NASA Earth Science

NASA’s Earth Science Division (ESD) missions help us to understand our planet’s interconnected systems, from a global scale down to minute processes. Working in concert with a satellite network of international partners, ESD can measure precipitation around the world, and it can employ its own constellation of small satellites to look into the eye of a hurricane. ESD technology can track dust storms across continents and mosquito habitats across cities.

For more information: https://science.nasa.gov/earth-science

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Atmospheric Composition

The Atmospheric Composition focus area (AC) studies the variations in and processes that affect aerosols, clouds, and trace gases, which influence climate, weather, and air quality. AC provides observations and modeling tools to assess the effects of climate change on ozone recovery and future atmospheric composition; improve climate forecasts based on fluctuations in global environmental change; and model past, present, and future air quality, both regionally and globally. This research, combined with observations, data assimilation, and modeling, improves society’s ability to predict how future changes in atmospheric composition will affect climate, weather, and air quality.
  • Earth's Energy Budget
    2017.07.20
    Earth's energy budget is a metaphor for the delicate equilibrium between energy received from the Sun versus energy radiated back out in to space. Research into precise details of Earth's energy budget is vital for understanding how the planet's climate may be changing, as well as variabilities in solar energy output.

    NASA’s (The Clouds and the Earth's Radiant Energy System) CERES and NASA's Total and Spectral solar Irradiance Sensor (TSIS-1), missions play key roles in our continued understanding of Earth’s Energy Budget.

    NASA’s TSIS helps scientists keep a close watch on the sun’s energy input to Earth. Various satellites have captured a continuous record of this solar energy input since 1978. TSIS-1 sensors advance previous measurements, enabling scientists to study the sun's natural influence on Earth's ozone layer, atmospheric circulation, clouds, and ecosystems. These observations are essential for a scientific understanding of the effects of solar variability on the Earth system.

    TSIS-1 makes two key measurements: total solar irradiance, or TSI, the sun's total energy input into Earth, and solar spectral irradiance (SSI), the distribution of the sun's energy input across ultraviolet, visible, and infrared wavelengths of light. TSI measurements are needed to quantify the solar variations in the total amount of energy input to the Earth. SSI measurements are also vital because different wavelengths of light are absorbed by different parts of the atmosphere.

    For more than 20 years, NASA Langley's CERES (System) instruments have measured the solar energy reflected by Earth, the heat the planet emits, and the role of clouds in that process. The final CERES Flight Model, CERES FM6 launched aboard NOAA’s JPSS-1 in Fall 2017.

    CERES FM6 contributes to an already extensive CERES dataset that helps scientists validate models that calculate the effect of clouds on planetary heating and cooling. The same data can also be helpful for improving near-term, seasonal forecasts influenced by weather events such as El Niño and La Niña. El Niño and La Niña are weather patterns that develop when ocean temperatures fluctuate between warm and cool phases in the Equatorial Pacific Ocean. Built by Northrop Grumman and managed by Langley, CERES FM6 joins five other CERES instruments orbiting the planet on three other satellites.

    NASA Goddard Space Flight Center manages the TSIS-1 project. The University of Colorado's Laboratory for Atmospheric and Space Physics (LASP) built both instruments and provides mission operations. The International Space Station carries TSIS-1. Earth's energy budget is a metaphor for the delicate equilibrium between energy received from the Sun versus energy radiated back out in to space. Research into precise details of Earth's energy budget is vital for understanding how the planet's climate may be changing, as well as variabilities in solar energy output.

    NASA’s (The Clouds and the Earth's Radiant Energy System) CERES and NASA's Total and Spectral solar Irradiance Sensor (TSIS-1), missions play key roles in our continued understanding of Earth’s Energy Budget.

    NASA’s TSIS helps scientists keep a close watch on the sun’s energy input to Earth. Various satellites have captured a continuous record of this solar energy input since 1978. TSIS-1 sensors advance previous measurements, enabling scientists to study the sun's natural influence on Earth's ozone layer, atmospheric circulation, clouds, and ecosystems. These observations are essential for a scientific understanding of the effects of solar variability on the Earth system.

    TSIS-1 makes two key measurements: total solar irradiance, or TSI, the sun's total energy input into Earth, and solar spectral irradiance (SSI), the distribution of the sun's energy input across ultraviolet, visible, and infrared wavelengths of light. TSI measurements are needed to quantify the solar variations in the total amount of energy input to the Earth. SSI measurements are also vital because different wavelengths of light are absorbed by different parts of the atmosphere.

    For more than 20 years, NASA Langley's CERES (System) instruments have measured the solar energy reflected by Earth, the heat the planet emits, and the role of clouds in that process. The final CERES Flight Model, CERES FM6 launched aboard NOAA’s JPSS-1 in Fall 2017.

    CERES FM6 contributes to an already extensive CERES dataset that helps scientists validate models that calculate the effect of clouds on planetary heating and cooling. The same data can also be helpful for improving near-term, seasonal forecasts influenced by weather events such as El Niño and La Niña. El Niño and La Niña are weather patterns that develop when ocean temperatures fluctuate between warm and cool phases in the Equatorial Pacific Ocean. Built by Northrop Grumman and managed by Langley, CERES FM6 joins five other CERES instruments orbiting the planet on three other satellites.

    NASA Goddard Space Flight Center manages the TSIS-1 project. The University of Colorado's Laboratory for Atmospheric and Space Physics (LASP) built both instruments and provides mission operations. The International Space Station carries TSIS-1.

  • Monsoons: Wet, Dry, Repeat...
    2016.06.23
    The monsoon is a seasonal rain and wind pattern that occurs over South Asia (among other places). Through NASA satellites and models we can see the monsoon patterns like never before. Monsoon rains provide important reservoirs of water that sustain human activities like agriculture and supports the natural environment through replenishment of aquifers. However, too much rainfall routinely causes disasters in the region, including flooding of the major rivers and landslides in areas of steep topography. This visualization uses a combination of NASA satellite data and models to show how and why the monsoon develops over this region. In the summer the land gets hotter, heating the atmosphere and pulling in cooler, moisture-laden air from the oceans. This causes pulses in heavy rainfall throughout the region. In the winter the land cools off and winds move towards the warmer ocean and suppressing rainfall on land.
  • High Resolution Layers from "Monsoons: Wet, Dry, Repeat..."
    2016.06.23
    The visualizations here are based on the visualization Monsoons: Wet, Dry, Repeat (#4397). Each data set is presented in three resolutions: 8192x4096, 4096x2048, and 2048x1024. Each the 8192x4096 and 4096x2048 layers have been rendered with alpha transparency channels to allow you to create your own combinations of layered data. NOTE: the preview movies are composited over a black background, but the individual 8192x4096 and 4096x2048 frames have transparency channels. The 2048x1024 frames do not have transparency channels. The layers have frame numbers from 01000 through 13000. Frame 01000 corresponds to 02 Jun 2014 at 00:00 GMT. Each successive frame is 15 minutes later. Frame 13000 corresponds to 05 Oct 2014 at 00:00 GMT. To determine the time for a specific layer's frame number, you can look at the date sequence's corresponding frame. Even though all layers are provided at 15 minute intervals, most data sets do not have such a high cadence. In these cases, the frames simply show the same data. See the annotation with each data set for the cadences.
  • 2017 Hurricanes and Aerosols Simulation
    2017.11.13
    Tracking the aerosols carried on the winds let scientists see the currents in our atmosphere. This visualization follows sea salt, dust, and smoke from July 31 to November 1, 2017, to reveal how these particles are transported across the map.

    The first thing that is noticeable is how far the particles can travel. Smoke from fires in the Pacific Northwest gets caught in a weather pattern and pulled all the way across the US and over to Europe. Hurricanes form off the coast of Africa and travel across the Atlantic to make landfall in the United States. Dust from the Sahara is blown into the Gulf of Mexico. To understand the impacts of aerosols, scientists need to study the process as a global system.

    The Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center has developed the Goddard Earth Observing System (GEOS), a family of mathematical models. Combined with data from NASA's Earth observing satellites, the supercomputer simulations enhance our scientific understanding of specific chemical, physical, and biological processes.

    During the 2017 hurricane season, the storms are visible because of the sea salt that is captured by the storms. Strong winds at the surface lift the sea salt into the atmosphere and the particles are incorporated into the storm. Hurricane Irma is the first big storm that spawns off the coast of Africa. As the storm spins up, the Saharan dust is absorbed in cloud droplets and washed out of the storm as rain. This process happens with most of the storms, except for Hurricane Ophelia. Forming more northward than most storms, Ophelia traveled to the east picking up dust from the Sahara and smoke from large fires in Portugal. Retaining its tropical storm state farther northward than any system in the Atlantic, Ophelia carried the smoke and dust into Ireland and the UK.

    Computer simulations using the GEOS models allow scientists to see how different processes fit together and evolve as a system. By using mathematical models to represent nature we can separate the system into component parts and better understand the underlying physics of each. GEOS runs on the Discover supercomputer at the NASA Center for Climate Simulation (NCCS) For more information: NASA@SC17: Glimpse at the Future of Global Weather Prediction and Analysis at NASA
  • Carbon Dioxide from GMAO using Assimilated OCO-2 Data
    2016.12.13
    Carbon dioxide is the most important greenhouse gas released to the atmosphere through human activities. It is also influenced by natural exchange with the land and ocean. This visualization provides a high-resolution, three-dimensional view of global atmospheric carbon dioxide concentrations from September 1, 2014 to August 31, 2015. The visualization was created using output from the GEOS modeling system, developed and maintained by scientists at NASA. The height of Earth’s atmosphere and topography have been vertically exaggerated and appear approximately 400 times higher than normal to show the complexity of the atmospheric flow. Measurements of carbon dioxide from NASA’s second Orbiting Carbon Observatory (OCO-2) spacecraft are incorporated into the model every 6 hours to update, or “correct,” the model results, called data assimilation.

    As the visualization shows, carbon dioxide in the atmosphere can be mixed and transported by winds in the blink of an eye. For several decades, scientists have measured carbon dioxide at remote surface locations and occasionally from aircraft. The OCO-2 mission represents an important advance in the ability to observe atmospheric carbon dioxide. OCO-2 collects high-precision, total column measurements of carbon dioxide (from the sensor to Earth’s surface) during daylight conditions. While surface, aircraft, and satellite observations all provide valuable information about carbon dioxide, these measurements do not tell us the amount of carbon dioxide at specific heights throughout the atmosphere or how it is moving across countries and continents. Numerical modeling and data assimilation capabilities allow scientists to combine different types of measurements (e.g., carbon dioxide and wind measurements) from various sources (e.g., satellites, aircraft, and ground-based observation sites) to study how carbon dioxide behaves in the atmosphere and how mountains and weather patterns influence the flow of atmospheric carbon dioxide. Scientists can also use model results to understand and predict where carbon dioxide is being emitted and removed from the atmosphere and how much is from natural processes and human activities.

    Carbon dioxide variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and orange shades represent regions where carbon dioxide concentrations are enhanced by carbon sources. During Northern Hemisphere fall and winter, when trees and plants begin to lose their leaves and decay, carbon dioxide is released in the atmosphere, mixing with emissions from human sources. This, combined with fewer trees and plants removing carbon dioxide from the atmosphere, allows concentrations to climb all winter, reaching a peak by early spring. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing it from the atmosphere and change the color to blue (low carbon dioxide concentrations). This three-dimensional view also shows the impact of fires in South America and Africa, which occur with a regular seasonal cycle. Carbon dioxide from fires can be transported over large distances, but the path is strongly influenced by large mountain ranges like the Andes. Near the top of the atmosphere, the blue color indicates air that last touched the Earth more than a year before. In this part of the atmosphere, called the stratosphere, carbon dioxide concentrations are lower because they haven’t been influenced by recent increases in emissions.

  • Hazardous Air Quality Conditions in Singapore
    2015.11.27
    Each year, peat fires start to burn in Indonesia because farmers engage in slash and burn agriculture—a technique that involves frequent burning of rainforest to clear the way for crops or grazing animals. The intent is often to make room for new plantings of oil palm and acacia pulp. In October 2015 more than 94,000 fires had burned across the island nation, affecting the health of millions of people in Indonesia, Malaysia, and Singapore. On September 24, 2015, dense haze carried by southerly winds was blown into Singapore. The PSI reading at 7:00 PM local time rose into the "Hazardous" range for the first time in 2015 with a reading of 313. It rose further to 317 at 8:00 PM, which prompted the Ministry of Education to close all primary and secondary schools on September 25. The haze deteriorated further by September 25, reaching a record high for the year at 5:00 AM with a reading of 341. Anti-pollution masks were distributed to the elderly and other vulnerable people. The smoke—which is an annual problem for the region—is a serious health hazard, especially for the elderly, children, and those with breathing problems.

    This set of images shows Singapore and the nearby region on May 29, 2015, when air quality conditions were normal, and on September 25, 2015, when a thick smoky haze covered the nation. Each image reveals a true-color image [top] from the Moderate Resolution Imaging Spectroradiometer (MODIS) and atmospheric cross-section [bottom] from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The CALIPSO image from September 25 reveals the thick layer of smoke (dark orange) in the atmosphere.

  • CALIPSO observes Saharan dust crossing the Atlantic Ocean
    2015.02.24
    For the first time, a NASA satellite has quantified in three dimensions how much dust makes the trans-Atlantic journey from the Sahara Desert the Amazon rainforest. Among this dust is phosphorus, an essential nutrient that acts like a fertilizer, which the Amazon depends on in order to flourish. The new dust transport estimates were derived from data collected by a lidar instrument on NASA's Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation, or CALIPSO, satellite from 2007 though 2013. The data show that wind and weather pick up on average 182 million tons of dust each year and carry it past the western edge of the Sahara at longitude 15W. This volume is the equivalent of 689,290 semi trucks filled with dust. The dust then travels 1,600 miles across the Atlantic Ocean, though some drops to the surface or is flushed from the sky by rain. Near the eastern coast of South America, at longitude 35W, 132 million tons remain in the air, and 27.7 million tons – enough to fill 104,908 semi trucks – fall to the surface over the Amazon basin. About 43 million tons of dust travel farther to settle out over the Caribbean Sea, past longitude 75W. Dust collected from the Bodélé Depression and from ground stations on Barbados and in Miami give scientists an estimate of the proportion of phosphorus in Saharan dust. This estimate is used to calculate how much phosphorus gets deposited in the Amazon basin from this dust transport, an estimated 22,000 tons per year. The finding is part of a bigger research effort to understand the role of dust and aerosols in the environment and on local and global climate.
  • Evolution of the Meteorological Observing System in the MERRA-2 Reanalysis
    2018.12.14
    The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center uses the Goddard Earth Observing System (GEOS) modeling and data assimilation system to produce gridded estimates of the atmospheric state by combining short-term forecasts with observations from numerous observing systems. While the GEOS system is under continual development, it is periodically frozen and used to reprocess the modern satellite era, which begins in about 1980. This period specifically has been the focus of the second version of the Modern-Era Retrospective analysis for Research and Applications (MERRA-2). The modern satellite era in the context of MERRA-2 stems from the launch of the NASA/NOAA Television InfraRed Observational Satellite N-series (TIROS-N) satellite. This satellite served as the space platform for the first of the TIROS Operational Vertical Sounder (TOVS) series, which included TIROS-N and NOAA-6 through NOAA-14. The series of TOVS observations included global infrared and microwave radiance observations that provided the first comprehensive space-based observations that served as the remotely sensed backbone of the assimilation system. These observations, along with wind estimates from geostationary satellites and the global surface and upper air conventional observing network (e.g. surface reporting stations, radiosondes, aircraft measurements) provide the observations for the beginning of MERRA-2 in 1980. The observing system has advanced substantially since the launch of TIROS-N. Both satellite and conventional observations have increased in both quality and quantity over the course of the past four decades. In 1980, the median number of observations assimilated over a six hour period was 175,000. In 2018, this number has approached 5 million. The transition from the TOVS to the ATOVS (Advanced TOVS) observing system, which began in 1998 with the launch of the NOAA-15 platform, provided better horizontal and vertical resolution, along with improved observational quality. NASA’s Atmospheric Infrared Sounder (AIRS) instrument on the EOS-Aqua spacecraft provided yet another major advance in remote sensing of Earth, providing the first well-calibrated hyperspectral infrared radiance observations of the atmosphere, leading to a massive increase in the number of observations available to constrain the system. Designed as a research instrument, AIRS has been adopted by international operational weather prediction centers in their analysis and forecasting systems and also provides a key part of the meteorological observing system for MERRA-2. The demonstrable value of NASA’s AIRS observations also provided the impetus for developing hyperspectral infrared radiance instruments by the weather agencies, with the Infrared Atmospheric Sounding Interferometers (IASI) on the EUMETSAT Metop spacecraft and the Cross-track Infrared Sounders (CrIS) on the NASA-NOAA Suomi-NPP and JPSS platforms providing massive boosts in the number of available observations for use in weather analysis and forecasting. These measurements all provide critical inputs to the observing system used in MERRA-2. One of the fundamental scientific goals of the GMAO reanalysis projects is to provide the optimal estimate atmospheric state in a manner that is consistent over time. These animations illustrate how different the observing system were in 1980 compared to today. On the one hand, these animations demonstrate the critical role that NASA has played in developing the observing systems that are used in satellite measurements, including the enhancements of the spacecraft observations between 1980 and the present time. They also highlight one of the great challenges in producing consistent long-term records of the atmospheric state in MERRA-2 and other reanalyses: technological advances lead to larger numbers of higher quality observations. Even though the underlying assimilation systems remain frozen over time, the great challenge is to overcome the impacts of an ever improving suite of observations.
  • From Observations to Models
    2015.05.07
    NASA’s Global Modeling and Assimilation Office (GMAO) uses the Goddard Earth Observing System Model, Version 5 Data Assimilation System (GEOS­-5 DAS) to produce global numerical weather forecasts on a routine basis. GMAO forecasts play important roles in managing NASA’s fleet of science satellites and in researching the impact of new satellite observations. In order to provide timely information about the state of the atmosphere for NASA instrument teams and researchers, the GMAO runs the GEOS-­5 DAS four times each day in real time. For each forecast, it is necessary to provide accurate initial conditions that drive the GEOS-­5 forecasts. To do this, the best estimate of the full, three-dimensional atmospheric state is determined by combining the latest observations and a short-term, 6-­hour forecast—a process known as data assimilation. The GEOS-­5 DAS assimilates more than 5 million observations during each 6-hour assimilation period. These observations are assembled from a number of sources from around the globe, including NASA, NOAA, EUMETSAT (European Organization for the Exploitation of Meteorological Satellites), commercial airlines, the US Department of Defense, and many others. Similarly, each observation type has its own sampling characteristics. It can be seen in the animation how different observation types have different strategies. One of the main challenges of data assimilation is to understand how all these observations are alike, how they differ, and how they interact with each other. Funding for the development of the GEOS-5 model and data assimilation system development comes from NASA's Modeling, Analysis, and Prediction Program and the NASA Weather Focus Area's contribution to the Joint Center for Satellite Data Assimilation. The GEOS-5 DAS runs at the NASA Center for Climate Simulation, which is funded by NASA’s High-End Computing Program. For More Information: http://gmao.gsfc.nasa.gov/ http://www.nccs.nasa.gov/images/data_assim_story_072815.pdf
  • Sulfur Dioxide 2018 Update
    2019.02.12
    Sulfur dioxide is an atmospheric pollutant that poses threats to both human health and the environment. High concentrations of sulfur dioxide irritate the eyes, nose, and lungs, and can result in temporary breathing impairment. It is also a precursor to sulfuric acid, a major constituent of acid rain.

    This visualization, created using data from the Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite, shows annual, average changes in sulfur dioxide concentrations from 2005 to 2017. Sulfur dioxide concentrations from volcanic (i.e., natural) sources have been removed.

    Sulfur dioxide is produced by the combustion of coal, fuel oil, and gasoline (since these fuels contain sulfur), and in the oxidation of naturally occurring sulfur gases, such as in volcanic eruptions. The largest source of sulfur dioxide in the atmosphere is the burning of fossil fuels by power plants and other industrial facilities. National and regional rules to reduce emissions of sulfur dioxide can improve air quality.

  • GEOS-5 Aerosols Simulation for SC 2014
    2014.12.10
    This animation was shown on the hyperwall at the Supercomputing conference in 2014 (SC 2014). This animation covers the period March 1, 2007 - June 16, 2007.
  • A 3-D Look at Weather, Clouds, and Aerosols
    2015.10.02

    This gallery was created for Earth Science Week 2015 and beyond. It includes a quick start guide for educators and first-hand stories (blogs) for learners of all ages by NASA visualizers, scientists and educators. We hope that your understanding and use of NASA's visualizations will only increase as your appreciation grows for the beauty of the science they portray, and the communicative power they hold. Read all the blogs and find educational resources for all ages at: The Earth Science Week 2015 page.

    I've always been fascinated by our atmosphere. Think about it: even though we don't see it, above us is a great aerial ocean! Over time my fascination has grown from weather maps and pondering the origins of storms, to learning all about the physics that surround our everyday lives. From as early as grade school I was also very interested in computers: diagnosing errors, developing programming skills and learning all about hardware and operating systems. So you might say my interests naturally led me to a career as a NASA scientist, where I create visualizations to study the underlying factors that drive weather patterns. Visualizations help us to see the world differently and actively.

    Many of you have no doubt seen your homes from space using a program called Google Earth™. But did you know you could do a lot more with the right data? In fact I often use it to map atmospheric data in three-dimensions (3-D) around the globe. But one of the challenges I often face is that data comes from many different sources, such as NASA and NOAA satellites or ground-observation stations. This means the data is stored on computer disks all over the country and are named and organized according to different standards, requiring us to customize techniques for producing accurate visualizations in one, 3-D display of the Earth. We do this in order to analyze atmospheric relationships more easily because many weather phenomena arise from physical interactions, both horizontally and vertically, in the global circulation.

    A big part of atmospheric research relies on using computer models to simulate what our atmosphere will do under different conditions. A great example of this is the data used to prepare the daily weather forecast. This data originates from weather forecasting models that calculate atmospheric motions using the world’s fastest supercomputers. But how do we know these forecasts are accurate? Researchers can verify a model's performance by visualizing one of the variables such as temperature, humidity, wind speed, wind direction, or air pressure and then using color shading, contour curves, and wind "barbs" to graph that data. Then they overlay the observations from NASA satellites such as cloud-top imagery, cloud-top temperature, and vertical distributions of clouds and aerosols, with the graph (it can be challenging to synchronize the data display as these times usually don't match). After this process, the display confirms the model's accuracy. This method is used to study many atmospheric events, such as timing of a storm system, precipitation, or the direction of dust or smoke transport.

    My passion is transforming weather data into rich visualizations that allow us to see things differently or tell us a story. My favorite part is using remotely-sensed NASA data to view clouds over the oceans. This is very important because ground observations are sparse to non-existent for oceans, which cover much of the Earth's surface. Warm oceans are what allow hurricanes to form. Visualization tools can greatly aid the interpretation of data used to understand and forecast hurricanes by integrating multiple datasets into a common display. This helps to communicate to the public the track and intensity of tropical storms, which is absolutely vital for the safety of millions of people around the world, especially those living in coastal communities.

    Ultimately, it's how my work impacts understanding of weather and potentially helps the rest of the world that keeps me motivated. I have been very lucky to explore our planet in a new and different way and to continually rediscover my passion for Earth science. It’s been a remarkable journey — challenging, fulfilling and ever-changing — and I hope many of you choose to undertake it!

    -- Roman Kowch, Staff Research Scientist (SSAI/NASA Langley Research Center)

  • NASA Scientists see Gravity Waves in Concentric Rings
    2018.10.10
    NASA scientists have tracked gravity waves spreading upward for hundreds of miles and outward for thousands of miles in concentric rings, like ripples in a pond. The waves were created by a large convective storm in 2013 that also spawned a deadly tornado. The visualization shows near-simultaneous measurements of the gravity waves in the troposphere, stratosphere and ionosphere. The Atmospheric Infrared Sounder (AIRS) instrument on NASA's Aqua satellite detected gravity waves in the troposphere and stratosphere 12 hours before a deadly EF5 tornado in Moore, Oklahoma. Even stronger waves were detected 11 hours later during AIRS’ next pass. The tornado and waves were produced by a long-lived storm system. In the ionosphere 250 miles (400 kilometers) above Earth's surface, the gravity waves appear as traveling ionospheric disturbances (TIDs) -- disturbances in the electron content of the region. These were observed in Total Electron Content measurements by ground-based GPS receivers throughout the south central United States. In the visualization, these ionospheric disturbances are shown in greens and yellows. Gravity waves are formed when a disturbance causes air to be displaced into a region of different air density. There are many common causes for this besides storms -- for example, an air current strikes a mountain and is pushed upward. As gravity waves grow and propagate upward, they play important roles in the upper levels of the atmosphere. In the stratosphere, gravity waves help drive the atmospheric circulation and move ozone from the tropics to the poles. Observations such as these at multiple heights in the atmosphere provide a unique perspective on how atmospheric layers are linked together. Understanding the spread of gravity waves improves global weather forecasting and space weather forecasting.
  • Monthly Aerosol Optical Thickness (Aqua/MODIS)
    2013.10.24
    Tiny solid and liquid particles suspended in the atmosphere are called aerosols. These particles are important to scientists because they represent an area of great uncertainty in their efforts to understand Earth's climate system. These maps show monthly aerosol optical thickness, derived using measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Aqua satellite, from July 2002 to the present. Aerosol optical thickness is a measure of how much light the airborne particles prevent from traveling through the atmosphere. Aerosols absorb and scatter incoming sunlight, thus reducing visibility and increasing optical thickness. Dark orange pixels show high aerosol concentrations, while light orange pixels show lower concentrations, and light yellow areas show little or no aerosols. Black shows where the sensor could not make its measurement. An optical thickness of less than 0.1 (light yellow) indicates a crystal clear sky with maximum visibility, whereas a value of 1 (dark orange) indicates the presence of aerosols so dense that people would have difficulty seeing the sun.
  • Monthly Aerosol Particle Radius (Aqua/MODIS)
    2013.10.24
    Tiny solid and liquid particles suspended in the atmosphere are called aerosols. These particles are important to scientists because they can affect climate, weather, and people's health. Using satellites scientists can tell whether a given plume of aerosols came from a natural source or were produced by human activities. Two important clues about aerosols' sources are particle size and location of the plume. Natural aerosols (such as dust and sea salts) tend to be larger than man-made aerosols (such as smoke and industrial pollution). These maps show monthly aerosol particle radius from July 2002 to the present, derived using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Aqua satellite. Red areas show aerosol plumes made up of smaller particles. These red-colored plumes are over regions where we know humans produce pollution. Green areas show aerosol plumes made up of larger particles. These green-colored plumes are over regions where we know aerosols occur naturally. Yellow areas show plumes in which large and small aerosol particles are intermingling. Black shows where the satellite could not measure aerosols. Maps such as these allow scientists to estimate the location and size of aerosol particles present in the atmosphere.
  • Ozone Transport in the Tropical Western Pacific
    2016.02.24
    NASA-funded scientists have traced the origins of mysterious pockets of high ozone concentrations and low water vapor in the air above the western Pacific Ocean near Guam to fires burning in Southeast Asia and in Africa, half a world away. These pockets of ozone—a powerful greenhouse gas—are three times more concentrated than surrounding air and are found at around 30,000 feet in the lower part of Earth’s atmosphere known as the troposphere, within the cruising altitude of most commercial airliners. As a greenhouse gas, ozone in the troposphere is an important contributor to global warming, but because it varies widely in where it occurs and how long it stays aloft, its true impact on climate change is hard to determine. Researchers studying the air over Guam during the winter of 2014 during a pair of airborne field campaigns captured a comprehensive picture of the chemicals traveling with the ozone—chemicals such as hydrogen cyanide and acetonitrile, which originate in fires. Using a data-driven computer model, they then traced the ozone-laden air pockets back 10 to 15 days in most cases—right back to fires in either Southeast Asia, about 2,000 miles away, or tropical Africa, over 8,000 miles away. The animation begins by showing a single NCAR Gulfstream V aircraft flight from the CONTRAST campaign that was outfitted to measure various trace gases. From the measurements taken on this flight, the backflow trajectories are modelled using the NOAA HYSPLIT model, stepping back in time for the previous 10 days or until the trajectories encountered convection. The trajectories are coloured by observed aircraft ozone level where blue values represent low concentrations of ozone and red represents high values. The ozone value is invariant along each trajectory. The active fire locations detected during the prior 48 hours are shown as yellow/gold points. Areas depicting highly convective regions are shown in white.
  • NPP Ceres Longwave Radiation
    2012.07.22
    The CERES experiment is one of the highest priority scientific satellite instruments developed for NASA's Earth Observing System (EOS). The doors are open on NASA's Suomi NPP satellite and the newest version of the Clouds and the Earth's Radiant Energy System (CERES) instrument is scanning Earth for the first time, helping to assure continued availability of measurements of the energy leaving the Earth-atmosphere system.

    CERES products include both solar-reflected and Earth-emitted radiation from the top of the atmosphere to the Earth's surface. Cloud properties are determined using simultaneous measurements by other EOS and NPP instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible and Infrared Sounder (VIRS). Analyses using CERES data, build upon the foundation laid by previous missions such as NASA Earth Radiation Budget Experiment (ERBE), leading to a better understanding of the role of clouds and the energy cycle in global climate change.

    The sun's radiant energy is the fuel that drives Earth's climate engine. The Earth-atmosphere system constantly tries to maintain a balance between the energy that reaches the Earth from the sun and the energy that flows from Earth back out to space. Energy received from the sun is mostly in the visible (or shortwave) part of the electromagnetic spectrum. About 30% of the solar energy that comes to Earth is reflected back to space. The ratio of reflected-to-incoming energy is called "albedo" from the Latin word meaning whiteness. The solar radiation absorbed by the Earth causes the planet to heat up until it is radiating (or emitting) as much energy back into space as it absorbs from the sun. The Earth's thermal emitted radiation is mostly in the infrared (or longwave part of the spectrum. The balance between incoming and outgoing energy is called the Earth's radiation budget.

    This global view shows CERES top-of-atmosphere (TOA) longwave radiation from Jan 26 and 27, 2012. Heat energy radiated from Earth (in watts per square meter) is shown in shades of yellow, red, blue and white. The brightest-yellow areas are the hottest and are emitting the most energy out to space, while the dark blue areas and the bright white clouds are much colder, emitting the least energy. Increasing temperature, decreasing water vapor, and decreasing clouds will all tend to increase the ability of Earth to shed heat out to space.

    For more information on the Clouds and Earth's Radiant Energy System (CERES) see http://ceres.larc.nasa.gov

  • NPP Ceres Shortwave Radiation
    2012.07.22
    The CERES experiment is one of the highest priority scientific satellite instruments developed for NASA's Earth Observing System (EOS). The doors are open on NASA's Suomi NPP satellite and the newest version of the Clouds and the Earth's Radiant Energy System (CERES) instrument is scanning Earth for the first time, helping to assure continued availability of measurements of the energy leaving the Earth-atmosphere system.

    CERES products include both solar-reflected and Earth-emitted radiation from the top of the atmosphere to the Earth's surface. Cloud properties are determined using simultaneous measurements by other EOS and NPP instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible and Infrared Sounder (VIRS). Analyses using CERES data, build upon the foundation laid by previous missions such as NASA Earth Radiation Budget Experiment (ERBE), leading to a better understanding of the role of clouds and the energy cycle in global climate change.

    The sun's radiant energy is the fuel that drives Earth's climate engine. The Earth-atmosphere system constantly tries to maintain a balance between the energy that reaches the Earth from the sun and the energy that flows from Earth back out to space. Energy received from the sun is mostly in the visible (or shortwave) part of the electromagnetic spectrum. About 30% of the solar energy that comes to Earth is reflected back to space. The ratio of reflected-to-incoming energy is called "albedo" from the Latin word meaning whiteness. The solar radiation absorbed by the Earth causes the planet to heat up until it is radiating (or emitting) as much energy back into space as it absorbs from the sun. The Earth's thermal emitted radiation is mostly in the infrared (or longwave part of the spectrum. The balance between incoming and outgoing energy is called the Earth's radiation budget.

    This global view shows CERES top-of-atmosphere (TOA) shortwave radiation from Jan 26 and 27, 2012. Thick cloud cover tends to reflect a large amount of incoming solar energy back to space (blue/green/white image).

    For more information on the Clouds and Earth's Radiant Energy System (CERES) see http://ceres.larc.nasa.gov

  • Earth System Diagram
    2018.08.29
    Like the human body, Earth comprises diverse processes and systems that interact with one another in complex ways. The purpose of NASA’s Earth science program is to advance our scientific understanding of Earth as an integrated system and its response to natural and human-induced changes. NASA works with its domestic and international partners to support a large number of Earth-observing satellite and airborne missions to observe and understand our planet on global and regional scales. These missions are able to collect measurements of surface temperature, winds, water vapor, clouds, precipitation, soil moisture, ocean salinity, and other aspects of the environment. While scientists learn a great deal from studying individual phenomena, improved observational capabilities, coupled with process-level and global numerical models increasingly allow them to study component system interactions, leading to unprecedented insight into how Earth functions as one integrated system of systems.

Weather and Atmospheric Dynamics

The Weather and Atmospheric Dynamics focus area (WAD) supports research to obtain accurate measurements of the atmosphere that help improve short-term, subseasonal, and seasonal weather predictions at local, regional, and global scales. Weather includes everything from localized microphysical processes that occur in minutes, to global-scale phenomena that can occur for an entire season. WAD helps improve our knowledge of the fundamental processes that drive these systems and inform the operational infrastructure upon which other federal agencies rely, including the National Oceanic and Atmospheric Administration (NOAA), the Federal Aviation Administration (FAA), and the Department of Defense (DOD). WAD further supports research into profiling winds, temperature, humidity, pressure, and aerosols; air-sea and land-atmosphere interactions; and lightning occurrences.
  • GPM observes Hurricane Dorian over the Bahamas
    2019.09.03
    The Global Precipitation Measurement (GPM) Core Observatory captured these images of Hurricane Dorian on September 1st (21:22 UTC) as the storm was directly over Abaco Island in The Bahamas. At that time, the storm was a category 5 hurricane with maximum sustained winds of 185 mph (295 km/h) with gusts over 200 mph.
  • Global Surface- and Upper-Level Winds
    2017.08.29
    This entry compiles a series of animations created for the use of WGBH in an educational webside. The animations visualize data from the MERRA reanalysis product, showing winds at both the 850 mb and 250 mb levels. The upper level is rainbow-colored, the lower level is white. Both color and opacity of each level are being driven by windspeed.

  • GPM observes Hurricane Dorian lashing Florida
    2019.09.06
    GPM captured Dorian at 10:41 UTC (6:41 am EDT) on the 4th of September when the storm was moving north-northwest parallel to the coast of Florida about 90 miles due east of Daytona Beach. Three days earlier, Dorian had struck the northern Bahamas as one of the most powerful Category 5 hurricanes on record in the Atlantic with sustained winds of 185 mph. Weakening steering currents allowed the powerful storm to ravage the northern Bahamas for 2 full days. During this time, Dorian began to weaken due to its interactions with the islands as well as the upwelling of cooler ocean waters from having remained in the same location for so long. Immediately apparent is Dorian’s well-defined but very large eye. This feature is often seen in the later stages of powerful tropical cyclones, which includes hurricanes and typhoons. As these mature, powerful storms age, their wind field tends to expand. They often undergo what is known as eye wall replacement cycles wherein a 2nd concentric eye wall forms outside of the original inner eye wall. The inner eye wall is choked off and weakens leaving the outer eye wall as the dominant eye wall. The outer eye wall can still contract, but often the storm is left with a larger eye as is the case with Dorian. At the time of this image, Dorian’s maximum sustained winds were still 105 mph, making it a Category 2 storm, but a very large Category 2 storm. GPM data is archived at https://pps.gsfc.nasa.gov/
  • GPM Satellite observes powerful super Typhoon Yutu hitting Northern Marianas
    2018.10.26
    NASA's GPM Core observatory satellite captured an image of Super Typhoon Yutu when it flew over the powerful storm just as the center was striking the central Northern Mariana Islands north of Guam. Early Thursday, Oct. 25 local time, Super Typhoon Yutu crossed over the U.S. commonwealth of the Northern Mariana Islands. It was the equivalent of a Category 5 hurricane. The National Weather Service in Guam said it was the strongest storm to hit any part of the U.S. this year. The Global Precipitation Measurement mission or GPM core satellite, which is managed by both NASA and the Japan Aerospace Exploration Agency, JAXA analyzed Yutu on Oct. 24 at 11:07 a.m. EDT (1507 UTC)/ 1:07 a.m. Guam Time, Oct. 25. GPM estimated rain rates within Super Typhoon Yutu fusing data from two instruments aboard: the GPM Dual-frequency Precipitation Radar or DPR, which covered the inner part of the storm, and the GPM Microwave Imager or GMI that analyzed the outer swath, just as the center was passing over the Island of Tinian. GPM shows the inner eyewall as a near perfect ring of heavy to intense rain. Peak rain rates of up to 269 mm/hr. (~10.6 inches/hr.) were estimated within the DPR swath. The almost perfect symmetry of the inner wall is indicative of an extremely powerful storm. In fact, at the time this image was taken, Yutu's maximum sustained winds were estimated at 155 knots (~178 mph) by the Joint Typhoon Warning Center, making it the strongest typhoon on record to strike Saipan and Tinian. GPM data is part of the toolbox of satellite data used by forecasters and scientists to understand how storms behave. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. Current and future data sets are available with free registration to users from NASA Goddard's Precipitation Processing Center website.
  • GPM Captures Super Typhoon Mangkhut Approaching The Philippines
    2018.09.19
    At nearly the same time that the US East Coast was experiencing the arrival of Hurricane Florence, a much more powerful storm was also arriving half a world away in the Philippines—Super Typhoon Mangkhut. While the slow-moving Florence arrived as a Category 1 hurricane that brought record flooding to the Carolinas, less than 7 hours later Mangkhut (known as Ompong in the Philippines) made landfall on the northern main island of Luzon as a full on Category 5 super typhoon with sustained winds reported at 165 mph. The visualization starts with a view of Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation rates from 15:11 UTC (11:11 pm PST) 12 September to 15:41 UTC (11:41 pm PST) 13 September 2018 as the storm was making its way across the Philippine Sea headed for Luzon. Before entering the Philippine Sea, Mangkhut passed just north of Guam on the evening of the 10th as a Category 2 typhoon with sustained winds reported at 105 mph by the Joint Typhoon Warning Center (JTWC) causing widespread power outages. The next day on the 11th as it entered the eastern Philippine Sea, Mangkhut underwent a rapid intensification cycle wherein the storm’s intensity shot from Category 2 on the afternoon of the 10th (local time) to Category 5 with sustained winds estimated at 160 mph by JTWC by the evening of the 11th (local time). Mangkhut is estimated to have reached its peak intensity at 18:00 UTC on the 12th (2:00 am PST 13 September) with maximum sustained winds estimated at 180 mph by JTWC, making it the strongest tropical cyclone of the year thus far. At the start of the visualization, Mangkhut was an extremely powerful Category 5 super typhoon and just approaching its peak intensity. Over the next 24 hours, Mangkhut’s intensity leveled out such that when the GPM core satellite over flew the storm, Mangkhut’s peak intensity was estimated at 165 mph, a still very powerful Category 5 storm. The end of the visualization shows the surface rainfall within Mangkhut as well as a 3D flyby of the storm courtesy of the GPM core satellite, which passed over the storm at around 15:40 UTC (11:40 pm PST) on the 13th. At the surface, a distinct eye is present surrounded by a large area of very heavy to intense rain (shown in dark red and magenta). Further out, heavy rain bands are rotating counter clockwise around the storm’s center. The flyby shows a 3D rendering of the radar structure of Mangkhut using data collected from GPM’s Dual-frequency Precipitation Radar or DPR. At the heart of the storm surrounding the eye is a ring of elevated echo tops associated with Mangkhut’s eyewall. The strong symmetry and continuity of the ring is consistent with an intense tropical cyclone and suggests no inhibiting effects such as dry air or wind shear are affecting the storm. In fact, after these images were taken, Mangkhut would continue on to strike the northern part of Luzon at the same estimated intensity, becoming the strongest typhoon to hit the Philippines since Super Typhoon Haiyan in 2013. So far the storm is being blamed for at least 95 fatalities in the Philippines, many due to a large landslide around the town of Itogon. After crossing Luzon, Mangkhut continued on to strike Hong Kong with winds reported at 121 mph before dissipating over mainland China, where it is being blamed for 6 fatalities. GPM data is part of the toolbox of satellite data used by forecasters and scientists to understand how storms behave. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. Current and future data sets are available with free registration to users from NASA Goddard's Precipitation Processing Center website.
  • GOES and GPM Capture Florence Trying to Intensify Over the Atlantic
    2018.09.12
    Hurricane Florence originally formed from an African Easterly wave that emerged off the west coast of Africa back on the 30th of August. When it reached the vicinity of the Cape Verde Islands the next day, it was organized enough to become a tropical depression. The following day the depression strengthened enough to become a tropical storm and Florence was born on the 1st of September. Over the next 3 days, Florence gradually strengthened as it moved in a general west-northwest direction into the central Atlantic. Then, on the 4th of September, Florence began to rapidly intensify. By the morning of the 5th, Florence was a Category 3 hurricane before reaching Category 4 intensity later that afternoon with maximum sustained winds estimated at 130 mph by the National Hurricane Center (NHC). At this point, Florence became the victim of increasingly strong southwesterly wind shear, which greatly weakened the storm all the way back down to a tropical storm the by evening of the 6th. The following GOES-East Infrared (IR) loop shows Florence from 17:54 UTC (1:54 pm EDT) 6 September to 19:27 UTC (3:27 pm EDT) 7 September when it was struggling against the strong southwesterly wind shear in the Central Atlantic. A very interesting looking feature is the arc-shaped cloud that propagates outward from the storm towards the west. This cloud feature is occurring at upper-levels and is likely tied to a gravity wave propagating outward from an area of intense convection that erupted from deep within the storm. When the tops of these smaller scale storms within a storm reach the upper troposphere, they can trigger gravity waves. As these waves progagate outward they can enhance cloud formation where they induce rising motion and erode cloud where they induce downward motion or subsidence. As this arc-shaped cloud is able to propagate outward uniformly from the center, it must be occurring above the shear layer. Compensating areas of subsidence can also surround the strong rising motion occurring within the tall convective clouds. This can help to erode surrounding clouds and may be contributing to the clearing that occurs between the arc-shaped cloud and the main area of convection. The end of the loop shows surface rainfall and a 3D flyby of Florence courtesy of the GPM core satellite, which passed over the storm at around 19:21 UTC (3:21 pm EDT) on the 7th. At the surface, two areas of intense rain (shown in magenta) reveal the presence of two areas of strong thunderstorms within Florence north and northeast of the center. The flyby shows a 3D rendering of the radar structure of the storm. The darker blue tower indicates an area of deep convection that has penetrated well over 10 km high and is associated with the southernmost area of intense rain just north of the center. It is these areas of deep convection that fuel the storm by releasing heat, known as latent heat, mainly from condensation, near the core. Although it would be nearly 2 days before Florence re-gained hurricane intensity, these convective towers are what helped Florence to survive the effects of the wind shear and eventually grow back into a Category 4 hurricane. GPM is a joint mission between NASA and the Japanese space agency JAXA. Caption by Stephen Lang (SSAI/NASA GSFC) and Joe Munchak (GSFC). A short 360 video flying under Florence is available here:
    Look for a longer narrated 360 video flying through Hurricane Maria in the coming weeks!
  • NASA's Black Marble night lights used to examine disaster recovery in Puerto Rico
    2018.12.09
    At night, Earth is lit up in bright strings of roads dotted with pearl-like cities and towns as human-made artificial light takes center stage. During Hurricane Maria, Puerto Rico's lights went out. In the days, weeks, and months that followed, research physical scientist Miguel Román at NASA's Goddard Space Flight Center in Greenbelt, Maryland, and his colleagues combined NASA's Black Marble night lights data product from the NASA/NOAA Suomi National Polar-orbiting Partnership satellite with USGS-NASA Landsat data and Google's OpenStreetMap to develop a neighborhood-scale map of energy use in communities across Puerto Rico as the electricity grid was slowly restored. They then analyzed the relationship between restoration rates in terms of days without electricity and the remoteness of communities from major cities.
  • Surface Flooding from Hurricane Harvey
    2017.09.08
    A new series of images generated with data from NASA's Soil Moisture Active Passive (SMAP) satellite illustrates the surface flooding caused by Hurricane Harvey from before its initial landfall through August 27, 2017. The SMAP observations detect the proportion of the ground covered by surface water within the satellite's field of view. The sequence of images depicts successive satellite orbital swath observations showing the surface water conditions on August 22, before Harvey's landfall (left), and then on August 27, two days after landfall (middle). The resulting increase in surface flooding from record rainfall over the three-day period, shown at right, depicts regionally heavy flooding around the Houston metropolitan area. The hardest hit areas (blue and purple shades) cover more than 23,000 square miles (about 59,600 square kilometers) and indicate a more than 1,000-fold increase in surface water cover from rainfall-driven flooding. SMAP's low-frequency (L-band) microwave radiometer features enhanced capabilities for detecting surface water changes in nearly all weather conditions and under low-to-moderate vegetation cover. The satellite provides global coverage with one- to three-day repeat sampling, which is well suited for monitoring dynamic inland waters around the world.
  • Hurricane Irma Turns Caribbean Islands Brown
    2017.09.20
    Hurricane Irma churned across the Atlantic Ocean in September 2017, battering several Caribbean islands before moving on to the Florida Keys and the U.S. mainland. As the clouds cleared over places like the Virgin Islands, the destruction became obvious even from space. These natural-color images, captured by the Operational Land Imager (OLI) on the Landsat 8 satellite, show some of Irma’s effect on the British and U.S. Virgin Islands. The views were acquired on August 25 and September 10, 2017, before and after the storm passed. They are among the few relatively cloud-free satellite images of the area so far. The most obvious change is the widespread browning of the landscape. There are a number of possible reasons for this. Lush green tropical vegetation can be ripped away by a storm’s strong winds, leaving the satellite with a view of more bare ground. Also, salt spray whipped up by the hurricane can coat and desiccate leaves while they are still on the trees. Irma passed the northernmost Virgin Islands on the afternoon of September 6. At the time, Irma was a category 5 storm with maximum sustained winds of 185 miles (295 kilometers) per hour. According to news reports, the islands saw “significant devastation.” The destruction is also clearly visible on Barbuda. This small island in the eastern Caribbean was directly hit by the category-5 storm early on September 6. These images were acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites. The left image shows Barbuda on August 21, 2017. The right image shows the ravaged landscape on September 8. In contrast, vegetation on Antigua appears relatively healthy and intact. With the storm’s center passing to the north, the island sustained less damage. Ground reports noted that by September 7, electricity had been restored to most of the island, and the international airport reopened.
  • Hurricane Train
    2017.11.13
    In September 2017, a train of hurricanes barreled into North America and the Caribbean.
  • GPM Examines Hurricane Irma
    2017.09.10
    The GPM core observatory satellite had an exceptional view of hurricane Irma's eye when it flew above it on September 5, 2017 at 12:52 PM AST (1652 UTC). This visualization shows a rainfall analysis that was derived from GPM's Microwave Imager (GMI) and Dual-Frequency Precipitation Radar (DPR) data. Irma was approaching the Leeward Islands with maximum sustained winds of about 178 mph (155 kts). This made Irma a dangerous category five hurricane on the Saffir-Simpson hurricane wind scale. Intense rainfall is shown within Irma's nearly circular eye. This 3-D cross-section through Irma's eye was constructed using GPM's radar (DPR Ku band) data. GPM's radar revealed that the heavy precipitation rotating around the eye was reaching altitudes greater than 7.75 miles (12.5 km). The tallest thunderstorms were found by GPM's radar in a feeder band that was located to the southwest of Irma's eye. These extreme storms were reaching heights of over 10.0 miles (16.2 km). Intense downpours in the eye wall were found to be returning radar reflectivity values of over 80dBZ to the GPM satellite. Irma rapidly intensified on September 4-5 as it moved over very warm waters and into an environment will weak vertical wind shear (the change of winds with height). Irma maintained maximum winds of 185 mph for a day and a half, making it one of the longest-lived storms at this intensity. That intensity made it the strongest observed storm over the Atlantic Ocean (excluding the Gulf of Mexico and Caribbean). Irma’s rapid intensification was very similar to Hurricane Harvey's in the Gulf about 10 days earlier.
  • Tracking Kilo from Hurricane to Typhoon
    2015.09.17
    The Global Precipitation Measurement (GPM) mission's core satellite captured Hurricane Kilo throughout its life cycle as Kilo slowly worked it's way westward across the Pacific Ocean. Kilo eventually crossed the international dateline where it officially changed from a "hurricane" to a "typhoon". Along it's way, Kilo put itself in the record books. Kilo was the 3rd named storm of the 2015 hurricane season to cross the international dateline. It was also a very long lasting storm persisting for 21 days, which made it a fairly rare event. Because it was such a long lasting storm, GPM was able to capture it several times throughout the course of it's life span. Such multiple captures of the same storm can help scientists better understand the development of hurricanes.
  • GPM Monitors Hurricane Matthew Flooding the Carolinas
    2016.10.11
    NASA's Global Precipitation Measurement mission or GPM core observatory satellite flew over Hurricane Matthew as the category 2 hurricane drenched North and South Carolina with record-breaking rainfall on October 8, 2016 resulting in historical flooding throughout the Carolinas. The GPM Core Observatory carries two instruments that show the location and intensity of rain and snow, which defines a crucial part of the storm structure – and how it will behave. The GPM Microwave Imager sees through the tops of clouds to observe how much and where precipitation occurs, and the Dual-frequency Precipitation Radar observes precise details of precipitation in 3-dimensions. GPM data is part of the toolbox of satellite data used by forecasters and scientists to understand how storms behave. GPM is a joint mission between NASA and the Japan Aerospace Exploration Agency. Current and future data sets are available with free registration to users from NASA Goddard's Precipitation Processing Center website.
  • 2017 North Atlantic Hurricane Season Simulation
    2017.11.13
    This visualization, created using simulated infrared brightness temperature data at 6-kilometer resolution, shows cloud patterns across the Western Hemisphere from September 5-30, 2017. At the start of the simulation, generated using NASA’s Goddard Earth Observing System (GEOS) model, you can see Hurricane Irma in the Atlantic. On September 5, Irma strengthened into a strong and “potentially catastrophic” category 5 hurricane. On September 7, 2017, hurricanes Katia (left, Category 1), Irma (center, Category 5), and Jose (right, Category 3) lined up across the Atlantic basin. The Atlantic hasn’t had three hurricanes at once since 2010 when hurricanes Igor, Julia, and Karl marched across the tropics—storms that also begin with letters I, J, and K. Later in the month, hurricane Maria reached Category 5 strength on September 18, just before making landfall on Dominica. On September 20, an eyewall replacement cycle took place, weakening Maria to a high-end Category 4 hurricane by the time it struck Puerto Rico. Hurricane Maria is regarded as the worst natural disaster on record in Dominica and Puerto Rico.
  • Hurricane Tracks from 2017 with Precipitation and Cloud Data
    2017.10.05
    These visualizations show the tracks of Atlantic hurricanes during 2017. Data from the Global Precipitation Mission called IMERG is used to show rainfall and data from NOAA's GOES East shows clouds. Storm position and wind speed data from UNISYS are used to show the track lines. The numbers 1 through 5 as well as "T" are displayed when storms change categories. The "T" stands for tropical storm. There are 2 visualizations at various resolutions: - a wide Atlantic view that shows all of the hurricane tracks - a view that follows and zooms in only on Hurricane Harvey These visualizaitons were created to support NASA talks given at the National Air and Space Musuem (NASM) in October 2017. The wide Atlantic view was updated at the end of hurricane season to include all Atlantic hurricanes in 2017 for display at the American Geophysical Union (AGU) conference. These visualizations only go through October 2017 because there were no Atlantic hurricanes in November or December 2017.
  • Inside Hurricane Maria in 360°
    2018.10.04
    Tour Hurricane Maria in a whole new way! Late on September 17, 2017 (10:08 p.m. EDT) Category 1 Hurricane Maria was strengthening in the Atlantic Ocean when the Global Precipitation Measurement (GPM) mission's Core Observatory flew over it. The Dual Frequency Precipitation Radar, measuring in a narrow band over the storm center, shows 3-D estimates of rain, with snow at higher altitudes. The tall "hot towers" characteristic of deepening hurricanes are actually topped by snow! Surface rainfall rates estimated by the GPM Microwave Imager paint the surface over a wider swath. During the tour, you'll see the radar-observed rain intensities displayed three different ways in various parts of the storm. Then, for the first time you'll see estimates of the precipitation particle sizes, which the GPM DPR is uniquely capable of showing, and which provide important insights into storm processes. GPM is a joint mission between NASA and the Japanese space agency JAXA.
  • Hurricane Matthew Rainfall Totals
    2016.11.14
    In 2016, Hurricane Matthew was a very powerful, long-lived and deadly tropical cyclone that became the first Category 5 Atlantic hurricane since Hurricane Felix in 2007. The storm travelled across the Western Atlantic, including parts of Haiti, Cuba, Dominican Republic and Lucayan Archipelago, the southeastern United States, and the Canadian Maritimes. This visualization shows the amount of rainfall dropped by Hurricane Matthew over the life and track of the storm from September 28 – October 10, 2016, using the global Integrated Multi-satellite Retrievals from GPM (IMERG) precipitation dataset. Hurricane Matthew’s interaction with a frontal boundary caused extreme rainfall in North Carolina resulting in over 20 inches (508 mm) of rain being reported in some locations. The area was already saturated before Hurricane Matthew arrived. Heavy rainfall from a slow moving low and frontal system moved through during the last week of September. Maximum rainfall total estimates for the real-time IMERG product have been adjusted to reflect observed values. The global IMERG precipitation dataset provides rainfall rates for the entire world every 30 minutes. IMERG is derived using data from the Global Precipitation Measurement (GPM) mission—a network of international satellites including the GPM Core Observatory.
  • NASA Studies Hurricane Matthew
    2017.07.31
    Hurricane Matthew was the first Category 5 Atlantic hurricane in almost ten years. Its torrential rains and winds caused significant damage and loss of life as it coursed through the Caribbean and up along the southeastern U.S. coast. Researchers use a combination of satellite observations to re-create a multi-dimensional picture of the hurricane in order to study the complex atmospheric interactions.
  • NASA Surveys Hurricane Damage to Puerto Rico's Forests (Data Viz Version)
    2019.07.29
    In September 2017, Hurricane Maria struck Puerto Rico head-on as a Category 4 storm with winds topping 155 miles per hour. The storm damaged homes, flooded towns, devastated the island's forests and caused the longest electricity black-out in U.S. history. Hurricane Maria's lashing rain and winds transformed Puerto Rico's lush tropical rainforest landscape. Research scientist Doug Morton of Goddard was part of the team of NASA researchers who had surveyed Puerto Rico's forests six months before the storm with Goddard’s Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager, a system designed to study the structure and species composition of Puerto Rican forests. Shooting 600,000 laser pulses per second, G-LiHT produces a 3D view of the forest structure in high resolution. In April 2018, post-Maria, they went back and surveyed the same tracks as in 2017. Comparing the before and after data, the team found that 40 to 60 percent of the tall trees that formed the canopy of the forest either lost large branches, were snapped in half or were uprooted by strong winds. "Maria gave the island's forests a haircut," said Morton. "The island lost so many large trees that forests were shortened by one-third. We basically saw 60 years' worth of what we would consider natural treefall disturbances happen in one day." This version was shown at the Association for Computing Machinery (ACM) / Special Interest Group on GRAPHics (SIGGRAPH) Computer Animation Festival (CAF) on July 29, 2019 at the Microsoft Theater in Los Angeles, CA. It will then be part of the ACM/SIGGRAPH CAF traveling show after that.
  • Major Hurricane Drought: Nine Years Without a Major Hurricane Making US Landfall
    2015.05.13
    Statistacal analyses from hurricane track data back to 1850 indicate that for any particular Atlantic Hurricane season, there is approximately a 40% chance that a major hurricane (categrory 3 or higher) will make landfall in the continental United States. However, during the 9-year period from 2006 to 2014, no major hurricanes have made landfall. These visualizations show hurricane tracks from 1980 through 2014. Green tracks are storms that did not make landfall in the continental US; yellow tracks are storms made landfall but were not category 3 or higher when they made landfall; and, red tracks are storms that made landfall and where category 3 or higher. A corresponding chart on the right accumulates the number and types of storms for each year. Notice the large gap in any red blocks between 2006 and 2014.
  • Global Hawk aircraft observes Hurricane Edouard
    2017.08.10
    NASA's Hurricane and Severe Storm Sentinel (HS3, 2012-2014) investigation was a mission that brought together several NASA centers with federal and university partners to investigate the processes that underlie hurricane formation and intensity change in the Atlantic Ocean basin. The aircraft was equipped with the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsonde system that releases small instrumented packages from the aircraft that fall to the surface while measuring profiles of temperature, humidity, and winds; the Scanning High-resolution Interferometer Sounder (S-HIS) that measures profiles of temperature and humidity; and the Cloud Physics Lidar (CPL) that measures cloud and aerosol total backscattered energy. NASA's HS3 mission pilots operated the Global Hawk aircraft on four consecutive 24-hour flights on Sept. 11-12, 14-15, 16-17, 18-19 into Hurricane Edouard and scored a bullseye by gathering information in the eye of the strengthening storm. During the Sept. 14-15 flight, the data from the Global Hawk revealed a storm that was quickly intensifying from a Category-1 to a Category-2 intensity storm. For more information about NASA's HS3 mission, visit: http://www.nasa.gov/hs3

  • High Resolution Layers from "Monsoons: Wet, Dry, Repeat..."
    2016.06.23
    The visualizations here are based on the visualization Monsoons: Wet, Dry, Repeat (#4397). Each data set is presented in three resolutions: 8192x4096, 4096x2048, and 2048x1024. Each the 8192x4096 and 4096x2048 layers have been rendered with alpha transparency channels to allow you to create your own combinations of layered data. NOTE: the preview movies are composited over a black background, but the individual 8192x4096 and 4096x2048 frames have transparency channels. The 2048x1024 frames do not have transparency channels. The layers have frame numbers from 01000 through 13000. Frame 01000 corresponds to 02 Jun 2014 at 00:00 GMT. Each successive frame is 15 minutes later. Frame 13000 corresponds to 05 Oct 2014 at 00:00 GMT. To determine the time for a specific layer's frame number, you can look at the date sequence's corresponding frame. Even though all layers are provided at 15 minute intervals, most data sets do not have such a high cadence. In these cases, the frames simply show the same data. See the annotation with each data set for the cadences.
  • Monsoons: Wet, Dry, Repeat...
    2016.06.23
    The monsoon is a seasonal rain and wind pattern that occurs over South Asia (among other places). Through NASA satellites and models we can see the monsoon patterns like never before. Monsoon rains provide important reservoirs of water that sustain human activities like agriculture and supports the natural environment through replenishment of aquifers. However, too much rainfall routinely causes disasters in the region, including flooding of the major rivers and landslides in areas of steep topography. This visualization uses a combination of NASA satellite data and models to show how and why the monsoon develops over this region. In the summer the land gets hotter, heating the atmosphere and pulling in cooler, moisture-laden air from the oceans. This causes pulses in heavy rainfall throughout the region. In the winter the land cools off and winds move towards the warmer ocean and suppressing rainfall on land.
  • 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.
  • IMERG Precipitation and MERRA Winds
    2015.10.08
    This visualization of assimilated surface winds from MERRA over the IMERG global precipitation data set was created for a forthcoming Science On a Sphere program about the Global Precipitation Measurement Mission.
  • Global Fire Weather Database
    2018.06.28
    The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, which tracks the dryness of three general fuel classes, and the potential behavior of a fire if it were to start. Each day, FWI values are calculated from global weather data, including satellite rainfall data from the Global Precipitation Measurement (GPM) mission. The FWI System is the most widely used fire danger rating system in the world, and has been adopted for different boreal, temperate and tropical fire environments. GFWED provides a globally consistent fire weather dataset for fire researchers and managers to apply locally. The Fire Weather Index component is suitable as a general index of fire danger. Globally, shifts in continental-scale fire activity follow seasonal changes in the FWI. Over South America and Africa, regions of high FWI and active agricultural burning shift with the tropical rain belts, seen in the GPM precipitation overlay. Over North America and Eurasia, the FWI will ‘activate’ in the spring, and shows how week-to-week surges in fire activity can be driven by high FWI values. In Indonesia, the Drought Code (DC) component is used to track the potential for agricultural fires to escape underground into peat soils, where they cannot be extinguished until the return of the monsoon rains. From August to October, areas of concentrated fire activity and high DC caused continuous smoke emissions and hazardously poor air quality until the return of the monsoon rains in November. Scientists are working with the Indonesian Agency for Meteorology, Climatology and Geophysics and the Ministry of Environment and Forestry to augment their operational FWI system with GPM precipitation. In British Columbia, Canada, 2017 was a severe fire year, where the FWI is used for fire prevention and pre-preparedness. Through July and August, stretches of high FWI in the interior led to periods of extreme fire behavior and the highest annual recorded burned area for the province. More information on GFWED and instructions on accessing the data are available from https://data.giss.nasa.gov/impacts/gfwed/

Climate Variability and Change

The Climate Variability and Change focus area (CVC) supports research to better understand the overall state of Earth’s climate and the physical processes that affect it. CVC supports focused and interdisciplinary research to better describe, understand, and predict the ways in which Earth’s ocean, atmosphere, land, and ice will interact and influence Earth’s climate over a wide range of timescales. To do this, CVC supports the development of climate data sets and computer models that leverage observations from relevant NASA and non-NASA platforms, including satellites, aircraft, and ships. These datasets include observations of sea surface height, temperature, and salinity; ocean currents and vector winds; sea ice extent and thickness; glacial topography, motion, and mass change; aerosol and cloud processes that affect Earth’s energy balance; and more. Through this work, CVC hopes to better predict changes in the Earth’s climate from sub-seasonal to multi-decadal time scales.
  • Global Sea Surface Currents and Temperature
    2012.03.16
    This visualization shows sea surface current flows. The flows are colored by corresponding sea surface temperature data. This visualization is rendered for display on very high resolution devices like hyperwalls or for print media.

    This visualization was produced using model output from the joint MIT/JPL project entitled Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2). ECCO2 uses the MIT general circulation model (MITgcm) to synthesize satellite and in-situ data of the global ocean and sea-ice at resolutions that begin to resolve ocean eddies and other narrow current systems, which transport heat and carbon in the oceans. The ECCO2 model simulates ocean flows at all depths, but only surface flows are used in this visualization.

  • Weekly Arctic Sea Ice Age with Graph of Ice Age By Area: 1984 - 2019
    2019.09.30
    One significant change in the Arctic region in recent years has been the rapid decline in perennial sea ice. Perennial sea ice, also known as multi-year ice, is the portion of the sea ice that survives the summer melt season. Perennial ice may have a life-span of nine years or more and represents the thickest component of the sea ice; perennial ice can grow up to four meters thick. By contrast, first year ice that grows during a single winter is generally at most two meters thick. Above is a visualization of the weekly sea ice age between 1984 and 2019. The animation shows the seasonal variability of the ice, growing in the Arctic winter and melting in the summer. In addition, this also shows the changes from year to year, depicting the age of the sea ice in different colors. Younger sea ice, or first-year ice, is shown in a dark shade of blue while the ice that is over four years old is shown as white. A color scale identifies the age of the intermediary years. Note that data for the sea ice age is not available along the coastlines. The region where data is not available is shown in a dark lavender color. A graph in the upper left corner the quantifies the change over time by showing the area covered by sea ice that is 4 years old or older in millions of square kilometers. This graph also includes a memory bar - the green line that indicates the maximum value seen thus far in the animation for the given week being displayed. For example, when viewing the sea ice age for the first week in September, the memory bar will display the maximum value seen for the first week of September in all prior years from the beginning of the animation (1984). In addition, a violet bar indicates the average area covered by sea ice greater than 4 years of age during the the 20-year time period from 1984 through 2003. Below are matching pairs of images showing identical weeks in two different years, where one year is late in the time series and the other is early. These matched images are labeled Pair 1A and Pair 1B. The caption below the image provides additional details. Each image is available with and without the graph.
  • Measuring Sea Ice Thickness with ICESat-2
    2019.09.06
    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. 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. Ice freeboard is calculated by differencing the heights of the ice surface and areas of open water next to the ice. Additional information including the depth and density of the snow layer on top of the ice is needed to convert this freeboard measurement to sea ice thickness. New state-of-the-art snow accumulation models have been developed to provide this extra data in preparation for the launch of ICESat-2. The very high precision of the ICESat-2 laser has enabled us for to measure the thickness of very thin sea ice for the first time. As the Arctic warms rapidly it is becoming increasingly dominated by a younger and thinner ice cover, making these new measurements extremely invaluable for understanding our changing polar regions.
  • Greenland's Glaciers as seen by RadarSat
    2015.08.25
    This animation is based on 30-meter topography data for Greenland along with an ocean and an ice sheet mask provided by the Greenland Ice Mapping Project (GIMP) at Ohio State. Each of these datasets consists of a 6 x 6 array of 124 megapixel tiles. The surface texture is derived from seven sets of 20-meter Radarsat reflectance data from the Canadian Space Agency, mosaicked at the University of Washington's Applied Physics Lab and accurately registered to the topography data. Each of six tile sets represents data for one year between 2000 and 2013, while the final one is a composite of the six years that has most areas of missing data resolved. Each of these tile sets consist of a 5 x 5 array of 421 megapixel tiles. The false color of the surface is derived as follows. Three different color scales are applied to the floating point Radarsat reflectance data based on their relationship within the GIMP masks. Areas within the ice sheet mask are mapped to a color ramp from white (high) to grey (low). Areas within the land region of the ocean mask but not in the ice sheet mask are similarly mapped to a color ramp of light to dark tan. The area indicating ocean is mapped to blue.
  • Hyperwall Show: CMIP5 - 21st Century Temperature and Precipitation Scenarios
    2014.03.05
    These data visualizations from the NASA Center for Climate Simulation and NASA's Scientific Visualization Studio at Goddard Space Flight Center, Greenbelt, Md., show how climate models used in the new report from the United Nations' Intergovernmental Panel on Climate Change (IPCC) estimate possible temperature and precipitation pattern changes throughout the 21st century.

    The United Nations' Intergovernmental Panel on Climate Change publishes a report on the consensus view of climate change science about every five to seven years. The first findings of the IPCC's Fifth Assessment Report (AR5) were released on Sept. 27, 2013, in the form of the Summary for Policymakers report and a draft of IPCC Working Group 1's Physical Science Basis. The IPCC does not perform new science but instead authors a report that establishes the established understanding of the world's climate science community.

    The report not only includes observations of the real world but also the results of climate model projections of how the Earth will respond as a system to rising greenhouse gas concentrations in the atmosphere. The IPCC's AR5 relies on the Coupled Model Intercomparison Project Phase 5 (CMIP5) effort, an international effort among the climate modeling community to coordinate climate change experiments.

    These visualizations represent the mean output of how certain groups of CMIP5 models responded to four different scenarios defined by the IPCC called Representative Concentration Pathways (RCPs). These four RCPs – 2.6, 4.5, 6 and 8.5 – represent a wide range of potential worldwide greenhouse gas emissions and sequestration scenarios for the coming century. The pathways are numbered based on the expected Watts per square meter – essentially a measure of how much heat energy is being trapped by the climate system – each scenario would produce. The pathways are partly based on the ultimate concentrations of carbon dioxide and other greenhouse gases. The current carbon dioxide concentration in the atmosphere is around 400 parts per million, up from less than 300 parts per million at the end of the 19th century.

    The carbon dioxide concentrations in the year 2100 for each RCP are:

    RCP 2.6: 421 ppm

    RCP 4.5: 538 ppm

    RCP 6: 670 ppm

    RCP 8.5: 936 ppm

    Each visualization represents the mean output of a different number of models for each RCP, because data from all models in the CMIP5 project was not available in the same format for visualization for each RCP. All of the models compare a projection of temperatures and precipitation from 2006-2099 to a baseline historical average from 1971-2000.

    Thus, the values shown for each year represent the departure for that year compared to the observed average global surface temperature from 1971-2000. The IPCC report used 1986-2005 as a baseline period, making its reported anomalies slightly different from those shown in the visualizations.

  • Global Temperature Anomalies from 1880 to 2018
    2019.02.06
    2018 Fourth Warmest Year in Continuing Warming Trend, According to NASA, NOAA Earth's global surface temperatures in 2018 were the fourth warmest since 1880, according to independent analyses by NASA and the National Oceanic and Atmospheric Administration (NOAA). Global temperatures in 2018 were 1.5 degrees Fahrenheit (0.83 degrees Celsius) warmer than the 1951 to 1980 mean, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. Globally, 2018's temperatures rank behind those of 2016, 2017 and 2015. The past five years are, collectively, the warmest years in the modern record. “2018 is yet again an extremely warm year on top of a long-term global warming trend,” said GISS Director Gavin Schmidt. Since the 1880s, the average global surface temperature has risen about 2 degrees Fahrenheit (1.1 degrees Celsius). This warming has been driven, in large part, by increased emissions into the atmosphere of carbon dioxide and other greenhouse gases caused by human activities, according to Schmidt. Warming trends are strongest in the Arctic region, where 2018 saw the continued loss of sea ice. In addition, mass loss from the Greenland and Antarctic ice sheets continued to contribute to sea level rise. Increasing temperatures can also contribute to longer fire seasons and some extreme weather events, according to Schmidt. Warming trends are strongest in the Arctic regions, where 2018 saw the continued loss of sea ice, as well as mass loss from the Greenland and Antarctic ice sheets that contribute to sea level rise. Increasing temperatures can also contribute to longer fire seasons and some extreme weather events, according to Schmidt. “The impacts of long-term global warming are already being felt - in coastal flooding, heat waves, intense precipitation and ecosystem change,” said Schmidt. NASA’s temperature analyses incorporate surface temperature measurements from 6,300 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. These raw 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. 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 2018’s global mean change is accurate to within 0.1 degree Fahrenheit, with a 95 percent certainty level. NOAA scientists used much of the same raw temperature data, but with a different baseline period and different interpolation into the Earth’s polar and other data poor regions. NOAA’s analysis found 2018 global temperatures were 1.42 degrees Fahrenheit (0.79 degrees Celsius) above the 20th century average. NASA’s full 2018 surface temperature data set — and the complete methodology used to make the temperature calculation — 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 monitoring, 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 missions, visit: https://www.nasa.gov/earth
  • Global Temperature Anomalies from 1880 to 2017
    2018.01.18
    Earth’s global surface temperatures in 2017 were the second warmest since modern recordkeeping began in 1880, according to an analysis by NASA. Continuing the planet’s long-term warming trend, globally averaged temperatures in 2017 were 1.62 degrees Fahrenheit (0.90 degrees Celsius) warmer than the 1951 to 1980 mean, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. That is second only to global temperatures in 2016. Last year was the third consecutive year in which temperatures were more than 1.8 degrees Fahrenheit (1 degree Celsius) above late nineteenth-century levels. NASA’s temperature analyses incorporate surface temperature measurements from 6,300 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. These raw measurements are analyzed using an algorithm that considers the varied spacing of temperature stations around the globe and urban heating effects that could skew the conclusions. These calculations produce the global average temperature deviations from the baseline period of 1951 to 1980. The full 2017 surface temperature data set and the complete methodology used to make the temperature calculation are available at:http://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 monitoring, 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.
  • Five-Year Global Temperature Anomalies from 1880 to 2016
    2017.01.18
    Earth’s 2016 surface temperatures were the warmest since modern recordkeeping began in 1880, according to independent analyses by NASA and the National Oceanic and Atmospheric Administration (NOAA). Globally-averaged temperatures in 2016 were 1.78 degrees Fahrenheit (0.99 degrees Celsius) warmer than the mid-20th century mean. This makes 2016 the third year in a row to set a new record for global average surface temperatures. The 2016 temperatures continue a long-term warming trend, according to analyses by scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York. NOAA scientists concur with the finding that 2016 was the warmest year on record based on separate, independent analyses of the data. Because weather station locations and measurement practices change over time, there are uncertainties in the interpretation of specific year-to-year global mean temperature differences. However, even taking this into account, NASA estimates 2016 was the warmest year with greater than 95 percent certainty. “2016 is remarkably the third record year in a row in this series,” said GISS Director Gavin Schmidt. “We don’t expect record years every year, but the ongoing long-term warming trend is clear.” The planet’s average surface temperature has risen about 2.0 degrees Fahrenheit (1.1 degrees Celsius) since the late 19th century, a change driven largely by increased carbon dioxide and other human-made emissions into the atmosphere. Most of the warming occurred in the past 35 years, with 16 of the 17 warmest years on record occurring since 2001. Not only was 2016 the warmest year on record, but eight of the 12 months that make up the year – from January through September, with the exception of June – were the warmest on record for those respective months. October and November of 2016 were the second warmest of those months on record – in both cases, behind records set in 2015. Phenomena such as El Niño or La Niña, which warm or cool the upper tropical Pacific Ocean and cause corresponding variations in global wind and weather patterns, contribute to short-term variations in global average temperature. A warming El Niño event was in effect for most of 2015 and the first third of 2016. Researchers estimate the direct impact of the natural El Nino warming in the tropical Pacific increased the annual global temperature anomaly for 2016 by 0.2 degrees Fahrenheit (0.12 degrees Celsius). Weather dynamics often affect regional temperatures, so not every region on Earth experienced record average temperatures last year. For example, both NASA and NOAA found the 2016 annual mean temperature for the contiguous 48 United States was the second warmest on record. In contrast, the Arctic experienced its warmest year ever, consistent with record low sea ice found in that region for most of the year. NASA’s analyses incorporate surface temperature measurements from 6,300 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. These raw measurements are analyzed using an algorithm that considers the varied spacing of temperature stations around the globe and urban heating effects that could skew the conclusions. The result of these calculations is an estimate of the global average temperature difference from a baseline period of 1951 to 1980. NOAA scientists used much of the same raw temperature data, but with a different baseline period, and different methods to analyze Earth’s polar regions and global temperatures. 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 monitors Earth's vital signs from land, air and space with a fleet of satellites, as well as airborne and ground-based observation campaigns. The agency develops new ways to observe and study Earth's interconnected natural systems with long-term data records and computer analysis tools to better see how our planet is changing. NASA shares this unique 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. The full 2016 surface temperature data set and the complete methodology used to make the temperature calculation are available at: http://data.giss.nasa.gov/gistemp
  • Five-Year Global Temperature Anomalies from 1880 to 2015
    2016.01.20
    Earth’s 2015 surface temperatures were the warmest since modern record keeping began in 1880, according to independent analyses by NASA and the National Oceanic and Atmospheric Administration (NOAA). Globally-averaged temperatures in 2015 shattered the previous mark set in 2014 by 0.23 degrees Fahrenheit (0.13 Celsius). Only once before, in 1998, has the new record been greater than the old record by this much. The 2015 temperatures continue a long-term warming trend, according to analyses by scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York (GISTEMP). NOAA scientists agreed with the finding that 2015 was the warmest year on record based on separate, independent analyses of the data. Because weather station locations and measurements change over time, there is some uncertainty in the individual values in the GISTEMP index. Taking this into account, NASA analysis estimates 2015 was the warmest year with 94 percent certainty. “Climate change is the challenge of our generation, and NASA’s vital work on this important issue affects every person on Earth,” said NASA Administrator Charles Bolden. “Today’s announcement not only underscores how critical NASA’s Earth observation program is, it is a key data point that should make policy makers stand up and take notice - now is the time to act on climate.” The planet’s average surface temperature has risen about 1.8 degrees Fahrenheit (1.0 degree Celsius) since the late-19th century, a change largely driven by increased carbon dioxide and other human-made emissions into the atmosphere. Most of the warming occurred in the past 35 years, with 15 of the 16 warmest years on record occurring since 2001. Last year was the first time the global average temperatures were 1 degree Celsius or more above the 1880-1899 average. Phenomena such as El Niño or La Niña, which warm or cool the tropical Pacific Ocean, can contribute to short-term variations in global average temperature. A warming El Niño was in effect for most of 2015. “2015 was remarkable even in the context of the ongoing El Niño,” said GISS Director Gavin Schmidt. “Last year’s temperatures had an assist from El Niño, but it is the cumulative effect of the long-term trend that has resulted in the record warming that we are seeing.” Weather dynamics often affect regional temperatures, so not every region on Earth experienced record average temperatures last year. For example, NASA and NOAA found that the 2015 annual mean temperature for the contiguous 48 United States was the second warmest on record.

    The GISTEMP analysis website is located at: http://data.giss.nasa.gov/gistemp/

  • Five-Year Global Temperature Anomalies from 1880 to 2014
    2015.01.16
    NASA Finds 2014 Was Warmest Year in Modern Record The year 2014 ranks as Earth’s warmest since 1880, according to an analysis by NASA scientists. The 10 warmest years in the instrumental record, with the exception of 1998, have now occurred since 2000. This trend continues a long-term warming of the planet, according to an analysis of surface temperature measurements by scientists at NASA’s Goddard Institute of Space Studies (GISS) in New York. In an independent analysis of the raw data, NOAA scientists also found 2014 to be the warmest on record. For understanding climate change, the long-term trend of rising temperatures across the planet is more important than any year’s individual ranking. These rankings can be sensitive to analysis methods and sampling. While 2014 ranks as the warmest year in NASA’s global temperature record, it is statistically close to the values from 2010 and 2005, the next warmest years. Since 1880, the average surface temperature of Earth has warmed by about 1.4 degrees Fahrenheit (0.8 degrees Celsius), a trend that is largely driven by the increase in carbon dioxide and other human emissions into the planet’s atmosphere. The majority of that warming has occurred in the past three decades. Regional differences in temperature in any year are more strongly affected by weather dynamics than the global mean. For example, in the U.S. in 2014, parts of the Midwest and East Coast were anomalously cool, while Alaska and three western U.S. states – California, Arizona and Nevada – recorded their warmest years on record, according to NOAA, which assesses official U.S. temperature records.

    The GISTEMP analysis website is located at: http://data.giss.nasa.gov/gistemp/

  • June 2019 Monthly Global Temperature Anomalies
    2019.08.08
    While many people in the continuous United States saw average temperatures in the month of June 2019, the average global temperature in June was 1.71 degrees F above the 20th-century average of 59.9 degrees. This makes June 2019 the hottest June in the 140-year record. Nine of the 10 hottest Junes have occurred since 2010. Last month also was the 43rd consecutive June and 414th consecutive month with above-average global temperatures. This visual of the GISTEMP anomalies for June of 2019 show the United States and then zooms out to show the global picture. Temperature anomalies indicate how much warmer (red) or colder(blue) it is than normal for a particular place and time. For the GISS analysis, normal always means the average over the 30-year period 1951-1980 for that place and time of year. For more information on the GISTEMP, see the GISTEMP analysis website located at: http://data.giss.nasa.gov/gistemp/
  • Global Temperature Anomalies from January 2016
    2016.03.25
    Weather dynamics often affect regional temperatures, so not every region on Earth experienced record average temperatures last year. This data visualization of NASA's Goddard Institute for Space Studies (GISS) Global temperature anomalies for January of 2016 show warmer than averag temperatures in red and colder than average temperatures in blue. The extremely warm arctic temperatures contributed to a new record low sea ice for January.

    For more information on the GISTEMP, see the GISTEMP analysis website located at: http://data.giss.nasa.gov/gistemp/

  • 2017 Global Temperature Visuals
    2018.01.19
    Earth’s global surface temperatures in 2017 were the second warmest since modern recordkeeping began in 1880, continuing the planet’s long-term warming trend. Globally averaged temperatures in 2017 were 1.62 degrees Fahrenheit (0.90 degrees Celsius) warmer than the 1951 to 1980 mean. That is second only to global temperatures in 2016. Last year was the third consecutive year in which temperatures were more than 1.8 degrees Fahrenheit (1 degree Celsius) above late nineteenth-century levels. 2017 was the warmest year that did not have an El Niño event. NASA’s temperature analyses incorporate surface temperature measurements from 6,300 weather stations, ship- and buoy-based observations of sea surface temperatures, and temperature measurements from Antarctic research stations. These raw measurements are analyzed using an algorithm that considers the varied spacing of temperature stations around the globe and urban heating effects that could skew the conclusions. These calculations produce the global average temperature deviations from the baseline period of 1951 to 1980. The full 2017 surface temperature data set and the complete methodology used to make the temperature calculation are available at: http://data.giss.nasa.gov/gistemp/
  • How Global Warming Stacks Up
    2015.07.21
    Skeptics of manmade climate change offer various natural causes to explain why the Earth has warmed 1.4 degrees Fahrenheit since 1880. But can these account for the planet’s rising temperature? Watch to see how much different factors, both natural and industrial, contribute to global warming, based on findings from NASA’s Goddard Institute for Space Studies.
  • El Niño: GMAO Daily Sea Surface Temperature Anomaly from 1997/1998 and 2015/2016
    2016.02.25
    Every two to seven years, an unusually warm pool of water -- sometimes two to three degrees Celsius higher than normal -- develops across the eastern tropical Pacific Ocean to create a natural short-term climate change event. This warm condition, known as El Niño, affects the local aquatic environment, but also spurs extreme weather patterns around the world, from flooding in California to droughts in Australia. In 2015 El Niño unfolded in the Pacific Ocean, as sea surface temperatures create different patterns than seen in the 1997-1998 El Niño. Computer models are just one tool that NASA scientists are using to study this large El Nino event, and compare it to other events in the past."The start of an El Niño is important," said Robin Kovach, a research scientist with the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The visualization shows how the 1997 event started from colder-than-average sea surface temperatures – but the 2015 event started with warmer-than-average temperatures not only in the Pacific but also in in the Atlantic and Indian Oceans."The '97 El Niño was much stronger in the Eastern Pacific, with much warmer water up to the coast of South America," Kovach said. In 2015, the warmest waters are instead in the Central Pacific and extend west of the International Date Line. The water temperature variations typical of El Niño are not only at the surface of the equatorial Pacific, but below the surface as well. And these variations were also different in 2015, compared to 1997. At the height of the El Niño in November, colder-than-average temperatures in the Western Pacific and warmer-than-average temperatures in the Eastern Pacific were stronger and extended deeper in 1997 than in 2015. Goddard’s computer models, with input from ocean buoys, atmospheric models, satellite data and other sources, can also simulate what ocean water temperatures could do in the coming months. The GMAO seasonal forecast, which takes 18 hours to complete, and creates more than nine terabytes of data, shows that this 2015 El Niño could be different until the end. "In the past, very strong El Niño events typically transition to neutral conditions and then a La Niña event," said Kovach. February computer model runs forecast a return to normal sea surface temperatures by June. The latest Feb 5, 2016 forecast does not yet predict below normal sea surface temperatures that would result in a large La Niña. As of Feb. 14, 2016, the latest ocean computer model shows colder-than-average water temperatures off the South American coast from Ecuador to Panama. "This current El Niño has been different so it will be interesting to see what happens in the next forecast and the coming months."
  • Link between Sea-Ice Fraction and Absorbed Solar Radiation over the Arctic Ocean
    2014.12.17
    While sea ice is mostly white and reflects the sun’s rays, ocean water is dark and absorbs the sun’s energy at a higher rate. A decline in the region’s albedo – its reflectivity, in effect – has been a key concern among scientists since the summer Arctic sea ice cover began shrinking in recent decades. As more of the sun’s energy is absorbed by the climate system, it enhances ongoing warming in the region, which is more pronounced than anywhere else on the planet.

    Since the year 2000, the rate of absorbed solar radiation in the Arctic in June, July and August has increased by five percent, said Norman Loeb, of NASA’s Langley Research Center, Hampton, Virginia. The measurement is made by NASA’s Clouds and the Earth’s Radiant Energy System (CERES) instruments, which fly on multiple satellites.

    While a five percent increase may not seem like much, consider that the rate globally has remained essentially flat during that same time. No other region on Earth shows a trend of potential long-term change.

    When averaged over the entire Arctic Ocean, the increase in the rate of absorbed solar radiation is about 10 Watts per square meter. This is equivalent to an extra 10-watt light bulb shining continuously over every 10.76 square feet of Arctic Ocean for the entire summer.

    As a region, the Arctic is showing more dramatic signs of climate change than any other spot on the planet. These include a warming of air temperatures at a rate two to three times greater than the rest of the planet and the loss of September sea ice extent at a rate of 13 percent per decade.

    CERES instruments fly on the Terra, Aqua and Suomi-NPP satellites, and one is scheduled to fly on the next orbiter of the Joint Polar Satellite System, a NASA-NOAA effort. The Terra satellite launched Dec. 18, 1999, and CERES first started collecting Arctic data in 2000 so 2015 will mark 15 continuous years of CERES measurements over the Arctic.

    The instruments include three radiometers – one measuring solar radiation reflected by Earth (shortwave), one measuring thermal infrared radiation emitted by Earth (longwave), and one measuring all outgoing radiation, whether emitted or reflected.

    For more information on the project, please visit http://ceres.larc.nasa.gov.

  • Altimetry: Past, Present and Future
    2014.05.13
    Launched in 1978, Seasat was the first NASA Earth-orbiting satellite mission designed to observe the world’s ocean. Seasat carried five major instruments, including a radar altimeter that measured the distance between the satellite and sea surface, indicating global sea surface height and the topography of the ocean surface. This visualization shows the progression of improved data resolution from satellite altimeters in the past, present, and future, beginning with 1.5-degree resolution data in 1978 from Seasat and ending with 0.05-degree resolution data from NASA’s Surface Water and Ocean Topography (SWOT) mission, planned to launch in 2020. A single satellite (Geosat) provided 0.5-degree resolution data from 1986 to 1990, while numerous international satellite missions (ERS-1, TOPEX/Poseidon, ERS-2, Jason-1, Envisat, and Jason-2) have provided 0.25-degree resolution data from 1992 until now. These measurements and their continuity are important for monitoring large-scale features such as Rossby and Kelvin waves, the evolution of El Niño and La Niña events, and variation of global sea level in relation to climate change. SWOT (with 0.05-degree-resolution) will offer an unprecedented combination of spatial and temporal resolution while continuing and extending the ocean altimeter data record for years to come.
  • Aquarius Sea Surface Salinity Tour 2012
    2013.02.27
    The Aquarius spacecraft is designed to measure global sea surface salinity. It is important to understand salinity, the amount of dissolved salts in water, because it will lead us to better understanding of the water cycle and can lead to improved climate models. Aquarius is a collaboration between NASA and the Space Agency of Argentina

    This visualization celebrates over a year of successful Aquarius observations. Sea surface salinity is shown at various locations around the globe highlighting the following:

    • the Atlantic Ocean is generally much more salty than the Pacific
    • low salinity waters in the Eastern Equatorial Pacific are transported westward
    • high influxes of fresh water from the Amazon River basin can be clearly seen
    • low salinity waters are transported by the Labrador current to the south
    • high influxes of fresh water from the Ganges River basin can be seen keeping the Eastern Indian Ocean lower salinity than the Western Indian Ocean

    The range of time shown is December 2011 through Decemeber 2012. The data continuously loops through this range every 6 seconds. This visualization was generated based on version 2.0 of the Aquarius data products with all 3 scanning beams.

  • Aquarius Sea Surface Salinity 2011-2014 - Rotating Globes
    2014.11.06
    The Aquarius spacecraft is designed to measure global sea surface salinity. It is important to understand salinity, the amount of dissolved salts in water, because it will lead us to better understanding of the water cycle and can lead to improved climate models. Aquarius is a collaboration between NASA and the Space Agency of Argentina

    This visualization celebrates over three years of successful Aquarius observations. Sea surface salinity is shown on a spinning globe (with and without grid lines).

    The range of time shown is September 2011 through September 2014. This visualization was generated based on version 3.0 of the Aquarius data products.

  • Aquarius Sea Surface Salinity 2011-2014 - Flat Maps
    2014.11.06
    The Aquarius spacecraft is designed to measure global sea surface salinity. It is important to understand salinity, the amount of dissolved salts in water, because it will lead us to better understanding of the water cycle and can lead to improved climate models. Aquarius is a collaboration between NASA and the Space Agency of Argentina

    This visualization celebrates over three years of successful Aquarius observations. Sea surface salinity is shown on a flat map using simple cartesian and extended Molleide projections. Versions are included with and without grid lines, and in both Altantic-centered and Pacific-centered projections.

    The range of time shown is September 2011 through September 2014. This visualization was generated based on version 3.0 of the Aquarius data products.

  • Multi-scale Ultra-high Resolution Sea Surface Temperature (MUR)
    2013.03.14
    These maps are made mostly from the satellite measurements of Sea Surface Temperature (SST), with help from surface observations that come from ships and bouys. Since the 1980's, there are a lot more SST data from satellites than surface observations.

    SST is invaluable for weather forecasting. But SST is also important for management of fishery, ocean acoustic communication, and the science including studies of climate and marine life.

    To "blend" the SST data from many different satellite is a tricky business. Satellite-based environmental data are usually irregularly sampled and always noisy. Every satellite has a unique sensor that measures SST. The infra-red (IR) type sensor can offer a very high resolution (down to 1 km in horizontal distance) but suffer from contamination by clouds and aerosols that block the signal. The micro-wave (MW) measurements are more reliable because of cloud-penetrating coverage but are coarser (25 km) in resolution and are not useful along the coasts due to contamination from land.

    So we are interested in making use of the best characteristics of each sensor data — be it resolution or coverage — and finding an optimal and objective ways to fill the data-voids under the clouds and near the coasts.

  • Atmospheric CO₂ Trends
    2014.12.10
    Fossil fuel combustion and other human activities are now increasing the atmospheric carbon dioxide (CO2) abundance to unprecedented rates. It is estimated that approximately 36 billion tons of CO2 are added to the atmosphere each year. The large graph shown here is an animated version of the standard Keeling curve from 1980 to September 2014. The red line denotes ground-based measurements from the Mauna Loa Observatory in Hawaii, while yellow denotes observations from the South Pole Observatory. Purple denotes the global trend. The smaller graph in the upper left shows satellite measurements of tropospheric CO2 concentrations (white dots) at different latitudes from September 2002 to September 2014, obtained by the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instruments. Note how the Northern Hemisphere has greater variably and generally higher levels of CO2 than the Southern Hemisphere.

    In May of 2013, these emissions pushed the monthly average CO2 concentrations above 400 parts per million (ppm)—a level that has not been reached during the past 800,000 years. These ever-increasing levels are raising concerns about greenhouse-gas-induced climate change.

  • Nino 3.4 Index and Sea Surface Temperature Anomaly Timeline: 1982-2017
    2019.02.28
    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 of Earth. This visualization captures sea surface temperature anomalies around the world from 1982 to 2017, along with a corresponding timeplot graph focusing on the Niño 3.4 Index, 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.

Water and Energy Cycle

The Water and Energy Cycle focus area (WEC) works to define, quantify, and model the different components of the water cycle that take place on land, including precipitation, snow, soil moisture, surface water and groundwater, and their interactions with other Earth systems. This research helps improve our understanding of how much water exists on Earth, how it’s changing over time, and what quality it’s in. It also helps us understand the energy that is transferred when water moves around the Earth and changes phase from liquid water to water vapor to snow. WEC uses observations from satellites and aircraft to help inform this research, and they partner with other Research and Analysis Program focus areas on crosscutting topics like ocean dynamics and cloud formation.
  • NASA GSFC MASCON Solution over Greenland from Jan 2004 - Jun 2014
    2015.08.26
    GRACE, NASA's Gravity Recovery and Climate Experiment, consists of twin co-orbiting satellites that fly in a near polar orbit separated by a distance of 220 km. GRACE precisely measures the distance between the two spacecraft in order to make detailed measurements of the Earth's gravitational field. Since its launch in 2002, GRACE has provided a continuous record of changes in the mass of the Earth's ice sheets. This animations shows the change in the the Greenland Ice Sheet between January 2004 and June 2014. The 1-arc-deg NASA GSFC mascon solution data was resampled to a 998 x 1800 data array using Kriging interpolation. A color scale was applied in the range of +250 to -250 centimeters of equivalent water height, where blue values indicate an increase in the ice sheet mass while red shades indicate a decrease. In addition, the running sum total of the accumulated mass change over the Greenland Ice Sheet is shown on a graph overlay in gigatons. Technical Note: The glacial isostatic adjustment signal (Earth mass redistribution in response to historical ice loading) has been removed using the ICE-6G model (Peltier et al. 2015).
  • Freshwater Losses In The Middle East
    2013.02.12
    The visualization shows variations in total water storage from normal, in millimeters, in the Tigris and Euphrates river basins, as measured by NASA's Gravity Recovery and Climate Experiment (GRACE) satellites, from January 2003 through December 2009. Reds represent drier conditions, while blues represent wetter conditions. The effects of the seasons are evident, as is the major drought that hit the region in 2007. The majority of the water lost was due to reductions in groundwater caused by human activities. By periodically measuring gravity regionally, GRACE tells scientists how much water storage changes over time.
  • GRACE measures California water
    2017.03.07
    NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, launched in 2002, maps changes in Earth's gravity field resulting from the movement of water over the planet. This animation shows how the total amount of water (snow, surface water, soil moisture, and groundwater) varies in space and time, with the passage of dry seasons and wet seasons as well as with flooding, drought, and transport due to water management. Blue colors represent wetter than average conditions (relative to 2002-2017), while red colors represent drier than average conditions. The yellow line in the graph at left shows the interannual variation for area outlined in ywllow on the map, while the fainter gray line in the graph shows variations with the seasonal cycle included. The Sacramento and San Joaquin River basins are outlined in yellow and rivers and tributaries are shown as blue lines. The basins include California's Central Valley, the most productive agricultural region in the U.S. Drought in California had drained the state of nearly 15 cubic kilometers (12 million acre feet; 4 trillion gallons) of water in 2010-2013, but a more normal 2016 and an even wetter 2017 hvae allowed some recovery along with extensive flooding.
  • Observing Freshwater Losses in the Middle East
    2013.11.01
    A study using data from NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites found that large parts of the arid Middle East region lost freshwater reserves rapidly during the past decade. Meanwhile, demand for freshwater continues to rise. The two natural-color images on the left were acquired by the Landsat 5 satellite and show the shrinking of the Qadisiyah Reservoir in Iraq between September 7, 2006 [top left] and September 15, 2009 [bottom left]. The graph below these two images shows the elevation of the water in that reservoir between January 2003 and December 2009. The elevation is a proxy measurement for the total volume of water stored there. The two regional images on the right were created with GRACE data and show total water storage in the Tigris and Euphrates river basins for September 2003 [top right] and September 2009 [bottom right]. The graph shows a decrease in water storage for the study area as measured by GRACE from January 2003 to December 2009. The gray line depicts total water storage—groundwater, surface water bodies, and soil moisture—while the green line depicts changes in surface water. The difference between those two lines reflects the change in water stored in underground aquifers. The total water storage shows a seasonal fluctuation, but also an overall downward trend, suggesting that groundwater is being pumped and used faster than natural processes can replenish it. Data from satellites such as GRACE are essential to providing a more complete global picture of water storage trends.

    Used in 2014 Calendar.

  • Water Level in Lake Powell
    2017.09.01
    Among the dams on the Colorado River is the Glen Canyon Dam, which creates Lake Powell. This series of natural-color Landsat images shows the dramatic drop in Lake Powell’s water level between 1999 and 2017 caused by prolonged drought and water withdrawals. At the beginning of the series, water levels were relatively high, and the water was a clear, dark blue. The sediment-filled river appeared green-brown. Dry conditions and falling water levels were unmistakable in the image from April 13, 2003, and again in early 2005 when water levels plummeted and the northwestern side branch of Lake Powell remained cut off from the rest of the reservoir.

    In the latter half of the decade the lake level began to rebound. Significant amounts of snowfall over the winter of 2010–2011 meant more water for the lake. Regional snowfall in the spring of 2012, on the other hand, was abnormally low, and inflow to Lake Powell did not begin to increase in May 2012 as it had in previous years. Since 2012, snow- and rainfall totals have been abnormally low as the region suffered through persistent drought. Inflow to Lake Powell has been minimal, and by April 2015, the reservoir stood at 42 percent of capacity. Droughts in this region are not unusual; however, global warming is expected to make droughts more severe in the future.

  • Improvements in Groundwater and Soil Moisture Measurements Derived from the GRACE Mission
    2017.10.06
    From space, we track water in the ground – whether it is a centimeter, a meter, or a kilometer below the surface. Around the world, NASA's GRACE satellites have provided unprecedented views of water storage in natural aquifers. These underground reserves are so massive that they affect Earth's gravity field. When their mass changes, the satellites detect the change in gravity. Droughts can affect deep groundwater stores when water users pump hundreds of billions of gallons out of their aquifers to compensate for the lack of rainfall – and GRACE can detect this change. This view from space has revolutionized our understanding of water stores beneath the surface. But scientists at NASA Goddard can combine GRACE data with sophisticated computer models to give decision makers in the continental US an otherwise unseen view, helping to trigger critical water conservation measures. These computer models help us decompose the GRACE signal to identify changes in both the shallow groundwater and the root zone where crops are actually drawing moisture to survive. Stations on the ground provide a connect-the-dots picture. The vantage point from space – combined with modeling – provides a comprehensive view of how the drought evolved over time and ultimately ended. This constantly changing snapshot of shallow groundwater conditions is now used every week in the US Drought Monitor, the benchmark relied upon by decision makers at the local, state, and federal level. This visualization shows the global Terrestrial Water Storage Anomaly from GRACE data, and then highlights the contiguous United States to show groundwater anomaly. This more detailed view is made by assimilating GRACEwater storage data into a supercomputer model of the land surface. The visualization dives into California, showing further detail by separating out the surface soil moisture (top 2 centimeters) and the root zone soil mositure (top 100 centimeters).
  • GRACE 15-Year Groundwater Trends
    2018.05.16
    NASA scientists used GRACE data to identify regional trends of freshwater movement, and combined that information with data from other satellites, climate models and precipitation measurements to determine the causes of major regional trends in freshwater storage. In these visualizations, the colors represent liquid water equivalent thinckness, while the animated graph overlay represents the terrestrial water storage anomaly.
  • Groundwater Depletion in India Revealed by GRACE
    2009.08.12
    Scientists using data from NASA's Gravity Recovery and Climate Experiment (GRACE) have found that the groundwater beneath Northern India has been receding by as much as one foot per year over the past decade. After examining many environmental and climate factors, the team of hydrologists led by Matt Rodell of NASA's Goddard Space Flight Center, Greenbelt, Md. concluded that the loss is almost entirely due to human consumption.

    Groundwater comes from the natural percolation of precipitation and other surface waters down through Earth's soil and rock, accumulating in aquifers - cavities and layers of porous rock, gravel, sand, or clay. In some subterranean reservoirs, the water may be thousands to millions of years old; in others, water levels decline and rise again naturally each year. Groundwater levels do not respond to changes in weather as rapidly as lakes, streams, and rivers do. So when groundwater is pumped for irrigation or other uses, recharge to the original levels can take months or years.

    More than 109 cubic km (26 cubic miles) of groundwater disappeared from the region's aquifers between 2002 and 2008 — double the capacity of India's largest surface water reservoir, the Upper Wainganga, and triple that of Lake Mead, the largest manmade reservoir in the U.S.

    The animation shown here depicts the change in groundwater levels as measured each November between 2002 to 2008.

  • 2015-2016 El Niño: Daily Sea Surface Temperature Anomaly and Ocean Currents
    2017.05.26
    El Niño is a recurring climate pattern characterized by warmer than usual ocean temperatures in the equatorial Pacific. This 3-D visualization tracks the changes in ocean temperatures and currents, respectively, throughout the life cycle of the 2015-2016 El Niño event, chronicling its inception in early 2015 to its dissipation by April 2016. Blue regions represent colder temperatures and red regions warmer temperatures when compared with normal conditions. Under normal conditions, equatorial trade winds in the Pacific Ocean blow from the east to the west, causing warm water to pile up in the Western Pacific, while also causing an upwelling- the rise of deep, cool water to the surface- in the Equatorial Pacific. During an El Niño, trade winds weaken or, as with this latest event, sometimes reverse course and blow from west to east. As a result, the warm surface water sloshes east along the equator from the Western Pacific and temporarily predominates in the Central and Eastern Pacific Ocean. At that time, cooler water slowly migrates westward just off the equator in the Western Pacific. The first visualization shows the 2015-2016 El Niño through changes in sea surface temperature as warmer water moves east across the Pacific Ocean.The Eastern Pacific Ocean undergoes the most warming from July 2015 to January 2016. In the west, just to the north of the equator, cooler waters hit the western boundary and reflect along the equator and then head east starting in February 2016. Just as the warming waves traveled east earlier in the video, these cool waters make their way to the central Pacific, terminating the warming event there. Hand-in-hand with an El Niño's changing sea surface temperatures are the wind-driven ocean currents that move the waters along the equator across the Pacific Ocean. The second visualization depicts these currents, which here comprise the ocean's surface to a depth of 225 meters: Yellow arrows illustrate eastward currents and white arrows are westward currents. The El Niño-inducing westerlies- winds coming from the west that blow east- causing eastward currents to occur in pulses. These visualizations are derived from NASA Goddard's Global Modeling and Assimilation Office, using Modern-Era Retrospective Analysis for Research and Applications(MERRA) dataset, which comprises an optimal combination of observations and ocean and atmospheric models. For more information, see https://gmao.gsfc.nasa.gov/reanalysis/MERRA/.
  • Painting the World with Water
    2015.03.31
    The ten satellites in the Global Precipitation Measurement Constellation provide unprecedented information about the rain and snow across the entire Earth. This visualization shows the constellation in action, taking precipitation measurements underneath the satellite orbits. As time progresses and the Earth's surface is covered with measurements, the structure of the Earth's preciptation becomes clearer, from the constant rainfall patterns along the Equator to the storm fronts in the mid-latitudes. The dynamic nature of the precipitation is revealed as time speeds up and the satellite data swaths merge into a continuous animation of changing rain and snowfall. Finally, the video fades into an animation of IMERG, the newly available data set of global precipitation every thirty minutes that is derived from this satellite data.
  • ECOSTRESS Installation and First Data
    2018.07.31
    Launched June 29, 2018, from Cape Canaveral Air Force Station, NASA's ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) instrument will measure the temperature of plants from space, enabling researchers to determine how much water plants use and to study how droughts affect plant health.

    ECOSTRESS rode to orbit in the "trunk" of SpaceX's Dragon spacecraft, which berthed at the station on July 2. On July 5, ground controllers at NASA's Johnson Space Center extracted ECOSTRESS from the trunk, robotically transferred it to the International Space Station’s Japanese Experiment Module - Exposed Facility (JEM-EF) and installed it. The ECOSTRESS payload fits within an enclosure measuring 6.1 x 2.6 x 2.9 ft (1.85 x 0.8 x 0.88 m).

    In the “first data” image, taken on July 9, yellow and red indicate generally higher surface temperatures. The Nile River is visible as a thin blue line on the main image. The black-and-white inset shows the level of detail available from ECOSTRESS, with the relatively cool Nile River and surrounding vegetation appearing darker.

    From the space station’s altitude of ~250 mi (400 km), ECOSTRESS will provide Earth surface temperature data with a spatial resolution of 226 ft (69 m) cross-track and 125 ft (38 m) in-track with a temperature sensitivity of a few tenths of a degree. The station orbits Earth about 16 times a day; and it flies over the same location on Earth approximately every few days at varying times. This orbit provides sufficient coverage for ECOSTRESS to produce data encompassing the complete daily cycle of plant water use.

  • Chesapeake Bay Flyover and Watershed Region
    2008.04.21
    The watershed that drains into the Chesapeake Bay is a huge expanse that extends 64,000 miles into six states across North America (New York, Pensylvania, Maryland, Delaware, Virginia, and West Virginia) and the District of Columbia. This visualization overlays the full watershed onto a Landsat satellite visualization of the Bay area. The eight different distinctly colored regions indicate the Chesapeake's major subwatersheds. These subwatershed regions are: Susquehanna, Potomac, Patuxent, MD West Shore, Rapahhannock, Eastern Shore, James and York. This visualization is an extension of the Chesapeake Bay Flyover (#3446) in order to demonstrate the entire Chesapeake Bay Watershed region. The imagery utilized for this animation is a false-color Chesapeake Bay Landsat-7 Mosaic (#3473) composed of eight scenes acquired between 1999-2002, which were put together and color corrected to resemble natural looking colors.

    Data Notes:
    The mosaic was created by EarthSat under contract with NASA as part of the GeoCover 2000 product. All images used in GeoCover were acquired by Landsat-7 during the period of 1999-2002. The pixel size of the full resolution image represents 14.25 m on the ground. The Chesapeake Bay mosaic uses portions of eight Landsat-7 scenes. Below you will find a listing of the eight Landsat 7 images that were put together to create the composite image. Landsat scenes are organized by a Path and Row number according to the Worldwide Reference System. (To learn more about Landsat's Worldwide Reference System, please visit: http://landsat.gsfc.nasa.gov/about/wrs.html)

    Scenes used in the Chesapeake Bay mosaic:

    • Landsat-7 WRS Path 15-Row 32 acquired on Oct. 05, 2001
    • Landsat-7 WRS Path 14-Row 32 acquired on Sept. 23, 1999
    • Landsat-7 WRS Path 15-Row 33 acquired on October 05, 2001
    • Landsat-7 WRS Path 14-Row 33 acquired on July 10, 2001
    • Landsat-7 WRS Path 15-Row 34 acquired on Sept. 30, 1999
    • Landsat-7 WRS Path 14-Row 34 acquired on July 10, 2001
    • Landsat-7 WRS Path 15-Row 35 acquired on Sept. 30, 1999
    • Landsat-7 WRS Path 14-Row 35 acquired on Sept. 23, 1999
  • Chesapeake Bay Watershed Region (short version)
    2008.04.21
    The watershed that drains into the Chesapeake Bay is a huge expanse that extends 64,000 miles into five states across North America (New York, Pensylvania, Maryland, Delaware, Virginia) and the District of Columbia. This visualization overlays the full watershed onto a Landsat satellite visualization of the Bay area. The eight different distinctly colored regions indicate the Chesapeake's major subwatersheds. These subwatershed regions are: Susquehanna, Potomac, Patuxent, MD West Shore, Rapahhannock, Eastern Shore, James and York. This visualization contains just the last part of the Chesapeake Bay Flyover and Watershed Region (#3472) animation and demonstrates the entire Watershed without the Chesapeake Bay flyover. This animation highlights and labels each subwatershed in turn.

    Data Notes:
    The mosaic was created by EarthSat under contract with NASA as part of the GeoCover 2000 product. All images used in GeoCover were acquired by Landsat-7 during the period of 1999-2002. The pixel size of the full resolution image represents 14.25 m on the ground. The Chesapeake Bay mosaic uses portions of eight Landsat-7 scenes. Below you will find a listing of the eight Landsat 7 images that were put together to create the composite image. Landsat scenes are organized by a Path and Row number according to the Worldwide Reference System. (To learn more about Landsat's Worldwide Reference System, please visit: http://landsat.gsfc.nasa.gov/about/wrs.html)

    Scenes used in the Chesapeake Bay mosaic:

    • Landsat-7 WRS Path 15-Row 32 acquired on Oct. 05, 2001
    • Landsat-7 WRS Path 14-Row 32 acquired on Sept. 23, 1999
    • Landsat-7 WRS Path 15-Row 33 acquired on October 05, 2001
    • Landsat-7 WRS Path 14-Row 33 acquired on July 10, 2001
    • Landsat-7 WRS Path 15-Row 34 acquired on Sept. 30, 1999
    • Landsat-7 WRS Path 14-Row 34 acquired on July 10, 2001
    • Landsat-7 WRS Path 15-Row 35 acquired on Sept. 30, 1999
    • Landsat-7 WRS Path 14-Row 35 acquired on Sept. 23, 1999
  • GEOS-5 Nature Run Collection
    2013.03.07
    Through numerical experiments that simulate the dynamical and physical processes governing weather and climate variability of Earth's atmosphere, models create a dynamic portrait of our planet. This 10-kilometer global mesoscale simulation (Nature Run) using the NASA Goddard Earth Observing System Model (GEOS-5) explores the evolution of surface temperatures as the sun heats the Earth and fuels cloud formation in the tropics and along baroclinic zones; the presence of water vapor and precipitation within these global weather patterns; the dispersion of global aerosols from dust, biomass burning, fossil fuel emissions, and volcanoes; and the winds that transport these aerosols from the surface to upper-levels.

    The full GEOS-5 simulation covered 2 years—from May 2005 to May 2007. It ran on 3,750 processors of the Discover supercomputer at the NASA Center for Climate Simulation, consuming 3 million processor hours and producing over 400 terabytes of data.

    GEOS-5 development is funded by NASA's Modeling, Analysis, and Prediction Program.

  • The Water Cycle
    2015.01.21
    The water cycle describes how water evaporates from the Earth’s surface, rises into the atmosphere, cools, condenses to form clouds, and falls again to the surface as precipitation. About 75% of the energy (or heat) in the global atmosphere is transferred through the evaporation of water from the Earth’s surface. On land, water evaporates from the ground, mainly from soils, plants (i.e., transpiration), lakes, and streams. In fact, approximately 15% of the water entering the atmosphere is from evaporation from Earth’s land surfaces and evapotranspiration from plants. Such evaporation cools the Earth’s surface, cools the lower atmosphere, and provides water to the atmosphere to form clouds.
  • Landsat Data Help Water-Resource Managers
    2013.11.01
    In the Western United States between 80 and 90% of freshwater is used for agriculture. In Southern California irrigated farmland stretches southward across the desert from the Salton Sea—an artificial inland sea—to the Mexico border. In the natural-color image [left] acquired on May 15, 2013, by Landsat 8’s Operational Land Imager, blocks of square farmland appear in shades of green and tan, while urban areas such as El Centro, California and Mexicali, Mexico appear in shades of gray. Accurate estimates of total crop area provided by Landsat satellites can be used to help forecast commodities in the United States and the world food market. On that same day, thermal measurements from Landsat 8’s Thermal Infrared Sensor [right] show different temperatures between crop fields as well as urban and desert areas. Cooler areas (e.g., irrigated crops) appear as dark purple and red shades, while warmer areas (e.g., urban and desert areas) appear as shades of bright yellow and white. Plants cool down when they transpire, so the combination of water evaporating from the plants and the ground (i.e., evapotranspiration) lowers the temperature of the irrigated land. Pixels representing cooler areas in thermal images from TIRS help water-resource managers determine where water is being used for irrigation, allowing them to make management decisions on water distribution to preserve this scarce resource. When an earlier design of Landsat 8 did not include a thermal infrared band, the Western States Water Council advocated for its inclusion.

    Used in 2014 Calendar.

  • AXIOM-1 Ocean chlorophyll, Sea Ice Thickness and Atmospheric Precipitable Water
    2015.02.13
    AXIOM-1 (eXperimental Analysis of sea Ice and Ocean Mesoscale version 1) is a coupled analysis of the global ocean and sea ice obtained by assimilating Aquarius sea surface salinity (SSS) and MODIS chlorophyll data together with sea surface temperature (SST) and sea ice concentrations from the OSTIA objective analysis into a global high-resolution coupled ocean/ atmosphere/sea ice model. The coupled model components are the MOM-5 ocean general circulation model, the GEOS-5 atmospheric general circulation model and the CICE sea ice model. The ocean and sea ice model horizontal resolutions vary from 11km to less than 3km in the Arctic and the atmospheric model resolution is the same as that used to produce the GMAO operational weather forecasts (25km).

    As a preamble to a fully coupled integrated earth system analysis, the atmospheric model is constrained to the GMAO MERRA-2 atmospheric reanalysis (prior to June 2013) and to the GMAO operational forward processing stream (after June 2013) while the SST, SSS, ice concentration and chlorophyll data are assimilated into the coupled model using a new methodology [State Adaptive Forecast-error Estimation (SAFE): https://gmao.gsfc.nasa.gov/pubs/docs/Keppenne721.pdf] developed especially for high-resolution data assimilation.

    This animation shows the ocean surface chlorophyll concentration and sea ice thickness fields (shown over grid cells where the fractional ice coverage is greater than 15%) and the vertical integral of atmospheric precipitable water (transparent overlay) sampled every 6 hours from January 1, 2013 to November 1, 2014 from a reanalysis completed with the AXIOM-1 system. The chlorophyll concentration is proportional to the ocean biomass and primary production and influences how deep solar radiation can heat the ocean sub-surface which needs to be accounted for in numerical ocean models.

Carbon Cycle and Ecosystems

The Carbon Cycle and Ecosystems focus area (CCE) supports interdisciplinary research initiatives into Earth’s ecosystems and biogeochemical cycles, including how carbon, nitrogen and other nutrients are stored and cycled throughout the environment. CCE uses satellite remote sensing instruments, field campaigns, laboratory studies, and modeling to improve our understanding of how terrestrial and aquatic ecosystems around the world, such as forests, jungles, deserts, oceans, coasts, and polar environments, are changing over time. CCE also studies how changes in these ecosystems may affect how the planet stores nutrients like carbon and nitrogen in the future. Resolving these uncertainties will help us understand fluctuations in Earth’s climate and have major implications for biodiversity and sustainable resource management.
  • Carbon Dioxide from GMAO using Assimilated OCO-2 Data
    2016.12.13
    Carbon dioxide is the most important greenhouse gas released to the atmosphere through human activities. It is also influenced by natural exchange with the land and ocean. This visualization provides a high-resolution, three-dimensional view of global atmospheric carbon dioxide concentrations from September 1, 2014 to August 31, 2015. The visualization was created using output from the GEOS modeling system, developed and maintained by scientists at NASA. The height of Earth’s atmosphere and topography have been vertically exaggerated and appear approximately 400 times higher than normal to show the complexity of the atmospheric flow. Measurements of carbon dioxide from NASA’s second Orbiting Carbon Observatory (OCO-2) spacecraft are incorporated into the model every 6 hours to update, or “correct,” the model results, called data assimilation.

    As the visualization shows, carbon dioxide in the atmosphere can be mixed and transported by winds in the blink of an eye. For several decades, scientists have measured carbon dioxide at remote surface locations and occasionally from aircraft. The OCO-2 mission represents an important advance in the ability to observe atmospheric carbon dioxide. OCO-2 collects high-precision, total column measurements of carbon dioxide (from the sensor to Earth’s surface) during daylight conditions. While surface, aircraft, and satellite observations all provide valuable information about carbon dioxide, these measurements do not tell us the amount of carbon dioxide at specific heights throughout the atmosphere or how it is moving across countries and continents. Numerical modeling and data assimilation capabilities allow scientists to combine different types of measurements (e.g., carbon dioxide and wind measurements) from various sources (e.g., satellites, aircraft, and ground-based observation sites) to study how carbon dioxide behaves in the atmosphere and how mountains and weather patterns influence the flow of atmospheric carbon dioxide. Scientists can also use model results to understand and predict where carbon dioxide is being emitted and removed from the atmosphere and how much is from natural processes and human activities.

    Carbon dioxide variations are largely controlled by fossil fuel emissions and seasonal fluxes of carbon between the atmosphere and land biosphere. For example, dark red and orange shades represent regions where carbon dioxide concentrations are enhanced by carbon sources. During Northern Hemisphere fall and winter, when trees and plants begin to lose their leaves and decay, carbon dioxide is released in the atmosphere, mixing with emissions from human sources. This, combined with fewer trees and plants removing carbon dioxide from the atmosphere, allows concentrations to climb all winter, reaching a peak by early spring. During Northern Hemisphere spring and summer months, plants absorb a substantial amount of carbon dioxide through photosynthesis, thus removing it from the atmosphere and change the color to blue (low carbon dioxide concentrations). This three-dimensional view also shows the impact of fires in South America and Africa, which occur with a regular seasonal cycle. Carbon dioxide from fires can be transported over large distances, but the path is strongly influenced by large mountain ranges like the Andes. Near the top of the atmosphere, the blue color indicates air that last touched the Earth more than a year before. In this part of the atmosphere, called the stratosphere, carbon dioxide concentrations are lower because they haven’t been influenced by recent increases in emissions.

  • Global Fire Observations and MODIS NDVI
    2011.10.18
    This visualization leads viewers on a narrated global tour of fire detections beginning in July 2002 and ending July 2011. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. The tour begins in Australia in 2002 by showing a network of massive grassland fires spreading across interior Australia as well as the greener Eucalyptus forests in the northern and eastern part of the continent. The tour then shifts to Asia where large numbers of agricultural fires are visible first in China in June 2004, then across a huge swath of Europe and western Russia in August, and then across India and Southeast Asia through the early part of 2005. It moves next to Africa, the continent that has more abundant burning than any other. MODIS observations have shown that some 70 percent of the world's fires occur in Africa alone. In what's a fairly average burning season, the visualization shows a huge outbreak of savanna fires during the dry season in Central Africa in July, August, and September of 2006, driven mainly by agricultural activities but also by the fact that the region experiences more lightning than anywhere else in the world. The tour shifts next to South America where a steady flickering of fire is visible across much of the Amazon rainforest with peaks of activity in September and November of 2009. Almost all of the fires in the Amazon are the direct result of human activity, including slash-and-burn agriculture, because the high moisture levels in the region prevent inhibit natural fires from occurring. It concludes in North America, a region where fires are comparatively rare. North American fires make up just 2 percent of the world's burned area each year. The fires that receive the most attention in the United States, the uncontrolled forest fires in the West, are less visible than the wave of agricultural fires prominent in the Southeast and along the Mississippi River Valley, but some of the large wildfires that struck Texas earlier this spring are visible.

    More information on the Fire Information for Resource Management System (FIRMS) is available at http://maps.geog.umd.edu/firms/.

  • African Fire Observations and MODIS NDVI
    2011.10.18
    From space, we can understand fires in ways that are impossible from the ground. The MODIS instrument onboard the Terra and Aqua satellite, was specifically designed to detect fires. As a result, it can see both smaller fires and a wide range of fires from cool grass fires to raging forest fires. Burning carbon particles both on the tiny soot particles in the flame and on the fuel itself emit a very specific wavelength of light, 3.8 to 4 microns. NASA research has contributed to much improved detection of fire for scientific purposes using satellite remote sensing and geographic information systems. This has helped advance our understanding of the impacts of fire in many areas of earth science, including atmospheric chemistry and the impacts on protected areas. This research has led to the development of a rapid response system widely used throughout the world for both natural resource management and for firefighting by providing near real-time information.

    The visualization shows fires detected in Africa from July 2002 through July 2011. Africa has more abundant burning than any other continent. MODIS observations have shown that some 70 percent of the world's fires occur in Africa alone. "It's incredibly satisfying to see such a long record of fires visualized," said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. "It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth."

    More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.

  • United States Fire Observations and MODIS NDVI
    2011.10.18
    From space, we can understand fires in ways that are impossible from the ground. NASA has released a series of new visualizations that show fires detected by key fire-monitoring instruments on NASA satellites over the last decade. The visualizations show fire observations made by MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. "It's incredibly satisfying to see such a long record of fires visualized," said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. "It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth." North America is a region where fires are comparatively rare. North American fires make up just 2 percent of the world's burned area each year. The fires that receive the most attention in the United States, the uncontrolled forest fires in the West, are less visible than the wave of agricultural fires prominent in the Southeast and along the Mississippi River Valley, but some of the large wildfires that struck Texas earlier this spring are visible.

    More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.

  • Boreal Forest Fire Observations and MODIS NDVI
    2011.10.18
    NASA has released a series of new visualizations that show the locations of the millions of fires detected by key fire-monitoring instruments on NASA satellites over the last decade. This visualization shows fire observations made by the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites in Europe and Asia from July 2002 through July 2011. "It's incredibly satisfying to see such a long record of fires visualized," said Chris Justice, a scientist from the University of Maryland who leads NASA's effort to use MODIS data to study the world's fires. "It's not only exciting visually, but what you see here is a very good representation of the data scientists use to understand the global distribution of fires and to determine where and how fires are responding to climate change and population growth."

    More information on the Fire Information for Resource Management System (FIRMS) is available at https://earthdata.nasa.gov/earth-observation-data/near-real-time/firms.

  • South American Fire Observations and MODIS NDVI
    2011.10.18
    From space, we can understand fires in ways that are impossible from the ground. NASA research has contributed to much improved detection of fire for scientific purposes using satellite remote sensing and geographic information systems. This visualization of South America shows fire observations made by MODerate Resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua satellites . South America exhibits a steady flickering of fire across much of the Amazon rainforest with peaks of activity in September and November. Almost all of the fires in the Amazon are the direct result of human activity, including slash-and-burn agriculture, because the high moisture levels in the region prevent inhibit natural fires from occurring.

    More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.

  • Australia Fire Observations and MODIS NDVI
    2011.10.18
    From space, we can understand fires in ways that are impossible from the ground. The MODIS instrument onboard the Terra and Aqua satellite, was specifically designed to detect fires. This visualization shows fire detections from July 2002 through July 2011. The visualization also includes vegetation and snow cover data to show how fires respond to seasonal changes. The tour begins in Australia in 2002 by showing a network of massive grassland fires spreading across interior Australia as well as the greener Eucalyptus forests in the northern and eastern part of the continent.

    More information on the Fire Information for Resource Management (FIRMS) is available at http://maps.geog.umd.edu/firms/.

  • PACE - Studying Plankton, Aerosols, Clouds, and the Ocean Ecosystem
    2018.12.05
    In terms of life on Earth, color describes more than simply how features look. In many cases color serves as a proxy for biological processes. When studying ocean biology, colors count in a big way. NASA’s PACE mission (Plankton, Aerosol, Cloud, ocean Ecosystem) has been conceived principally as a way to measure ocean color for assessing large scale ocean health. These measurements will provide data to determine the distribution of phytoplankton, tiny plants and algae that sustain the marine food web. A simple way to think about this is the more “green” that’s visible from space, the more prevalent are plant cells containing chlorophyll, an essential green pigment responsible for energy-producing photosynthesis in plants. Phytoplankton populations are fundamental to understanding the overall health of the ocean food web, as well as a wide range of related processes. PACE will be able to see other colors too—a broad range of color, in fact, stretching beyond the bounds of visible light into both ultraviolet as well as infrared. PACE will also be able to make measurements of aerosols in the atmosphere, essential for scientists to improve our understanding of and our ability to forecast weather and climate. PACE continues a more than 20 year legacy of ocean color measurements, providing the scientific community with a long time series of data. That legacy enables better assessments of long term trends about complex processes on Earth.
  • Watching the Earth Breathe:
    An Animation of Seasonal Vegetation and its effect on Earth's Global Atmospheric Carbon Dioxide
    2012.07.08
    In this animation, NASA instruments show the seasonal cycle of vegetation and the concentration of carbon dioxide in the atmosphere. The animation begins on January 1, when the northern hemisphere is in winter and the southern hemisphere is in summer. At this time of year, the bulk of living vegetation, shown in green, hovers around the equator and below it, in the southern hemisphere.

    As the animation plays forward through mid-April, the concentration of carbon dioxide, shown in orange-yellow, in the middle part of Earth's lowest atmospheric layer, the troposphere, increases and spreads throughout the northern hemisphere, reaching a maximum around May. This blooming effect of carbon dioxide follows the seasonal changes that occur in northern latitude ecosystems, in which deciduous trees lose their leaves, resulting in a net release of carbon dioxide through a process called respiration. Carbon dioxide is also released in early spring as soils begin to warm. Almost 10 percent of atmospheric carbon dioxide passes through soils each year.

    After April, the northern hemisphere moves into late spring and summer and plants begin to grow, reaching a peak in the late summer. The process of plant photosynthesis removes carbon dioxide from the air. The animation shows how carbon dioxide is scrubbed out of the atmosphere by the large volume of new and growing vegetation. Following the peak in vegetation, the drawdown of atmospheric carbon dioxide due to photosynthesis becomes apparent, particularly over the boreal forests.

    Note that there is roughly a three-month lag between the state of vegetation at Earth's surface and its effect on carbon dioxide in the middle troposphere.

    Data like these give scientists a new opportunity to better understand the relationships between carbon dioxide in Earth's middle troposphere and the seasonal cycle of vegetation near the surface.

    Creating the Animation

    This animation was created with data taken from two NASA spaceborne instruments. The concentration of carbon dioxide data from the Atmospheric Infrared Sounder (AIRS), a weather and climate instrument that flies aboard NASA's Aqua spacecraft, is overlain on measurements of vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on NASA's Aqua spacecraft, to better understand how photosynthesis and respiration influences the atmospheric carbon dioxide cycle over the globe. The animation runs from January through December and repeats. The AIRS tropospheric carbon dioxide seasonal cycle values were made by averaging AIRS data collected between 2003 and 2010, from which the annual carbon dioxide growth trend of 2 parts per million per year has been removed. For example, the data used for January 1 is actually an average of eight years of AIRS carbon dioxide data taken each year on January 1. The vegetation values were made using data averaged over a four-year period, from 2003 to 2006.

    Further Detail

    AIRS uses infrared technology to determine the concentration of atmospheric water vapor and several important trace gases as well as information about temperature and clouds. AIRS orbits Earth from pole-to-pole at an altitude of 438 miles (705 kilometers), measuring Earth's infrared spectrum in 3,278 channels spanning a wavelength range from 3.74 microns to 15.4 microns. Originally designed to improve weather forecasts, AIRS has improved operational five-day weather forecasts more than any other single instrument over the past decade. AIRS has also been found to be sensitive to atmospheric carbon dioxide in the middle troposphere, at an altitude of 5 to 10 kilometers or 3 to 6 miles. AIRS is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena. For further information, access the AIRS project

    The MODIS instrument is managed by NASA's Goddard Space Flight Center, Greenbelt, Md. For further information, access the MODIS project.

  • Study Domain for the Arctic-Boreal Vulnerability Experiment
    2016.08.19
    Climate change in the Arctic and Boreal region is unfolding faster than anywhere else on Earth, resulting in reduced Arctic sea ice, thawing of permafrost soils, decomposition of long- frozen organic matter, widespread changes to lakes, rivers, coastlines, and alterations of ecosystem structure and function. NASA's Terrestrial Ecology Program is conducting a major field campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE), in Alaska and western Canada, for 8 to 10 years, starting in 2015. ABoVE seeks a better understanding of the vulnerability and resilience of ecosystems and society to this changing environment. The image shown here outlines the core region of the study domain in red and the extended region of the study domain in purple. ABoVE’s science objectives are broadly focused on (1) gaining a better understanding of the vulnerability and resilience of Arctic and boreal ecosystems to environmental change in western North America, and (2) providing the scientific basis for informed decision-making to guide societal responses at local to international levels. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite sensors, providing a foundation for improving the analysis, and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The background shown over the study region is a spatially complete view of the vegetation greenness change for all of Canada and Alaska obtained by calculating per-pixel NDVI trend from all available 1984–2012 peak-summer Landsat-5 and -7 surface reflectance data, establishing the mid-Summer greenness trend. More information on this NDVI trend can be found here.
  • Modeled Phytoplankton Communities in the Global Ocean
    2015.09.30
    Phytoplankton are the base of the marine food web and are crucial players in the Earth's carbon cycle. They are also incredibly diverse. This visualization shows dominant phytoplankton types from 1994-1998 generated by the Darwin Project using a high-resolution ocean and ecosystem model. The model contains flow fields from 1994-1998 (generated by the ECCO2 model), inorganic nutrients, 78 species of phytoplankton, zooplankton, as well as particulate and dissolved organic matter. Colors represent the most dominant type of phytoplankton at a given location based on their size and ability to uptake nutrients. Red represents diatoms (big phytoplankton, which need silica), yellow represents flagellates (other big phytoplankton), green represents prochlorococcus (small phytoplankton that cannot use nitrate), and cyan represents synechococcus (other small phytoplankton). Opacity indicates concentration of the carbon biomass. A key part of the Darwin Project is developing theoretical and numerical models of the marine ecosystems. The data shown here are from a simulation of the Darwin model in a physical run of the Massachusetts Institute of Technology general circulation model by the Estimating the Circulation and Climate of the Ocean (ECCO) group. The model provides a laboratory to explore the controls on biodiversity and the biogeography of different phytoplankton species. In particular, the role of the swirls and filaments (mesoscale features) appear important in maintaining high biodiversity in the ocean.
  • Atmospheric CO2 from AIRS 2002-2016
    2016.12.15
    This visualization is an update of the global distribution and variation of the concentration of mid-tropospheric carbon dioxide observed by the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua spacecraft. For comparison, it is overlain by a graph of the seasonal variation and interannual increase of carbon dioxide observed at the Mauna Loa, Hawaii observatory. The two most notable features of this visualization are the seasonal variation of CO2 and the trend of increase in its concentration from year to year. The global map clearly shows that the CO2 in the northern hemisphere peaks in April-May and then drops to a minimum in September-October. Although the seasonal cycle is less pronounced in the southern hemisphere it is opposite to that in the northern hemisphere. This seasonal cycle is governed by the growth cycle of plants. The northern hemisphere has the majority of the land masses, and so the amplitude of the cycle is greater in that hemisphere. The overall color of the map shifts toward the red with advancing time due to the annual increase of CO2.
  • Atmospheric CO₂ Trends
    2014.12.10
    Fossil fuel combustion and other human activities are now increasing the atmospheric carbon dioxide (CO2) abundance to unprecedented rates. It is estimated that approximately 36 billion tons of CO2 are added to the atmosphere each year. The large graph shown here is an animated version of the standard Keeling curve from 1980 to September 2014. The red line denotes ground-based measurements from the Mauna Loa Observatory in Hawaii, while yellow denotes observations from the South Pole Observatory. Purple denotes the global trend. The smaller graph in the upper left shows satellite measurements of tropospheric CO2 concentrations (white dots) at different latitudes from September 2002 to September 2014, obtained by the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instruments. Note how the Northern Hemisphere has greater variably and generally higher levels of CO2 than the Southern Hemisphere.

    In May of 2013, these emissions pushed the monthly average CO2 concentrations above 400 parts per million (ppm)—a level that has not been reached during the past 800,000 years. These ever-increasing levels are raising concerns about greenhouse-gas-induced climate change.

  • 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.
  • Ocean Surface CO2 Flux with Wind Stress
    2015.11.18
    There are no direct global-scale observations of carbon fluxes between the land and oceans and the overlying atmosphere. Understanding the carbon cycle requires estimates of these fluxes, which can be computed indirectly using models constrained with global space-based observations that provide information about the physical and biological state of the land, atmosphere, and ocean. This animation shows results from the ECCO2-Darwin ocean carbon cycle model, which was developed as part of the NASA Carbon Monitoring System (CMS) Flux Project. The objective of the CMS-Flux project is to attribute changes in atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. ECCO2-Darwin is based on a global, eddying, ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) and on results from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) Project, which provides a data-constrained estimate of the time-evolving physical ocean state, and the Darwin Project, which provides time-evolving ocean ecosystem variables. Together, ECCO2 and Darwin provide a time-evolving physical and biological environment for carbon biogeochemistry, which is used to compute surface fluxes of carbon at high spatial and temporal resolution. The animation shows air-sea carbon flux and surface wind stress for the 2009-2010 period. Blue colors indicate uptake and orange-red colors indicate outgassing of ocean carbon by the ocean ranging from -5 to 5 x 10-7 mol C/m2/s. The pathlines indicate surface wind stress, which is one of the drivers of air-sea carbon exchange. For example, note the hurricanes in the North Atlantic and East Pacific in June to November, shown as outgassing events around the hurricane eye in regions of maximum wind.
  • Coccolithophores Near the Patagonia Shelf
    2014.06.03
    Coccolithophores, a type of phytoplankton, are one-celled, microscopic marine plants that live in large numbers throughout the upper layers of the ocean. They surround themselves with minute calcium carbonate plates called “coccoliths,” which are highly reflective such that populations of these plants can be seen from space. Near the Patagonia Shelf, located east of Argentina and Uruguay, ocean waters thrive with high concentrations of microscopic phytoplankton—e.g., coccolithiphores, dinoflagellates, and diatoms to name a few. That is because in this region the warm, saline, southward-flowing Brazil Current flows past and mixes with the cool, less-saline, nutrient-rich northward-flowing Falklands/Malvinas Current, creating an ideal environment for biological productivity. Scientists use true color satellite images like these, taken by Aqua/MODIS from December 15, 2010 to February 15, 2011, to observe the recurring coccolithophore blooms in the Patagonia Shelf region and study the impacts of ocean acidification on these microscopic organisms. Imagery from these two months shows a coccolithophore bloom (turquoise) near the shelf break. The shelf's unique ecosystem supports important fisheries in the region, providing a favorable reproductive habitat for anchovies and sardines.
  • Coloring The Seas
    2015.04.09
    Marine plants bloom and paint the water in extraordinary hues.
  • OCO-2 Early Glint Retrievals Over Water
    2015.05.18
    Launched on July 2, 2014, the second Orbiting Carbon Observatory (OCO-2) is the first NASA Earth-observing satellite designed to study atmospheric carbon dioxide (CO2) from space. Measurements from OCO-2 will be used to find the human and natural sources that are emitting CO2 into the atmosphere and the natural sinks that are absorbing this gas at the Earth’s surface.

    This pair of images compares preliminary estimates of column-averaged volume mixing ratios of carbon dioxide, or XCO2, from OCO-2 glint observations over the ocean to those generated by the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5). The large scale features are quite similar, but there are subtle differences that are being studied to determine whether they indicate biases in these early OCO-2 XCO2 estimates or limitations of the model. Over time, these comparisons are expected to substantially improve the accuracy and reliability of both the measurements and the models.

  • A Quarter Century US Forest Disturbance History from Landsat – the NAFD-NEX Products
    2015.11.30
    The North American Forest Dynamics (NAFD) study provides annual maps of forest disturbance in the conterminous United States, from 1986-2010. Using data from the NASA/USGS Landsat satellite program, the NAFD study produces maps at a spatial resolution of 30-meters. Spanning the 25 years of the study required 26,142 Landsat images and the use of the NASA Earth Exchange (NEX) supercomputing facility. Each annual map has classified pixels showing water, no forest cover, forest cover, no data available (data gaps) in present year, and forest disturbances that occurred in that year. Forest disturbance, in this study, refers to any removal or loss of the forest canopy. There were disturbances from natural causes, such as fires, insect outbreaks, hurricanes, tornadoes, and snow storms. There were also human-caused disturbances such as timber harvesting, urban development, and mining. Major timber harvest areas included the Southeast, the Pacific Northwest, and Maine. Extensive mountaintop mining was found in the Southern Appalachians, extending from Western Virginia to Tennessee. The eastern coast suffered substantial damages from hurricanes, while large scale damages from fire and insect outbreak were mostly in the western U.S. This study is a core project of the North American Carbon Program (NACP), a multidisciplinary research program designed to obtain scientific understanding of North America’s carbon sources and sinks and quantify changes in carbon stocks. This information is being used to evaluate the role of forest disturbance in the North American carbon cycle, which will help meet societal concerns and provide tools for decision makers. The NAFD (North American Forest Dynamics) study, a core project of the North American Carbon Program (NACP), was supported by grants from NASA’s Terrestrial Ecology, Carbon Cycle Sciences, and Applied Sciences Programs. The UMD group was supported under NASA Grant NNX11AJ78G S01. Associated NAFD-NEX activities have been carried out by Warren Cohen, USFS Pacific Northwest Research Station (Product Validation), Jeffrey Masek, NASA Goddard Space Flight Center (Regrowth Dynamics), Gretchen Moisen, USFS Rocky Mountain Research Station (Causal Factors Attribution) and Ramakrishna Nemani, NASA Ames Research Center (NEX computing). Data Citation: Goward, S.N., C. Huang, F. Zhao, K. Schleeweis, K. Rishmawi, M. Lindsey, J.L. Dungan, and A. Michaelis. 2015. NACP NAFD Project: Forest Disturbance History from Landsat, 1986-2010. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1290
  • Monthly burned area from the Global Fire Emissions Database (GFED)
    2015.12.15
    This time series was created using data from the Moderate Resolution Imaging Spectrometer (MODIS) onboard NASA’s Terra and Aqua satellites. Burned area is estimated by applying an algorithm that detects rapid changes in visible and infrared surface reflectance imagery. Fires typically darken the surface in the visible part of the electromagnetic spectrum, and brighten the surface in several wavelength bands in the shortwave infrared that are sensitive to the surface water content of vegetation. Thermal emissions from actively burning fires also are measured by MODIS and are used to improve the burned area estimates in croplands and other areas where the fire sizes are relatively small. This animation portrays burned area between September 2000 and August 2015 as a percent of the 1/4 degree grid cell that was burned each month. The values on the color bar are on a log scale, so the regions shown in blue and green shades indicate small burned areas while those in red and orange represent a larger percent of the region burned. Beneath the burned area, the seasonal Blue Marble landcover shows the advance and retreat of snow in the northern hemisphere. More information about the Global Fire Emissions Database, including maps of burned area and fire emissions, can be found here.

Earth Surface and Interior

The Earth Surface and Interior focus area (ESI) supports innovative, cross-cutting research into solid Earth processes and properties. ESI uses NASA’s unique global observations to better understand the Earth from its inner core to its outer lithospheric crust, as well as the dynamics between these component parts and the Earth’s atmosphere and ocean. This research provides the foundational data, measurements, and observations that help us understand Earth’s shape, motion, and magnetism, as well as the basis for products needed to inform the assessment, mitigation, and forecasting of natural hazards like earthquakes, volcanic eruptions, tsunamis, landslides, and more.
  • NASA Surveys Hurricane Damage to Puerto Rico's Forests (Data Viz Version)
    2019.07.29
    In September 2017, Hurricane Maria struck Puerto Rico head-on as a Category 4 storm with winds topping 155 miles per hour. The storm damaged homes, flooded towns, devastated the island's forests and caused the longest electricity black-out in U.S. history. Hurricane Maria's lashing rain and winds transformed Puerto Rico's lush tropical rainforest landscape. Research scientist Doug Morton of Goddard was part of the team of NASA researchers who had surveyed Puerto Rico's forests six months before the storm with Goddard’s Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager, a system designed to study the structure and species composition of Puerto Rican forests. Shooting 600,000 laser pulses per second, G-LiHT produces a 3D view of the forest structure in high resolution. In April 2018, post-Maria, they went back and surveyed the same tracks as in 2017. Comparing the before and after data, the team found that 40 to 60 percent of the tall trees that formed the canopy of the forest either lost large branches, were snapped in half or were uprooted by strong winds. "Maria gave the island's forests a haircut," said Morton. "The island lost so many large trees that forests were shortened by one-third. We basically saw 60 years' worth of what we would consider natural treefall disturbances happen in one day." This version was shown at the Association for Computing Machinery (ACM) / Special Interest Group on GRAPHics (SIGGRAPH) Computer Animation Festival (CAF) on July 29, 2019 at the Microsoft Theater in Los Angeles, CA. It will then be part of the ACM/SIGGRAPH CAF traveling show after that.
  • Improvements in Groundwater and Soil Moisture Measurements Derived from the GRACE Mission
    2017.10.06
    From space, we track water in the ground – whether it is a centimeter, a meter, or a kilometer below the surface. Around the world, NASA's GRACE satellites have provided unprecedented views of water storage in natural aquifers. These underground reserves are so massive that they affect Earth's gravity field. When their mass changes, the satellites detect the change in gravity. Droughts can affect deep groundwater stores when water users pump hundreds of billions of gallons out of their aquifers to compensate for the lack of rainfall – and GRACE can detect this change. This view from space has revolutionized our understanding of water stores beneath the surface. But scientists at NASA Goddard can combine GRACE data with sophisticated computer models to give decision makers in the continental US an otherwise unseen view, helping to trigger critical water conservation measures. These computer models help us decompose the GRACE signal to identify changes in both the shallow groundwater and the root zone where crops are actually drawing moisture to survive. Stations on the ground provide a connect-the-dots picture. The vantage point from space – combined with modeling – provides a comprehensive view of how the drought evolved over time and ultimately ended. This constantly changing snapshot of shallow groundwater conditions is now used every week in the US Drought Monitor, the benchmark relied upon by decision makers at the local, state, and federal level. This visualization shows the global Terrestrial Water Storage Anomaly from GRACE data, and then highlights the contiguous United States to show groundwater anomaly. This more detailed view is made by assimilating GRACEwater storage data into a supercomputer model of the land surface. The visualization dives into California, showing further detail by separating out the surface soil moisture (top 2 centimeters) and the root zone soil mositure (top 100 centimeters).
  • A possible second large subglacial impact crater in northwest Greenland
    2019.02.11
    It is increasingly rare to find new large impact craters on Earth, let alone such craters buried beneath ice. This study by MacGregor et al. describes a possible impact crater buried beneath two kilometers of ice in northwest Greenland. The circular structure is more than 36 kilometers wide, and both its shape and other geophysical properties are consistent with an impact origin. If eventually confirmed as an impact crater, it would be only the second found beneath either of Earth’s ice sheets. The first was the Hiawatha impact crater, which is also in northwest Greenland and only 183 kilometers away from this new structure, so this team also evaluated whether these two craters could be related. They are similarly sized, but the candidate second crater appears more eroded and ice above it is much less disturbed than above the Hiawatha impact crater. Statistical analysis of the frequency of two unrelated but nearby large impacts indicates that it is improbable but not impossible that this pair is unrelated. This study expands knowledge of the impact history of the Earth and raises the question as to how many other impact craters buried beneath ice have yet to be found.
  • The Hiawatha Impact Crater
    2018.11.14
    The series of visualizations below are derived from satellite imagery and radar sounding. They portray both the location and size of the 31-kilometer-wide impact crater beneath Hiawatha Glacier. They also portray the structure of the glacier ice that flows into and fills the crater. The Hiawatha impact crater was first suspected to exist in the summer of 2015, from examination of a compilation of Greenland's sub-ice topography radar measurements made by NASA over two decades. The visualizations of the subsurface shown below are derived from a spring 2016 airborne survey by Germany's Alfred Wegener Institute, using a new ultrawideband radar sounder developed by the Center for Remote Sensing of Ice Sheets at The University of Kansas. Subsequent helicopter visits to the deglaciated terrain in front of Hiawatha Glacier by scientists from the Natural History Museum in Denmark recovered sediment samples from the main river that discharges water from beneath Hiawatha Glacier, through the northwestern rim breach. Laboratory examination revealed that these sediment samples contained shocked quartz and elevated platinum-group-element concentrations, both signs that the sediment records evidence of the impact of an iron asteroid more than one kilometer wide. The Hiawatha impact crater is potentially one of the youngest large impact craters on Earth. In the visualizations below, the elevation of the topography of the bed, the ice surface and the radar curtains have been exaggerated ten times in order to better illustrate their structure.
  • Groundwater Depletion in India Revealed by GRACE
    2009.08.12
    Scientists using data from NASA's Gravity Recovery and Climate Experiment (GRACE) have found that the groundwater beneath Northern India has been receding by as much as one foot per year over the past decade. After examining many environmental and climate factors, the team of hydrologists led by Matt Rodell of NASA's Goddard Space Flight Center, Greenbelt, Md. concluded that the loss is almost entirely due to human consumption.

    Groundwater comes from the natural percolation of precipitation and other surface waters down through Earth's soil and rock, accumulating in aquifers - cavities and layers of porous rock, gravel, sand, or clay. In some subterranean reservoirs, the water may be thousands to millions of years old; in others, water levels decline and rise again naturally each year. Groundwater levels do not respond to changes in weather as rapidly as lakes, streams, and rivers do. So when groundwater is pumped for irrigation or other uses, recharge to the original levels can take months or years.

    More than 109 cubic km (26 cubic miles) of groundwater disappeared from the region's aquifers between 2002 and 2008 — double the capacity of India's largest surface water reservoir, the Upper Wainganga, and triple that of Lake Mead, the largest manmade reservoir in the U.S.

    The animation shown here depicts the change in groundwater levels as measured each November between 2002 to 2008.

  • GRACE 15-Year Groundwater Trends
    2018.05.16
    NASA scientists used GRACE data to identify regional trends of freshwater movement, and combined that information with data from other satellites, climate models and precipitation measurements to determine the causes of major regional trends in freshwater storage. In these visualizations, the colors represent liquid water equivalent thinckness, while the animated graph overlay represents the terrestrial water storage anomaly.
  • Subsidence in California's Central Valley
    2013.10.17
    This animation shows, in exaggerated terms, how the surface of the southern Central Valley of California deformed from the period 2007 to 2011. Interferometric data from the Japanese ALOS PALSAR imaging radar was used to measure the deformation, shown in color overlaid on an ASTER image. The large subsidence "bowl" that developed over this time period was caused by withdrawal of groundwater, causing subsurface layers to compact. Interferometric synthetic aperture radar, or InSAR, can be used to monitor subsidence in order to prevent groundwater overdraft and irreversible compaction of aquifers. ALOS PALSAR data is copyright JAXA/METI and was provided by the GEO Supersites and the U.S. Government Research Consortium datapool at the Alaska Satellite Facility.
  • High-Resolution Soil Moisture Maps
    2015.12.16
    These maps combine data from the twin satellites of the Gravity Recovery and Climate Experiment (GRACE) with other satellite and ground-based measurements to model the relative amount of water stored at two different levels: at plant root level and underground. The wetness, or water content, of each layer is compared to the average between 1948 and 2009. The darkest red regions represent dry conditions that should occur only 2 percent of the time (about once every 50 years). All of the maps are experimental products funded by NASA’s Applied Sciences Program and developed by scientists at NASA’s Goddard Space Flight Center and the National Drought Mitigation Center. The maps do not attempt to represent human consumption of water; but rather, they show changes in water storage related to weather, climate, and seasonal patterns.
  • Landsat Data Help Water-Resource Managers
    2013.11.01
    In the Western United States between 80 and 90% of freshwater is used for agriculture. In Southern California irrigated farmland stretches southward across the desert from the Salton Sea—an artificial inland sea—to the Mexico border. In the natural-color image [left] acquired on May 15, 2013, by Landsat 8’s Operational Land Imager, blocks of square farmland appear in shades of green and tan, while urban areas such as El Centro, California and Mexicali, Mexico appear in shades of gray. Accurate estimates of total crop area provided by Landsat satellites can be used to help forecast commodities in the United States and the world food market. On that same day, thermal measurements from Landsat 8’s Thermal Infrared Sensor [right] show different temperatures between crop fields as well as urban and desert areas. Cooler areas (e.g., irrigated crops) appear as dark purple and red shades, while warmer areas (e.g., urban and desert areas) appear as shades of bright yellow and white. Plants cool down when they transpire, so the combination of water evaporating from the plants and the ground (i.e., evapotranspiration) lowers the temperature of the irrigated land. Pixels representing cooler areas in thermal images from TIRS help water-resource managers determine where water is being used for irrigation, allowing them to make management decisions on water distribution to preserve this scarce resource. When an earlier design of Landsat 8 did not include a thermal infrared band, the Western States Water Council advocated for its inclusion.

    Used in 2014 Calendar.