NASA-led Study Solves a Methane Puzzle

NASA-led Study Solves a Methane Puzzle

A new NASA-led study has solved a puzzle involving the recent rise in atmospheric methane, a potent greenhouse gas, with a new calculation of emissions from global fires. The new study resolves what looked like irreconcilable differences in explanations for the increase.

Methane emissions have been rising sharply since 2006. Different research teams have produced viable estimates for two known sources of the increase: emissions from the oil and gas industry, and microbial production in wet tropical environments like marshes and rice paddies. But when these estimates were added to estimates of other sources, the sum was considerably more than the observed increase. In fact, each new estimate was large enough to explain the whole increase by itself.

Scientist John Worden of NASA's Jet Propulsion Laboratory in Pasadena, California, and colleagues focused on fires because they're also changing globally. The area burned each year decreased about 12 percent between the early 2000s and the more recent period of 2007 to 2014, according to a new study using observations by NASA's Moderate Resolution Imaging Spectrometer satellite instrument. The logical assumption would be that methane emissions from fires have decreased by about the same percentage. Using satellite measurements of methane and carbon monoxide, Worden's team found the real decrease in methane emissions was almost twice as much as that assumption would suggest.

When the research team subtracted this large decrease from the sum of all emissions, the methane budget balanced correctly, with room for both fossil fuel and wetland increases. The research is published in the journal Nature Communications.

Fast Facts:

› Atmospheric methane concentrations are given by their weight in teragrams.

› One teragram equals 110,000 tons -- the weight of about 17,000 elephants.

› Methane emissions are increasing by about 25 teragrams a year, with total emissions currently around 550 teragrams a year.

Most methane molecules in the atmosphere don't have identifying features that reveal their origin. Tracking down their sources is a detective job involving multiple lines of evidence: measurements of other gases, chemical analyses, isotopic signatures, observations of land use, and more. "A fun thing about this study was combining all this different evidence to piece this puzzle together," Worden said.

Carbon isotopes in the methane molecules are one clue. Of the three methane sources examined in the new study, emissions from fires contain the largest percentage of heavy carbon isotopes, microbial emissions have the smallest, and fossil fuel emissions are in between. Another clue is ethane, which (like methane) is a component of natural gas. An increase in atmospheric ethane indicates increasing fossil fuel sources. Fires emit carbon monoxide as well as methane, and measurements of that gas are a final clue.

Worden's team used carbon monoxide and methane data from the Measurements of Pollutants in the Troposphere instrument on NASA's Terra satellite and the Tropospheric Emission Spectrometer instrument on NASA's Aura to quantify fire emissions of methane. The results show these emissions have been decreasing much more rapidly than expected.

Combining isotopic evidence from ground surface measurements with the newly calculated fire emissions, the team showed that about 17 teragrams per year of the increase is due to fossil fuels, another 12 is from wetlands or rice farming, while fires are decreasing by about 4 teragrams per year. The three numbers combine to 25 teragrams a year -- the same as the observed increase.

Worden's coauthors are at the National Center for Atmospheric Research, Boulder, Colorado; and the Netherlands Institute for Space Research and University of Utrecht, both in Utrecht, the Netherlands.

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Written by Carol Rasmussen

NASA's Earth Science News Team

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NASA Briefing Previews Mission to Explore Nearest Reaches of Space

NASA will host a briefing at 1 p.m. EST Thursday, Jan. 4, about the agency’s upcoming science mission to explore where Earth’s atmosphere meets space.

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Arecibo Radar Returns with Asteroid Phaethon Images

After several months of downtime after Hurricane Maria blew through, the Arecibo Observatory Planetary Radar has returned to normal operation, providing the highest-resolution images to date of near-Earth asteroid 3200 Phaethon during its Dec. 16 flyby of Earth. The radar images, which are subtle at the available resolution, reveal the asteroid is spheroidal in shape and has a large concavity at least several hundred meters in extent near the leading edge, and a conspicuous dark, circular feature near one of the poles. Arecibo's radar images of Phaethon have resolutions as fine as about 250 feet (75 meters) per pixel.

"These new observations of Phaethon show it may be similar in shape to asteroid Bennu, the target of NASA's OSIRIS-REx spacecraft, but 10 times larger," said Patrick Taylor, a Universities Space Research Association (USRA), Columbia, Maryland, scientist and group leader for Planetary Radar at Arecibo Observatory. "The dark feature could be a crater or some other topographic depression that did not reflect the radar beam back at us."

Radar images obtained by Arecibo indicate Phaethon has a diameter of about 3.6 miles (6 kilometers) -- roughly 0.6 miles (1 kilometer) larger than previous estimates. Phaethon is the second largest near-Earth asteroid classified as "Potentially Hazardous." Near-Earth objects are classified as potentially hazardous asteroids (PHAs), based on their size and how closely their orbits approach Earth.

"Arecibo is an important global asset, crucial for planetary defense work because of its unique capabilities," said Joan Schmelz of USRA and deputy director of Arecibo Observatory. "We have been working diligently to get it back up and running since Hurricane Maria devastated Puerto Rico."

The Arecibo Observatory has the most powerful astronomical radar system on Earth. On Sept. 20, the telescope suffered minor structural damage when Maria, the strongest hurricane to hit the island since 1928, made landfall. Some days after the storm, the telescope resumed radio astronomy observations, while radar observations, which require high power and diesel fuel for generators at the site, resumed operations in early December after commercial power returned to the observatory.

Asteroid Phaethon was discovered on Oct. 11, 1983, by NASA's Infrared Astronomical Satellite (IRAS). Observations of Phaethon were conducted at Arecibo from Dec. 15 through 19, 2017, using the NASA-funded planetary radar system. At time of closest approach on Dec. 16 at 3 p.m. PST (3 p.m. EST, 11 p.m. UTC) the asteroid was about 1.1 million miles (1.8 million kilometers) away, or about 4.6 times the distance from Earth to the moon. The encounter is the closest the object will come to Earth until 2093.

Radar has been used to observe hundreds of asteroids. When these small, natural remnants of the formation of our solar system pass relatively close to Earth, deep space radar is a powerful technique for studying their sizes, shapes, rotation, surface features and roughness, and for more precise determination of their orbital path.

The Arecibo Planetary Radar Program is fully funded by NASA through a grant to Universities Space Research Association (USRA), from the Near-Earth Object Observations program. The Arecibo Observatory is a facility of the National Science Foundation operated under cooperative agreement by SRI International, USRA, and Universidad Metropolitana.

NASA's Planetary Defense Coordination Office is responsible for finding, tracking and characterizing potentially hazardous asteroids and comets coming near Earth, issuing warnings about possible impacts, and assisting coordination of U.S. government response planning, should there be an actual impact threat.

More information about the National Science Foundation's Arecibo Observatory can be found at:

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Wet Winters May Not Dampen Small Wildfires

NASA scientists conducting research on the connection between fuel moisture and fires have uncovered a paradox: a wet winter corresponds to more small wildfires in the following fire season, not fewer, as is commonly assumed. Large fires behave more "logically," with fewer large fires after a wet winter and more after a dry one.

"This is the most surprising result from our study, because we would expect small fires to follow suit with larger fires," said Daniel Jensen, a Ph.D. candidate at UCLA who worked on the project under the direction of scientist J.T. Reager of NASA's Jet Propulsion Laboratory in Pasadena, California. When there is ample moisture for plant growth, Jensen pointed out, "It seems that the buildup of fuel content alone causes there to be more fires -- but not necessarily more devastating fires."

The research is a step toward understanding the role of fuel moisture in wildfires, which could help in determining how severe a fire season may be several months before it arrives. A paper on the research is online in the journal Environmental Research Letters.

As anyone who has ever lit a campfire knows, dry fuel catches fire and burns faster than damp fuel. Knowing the moisture of a fuel supply can improve predictions of how fast a wildfire may spread, but measuring it from samples collected in the field is time-consuming and labor-intensive. Remote sensing offers a possible alternative, and earlier studies have shown that soil moisture (the water contained in the soil) correlates well with fuel moisture.

Jensen and co-authors correlated records of wildfire occurrences across the contiguous United States from 2003 through 2012 with soil moisture measurements from the U.S./German Gravity Recovery and Climate Experiment (GRACE) satellite mission and U.S. Geological Survey data on vegetation and landscape types. They found that although each landscape type varied in average soil moisture and average number of fires, in every landscape type, the number of small fires increased after a wet pre-season.

Jensen explained that a wet winter causes grasses and other small plants to grow profusely. These plants dry out and die at the end of the growing season, leaving abundant fuel for a wildfire. Trees and larger shrubs, however, retain more moisture after a wet winter. That might hamper the ability of small fires to grow into large ones in landscapes containing trees.

To obtain their results, the researchers developed techniques to assimilate GRACE data into a high-resolution U.S. hydrology model called the Catchment Land Surface Model, from NASA's Goddard Space Flight Center in Greenbelt, Maryland, for a product with both accuracy and high resolution. They parceled each GRACE estimate, which covers a region about 186 miles (300 kilometers) square, into dozens of smaller "boxes" to match the resolution of the model, using data assimilation techniques to refine the "fit" until the results added up correctly to match the GRACE data. Data assimilation, a technique commonly used with weather forecasting models, adds ongoing observational data throughout the course of a simulation to keep a model on track.

The scientists chose GRACE because of the mission's longevity, said Reager. Other missions such as NASA's Soil Moisture Active Passive (SMAP) satellite offer higher resolution, but none has been in orbit as long as GRACE. "Without that long record, we wouldn't have been able to do the model fitting," Reager said. "Now that we've built the model, we can plug in SMAP data. This methodology will help us get a better look at the ecosystem dynamics of fire activity."

For more on GRACE and GRACE-Follow-On, which is launching next spring to continue the GRACE measurement, see:

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Written by Carol Rasmussen

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NASA Chooses New Frontiers Mission Finalists

NASA has announced two finalist proposals under its New Frontiers program.

The CAESAR mission, led by Cornell University in Ithaca, New York, and managed by NASA's Goddard Space Flight Center in Greenbelt, Maryland, would attempt to return a sample from a comet successfully explored by the European Space Agency's Rosetta spacecraft. Dragonfly, led by the Johns Hopkins University Applied Physics Laboratory in Laurel, Maryland, would explore the prebiotic chemistry and habitability of dozens of sites on Saturn's moon Titan.

NASA's Jet Propulsion Laboratory in Pasadena, California, would provide navigation support for the Dragonfly mission. JPL also would provide instruments for two other proposals selected for technology development funds to prepare them for future mission competitions. One mission would explore Venus, the other would explore Saturn's moon Enceladus.

The selected mission will be the fourth in NASA's New Frontiers program. Previously funded proposals include the JPL-led Juno mission, which is currently orbiting Jupiter.

For more information, see NASA's news release on the announcement at:

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Prototype Space Sensors Take Test Ride on NASA ER-2

Scientists recently completed test flights with prototypes of potential satellite sensors - including two from NASA's Jet Propulsion Laboratory in Pasadena, California -- over the Western United States, probing basic science questions about aerosols, clouds, air quality and global ocean ecosystems.

The flight campaign, called Aerosol Characterization from Polarimeter and Lidar (ACEPOL), sought to test capabilities of several proposed instruments for the Aerosol-Cloud-Ecosystem (ACE) pre-formulation study.

Aerosols are small solid or liquid particles suspended in Earth's atmosphere, like fine dust, smoke, pollen or soot. These particles scatter and absorb sunlight and are critical to the formation of clouds and precipitation. Scientists can analyze this scattered light using instruments like polarimeters, which measure the color and polarization of the scattered light, and lidars, which use lasers to probe the atmosphere. Together these data sets provide key information about aerosol properties, including size, shape and chemical composition -- information that provides a better understanding and assessment of their effects on weather, climate and air quality.

Prior to being launched into space, airborne versions of satellite sensors typically take a test ride on NASA's ER-2 high-altitude aircraft. The platform, based at NASA's Armstrong Flight Research Center in Palmdale, California, flies at altitudes of up to 70,000 feet (21,336 meters), and provides a vantage point and conditions similar to space. By flying these instruments on an aircraft before the expense of launching them into space, scientists and engineers can make adjustments to the hardware and data retrieval algorithms.

The ER-2 also enables scientists to observe specific events of interest, like wildfires or volcanic eruptions, to gain a more comprehensive collection of different types of aerosols in different conditions. The aircraft test phase in sensor development is helpful for ensuring instruments are collecting both accurate and useful data prior to the time the final version of the sensors makes its trip into space.

In addition to testing capabilities of new sensors, ACEPOL flights also provided calibration and evaluation data for NASA's Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite lidar by staging satellite underpasses as part of their flight plans. In addition to comparisons with CALIPSO, ACEPOL also contributes to the development of future satellite missions, including the European Space Agency's EarthCare, the European Organization for the Exploitation of Meteorological Satellites' Meteorological Operational Satellite - Second Generation (METOP-SG), and NASA's Multi-Angle Imager for Aerosols (MAIA) and Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) programs. MAIA is being built and is managed by JPL.

The team completed nine flights that wrapped up in mid-November, observing targets such as California's Central Valley and the Pacific Ocean, and as far east as Arizona, where the team observed smoke from controlled forest fires near Flagstaff.

The ER-2's payload included four airborne polarimeters -- Airborne Hyper-Angular Rainbow Polarimeter (AirHARP), JPL's Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), Airborne Spectropolarimeter for Planetary Exploration (AirSPEX) and Research Scanning Polarimeter (RSP) -- and two lidar instruments - Cloud Physics Lidar (CPL) and High Spectral Resolution Lidar-2 (HSRL-2). Each of the polarimeters used different techniques and angles to measure and record data. The instruments also differed from one another in size and power. From an engineering perspective, the ultimate goal of the ACEPOL mission was to better understand how those overall differences translate into data collection.

The combination of the polarimeter and lidar instruments, along with ground-based data from stationary air quality measurement stations, provide scientists with a more complete picture of the three-dimensional distribution of aerosols in Earth's atmosphere. Using a variety of different approaches for collecting data also enables scientists to differentiate between various types of aerosols (e.g., smoke, dust, pollution) and clouds (cirrus, stratus, etc.).

The ACEPOL mission involved partnership between multiple NASA centers, including Langley Research Center in Hampton, Virginia; Goddard Space Flight Center in Greenbelt, Maryland; the Goddard Institute for Space Studies in New York City; and JPL. The mission also included international partnership with the Netherlands Institute for Space Research, which flew the AirSPEX instrument on board the ER-2 for the second time. The instrument made its maiden flight on the ER-2 in January 2016.

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NASA Armstrong Flight Research Center, Edwards, California

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Artificial Intelligence, NASA Data Used to Discover Eighth Planet Circling Distant Star

Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA's Kepler Space Telescope.

The newly-discovered Kepler-90i - a sizzling hot, rocky planet that orbits its star once every 14.4 days - was found using machine learning from Google. Machine learning is an approach to artificial intelligence in which computers "learn." In this case, computers learned to identify planets by finding in Kepler data instances where the telescope recorded changes in starlight caused by planets beyond our solar system, known as exoplanets.

Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA's Kepler Space Telescope.

NASA will host a Reddit Ask Me Anything at noon PST (3 p.m. EST) today on this discovery.

"Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them," said Paul Hertz, director of NASA's Astrophysics Division in Washington. "This finding shows that our data will be a treasure trove available to innovative researchers for years to come."

The discovery came about after researchers Christopher Shallue and Andrew Vanderburg trained a computer to learn how to identify exoplanets in the light readings recorded by Kepler - the miniscule change in brightness captured when a planet passed in front of, or transited, a star. Inspired by the way neurons connect in the human brain, this artificial "neural network" sifted through Kepler data and found weak transit signals from a previously-missed eighth planet orbiting Kepler-90, in the constellation Draco.

Machine learning has previously been used in searches of the Kepler database, and this continuing research demonstrates that neural networks are a promising tool in finding some of the weakest signals of distant worlds.

Other planetary systems probably hold more promise for life than Kepler-90. About 30 percent larger than Earth, Kepler-90i is so close to its star that its average surface temperature is believed to exceed 800 degrees Fahrenheit, on par with Mercury. Its outermost planet, Kepler-90h, orbits at a similar distance to its star as Earth does to the Sun.

"The Kepler-90 star system is like a mini version of our solar system. You have small planets inside and big planets outside, but everything is scrunched in much closer," said Vanderburg, a NASA Sagan Postdoctoral Fellow and astronomer at the University of Texas at Austin.

Shallue, a senior software engineer with Google's research team Google AI, came up with the idea to apply a neural network to Kepler data. He became interested in exoplanet discovery after learning that astronomy, like other branches of science, is rapidly being inundated with data as the technology for data collection from space advances.

"In my spare time, I started Googling for 'finding exoplanets with large data sets' and found out about the Kepler mission and the huge data set available," said Shallue. "Machine learning really shines in situations where there is so much data that humans can't search it for themselves."

Kepler's four-year dataset consists of 35,000 possible planetary signals. Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. Shallue and Vanderburg thought there could be more interesting exoplanet discoveries faintly lurking in the data.

First, they trained the neural network to identify transiting exoplanets using a set of 15,000 previously vetted signals from the Kepler exoplanet catalogue. In the test set, the neural network correctly identified true planets and false positives 96 percent of the time. Then, with the neural network having "learned" to detect the pattern of a transiting exoplanet, the researchers directed their model to search for weaker signals in 670 star systems that already had multiple known planets. Their assumption was that multiple-planet systems would be the best places to look for more exoplanets.

"We got lots of false positives of planets, but also potentially more real planets," said Vanderburg. "It's like sifting through rocks to find jewels. If you have a finer sieve then you will catch more rocks but you might catch more jewels, as well."

Kepler-90i wasn't the only jewel this neural network sifted out. In the Kepler-80 system, they found a sixth planet. This one, the Earth-sized Kepler-80g, and four of its neighboring planets form what is called a resonant chain - where planets are locked by their mutual gravity in a rhythmic orbital dance. The result is an extremely stable system, similar to the seven planets in the TRAPPIST-1 system.

Their research paper reporting these findings has been accepted for publication in The Astronomical Journal. Shallue and Vanderburg plan to apply their neural network to Kepler's full set of more than 150,000 stars.

Kepler has produced an unprecedented data set for exoplanet hunting. After gazing at one patch of space for four years, the spacecraft now is operating on an extended mission and switches its field of view every 80 days.

"These results demonstrate the enduring value of Kepler's mission," said Jessie Dotson, Kepler's project scientist at NASA's Ames Research Center in California's Silicon Valley. "New ways of looking at the data - such as this early-stage research to apply machine learning algorithms - promise to continue to yield significant advances in our understanding of planetary systems around other stars. I'm sure there are more firsts in the data waiting for people to find them."

Ames manages the Kepler and K2 missions for NASA's Science Mission Directorate in Washington. NASA's Jet Propulsion Laboratory in Pasadena, California, managed Kepler mission development. Ball Aerospace & Technologies Corporation operates the flight system with support from the Laboratory for Atmospheric and Space Physics at the University of Colorado in Boulder. This work was performed through the Carl Sagan Postdoctoral Fellowship Program executed by the NASA Exoplanet Science Institute.

For more information on this announcement, visit:

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For more information about the Kepler mission, visit:

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News Media Contact

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NASA Headquarters, Washington

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Ames Research Center, California's Silicon Valley

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Elizabeth Landau

Jet Propulsion Laboratory, Pasadena, California

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NASA Invests in Concept Development for Missions to Comet, Saturn Moon Titan

NASA has selected two finalist concepts for a robotic mission planned to launch in the mid-2020s: a comet sample return mission and a drone-like rotorcraft that would explore potential landing sites on Saturn’s largest moon, Titan.

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NASA to Name Finalists for Future Solar System Mission

NASA will announce finalist concepts for a future robotic mission to explore the solar system during a media teleconference at 2 p.m. EST Wednesday, Dec. 20.

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NASA Awards Contract for Aircraft Operations Support

NASA has awarded the Aircraft Maintenance, Logistics, Integration, Configuration Management and Engineering (ALICE) contract to Yulista Tactical Services, LLC in Huntsville, Alabama.

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Nominations Process Opens for National Space Council Users’ Advisory Group

Public nominations now are being accepted from U.S. citizens and organizations for potential membership on an advisory group that will represent the perspectives, interests and expertise of industry and other non-federal entities to the National Space Council.

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