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Mining Old Data From NASA’s Voyager 2 Solves Several Uranus Mysteries
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By NASA
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Jupiter, Saturn, and Neptune each emit more energy than they receive from the Sun, meaning they have comparatively warm interiors. NASA’s Uranus flyby with Voyager 2 in 1986 found the planet colder than expected, which challenged ideas of how planets formed and evolved. However, with advanced computer modeling and a new look at old data, scientists think the planet may actually be warmer than previously expected. For millennia, astronomers thought Uranus was no more than a distant star. It wasn’t until the late 18th century that Uranus was universally accepted as a planet. To this day, the ringed, blue world subverts scientists’ expectations, but new NASA research helps puzzle out some of the world’s mystique.
This zoomed-in image of Uranus, captured by the Near-Infrared Camera on NASA’s James Webb Space Telescope on Feb. 6, 2023, reveals stunning views of Uranus’ rings. Credits: NASA, ESA, CSA, STScI Uranus is unlike any other planet in our solar system. It spins on its side, which means each pole directly faces the Sun for a continuous 42-year “summer.” Uranus also rotates in the opposite direction of all planets except Venus. Data from NASA’s Voyager 2 Uranus flyby in 1986 also suggested the planet is unusually cold inside, challenging scientists to reconsider fundamental theories of how planets formed and evolved throughout our solar system.
“Since Voyager 2’s flyby, everybody has said Uranus has no internal heat,” said Amy Simon, a planetary scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “But it’s been really hard to explain why that is, especially when compared with the other giant planets.”
These Uranus projections came from only one up-close measurement of the planet’s emitted heat made by Voyager 2: “Everything hinges on that one data point,” said Simon. “That is part of the problem.”
Now, using an advanced computer modeling technique and revisiting decades of data, Simon and a team of scientists have found that Uranus does in fact generate some heat, as they reported on May 16 in the Monthly Notices of the Royal Astronomical Society journal.
A planet’s internal heat can be calculated by comparing the amount of energy it receives from the Sun to the amount it of energy it releases into space in the form of reflected light and emitted heat. The solar system’s other giant planets — Saturn, Jupiter, and Neptune — emit more heat than they receive, which means the extra heat is coming from inside, much of it left over from the high-energy processes that formed the planets 4.5 billion years ago. The amount of heat a planet exudes could be an indication of its age: the less heat released relative to the heat absorbed from the Sun, the older the planet is.
Uranus stood out from the other planets because it appeared to give off as much heat as it received, implying it had none of its own. This puzzled scientists. Some hypothesized that perhaps the planet is much older than all the others and has cooled off completely. Others proposed that a giant collision — the same one that may have knocked the planet on its side — blasted out all of Uranus’ heat. But none of these hypotheses satisfied scientists, motivating them to solve Uranus’ cold case.
“We thought, ‘Could it really be that there is no internal heat at Uranus?’” said Patrick Irwin, the paper’s lead author and professor of planetary physics at the University of Oxford in England. “We did many calculations to see how much sunshine is reflected by Uranus and we realized that it is actually more reflective than people had estimated.”
The researchers set out to determine Uranus’ full energy budget: how much energy it receives from the Sun compared to how much it reflects as sunlight and how much it emits as heat. To do this, they needed to estimate the total amount of light reflected from the planet at all angles. “You need to see the light that’s scattered off to the sides, not just coming straight back at you,” Simon said.
To get the most accurate estimate of Uranus’ energy budget yet, Oxford researchers developed a computer model that brought together everything known about Uranus’ atmosphere from decades of observations from ground- and space-based telescopes, including NASA’s Hubble Space Telescope and NASA’s Infrared Telescope Facility in Hawaii. The model included information about the planet’s hazes, clouds, and seasonal changes, all of which affect how sunlight is reflected and how heat escapes.
These side-by-side images of Uranus, taken eight years apart by NASA’s Hubble Space Telescope, show seasonal changes in the planet’s reflectivity. The left image shows the planet seven years after its northern spring equinox when the Sun was shining just above its equator. The second photo, taken six years before the planet’s summer solstice, portrays a bright and large northern polar cap. Credit: NASA, ESA, STScI, A. Simon (NASA-GSFC), M. H. Wong (UC Berkeley), J. DePasquale (STScI) The researchers found that Uranus releases about 15% more energy than it receives from the Sun, a figure that is similar to another recent estimate from a separate study funded in part by NASA that was published July 14 in Geophysical Research Letters. These studies suggest Uranus it has its own heat, though still far less than its neighbor Neptune, which emits more than twice the energy it receives.
“Now we have to understand what that remnant amount of heat at Uranus means, as well as get better measurements of it,” Simon said.
Unraveling Uranus’ past is useful not only for mapping the timeline of when solar system planets formed and migrated to their current orbits, but it also helps scientists better understand many of the planets discovered outside the solar system, called exoplanets, a majority of which are the same size as Uranus.
By Emma Friedman
NASA’s Goddard Space Flight Center, Greenbelt, Md.
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Last Updated Jul 17, 2025 Editor Lonnie Shekhtman Contact Lonnie Shekhtman lonnie.shekhtman@nasa.gov Location NASA Goddard Space Flight Center Related Terms
Planetary Science Planets The Solar System Uranus View the full article
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By NASA
4 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
An international team of astronomers has uncovered new evidence to explain how pulsing remnants of exploded stars interact with surrounding matter deep in the cosmos, using observations from NASA’s IXPE (Imaging X-ray Polarimetry Explorer) and other telescopes.
Scientists based in the U.S., Italy, and Spain, set their sights on a mysterious cosmic duo called PSR J1023+0038, or J1023 for short. The J1023 system is comprised of a rapidly rotating neutron star feeding off of its low-mass companion star, which has created an accretion disk around the neutron star. This neutron star is also a pulsar, emitting powerful twin beams of light from its opposing magnetic poles as it rotates, spinning like a lighthouse beacon.
The J1023 system is rare and valuable to study because the pulsar transitions clearly between its active state, in which it feeds off its companion star, and a more dormant state, when it emits detectable pulsations as radio waves. This makes it a “transitional millisecond pulsar.”
An artist’s illustration depicting the central regions of the binary system PSR J1023+0038, including the pulsar, the inner accretion disc and the pulsar wind. Credit: Marco Maria Messa, University of Milan/INAF-OAB; Maria Cristina Baglio, INAF-OAB “Transitional millisecond pulsars are cosmic laboratories, helping us understand how neutron stars evolve in binary systems,” said researcher Maria Cristina Baglio of the Italian National Institute of Astrophysics (INAF) Brera Observatory in Merate, Italy, and lead author of a paper in The Astrophysical Journal Letters illustrating the new findings.
The big question for scientists about this pulsar system was: Where do the X-rays originate? The answer would inform broader theories about particle acceleration, accretion physics, and the environments surrounding neutron stars across the universe.
The source surprised them: The X-rays came from the pulsar wind, a chaotic stew of gases, shock waves, magnetic fields, and particles accelerated near the speed of light, that hits the accretion disk.
To determine this, astronomers needed to measure the angle of polarization in both X-ray and optical light. Polarization is a measure of how organized light waves are. They looked at X-ray polarization with IXPE, the only telescope capable of making this measurement in space, and comparing it with optical polarization from the European Southern Observatory’s Very Large Telescope in Chile. IXPE launched in Dec. 2021 and has made many observations of pulsars, but J1023 was the first system of its kind that it explored.
NASA’s NICER (Neutron star Interior Composition Explorer) and Neil Gehrels Swift Observatory provided valuable observations of the system in high-energy light. Other telescopes contributing data included the Karl G. Jansky Very Large Array in Magdalena, New Mexico.
The result: scientists found the same angle of polarization across the different wavelengths.
“That finding is compelling evidence that a single, coherent physical mechanism underpins the light we observe,” said Francesco Coti Zelati of the Institute of Space Sciences in Barcelona, Spain, co-lead author of the findings.
This interpretation challenges the conventional wisdom about neutron star emissions of radiation in binary systems, the researchers said. Previous models had indicated that the X-rays come from the accretion disk, but this new study shows they originate with the pulsar wind.
“IXPE has observed many isolated pulsars and found that the pulsar wind powers the X-rays,” said NASA Marshall astrophysicist Philip Kaaret, principal investigator for IXPE at NASA’s Marshall Space Flight Center in Huntsville, Alabama. “These new observations show that the pulsar wind powers most of the energy output of the system.”
Astronomers continue to study transitional millisecond pulsars, assessing how observed physical mechanisms compare with those of other pulsars and pulsar wind nebulae. Insights from these observations could help refine theoretical models describing how pulsar winds generate radiation – and bring researchers one step closer, Baglio and Coti Zelati agreed, to fully understanding the physical mechanisms at work in these extraordinary cosmic systems.
More about IXPE
IXPE, which continues to provide unprecedented data enabling groundbreaking discoveries about celestial objects across the universe, is a joint NASA and Italian Space Agency mission with partners and science collaborators in 12 countries. IXPE is led by NASA’s Marshall Space Flight Center in Huntsville, Alabama. BAE Systems, Inc., headquartered in Falls Church, Virginia, manages spacecraft operations together with the University of Colorado’s Laboratory for Atmospheric and Space Physics in Boulder. Learn more about IXPE’s ongoing mission here:
https://www.nasa.gov/ixpe
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Last Updated Jul 15, 2025 EditorBeth RidgewayContactCorinne M. Beckingercorinne.m.beckinger@nasa.govLocationMarshall Space Flight Center Related Terms
IXPE (Imaging X-ray Polarimetry Explorer) Marshall Astrophysics Marshall Science Research & Projects Marshall Space Flight Center Explore More
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Explore This Section Science Goddard Space Flight Center Linking Satellite Data and… Overview Learning Resources Science Activation Teams SME Map Opportunities More Science Activation Stories Citizen Science 4 min read
Linking Satellite Data and Community Knowledge to Advance Alaskan Snow Science
Seasonal snow plays a significant role in global water and energy cycles, and billions of people worldwide rely on snowmelt for water resources needs, including water supply, hydropower, agriculture, and more. Monitoring snow water equivalent (SWE) is critical for supporting these applications and for mitigating damages caused by snowmelt flooding, avalanches, and other snow-related disasters. However, our ability to measure SWE remains a challenge, particularly in northern latitudes where in situ SWE observations are sparse and satellite observations are impacted by the boreal forest and environmental conditions. Despite limited in situ SWE measurements, local residents in Arctic and sub-Arctic regions provide a vast and valuable body of place-based knowledge and observations that are essential for understanding snowpack behavior in northern regions.
As part of a joint NASA SnowEx, NASA’s Minority University Research and Education Project (MUREP) for American Indian and Alaska Native STEM (Science, Technology, Engineering, & Mathematics) Engagement (MAIANSE), and Global Learning & Observations to Benefit the Environment (GLOBE) Program partnership, a team of scientists including NASA intern Julia White (NASA Goddard Space Flight Center, University of Alaska Fairbanks), Carrie Vuyovich (NASA Goddard Space Flight Center), Alicia Joseph (NASA Goddard Space Flight Center), and Christi Buffington (University of Alaska Fairbanks, GLOBE Implementation Office) is studying snow water equivalent (SWE) across Interior Alaska. This project combines satellite-based interferometric synthetic aperture radar (InSAR) data, primarily from the Sentinel-1 satellite, with ground-based observations from the Snow Telemetry (SNOTEL) network and GLOBE (Global Learning Observations to Benefit the Environment). Together, these data sources help the team investigate how SWE varies across the landscape and how it affects local ecosystems and communities. The team is also preparing for future integration of data from NASA’s upcoming NISAR (NASA ISRO Synthetic Aperture Radar) mission, which is expected to enhance SWE retrieval capabilities.
After a collaborative visit to the classroom of Tammie Kovalenko in November 2024, Delta Junction junior and senior high school students in vocational agriculture (Vo Ag) classes, including members of Future Farmers of America (FFA), began collecting GLOBE data on a snowdrift located just outside their classroom. As the project progressed, students developed their own research questions. One student, Fianna Rooney, took the project even further — presenting research posters at both the GLOBE International Virtual Science Symposium (IVSS) and both the FFA Regional and National Conventions. Her work highlights the growing role of Alaskan youth in science, and how student-led inquiry can enrich both education and research outcomes. (This trip was funded by the NASA Science Activation Program’s Arctic and Earth SIGNs – STEM Integrating GLOBE & NASA – project at the University of Alaska Fairbanks.)
In February 2025, the team collaborated with Delta Junction Junior High and High School students, along with the Delta Junction Trails Association, to conduct a GLOBE Intensive Observation Period (IOP), “Delta Junction Snowdrifts,” to collect Landcover photos, snow depth, and snow water equivalent data. Thanks to aligned interests and research goals at the Alaska Satellite Facility (ASF), the project was further expanded into Spring 2025. Collaborators from ASF and the Alaska Center for Unmanned Aircraft Systems Integration (ACUASI) collected high resolution airborne data over the snowdrift at the Delta Junction Junior and Senior High School. This complementary dataset helped strengthen connections between satellite observations and ground-based student measurements.
This effort, led by a NASA intern, scientists, students, and Alaskan community members, highlights the power of collaboration in advancing science and education. Next steps will include collaboration with Native Alaskan communities near Delta Junction, including the Healy Lake Tribe, whose vast, generational knowledge will be of great value to deepening our understanding of Alaskan snow dynamics.
Learn more about how NASA’s Science Activation program connects NASA science experts, real content, and experiences with community leaders to do science in ways that activate minds and promote deeper understanding of our world and beyond: https://science.nasa.gov/learn/about-science-activation/
Julia White and Delta Junction student following GLOBE protocols for snow depth. Tori Brannan Share
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Last Updated Jul 14, 2025 Editor NASA Science Editorial Team Location Goddard Space Flight Center Related Terms
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Smarter Searching: NASA AI Makes Science Data Easier to Find
Image snapshot taken from NASA Worldview of NASA’s Global Precipitation Measurement (GPM) mission on March 15, 2025 showing heavy rain across the southeastern U.S. with an overlay of the GCMD Keyword Recommender for Earth Science, Atmosphere, Precipitation, Droplet Size. NASA Worldview Imagine shopping for a new pair of running shoes online. If each seller described them differently—one calling them “sneakers,” another “trainers,” and someone else “footwear for exercise”—you’d quickly feel lost in a sea of mismatched terminology. Fortunately, most online stores use standardized categories and filters, so you can click through a simple path: Women’s > Shoes > Running Shoes—and quickly find what you need.
Now, scale that problem to scientific research. Instead of sneakers, think “aerosol optical depth” or “sea surface temperature.” Instead of a handful of retailers, it is thousands of researchers, instruments, and data providers. Without a common language for describing data, finding relevant Earth science datasets would be like trying to locate a needle in a haystack, blindfolded.
That’s why NASA created the Global Change Master Directory (GCMD), a standardized vocabulary that helps scientists tag their datasets in a consistent and searchable way. But as science evolves, so does the challenge of keeping metadata organized and discoverable.
To meet that challenge, NASA’s Office of Data Science and Informatics (ODSI) at the agency’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, developed the GCMD Keyword Recommender (GKR): a smart tool designed to help data providers and curators assign the right keywords, automatically.
Smarter Tagging, Accelerated Discovery
The upgraded GKR model isn’t just a technical improvement; it’s a leap forward in how we organize and access scientific knowledge. By automatically recommending precise, standardized keywords, the model reduces the burden on human curators while ensuring metadata quality remains high. This makes it easier for researchers, students, and the public to find exactly the datasets they need.
It also sets the stage for broader applications. The techniques used in GKR, like applying focal loss to rare-label classification problems and adapting pre-trained transformers to specialized domains, can benefit fields well beyond Earth science.
Metadata Matchmaker
The newly upgraded GKR model tackles a massive challenge in information science known as extreme multi-label classification. That’s a mouthful, but the concept is straightforward: Instead of predicting just one label, the model must choose many, sometimes dozens, from a set of thousands. Each dataset may need to be tagged with multiple, nuanced descriptors pulled from a controlled vocabulary.
Think of it like trying to identify all the animals in a photograph. If there’s just a dog, it’s easy. But if there’s a dog, a bird, a raccoon hiding behind a bush, and a unicorn that only shows up in 0.1% of your training photos, the task becomes far more difficult. That’s what GKR is up against: tagging complex datasets with precision, even when examples of some keywords are scarce.
And the problem is only growing. The new version of GKR now considers more than 3,200 keywords, up from about 430 in its earlier iteration. That’s a sevenfold increase in vocabulary complexity, and a major leap in what the model needs to learn and predict.
To handle this scale, the GKR team didn’t just add more data; they built a more capable model from the ground up. At the heart of the upgrade is INDUS, an advanced language model trained on a staggering 66 billion words drawn from scientific literature across disciplines—Earth science, biological sciences, astronomy, and more.
NASA ODSI’s GCMD Keyword Recommender AI model automatically tags scientific datasets with the help of INDUS, a large language model trained on NASA scientific publications across the disciplines of astrophysics, biological and physical sciences, Earth science, heliophysics, and planetary science. NASA “We’re at the frontier of cutting-edge artificial intelligence and machine learning for science,” said Sajil Awale, a member of the NASA ODSI AI team at MSFC. “This problem domain is interesting, and challenging, because it’s an extreme classification problem where the model needs to differentiate even very similar keywords/tags based on small variations of context. It’s exciting to see how we have leveraged INDUS to build this GKR model because it is designed and trained for scientific domains. There are opportunities to improve INDUS for future uses.”
This means that the new GKR isn’t just guessing based on word similarities; it understands the context in which keywords appear. It’s the difference between a model knowing that “precipitation” might relate to weather versus recognizing when it means a climate variable in satellite data.
And while the older model was trained on only 2,000 metadata records, the new version had access to a much richer dataset of more than 43,000 records from NASA’s Common Metadata Repository. That increased exposure helps the model make more accurate predictions.
The Common Metadata Repository is the backend behind the following data search and discovery services:
Earthdata Search International Data Network Learning to Love Rare Words
One of the biggest hurdles in a task like this is class imbalance. Some keywords appear frequently; others might show up just a handful of times. Traditional machine learning approaches, like cross-entropy loss, which was used initially to train the model, tend to favor the easy, common labels, and neglect the rare ones.
To solve this, NASA’s team turned to focal loss, a strategy that reduces the model’s attention to obvious examples and shifts focus toward the harder, underrepresented cases.
The result? A model that performs better across the board, especially on the keywords that matter most to specialists searching for niche datasets.
From Metadata to Mission
Ultimately, science depends not only on collecting data, but on making that data usable and discoverable. The updated GKR tool is a quiet but critical part of that mission. By bringing powerful AI to the task of metadata tagging, it helps ensure that the flood of Earth observation data pouring in from satellites and instruments around the globe doesn’t get lost in translation.
In a world awash with data, tools like GKR help researchers find the signal in the noise and turn information into insight.
Beyond powering GKR, the INDUS large language model is also enabling innovation across other NASA SMD projects. For example, INDUS supports the Science Discovery Engine by helping automate metadata curation and improving the relevancy ranking of search results.The diverse applications reflect INDUS’s growing role as a foundational AI capability for SMD.
The INDUS large language model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence.
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Last Updated Jul 09, 2025 Related Terms
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NASA/JPL-Caltech/MSSS The United States flag adorns an aluminum plate mounted at the base of the mast, or “head,” of NASA’s Perseverance Mars rover. This image of the plate was taken on June 28, 2025 (the 1,548th day, or sol, of the mission), by the WATSON (Wide Angle Topographic Sensor for Operations and eNgineering) camera on the end of the rover’s robotic arm.
WATSON, part of an instrument called SHERLOC (Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals), was built by Malin Space Science Systems (MSSS) in San Diego and is operated jointly by MSSS and NASA’s Jet Propulsion Laboratory in Southern California. JPL, which is managed for the agency by Caltech, built and manages operations of the Perseverance rover.
Learn more about Perseverance’s latest science.
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