts
    Gallery
    NASA, ESA (European Space Agency) and JAXA (Japan Aerospace Exploration Agency) have created a dashboard of satellite data showing impacts on the environment and socioeconomic activity caused by the global response to the coronavirus (COVID-19) pandemic.
  • Greenland Ice Sheet: Three Futures
    2020.10.13
    The Greenland Ice Sheet holds enough water to raise the world’s sea level by over 7 meters (23 feet). Rising atmosphere and ocean temperatures have led to an ice loss equivalent to over a centimeter increase in global mean sea-level between 1991 and 2015. Large outlet glaciers, rivers of ice moving to the sea, drain the ice from the interior of Greenland and cause the outer margins of the ice sheet to recede. Improvements in measuring the ice thickness in ice sheets is enabling better simulation of the flow in outlet glaciers, which is key to predicting the retreat of ice sheets into the future. Recently, a simulation of the effects of outlet glacier flow on ice sheet thickness coupled with improved data and comprehensive climate modeling for differing future climate scenarios has been used to estimate Greenland’s contribution to sea-level over the next millennium. Greenland could contribute 5–34 cm (2-13 inches) to sea-level by 2100 and 11–162 cm (4-64 inches) by 2200, with outlet glaciers contributing 19–40 % of the total mass loss. The analysis shows that uncertainties in projecting mass loss are dominated by uncertainties in climate scenarios and surface processes, followed by ice dynamics. Uncertainties in ocean conditions play a minor role, particularly in the long term. Greenland will very likely become ice-free within a millennium without significant reductions in greenhouse gas emissions. This movie shows the evolution of several regions of the Greenland Ice Sheet between 2008 and 2300 based on three different climate scenarios. Each scenario reflects a potential future climate outcome based on current and future greenhouse gas emmisions. The scenario labelled "LOW" here is based on the Representative Concentration Pathway (RCP) 2.6 climate scenario while the one labelled "MEDIUM" is based on RPC 4.6. The visualization labelled "HIGH" is based on RPC 8.5 and reflects the current trajectory of emissions in the 21st century. The regions shown in a violet color are exposed areas of the Greenland bed that were covered by the ice sheet in 2008. The data sets used for these animations are the control (“CTRL”) simulations and were produced with the open-source Parallel Ice Sheet Model . All data sets for this study are publicly available at the NSF Arctic Data Center
  • NASA's captures powerful Hurricane Laura over Louisiana
    2020.08.27
    After crossing western Cuba, Tropical Storm Laura emerged into the Gulf of Mexico where warm water, low wind shear and a moist environment made conditions ideal for intensification. As it made its way through the Gulf of Mexico Laura strengthened - from a category 1 hurricane with sustained winds of 75 mph on the morning of Tuesday August 25th, to a powerful category 4 storm, with sustained winds of 150 mph on the evening of Wednesday August 26th - an increase of 75 mph in just 36 hours. At this point Laura was nearing the coast of western Louisiana, and made landfall near Cameron, Louisiana at around 1:00 a.m. CDT at the same 150 mph intensity. As it moved inland heading north over western Louisiana, Laura was overflown by the NASA / JAXA GPM Core Observatory satellite at 10:00 p.m. CDT on Wednesday August 26th, shortly before the storm made landfall, then again at 8:11 a.m. CDT on Thursday August 27th, about 7 hours after making landfall, as shown in the animation below. Rainfall rates derived directly from the GPM Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) instruments show heavy rain (in red) pushing up into northern Louisiana and southern Arkansas as strong southerly winds drew moisture from the Gulf of Mexico on the eastern side of the storm’s strong cyclonic circulation. With its ability to penetrate through the clouds using active radar, the DPR also provided a detailed look at Laura’s structure. Precipitation cloud-top heights from the DPR (highlighted in blue, indicating frozen precipitation) show Laura still had the overall structure of a powerful hurricane, as evidenced by both the symmetry of the outer rainbands that still wrap completely around the storm, as well as the residual structure of a strong core near the center containing elements of very heavy rain (shown in pink). At the time of this GPM overpass, Laura’s maximum sustained winds were still reported at 100 mph by the National Hurricane Center, the equivalent of a category 2 hurricane. GPM data is archived at https://pps.gsfc.nasa.gov/
  • First Global Survey of Glacial Lakes Shows 30-Years of Dramatic Growth
    2020.08.31
    Glaciers are retreating on a near-global scale due to rising temperatures and climate change. The melt and retreat of glaciers contributes to sea level rise and in the formation of glacial lakes typically right at the foot of the glaciers. In the largest-ever study of glacial lakes, NASA-funded researchers Dan Shugar et al. working under a grant from NASA’s High Mountain Asia Program found that glacial lake volume has increased by about 50% worldwide since 1990. The findings, published in the journal Nature Climate Change with the title Rapid worldwide growth of glacial lakes since 1990 affect how researchers evaluate the amount of glacial meltwater reaching the oceans and contributing to sea level rise as well as evaluate hazard risks for mountain communities downstream. Glacial lakes, which are often dammed by ice or glacial sediment called a moraine, are not stable like the lakes most people are used to swimming or boating in. Rather, they can be quite unstable and can burst their banks or dams, causing massive floods downstream. These kinds of floods from glacial lakes, also known as glacial lake outburst floods or GLOFs, have been responsible for thousands of deaths over the last century, as well as the destruction of villages, infrastructure and livestock. The data visualization featured on this page showcases the glacier rich and wondrous landscape of High Mountain Asia and provides a glimpse into how glacial lakes have increased during the last thirty years, by demonstrating the growth of Imja Lake for the period 1989-2019. It is important to mention that while Imja Lake is just one of the 14,394 glacial lakes analyzed by the science team in the study for the period of 2015-2018, it serves as a vivid example due to its dramatic growth. The visualization sequence starts with a wide view of Asia and the Tibetan plateau and slowly zooms into the Himalayan region, which includes many of Earth’s highest peaks and is paired with the highest concentration of snow and glaciers outside of the polar regions. Soon after a block of the Eastern Himalayan region rises featuring realistically scaled terrain data from the High Mountain Asia 8-meter Digital Elevation Model (DEM). The 8-meter DEM is draped over with Landsat 8 data from the same region. The sequence takes us on a hiking path from Mt. Everest (8,848 m / 29,029 ft), Mt. Lhotse (8,516 m / 27,940 ft) and Mt. Nuptse (7,861 m / 25,791 ft), to the Everest Base Camp, the Khumbu Glacier all the way to Imja Lake. Moving to a top-down view, a time series of geo-registered Landsat data unveils the growth of Imja Lake from 1989 to 2019. Outlines of the Imja Lake extents highlight the growth during the 30 years occurring from meltwater from the adjacent glaciers. Until now climate models that translated glacier melt into sea level change assumed that water from glacier melt is instantaneously transported to the oceans, which presented an incomplete picture. Therefore, understanding how much of glacial meltwater is stored in lakes or groundwater underscores the importance of studying and monitoring glacial lakes worldwide.
    Data Sources:
    • High Mountain Asia 8-meter Digital Elevation Model (DEM) derived from Optical Imagery, Version 1. The dataset is available from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). The DEM is realistically scaled (Vertical exaggeration 1x) in this visualization. The DEM is generated from very-high-resolution imagery from DigitalGlobe satellites (GEOEYE-1, QUICKBIRD-2, WORLDVIEW-1, WORLDVIEW-2, WORLDVIEW-3) during the period of 28 January 2002 to 24 November 2016. Citation: Shean, D. 2017. High Mountain Asia 8-meter DEM Mosaics Derived from Optical Imagery, Version 1. [Subset Used: HMA_DEM8m_MOS_20170716_tile-677 | subregion with extents 27.7394° -28.1638° N, 86.6007°-87.2118° E ]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/KXOVQ9L172S2. [Date Accessed: 06/17/2020].
    • Landsat 5, Landsat 7 and Landsat 8 data comprise the time series of Imja Lake for the period 1989-2019. Landsat 5 Thematic Mapper (TM) Level-1 Data Products (doi: https://doi.org/10.5066/F7N015TQ) were used for the period 1989-1999. The Landsat 5 Product Identifiers are: LT05_L1TP_140041_19891109_20170201_01_T1 LT05_L1TP_140041_19900112_20170201_01_T1 LT05_L1TP_140041_19910131_20170128_01_T1 LT05_L1TP_140041_19921117_20170121_01_T1 LT05_L1TP_140041_19931120_20170116_01_T1 LT05_L1TP_140041_19941022_20170111_01_T1 LT05_L1TP_140041_19951009_20170106_01_T1 LT05_L1TP_140041_19961112_20170102_01_T1 LT05_L1TP_140041_19970216_20170101_01_T1 LT05_L1TP_140041_19981102_20161220_01_T1 LT05_L1TP_140041_19990427_20161219_01_T1 Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Level-1 Data Products (doi: https://doi.org/10.5066/F7WH2P8G) were used for the period 2000-2012. The Landsat 7 Product Identifiers are: LE07_L1TP_140041_20001030_20170209_01_T1 LE07_L1TP_140041_20011017_20170202_01_T1 LE07_L1TP_140041_20021020_20170127_01_T1 LE07_L1TP_140041_20030124_20170126_01_T1 LE07_L1TP_140041_20041110_20170117_01_T1 LE07_L1TP_140041_20051113_20170112_01_T1 LE07_L1TP_140041_20060116_20170111_01_T1 LE07_L1TP_140041_20070103_20170105_01_T1 LE07_L1TP_140041_20081020_20161224_01_T1 LE07_L1TP_140041_20091023_20161217_01_T1 LE07_L1TP_140041_20101026_20161212_01_T1 LE07_L1TP_140041_20111013_20161206_01_T1 LE07_L1TP_140041_20121015_20161127_01_T1 Landsat 8 Operational Land Imagery (OLI) and Thermal Infrared Sensor (TIRS) Level-1 Data Products (doi: https://doi.org/10.5066/F71835S6) were used for the period 2013-2019. The Landsat 8 Product Identifiers are: LC08_L1TP_140041_20131010_20170429_01_T1 LC08_L1TP_140041_20140927_20170419_01_T1 LC08_L1TP_140041_20150930_20170403_01_T1 LC08_L1TP_140041_20161018_20170319_01_T1 LC08_L1TP_140041_20171021_20171106_01_T1 LC08_L1TP_140041_20181024_20181031_01_T1 LC08_L1TP_140041_20191112_20191115_01_T1* *Draped over the High Mountain Asia 8-meter Digital Elevation Model (DEM) during the visualization. For the purposes of this data visualization the above Landsat data were processed and color-stretched. Bands 3-2-1 were used for Landsat 5 and 7 data. Bands 4-3-2 were used for Landsat 8 data. In addition, Landsat 7 and 8 data used pan-chromatic sharpening (Band 8). Landsat 5, Landsat 7 and Landsat 8 data courtesy of the U.S Geological Survey and NASA Landsat.
    • Blue Marble: Next Generation was produced by Reto Stöckli, NASA Earth Observatory (NASA Goddard Space Flight Center). Citation: Reto Stöckli, Eric Vermote, Nazmi Saleous, Robert Simmon and David Herring. The Blue Marble Next Generation – A true color earth dataset including seasonal dynamics from MODIS, October 17, 2005.
    • Global 30 Arc-Second Eleveation (GTOPO 30) from USGS. doi: https://doi.org/10.5066/F7DF6PQS
    • Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global. doi: https://doi.org/10.5066/F7PR7TFT
    • Nepal city labels and locations were created using Natural Earth 1:10m Cultural Vectors (Populated places database) and OpenStreetMap data.

    The rest of this webpage offers additional versions and visual material associated with the development of this data-driven visualization.
  • NASA captures Isaias over the U.S. East Coast
    2020.08.04
    After regaining hurricane intensity over the Gulf Stream, Hurricane Isaias made landfall on the south coast of North Carolina on Monday August 3rd at 11:10 pm EDT near Ocean Isle Beach. This data visualization shows Isaias as is makes its way northward from the Bahamas to the coast of North Carolina using NASA’s IMERG rainfall product. With IMERG, precipitation estimates from the GPM core satellite are used to calibrate precipitation estimates from microwave and IR sensors on other satellites to produce half-hourly precipitation maps at 0.1 degrees horizontal resolution. After making landfall, Isaias continued tracking northward over eastern North Carolina in response to a large upper-level trough located over the eastern half of the US. It was at this time that Isaias was again overflown by the GPM core satellite at 8:51 UTC (4:51 am EDT) on the morning of Tuesday August 4th, as shown in the second part of the data visualization. Here rainfall rates derived directly from the GPM Microwave Instrument (or GMI) and Dual-Polarization Radar (or DPR) provide a detailed look at Isaias, which at the time was still a strong tropical storm with sustained winds reported at 70 mph by the National Hurricane Center. GPM clearly shows the center of circulation over northeastern North Carolina, which at the time was just southeast of Roanoke Rapids, NC, with a large eye that is open on the southern side. Amazingly, despite the center being located down in North Carolina, GPM shows a large rain shield extending from North Carolina all the way into New England to the Canadian border as a result of the storm’s counterclockwise circulation drawing abundant moisture off the Atlantic and over land where the combination of an old frontal boundary and the Appalachian terrain squeeze out this moisture to form large amounts of precipitation ahead of the storm, which is then drawn further northward by southerly flow aloft from the upper-level trough. GPM data is archived at https://pps.gsfc.nasa.gov/
  • NASA follows Hanna to the South Texas Coast
    2020.07.29
    After forming from a tropical easterly wave in the central Gulf of Mexico, Tropical Depression #8 had intensified enough by the evening of July 21st to be named Tropical Storm Hanna by the National Hurricane Center (NHC) and in the process became the earliest 8th named storm in an Atlantic season on record. As Hanna made its way westward from the central Gulf towards the South Texas coastline, it was constantly being monitored by an array of satellites. This animation shows Hanna’s progression from a tropical storm in the western Gulf of Mexico to a strong Category 1 hurricane at landfall on the South Texas coast using NASA’s IMERG rainfall product. With IMERG, precipitation estimates from the GPM core satellite are used to calibrate precipitation estimates from microwave and IR sensors on other satellites to produce half-hourly precipitation maps at 0.1o horizontal resolution. The start of the animation shows Tropical Storm Hanna on the evening of July 24th spinning counterclockwise in the western Gulf. Hanna’s surface rainfall pattern is rather asymmetric with a broad area of heavy rain southeast of the center with several rainbands wrapping up into the northern Gulf Coast on the east side of the storm. As Hanna continues westward towards Texas, the storm becomes more symmetric with heavy rain starting to wrap around the eastern side of the storm while an eye develops, both of which indicate that the storm is intensifying. Indeed, on the morning of July 25th, NHC reported that Hanna had reached hurricane intensity, becoming the first of the season. Hannah continued to strengthen until making landfall later that same day around 5 pm (CDT) over Padre Island as a strong Category 1 storm with sustained winds reported at 90 mph by NHC. This is reflected in the final part of the animation, which shows an overpass from the GPM core satellite, which overflew the storm around 22:26 UTC (5:26 pm CDT) just after it made landfall. Here rainfall rates derived directly from the GPM Microwave Instrument (or GMI) provide a detailed look into Hanna and show a very well-defined eye surrounded by a complete eyewall containing heavy to very heavy rain rates in nearly every quadrant of the storm. These structural characteristics reflect a strong, well-defined circulation and suggest Hanna quite likely would have reached Category 2 intensity had it remained over open water much longer. GPM data is archived at https://pps.gsfc.nasa.gov/
  • South Atlantic Anomaly: 2015 through 2025
    2020.08.17
    The bulk of Earth’s magnetic field originates deep within its core, at the boundary between the molten outer core and the solid mantle. The magnetic field extends past the surface into space and acts like a protective shield around the planet, repelling and trapping charged particles from the Sun. But over South America and the southern Atlantic ocean, an unusually weak spot in the field, called the South Atlantic Anomaly (SAA), allows these particles to dip much closer to the surface. Particle radiation in the SAA can knock out onboard computers and interfere with the data collection of satellites that pass through it. The SAA creates no visible impacts on daily life on the surface, and its weakening magnetic intensity is still within the bounds of what scientists consider normal variation. However, recent observations and forecasts show that the region is expanding westward and continuing to weaken in intensity. Observational data from 2015-2020 found that the SAA has recently started to split from a single valley, or region of minimum field strength, into two cells; and models out to the year 2025 show the split continuing in the future, creating additional challenges for satellite missions. NASA’s geomagnetic and geophysical research groups are using observations and models to monitor and predict future changes in the SAA and the rest of Earth’s geomagnetic field – helping prepare for future challenges to satellites and humans in space.
  • ICESat-2 and Cryosat-2 Coincident Measurements
    2020.07.16
    One of the big challenges in polar science is measuring the thickness of the floating sea ice that blankets the Arctic and Southern Oceans. Newly formed sea ice might be only a few inches thick, whereas sea ice that survives several winter seasons can grow to several feet in thickness (over ten feet in some places). Sea ice thickness is typically estimated by first measuring sea ice freeboard - how much of the floating ice can be observed above sea level. Sea ice floats slightly above sea level because it is less dense than water. An additional complexity is that snow fall on sea ice pushes the floating ice downward and has a lower density than the sea ice. In order to estimate the sea ice thickness, some accommodation for the overlying snow must be made. NASA’s ICESat-2 satellite measures the Earth’s surface height by firing green laser pulses towards Earth and timing how long it takes for those laser pulses to reflect back to the satellite. The laser light reflects off the top of the snow layer on top of the sea ice. In contrast, the European Space Agency’s CryoSat-2 mission uses radar waves to measure height. These radar waves penetrate the overlying snow and are reflected off the sea ice, rather than the overlying snow. In July 2020, ESA elected to slightly perturb the orbit of CryoSat-2 to increase the overlap with ICESat-2. Given their different orbit altitudes, the result is a ~3000km stretch of sea ice that is measured by both ICESat-2 and CryoSat-2. By combining data from these two sensors, scientists can measure the snow layer thickness, and produce substantially improved sea ice thickness estimates.
  • NOAA-20 satellite orbit with Suomi NPP and JPSS-2
    2020.05.08
    The Joint Polar Satellite System (JPSS) is the nation’s advanced series of polar-orbiting environmental satellites. JPSS satellites circle the Earth from pole-to-pole and cross the equator 14 times daily in the afternoon orbit—providing full global coverage twice a day. Polar satellites are considered the backbone of the global observing system. The operational JPSS constellation currently consists of the NASA-NOAA Suomi National Polar-Orbiting Partnership satellite, the technology pathfinder mission for JPSS launched in 2011, and NOAA-20, previously called JPSS-1 and launched in 2017. The next satellite in the series, JPSS-2, is scheduled to launch in the first quarter of 2022. Once it is accepted into the constellation post-launch, JPSS-2 will be renamed NOAA-21 and replace Suomi-NPP. JPSS represents significant technological and scientific advancements in observations used for severe weather prediction and environmental monitoring. These data are critical to the timeliness and accuracy of forecasts three to seven days in advance of a severe weather event. JPSS is a collaborative effort between NOAA and NASA.
  • Sources of Methane
    2020.07.09
    Methane is a powerful greenhouse gas that traps heat 28 times more effectively than carbon dioxide over a 100-year timescale. Concentrations of methane have increased by more than 150% since industrial activities and intensive agriculture began. After carbon dioxide, methane is responsible for about 23% of climate change in the twentieth century. Methane is produced under conditions where little to no oxygen is available. About 30% of methane emissions are produced by wetlands, including ponds, lakes and rivers. Another 20% is produced by agriculture, due to a combination of livestock, waste management and rice cultivation. Activities related to oil, gas, and coal extraction release an additional 30%. The remainder of methane emissions come from minor sources such as wildfire, biomass burning, permafrost, termites, dams, and the ocean. Scientists around the world are working to better understand the budget of methane with the ultimate goals of reducing greenhouse gas emissions and improving prediction of environmental change. For additional information, see the Global Methane Budget. The NASA SVS visualization presented here shows the complex patterns of methane emissions produced around the globe and throughout the year from the different sources described above. The visualization was created using output from the Global Modeling and Assimilation Office, GMAO, GEOS modeling system, developed and maintained by scientists at NASA. Wetland emissions were estimated by the LPJ-wsl model, which simulates the temperature and moisture dependent methane emission processes using a variety of satellite data to determine what parts of the globe are covered by wetlands. Other methane emission sources come from inventories of human activity. The height of Earth’s atmosphere and topography have been vertically exaggerated and appear approximately 50-times higher than normal in order to show the complexity of the atmospheric flow. As the visualization progresses, outflow from different source regions is highlighted. For example, high methane concentrations over South America are driven by wetland emissions while over Asia, emissions reflect a mix of agricultural and industrial activities. Emissions are transported through the atmosphere as weather systems move and mix methane around the globe. In the atmosphere, methane is eventually removed by reactive gases that convert it to carbon dioxide. Understanding the three-dimensional distribution of methane is important for NASA scientists planning observations that sample the atmosphere in very different ways. Satellites like GeoCarb, a planned geostationary mission to observe both carbon dioxide and methane, look down from space and will estimate the total number of methane molecules in a column of air. Aircraft, like those launched during NASA’s Arctic Boreal Vulnerability Experiment (ABOVE) sample the atmosphere along very specific flight lines, providing additional details about the processes controlling methane emissions at high latitudes. Atmospheric models help place these different types of measurements in context so that scientists can refine estimates of sources and sinks, understand the processes controlling them and reduce uncertainty in future projections of carbon-climate feedbacks.
  • Arctic Sea Ice Maximum 2020
    2020.03.21
    After growing through the fall and winter, sea ice in the Arctic appears to have reached its annual maximum extent. The image above shows the ice extent—defined as the total area in which the ice concentration is at least 15 percent—at its 2020 maximum, which occurred on March 5. On this day the extent of the Arctic sea ice cover peaked at 15.05 million square kilometers (5.81 million square miles). While this maximum was the largest since 2013, it remained 590,000 square kilometers (230,000 square miles) below the average maximum for the 1981-2010 period.
  • Global Temperature Anomalies from 1880 to 2019
    2020.01.15
    NASA, NOAA Analyses Reveal 2019 Second Warmest Year on Record According to independent analyses by NASA and the National Oceanic and Atmospheric Administration (NOAA), Earth's global surface temperatures in 2019 were the second warmest since modern recordkeeping began in 1880. Globally, 2019 temperatures were second only to those of 2016 and continued the planet's long-term warming trend: the past five years have been the warmest of the last 140 years. This past year, they were 1.8 degrees Fahrenheit (0.98 degrees Celsius) warmer than the 1951 to 1980 mean, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. “The decade that just ended is clearly the warmest decade on record,” said GISS Director Gavin Schmidt. “Every decade since the 1960s clearly has been warmer than the one before.” Since the 1880s, the average global surface temperature has risen and the average temperature is now more than 2 degrees Fahrenheit (a bit more than 1 degree Celsius) above that of the late 19th century. For reference, the last Ice Age was about 10 degrees Fahrenheit colder than pre-industrial temperatures. Using climate models and statistical analysis of global temperature data, scientists have concluded that this increase mostly has been driven by increased emissions into the atmosphere of carbon dioxide and other greenhouse gases produced by human activities. “We crossed over into more than 2 degrees Fahrenheit warming territory in 2015 and we are unlikely to go back. This shows that what’s happening is persistent, not a fluke due to some weather phenomenon: we know that the long-term trends are being driven by the increasing levels of greenhouse gases in the atmosphere,” Schmidt said. Because weather station locations and measurement practices change over time, the interpretation of specific year-to-year global mean temperature differences has some uncertainties. Taking this into account, NASA estimates that 2019’s global mean change is accurate to within 0.1 degrees Fahrenheit, with a 95% certainty level. Weather dynamics often affect regional temperatures, so not every region on Earth experienced similar amounts of warming. NOAA found the 2019 annual mean temperature for the contiguous 48 United States was the 34th warmest on record, giving it a “warmer than average” classification. The Arctic region has warmed slightly more than three times faster than the rest of the world since 1970. Rising temperatures in the atmosphere and ocean are contributing to the continued mass loss from Greenland and Antarctica and to increases in some extreme events, such as heat waves, wildfires, intense precipitation. NASA’s temperature analyses incorporate surface temperature measurements from more than 20,000 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. These in situ measurements are analyzed using an algorithm that considers the varied spacing of temperature stations around the globe and urban heat island effects that could skew the conclusions. These calculations produce the global average temperature deviations from the baseline period of 1951 to 1980. NOAA scientists used much of the same raw temperature data, but with a different interpolation into the Earth’s polar and other data-poor regions. NOAA’s analysis found 2019 global temperatures were 1.7 degrees Fahrenheit (0.95 degrees Celsius) above the 20th century average. NASA’s full 2019 surface temperature data set and the complete methodology used for the temperature calculation and its uncertainties are available at: https://data.giss.nasa.gov/gistemp GISS is a laboratory within the Earth Sciences Division of NASA’s Goddard Space Flight Center in Greenbelt, Maryland. The laboratory is affiliated with Columbia University’s Earth Institute and School of Engineering and Applied Science in New York. NASA uses the unique vantage point of space to better understand Earth as an interconnected system. The agency also uses airborne and ground-based measurements, and develops new ways to observe and study Earth with long-term data records and computer analysis tools to better see how our planet is changing. NASA shares this knowledge with the global community and works with institutions in the United States and around the world that contribute to understanding and protecting our home planet. For more information about NASA’s Earth science activities, visit: https://www.nasa.gov/earth The slides for the Jan. 15 news conference are available at: https://www.ncdc.noaa.gov/sotc/briefings/20200115.pdf NOAA’s Global Report is available at: https://www.ncdc.noaa.gov/sotc/global/201913
  • Near Real-Time Global Precipitation from the Global Precipitation Measurement Constellation
    2015.03.31
    The Global Precipitation Measurement (GPM) mission produces NASA's most comprehensive global rain and snowfall product to date, called the Integrated Multi-satellite Retrievals for GPM (IMERG). It is computed using data from the GPM constellation of satellites — a network of international satellites that currently includes the GPM Core Observatory, GCOM-W1, NOAA-18, NOAA-19, DMSP F-16, DMSP F-17, DMSP F-18, Metop-A, and Metop-B. The global IMERG dataset provides precipitation rates for the entire world every 30 minutes. Although the process to create the combined dataset is intensive, the GPM team creates a preliminary, near-real-time dataset of precipitation within several hours of data acquisition. This visualization shows the most currently available precipitation data from IMERG, depicting how rain and snowstorms move around the planet. As scientists work to understand all the elements of Earth's climate and weather systems, and how they could change in the future, GPM provides a major step forward in providing comprehensive and consistent measurements of precipitation for scientists and a wide variety of user communities.
  • 20 Years of Global Biosphere (updated)
    2017.11.14
    By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This data visualization represents twenty years' worth of data taken primarily by SeaStar/SeaWiFS, Aqua/MODIS, and Suomi NPP/VIIRS satellite sensors, showing the abundance of life both on land and in the sea. In the ocean, dark blue to violet represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. On land, green represents areas of abundant plant life, such as forests and grasslands, while tan and white represent areas where plant life is sparse or non-existent, such as the deserts in Africa and the Middle East and snow-cover and ice at the poles.
  • Sea Surface Temperature anomalies and patterns of Global Disease Outbreaks: 2009-2018
    2019.12.10
    The El Niño-Southern Oscillation (ENSO) phenomenon is an irregularly recurring climate pattern characterized by warmer (El Niño) and colder (La Niña) than usual ocean temperatures in the equatorial Pacific, which creates a ripple effect of anticipated weather changes in far-spread regions of Earth. Weather changes associated with the El Niño-Southern Oscillation phenomenon result in rainfall, temperature and environmental anomaly conditions worldwide that directly favor outbreaks of infectious diseases of public health concern. During the last 20 years NASA scientist Dr. Assaf Anyamba and colleagues have been studying interannual climate variability patterns associated with El Niño by monitoring various climate datasets, among them land surface temperature and vegetation data from the Advanced High Resolution Radiometer (AVHRR) on board NOAA POES satelittes, the Moderate Resolution Imaging Spectroradiometer aboard NASA's Terra and Aqua satellites, and Sea Surface Temperature and precipitation anomaly datasets from NASA and the National Oceanic and Atmospheric Administration (NOAA). At the same time, the science team has been collecting, cataloguing and analyzing patterns of 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 published in the journal Nature Scientific Reports, with the title Global Disease Outbreaks Associated with the 2015-2016 El Niño event and is open access available. According to this study, the 2015-2016 El Niño event brought weather conditions that triggered disease outbreaks in ENSO teleconnected regions throughout the world. The visualization showcases a global flat map with monthly Sea Surface Temperature (SST) anomaly data on the water, the locations of Global Disease Outbreaks of ten infectious diseases on land, along with a timeline plot of the ENSO Index (Niño 3.4 Index region SST anomaly) for the period 2009-2018 on the bottom. The Nino 3.4 Index region SST with extents (5N-5S, 120W-170W) is the box region, highlighted on the Pacific Ocean. During ENSO events, SST anomalies influence the nature and patterns of rainfall, vegetation and land surface temperatures on the land surface, which in turn influence the disease outbreaks that are mapped on a global scale. The 10 diseases mapped on this visualization are: chinkungunya, cholera, dengue virus, hantavirus, respiratory illness, Rift Valley fever, Ross River virus, St. Louis encephalitis, and tularemia. During the 2015-2016 El Nino event, which is manifested in the visualization with increased sea surface temperature anomaly (reds in Niño 3.4 Index Region), changes in precipitation, land surface temperatures and vegetation created and facilitated conditions for transmission of diseases, resulting in an uptick in reported cases for plague and hantavirus in Colorado and New Mexico (in 2015), cholera in East Africa’s Tanzania (during 2015 and 2016), and dengue fever in Brazil and Southeast Asia (during 2015), among others. According to the study, El Niño-driven increase in rainfall and milder temperatures over the American Southwest, spurred vegetative growth, providing more food for rodents that carry hantavirus. A resulting rodent population explosion put them in more frequent contact with humans, who contract the potentially fatal disease mostly through rodent fecal or urine contamination. As their rodent hosts proliferated, so did plague-carrying fleas. Regarding dengue outbreaks, the strong El Niño period produced higher than normal land surface temperatures and therefore drier habitats, which drew mosquitoes into populated, urban areas where there are open water storage containers providing ideal habitats for mosquito production. In addition, the higher the normal temperatures increase the maturation time of larvae to adult mosquitos and also induce frequent blood feeding/biting by mosquito vectors resulting in increased number of disease cases. The following 3 data driven visualizations demonstrate the complex relationships between the El Niño event in 2015-2016 and disease outbreaks of dengue in the South East Asia region: The effects of ENSO induced anomalous rainfall are clearly illustrated by outbreak patterns of Rift Valley fever (RVF) in East and South Africa. During ENSO events, Eastern Africa (El Niño) and South Africa (La Niña) receive 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. The results is the sea-saw pattern exhibited by the ENSO events drives patterns of disease outbreaks in different regions around the world. To learn more about the relationship between ENSO and Rift Valley fever outbreaks in the region of South Africa, please refer to: The strong relationship between ENSO events (i.e El Niño, La Niña) and disease outbreaks underscores the importance of seasonal forecasts. Since disease outbreaks typically manifest 2-3 months after the start of El Niño 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 suggest that by monitoring monthly climate datasets, country public health agencies and 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.
    Data Sources:
    • Sea Surface Temperature (SST) data: The SST known as the NOAA OI.v2 SST monthly fields are derived by a linear interpolation of the weekly optimum interpolation (OI) version 2 fields to daily fields then averaging the daily values over a month. The analysis uses in situ and satellite SST's plus SST's simulated by sea-ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the method of Reynolds (1988) and Reynolds and Marsico (1993). The SST dataset is available here.
    • Disease Outbreak data were collected from the Program for Monitoring Emerging Diseases (ProMED), the Pan-American Health Organization (PAHO) online country reports, weekly summaries of disease outbreaks reported by the Department of Defense Armed Forces Health Surveillance Branch and from the World Organisation for Animal Health/Organisation mondiale de la santé animale (OIE).
    • SST ENSO index (Niño 3.4) for the period 2009-2018 is obtained from the NOAA National Center for Climate Prediction online archives. The warm (El Niño) and cold (La Niña) periods of ENSO events were determined using the Oceanic Niño Index (ONI) threshold of +/- 0.5°C based on centered 30-year base periods updated every 5 years. The ONI is a 3-month running mean of Extended Reconstructed Sea Surface Temperature (ERSST) Version 4 (v4) SST anomalies in the Niño 3.4 region (5 N-5 S, 120W-170W).

    This visualization was created to support the AGU 2019 conference presentation, titled El Niño-Southern Oscillation Teleconnections and Global Patterns of Disease Outbreaks (December 11 2019, Moscone Conference Center, San Francisco, CA) 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.
    Below, you can find frames, alternate movies, colorbar information and layers associated with the development of this data-driven visualization.
  • Global Transport of Smoke from Australian Bushfires
    2020.03.30
    This visualization shows the global distribution of aerosols, generated by NASA’s GEOS-FP data assimilation system, from August 1, 2019 to January 14,2020—capturing the aerosols released by the extreme bushfires in Australia in December 2019 and January 2020 and how they are transported around the globe over the South Pacific Ocean. Different aerosol species are highlighted by color, including dust (orange), sea-salt (blue), nitrates (pink), sulfates (green), and carbon (red), with brighter regions corresponding to higher aerosol amounts. NASA's MODIS observations constrain regions with biomass burning as well as the aerosol optical depths in GEOS, capturing the prominent bushfires in Australia and transport of emitted aerosols well downstream over the South Pacific Ocean. Weather events including Hurricane Dorian in August – September 2019 and other tropical cyclones around the world, along with major fire events in South America and Indonesia in August - September 2019 are also shown. The local impacts of the Australian bushfires have been devastating to property and life in Australia while producing extreme air quality impacts throughout the region. As smoke from the massive fires has interacted with the global weather, the transport of smoke plumes around the global have accelerated through deep vertical transport into the upper troposphere and even the lowermost stratosphere, leading to long-range transport around the globe.
  • GRACE Data Assimilation and GEOS-5 Forecasts
    2020.03.31
    NASA researchers have developed new satellite-based, weekly global maps of soil moisture and groundwater wetness conditions and one to three-month U.S. forecasts of each product. While maps of current dry/wet conditions for the United States have been available since 2012, this is the first time they have been available globally. Both the global maps and the U.S. forecasts use data from NASA and German Research Center for Geosciences’s Gravity Recovery and Climate Experiment Follow On (GRACE-FO) satellites, a pair of spacecraft that detect the movement of water on Earth based on variations of Earth’s gravity field. GRACE-FO succeeds the highly successful GRACE satellites, which ended their mission in 2017 after 15 years of operation. With the global expansion of the product, and the addition of U.S. forecasts, the GRACE-FO data are filling in key gaps for understanding the full picture of wet and dry conditions that can lead to drought. The satellite-based observations of changes in water distribution are integrated with other data within a computer model that simulates the water and energy cycles. The model then produces, among other outputs, time-varying maps of the distribution of water at three depths: surface soil moisture, root zone soil moisture (roughly the top three feet of soil), and shallow groundwater. The maps have a resolution of 1/8th degree of latitude, or about 8.5 miles, providing continuous data on moisture and groundwater conditions across the landscape. The new forecast product that projects dry and wet conditions 30, 60, and 90 days out for the lower 48 United States uses GRACE-FO data to help set the current conditions. Then the model runs forward in time using the Goddard Earth Observing System, Version 5 seasonal weather forecast model as input. The researchers found that including the GRACE-FO data made the resulting soil moisture and groundwater forecasts more accurate.
  • Witness the Breathtaking Beauty of Earth's Polar Regions with NASA's Operation IceBridge
    2020.04.07
    VIDEO: "Witness the Breathtaking Beauty of Earth’s Polar Regions"

    Operation IceBridge recorded the diversity and fragility of our rapidly changing polar regions. These areas are some of the most inhospitable, but breathtaking places on Earth. Sit back and witness the polar regions, from western Greenland to Antarctica. Notable features include the Pine Island Glacier, Larsen C ice shelf, and rapid summer melt on the western Greenland Ice Sheet.

    Learn more: Operation IceBridge

    Music Provided by Universal Production Music: "Arabesque No.1" by Claude Debussy [PD]



    Coming soon to our YouTube channel.

  • JPSS Green Vegetation Fraction (GVF)
    2020.03.19
    If it feels like spring came early this year, it’s not your imagination. Thanks to the leap year, this is the earliest spring equinox since 1896 — more than 120 years ago. NOAA satellites, launched by NASA, can see signs of spring everywhere from the unique vantage point of space. From plants greening up to changes in our weather, NOAA satellites have you covered by continuously monitoring instant and long-term change. For 50 years, NOAA’s weather satellites have provided observations and imagery of storm systems, which helps forecasters monitor and assess a storm’s evolution. Orbiting Earth at different heights and paths, NOAA’s fleet of satellites gives us an important, comprehensive view of our planet. The Geostationary Operational Environmental Satellite (GOES) system is parked in an orbit over the equator and continuously tracks the same area. Meanwhile, the Joint Polar Satellite System (JPSS) is in a lower orbit, flying over the north and south poles to give us a constantly shifting global perspective. These satellites work in concert to provide imagery for monitoring a storm, and temperature and moisture data to be fed into the weather forecast models meteorologists use to develop the weather forecast you rely on every day.
  • Landsat with Sentinel - Global Coverage
    2020.03.03
    Satellite data offers a broad, global view of land surface changes, but cloud cover interferes with collecting data. Landsat satellites provide observations every 16 days, and having two satellites reduces that to every 8 days. The European Space Agency Sentinel-2 satellites collect data in similar wavelengths and at a similar spatial resolution, enabling the data to be combined for even more observations. When harmonized into one data set, the result is global observations every two or three days at 30-meter resolution. Any application looking at very dynamic phenomena, where changes occur on the timescales of a few days or weeks, will benefit from the harmonized Landsat/Sentinel dataset. For example, crop condition and area, burned area, or surface water extent. Also, this will benefit any application where short-term environmental conditions (like drought) have a rapid impact on ecosystems.
  • CERES Radiation Balance
    2020.02.21
    The Clouds and the Earth’s Energy Radiant System (CERES) instrument is a key component of NASA’s Earth Observing System, with six active CERES instruments on satellites orbiting Earth and taking data.   For Earth’s temperature to be stable over long periods of time, absorbed solar and emitted thermal radiation must be equal. Increases in greenhouse gases, like carbon dioxide and methane, trap emitted thermal radiation from the surface and reduce how much is lost to space, resulting in a net surplus of energy into the Earth system. Most of the extra energy ends up being stored as heat in the ocean and the remainder warms the atmosphere and land, and melts snow and ice. As a consequence, global mean surface temperature increases and sea levels rise. Much like a pulse or heartbeat, CERES monitors reflected solar and emitted thermal infrared radiation, which together with solar irradiance measurements is one of Earth’s ‘vital signs.’ Better understanding Earth’s energy balance enables us to be informed and adapt to a changing world.
  • Earth Observing Fleet (December 2019)
    2019.12.06
    This animation shows the orbits of NASA's fleet of Earth observing spacecraft that are considered operational as of December 2019. The clouds used in this version are from a high resolution GEOS model run at 10 minute time steps interpolated down to the per-frame level. Changes to this version include: removal of Jason-2 and Jason-3 and the camera does not show DSCOVR within its view.
    Spacecraft included: Aqua Aura CALIPSO: Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation CYGNSS-1: Cyclone Global Navigation Satellite System 1 CYGNSS-2: Cyclone Global Navigation Satellite System 2 CYGNSS-3: Cyclone Global Navigation Satellite System 3 CYGNSS-4: Cyclone Global Navigation Satellite System 4 CYNGSS-5: Cyclone Global Navigation Satellite System 5 CYGNSS-6: Cyclone Global Navigation Satellite System 6 CYGNSS-7: Cyclone Global Navigation Satellite System 7 CYGNSS-8: Cyclone Global Navigation Satellite System 8 Cloudsat GPM: Global Precipitation Measurement GRACE-FO-1: Gravity Recovery and Climate Experiment Follow On-1 GRACE-FO-2: Gravity Recovery and Climate Experiment Follow On-2 ICESat-2 ISS: International Space Station Landsat 7 Landsat 8 OCO-2: Orbiting Carbon Observatory-2 SMAP: Soil Moisture Passive Active SORCE: Solar Radiation and Climate Experiment Suomi NPP: Suomi National Polar-orbiting Partnership Terra
  • The Complex Chemistry of Surface Ozone Depicted in a New GEOS Simulation
    2019.12.09
    Earth’s atmosphere is mainly comprised of nitrogen and oxygen but also contains traces of hundreds of chemical compounds. While tiny in abundance, these chemicals have an outsized impact on humans and the environment due to their reactivity and toxicity. This visualization shows a computer simulation of the complexity of the chemical system of the atmosphere produced by NASA's GEOS modeling system with atmospheric chemistry. Shown is a sequence of modeled surface concentrations of 96 chemical species during the time period July 22, 2018 to October 2, 2018. These chemicals undergo rapid changes as they are being emitted by natural and anthropogenic activities, transported by prevailing winds and vertical lifting motions, deposited to the surface, or chemically transformed. The visualization starts with a global map of model predicted concentrations of surface ozone, a potent air pollutant that is chemically produced from hydrocarbons and nitrogen oxides under the presence of sunlight. Consequently, the highest concentrations of surface ozone can be found during daytime close to urban areas and in the vicinity of forest fires (e.g., Africa). At night, ozone is chemically destroyed in highly polluted environments, leading to very low nighttime concentrations over industrial areas such as Eastern China. These processes are captured in detail by NASA’s GEOS composition forecast (CF) system, which incorporates the latest scientific understanding of the physics and chemistry that guide the formation of ozone, along with measurements from satellites and other instrument platforms. A particular feature of the model system used here is its comprehensive representation of atmospheric chemistry using the GEOS-Chem chemistry model, capturing 240 gaseous species that react with each other via 725 chemical reactions. Directly or indirectly, all of these species impact the formation of ozone. The visualization shows snapshots of modeled concentrations of 96 of the most important chemical compounds, loosely grouped into seven ‘families’ based on their physical and chemical properties. Very tightly linked to ozone is the hydrogen oxides “HOx” family. It contains the highly reactive hydroxyl radical, OH, which plays a prominent role in atmospheric chemistry due to its role as a ‘cleansing agent’ of the atmosphere. The abundance of OH, which is subject to the availability of water vapor and sunlight, in turn directly impacts the atmospheric lifetime of hydrocarbons such as methane and carbon monoxide. Human activities constitute an important source for both of these gases (beside natural sources) and directly influence the long-term concentration trends of these pollutants, as can be directly observed from NASA satellites. Another related group of chemicals are hydrocarbons from biogenic activity: “Isoprene oxidation”. Plants emit hundreds of (structurally similar) compounds, with isoprene being the most important one. These compounds rapidly react with each other through a complex cascade of reactions, which makes the chemistry over vegetation-rich areas such as rain forests or the Southeast US challenging to simulate. Biogenic compounds also play an important role for the formation of aerosols: tiny particles that can constitute a major health risk when inhaled. The abundance and composition of aerosol particles is highly variable and is influenced by anthropogenic activities (e.g., soot from biofuel burning) as well as natural events, such as wildfires, dust storms, volcanic eruptions, and sea spray. The ocean is also a source of another group of chemicals, the halogens. These species tend to be highly reactive and can effectively destroy ozone, especially over remote areas. The last chemical group depicted in the visualization is related to nitrogen. Nitrogen oxides are central to atmospheric chemistry in general and ozone formation in particular. At the surface, the most important source of nitrogen dioxide (NO2) is the combustion of fossil fuels. As a result, NO2 concentrations are highest over urban areas (e.g. highways, power plants) and along ship routes. The visualization ends back at the beginning with ozone, illustrating the connectiveness of the chemical system of the atmosphere. Given the complexity of atmospheric chemistry, computer simulations – such as those by the NASA GEOS composition forecasting system – are an essential tool to understanding the formation of air pollution and to help formulate effective mitigation strategies. Here's a list of each of the chemical species shown and their groupings (ppbV=pars per billion by volume):
  • IMERG Monthly Climatology
    2020.07.03
    The monthly climatology dataset covers January 2001 to December 2018 as was created for the unveiling of the Global Precipitation Missions's (GPM) newly redesigned website
  • Goddard Earth Science Overview
    2020.04.20
    The Earth Sciences Division at NASA's Goddard Space Flight Center plans, organizes, evaluates, and implements a broad program of research on our planet's natural systems and processes. Major focus areas include climate change, severe weather, the atmosphere, the oceans, sea ice and glaciers, and the land surface. To study the planet from the unique perspective of space, the Earth Science Division develops and operates remote-sensing satellites and instruments. We analyze observational data from these spacecraft and make it available to the world's scientists. Our Education and Public Outreach efforts raise public awareness of the Division's research and its benefits to society.

Earth Day 2020

  • NASA Looks Back at 50 Years of Earth Day
    2020.04.21
    It’s been five decades since Apollo 8 astronaut William Anders photographed Earth peaking over the Moon’s horizon. The iconic image, dubbed Earthrise, inspired a new appreciation of the fragility of our place in the universe. Two years later, Earth Day was born to honor our home planet. As the world prepares to commemorate the 50th anniversary of Earth Day, NASA reflects on how the continued growth of its fleet of Earth-observing satellites has sharpened our view of the planet’s climate, atmosphere, land, polar regions and oceans.
  • Earth Day 2020: CERES Net TOA Radiation
    2020.04.17
    This visualization shows sea surface temperature (SST) data of the oceans from January 2016 through March 2020. The data set used is from the Jet Propulsion Laboratory (JPL) Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperature Analysis. The ocean temperatures are displayed between 0 degrees celcius (C) and 32 degrees C. This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: IMERG Precipitation
    2020.04.20
    This visualization shows the IMERG precipitation product for April, May, and June of 2014. This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: Normalized Difference Vegetation Idex (NDVI) Seasonal Cycles
    2020.04.20
    This visualization shows the Normalized Difference Vegetation Index (NDVI) over seaveral seasonal cycles. This NDVI dataset is part of the Next Generation Blue Marble product. This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: GRACE Groundwater Storage
    2020.04.20
    This visualization shows groundwater storage as measured by the Gravity Recovery and Climate Experiment (GRACE) between August 2005 and June 2014 (the date range for the visualization was chosen for convenience rather than scientific significance). This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: GEOS-5 Modeled Cloud Cover
    2020.04.20
    This visualization shows cloud cover as modeled by the GEOS-5 atmospheric model, using observations as its input, over the course of three days. The time period repeats halfway through the animation. This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: Sea Surface Temperature (SST) from January 2016 through March 2020
    2020.04.21
    This visualization shows sea surface temperature (SST) data of the oceans from January 2016 through March 2020. The data set used is from the Jet Propulsion Laboratory (JPL) Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperature Analysis. The ocean temperatures are displayed between 0 degrees celcius (C) and 32 degrees C. This visualization was created in part to support Earth Day 2020 media releases.
  • Earth Day 2020: Apollo-8 to Earth observing fleet
    2020.04.21
    This visualization was created as an introductory shot to video celebrating the 50th anniersary of Earth Day. The camera approaches the moon from the far side, with Earth behind the moon. The camera moves over the limb revealing Apollo-8, when Bill Anders took the iconic "Earthrise" photo that inspired Earth Day and the environmental movement. The camera then pushes in quickly to the Earth revealing the Earth observing spacecraft that were in orbit in 1970, the year of the first Earth Day. Finally, the orbits from other years are flashed on until we reach the orbits for 2020, the 50th anniversary of Earth Day.
  • Earth Day 2020: Biosphere
    2020.04.21
    By monitoring the color of reflected light via satellite, scientists can determine how successfully plant life is photosynthesizing. A measurement of photosynthesis is essentially a measurement of successful growth, and growth means successful use of ambient carbon. This data visualization represents twenty years' worth of data taken primarily by SeaStar/SeaWiFS, Aqua/MODIS, and Suomi NPP/VIIRS satellite sensors, showing the abundance of life both on land and in the sea. In the ocean, dark blue to violet represents warmer areas where there is little life due to lack of nutrients, and greens and reds represent cooler nutrient-rich areas. The nutrient-rich areas include coastal regions where cold water rises from the sea floor bringing nutrients along and areas at the mouths of rivers where the rivers have brought nutrients into the ocean from the land. On land, green represents areas of abundant plant life, such as forests and grasslands, while tan and white represent areas where plant life is sparse or non-existent, such as the deserts in Africa and the Middle East and snow-cover and ice at the poles.
  • Earth Day 2020: Gulf Stream ocean current pull out to Earth observing fleet
    2020.04.21
    This visualization was created to be one of the final shots of a video celebrating the 50th anniversary of Earth Day. The camera starts under water off the coast of the Eastern United States showing layers of ocean currents from a computational model called ECCO-2. The camera slowly pulls back revealing the Gulf Stream, one of the most powerful ocean currents on Earth. The camera continues to pull back revealing NASA's Earth observing fleet.
  • Earth Day 2020: Global Atmospheric Methane
    2020.04.21
    Methane is a powerful greenhouse gas that traps heat 28 times more effectively than carbon dioxide over a 100-year timescale. Concentrations of methane have increased by more than 150% since industrial activities and intensive agriculture began. After carbon dioxide, methane is responsible for about 20% of climate change in the twentieth century. Methane is produced under conditions where little to no oxygen is available. About 30% of methane emissions are produced by wetlands, including ponds, lakes and rivers. Another 20% is produced by agriculture, due to a combination of livestock, waste management and rice cultivation. Activities related to oil, gas, and coal extraction release an additional 30%. The remainder of methane emissions come from minor sources such as wildfire, biomass burning, permafrost, termites, dams, and the ocean. Scientists around the world are working to better understand the budget of methane with the ultimate goals of reducing greenhouse gas emissions and improving prediction of environmental change. For additional information, see the Global Methane Budget. The NASA SVS visualization presented here shows the complex patterns of methane emissions produced around the globe and throughout the year from the different sources described above. The visualization was created using output from the Global Modeling and Assimilation Office, GMAO, GEOS modeling system, developed and maintained by scientists at NASA. Wetland emissions were estimated by the LPJ-wsl dynamic global vegetation model, which simulates the temperature and moisture dependent methane emission processes using a variety of satellite data to determine what parts of the globe are covered by wetlands. Other methane emission sources come from inventories of human activity. The height of Earth’s atmosphere and topography have been vertically exaggerated and appear approximately 50-times higher than normal in order to show the complexity of the atmospheric flow while the bathymetry below sea level is exaggerated by 11.6-times. Outflow from different regions result from different sources. For example, high methane concentrations over South America are driven by wetland emissions while over Asia, emissions reflect a mix of agricultural and industrial activities. Emissions are transported through the atmosphere as weather systems move and mix methane around the globe. In the atmosphere, methane is eventually removed by reactive gases that convert it to carbon dioxide. Understanding the three-dimensional distribution of methane is important for NASA scientists planning observations that sample the atmosphere in very different ways. Satellites like GeoCarb, a planned geostationary mission to observe both carbon dioxide and methane, look down from space and will estimate the total number of methane molecules in a column of air. Aircraft, like those launched during NASA’s Arctic Boreal Vulnerability Experiment (ABOVE) sample the atmosphere along very specific flight lines, providing additional details about the processes controlling methane emissions at high latitudes. Atmospheric models help place these different types of measurements in context so that scientists can refine estimates of sources and sinks, understand the processes controlling them and reduce uncertainty in future projections of carbon-climate feedbacks.

COVID-19 Earth Observations

As cities and countries locked down during COVID-19, some changes were visible from space.
  • NASA, ESA and JAXA Partner to Create COVID-19 Earth Observation Dashboard
    2020.06.25
    As cities and countries locked down during COVID-19, some changes were visible from space. NASA, ESA and JAXA have partnered to create a dashboard making those data available. Read more: https://www.nasa.gov/press-release/nasa-partner-space-agencies-amass-global-view-of-covid-19-impacts
  • NASA, ESA, JAXA Release Global View of COVID-19 Impacts
    2020.06.25
    NASA, ESA (European Space Agency) and JAXA (Japan Aerospace Exploration Agency) have created a dashboard of satellite data showing impacts on the environment and socioeconomic activity caused by the global response to the coronavirus (COVID-19) pandemic. The dashboard will be released on Thursday, June 25 during a tri-agency media briefing. The briefing speakers are: • Josef Aschbacher, director of ESA Earth Observation Programmes • Thomas Zurbuchen, associate administrator of NASA’s Science Mission Directorate • Koji Terada, vice president and director general for the Space Technology Directorate at JAXA • Shin-ichi Sobue, project manager for JAXA’s ALOS-2 mission • Ken Jucks, program scientist for NASA’s OCO-2 and Aura missions • Anca Anghelea, open data scientist, ESA Earth observation programmes
  • NO2 Decline Related to Restrictions Due to COVID-19 in South America
    2020.06.18
    On June 1, the World Health Organization noted that Central and South American countries have become “the intense zones” for COVID-19 transmission. The Ozone Monitoring Instrument (OMI) on board NASA’s Aura satellite provides data that indicate that restrictions on human activity have led to about a 36% decrease in NO2 levels in Rio de Janeiro, Brazil, relative to previous years. Other large cities in South America show similar decreases in NO2: 36% in Santiago, Chile; 35% in São Paolo, Brazil; and 40% in Buenos Aires, Argentina. One notable exception is in Lima, Peru, showing a 69% decrease. The large decrease may partly be associated with natural variations in weather that can, for instance, disperse air pollution more quickly. Additional analysis is required to determine the amount of the decrease of NO2 in Lima that is associated with a decrease in human activity. A notable increase in NO2 occurred in northern South America, which is likely associated with increased agricultural burning in 2020 relative to previous years.
  • Reductions in Pollution Associated with Decreased Fossil Fuel Use Resulting from COVID-19 Mitigation
    2020.04.24
    Over the past several weeks, the United States has seen significant reductions in air pollution over its major metropolitan areas. Similar reductions in air pollution have been observed in other regions of the world. These recent improvements in air quality have come at a high cost, as communities grapple with widespread lockdowns and shelter-in-place orders as a result of the spread of COVID-19. One air pollutant, nitrogen dioxide (NO2), is primarily emitted from burning fossil fuels (diesel, gasoline, coal), coming out of our tailpipes when driving cars and smokestacks when generating electricity. Therefore, changes in NO2 levels can be used as an indicator of changes in human activity. However, care must be taken when processing and interpreting satellite NO2 data as the quantity observed by the satellite is not exactly the same as the NO2 abundance at ground level. NO2 levels are influenced by dynamical and chemical processes in the atmosphere. For instance, atmospheric NO2 levels can vary day-to-day due to changes in the weather, which influences both the lifetime of NO2 molecules as well as the dispersal of the molecules by the wind. It is also important to note that satellites that observe NO2 cannot see through clouds, so all data shown is for days with low amounts of cloudiness. If processed and interpreted carefully, NO2 levels observed from space serve as an effective proxy for NO2 levels at Earth's surface. NASA's air quality group is also monitoring other air pollutants, such as sulfur dioxide (SO2). Major anthropogenic activities that emit SO2 include electricity generation, oil and gas extraction, and metal smelting. SO2 is emitted during electricity generation if the coal burned has sulfur impurities that are not removed (or not “scrubbed”) from the plant’s exhaust stacks. For more information on what pollutants NASA satellites observe, visit the NASA Air Quality website.
  • New-Generation Satellite Observations Monitor Air Pollution During COVID-19 Lockdown Measures in California
    2020.05.08
    Preventative measures adopted to reduce the rate of spread of COVID-19 in the U.S. prompted an overall slowdown in economic activity and fewer vehicles on the roadways in the spring of 2020. To examine changes in air quality in California, NASA constructed weekly averaged nitrogen dioxide (NO2) maps for March and April 2020 at 0.05° grid spacing from high-quality, cloud-free retrievals provided by Tropospheric Monitoring Instrument (TROPOMI) level 2 data. During first weekday period (March 2-6, pre-shutdown) when COVID-19 measures were yet to be implemented, the largest tropospheric NO2 concentrations were observed in Los Angeles and bordering counties with a less prominent peak in NO2 around San Francisco. The TROPOMI scans also resolved areas of enhanced NO2 along the heavily trafficked corridor of State Route 99 (SR-99) in the Central Valley. As initial, soft COVID-19 measures were adopted by businesses in California during the second weekday period, March 9-13, TROPOMI observed strong reductions in tropospheric column NO2 around the large cities of Los Angeles and San Francisco along with noticeable decreases along SR-99. When California announced statewide “shelter-in-place” orders during the third weekday period, March 16-20, further decreases in NO2 were apparent throughout all populated areas in the state and along SR-99. Further weekly areages showed variable decreases in NO2 as decreased economic activity continued. Overall, these observed reductions in TROPOMI NO2 throughout the spring season are the result of decreased emissions on top of the seasonal changes in meteorological conditions.
  • COVID-19: NASA Satellite Data Show Drop in Air Pollution Over U.S.
    2020.05.18
    These images show the impact the spread of the novel coronavirus (COVID-19) has had on reducing air pollution in the United States as widespread lockdowns and shelter-in-place orders have been put in place. The images show a reduction in the levels of nitrogen dioxide (NO2)—a noxious gas emitted by motor vehicles, power plants, and industrial facilities—as measured by the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite in March 2020. The “without stay-at-home orders” images show average monthly NO2 concentrations during March and April from 2015 through 2019, while the “during stay-at-home orders” images show average monthly concentrations in March and April 2020. These improvements in air quality have come at a high cost, as communities grapple with the impacts of COVID-19. The data indicate that the NO2 levels in March and April 2020 are much lower on average across the United States when compared to the mean of 2015 to 2019.