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By NASA
NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute/Alex Parker This image, taken by NASA’s New Horizons spacecraft on July 14, 2015, is the most accurate natural color image of Pluto. This natural-color image results from refined calibration of data gathered by New Horizons’ color Multispectral Visible Imaging Camera (MVIC). The processing creates images that would approximate the colors that the human eye would perceive, bringing them closer to “true color” than the images released near the encounter. This single color MVIC scan includes no data from other New Horizons imagers or instruments added. The striking features on Pluto are clearly visible, including the bright expanse of Pluto’s icy, nitrogen-and-methane rich “heart,” Sputnik Planitia.
Image credit: NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute/Alex Parker
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By Amazing Space
Massive Solar Prominence "The Beast" Threatens Eruption? Space Weather Update July 14 2025 NASA SDO
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By NASA
7 min read
NASA’s Parker Solar Probe Snaps Closest-Ever Images to Sun
KEY POINTS
NASA’s Parker Solar Probe has taken the closest ever images to the Sun, captured just 3.8 million miles from the solar surface. The new close-up images show features in the solar wind, the constant stream of electrically charged subatomic particles released by the Sun that rage across the solar system at speeds exceeding 1 million miles an hour. These images, and other data, are helping scientists understand the mysteries of the solar wind, which is essential to understanding its effects at Earth. On its record-breaking pass by the Sun late last year, NASA’s Parker Solar Probe captured stunning new images from within the Sun’s atmosphere. These newly released images — taken closer to the Sun than we’ve ever been before — are helping scientists better understand the Sun’s influence across the solar system, including events that can affect Earth.
“Parker Solar Probe has once again transported us into the dynamic atmosphere of our closest star,” said Nicky Fox, associate administrator, Science Mission Directorate at NASA Headquarters in Washington. “We are witnessing where space weather threats to Earth begin, with our eyes, not just with models. This new data will help us vastly improve our space weather predictions to ensure the safety of our astronauts and the protection of our technology here on Earth and throughout the solar system.”
Parker Solar Probe started its closest approach to the Sun on Dec. 24, 2024, flying just 3.8 million miles from the solar surface. As it skimmed through the Sun’s outer atmosphere, called the corona, in the days around the perihelion, it collected data with an array of scientific instruments, including the Wide-Field Imager for Solar Probe, or WISPR.
Parker Solar Probe has revolutionized our understanding of the solar wind thanks to the spacecraft’s many passes through the Sun’s outer atmosphere.
Credit: NASA’s Goddard Space Flight Center/Joy Ng The new WISPR images reveal the corona and solar wind, a constant stream of electrically charged particles from the Sun that rage across the solar system. The solar wind expands throughout of the solar system with wide-ranging effects. Together with outbursts of material and magnetic currents from the Sun, it helps generate auroras, strip planetary atmospheres, and induce electric currents that can overwhelm power grids and affect communications at Earth. Understanding the impact of solar wind starts with understanding its origins at the Sun.
The WISPR images give scientists a closer look at what happens to the solar wind shortly after it is released from the corona. The images show the important boundary where the Sun’s magnetic field direction switches from northward to southward, called the heliospheric current sheet. It also captures the collision of multiple coronal mass ejections, or CMEs — large outbursts of charged particles that are a key driver of space weather — for the first time in high resolution.
“In these images, we’re seeing the CMEs basically piling up on top of one another,” said Angelos Vourlidas, the WISPR instrument scientist at the Johns Hopkins Applied Physics Laboratory, which designed, built, and operates the spacecraft in Laurel, Maryland. “We’re using this to figure out how the CMEs merge together, which can be important for space weather.”
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This video, made from images taken by Parker Solar Probe’s WISPR instrument during its record-breaking flyby of the Sun on Dec. 25, 2024, shows the solar wind racing out from the Sun’s outer atmosphere, the corona. NASA/Johns Hopkins APL/Naval Research Lab When CMEs collide, their trajectory can change, making it harder to predict where they’ll end up. Their merger can also accelerate charged particles and mix magnetic fields, which makes the CMEs’ effects potentially more dangerous to astronauts and satellites in space and technology on the ground. Parker Solar Probe’s close-up view helps scientists better prepare for such space weather effects at Earth and beyond.
Zooming in on Solar Wind’s Origins
The solar wind was first theorized by preeminent heliophysicist Eugene Parker in 1958. His theories about the solar wind, which were met with criticism at the time, revolutionized how we see our solar system. Prior to Parker Solar Probe’s launch in 2018, NASA and its international partners led missions like Mariner 2, Helios, Ulysses, Wind, and ACE that helped scientists understand the origins of the solar wind — but from a distance. Parker Solar Probe, named in honor of the late scientist, is filling in the gaps of our understanding much closer to the Sun.
At Earth, the solar wind is mostly a consistent breeze, but Parker Solar Probe found it’s anything but at the Sun. When the spacecraft reached within 14.7 million miles from the Sun, it encountered zig-zagging magnetic fields — a feature known as switchbacks. Using Parker Solar Probe’s data, scientists discovered that these switchbacks, which came in clumps, were more common than expected.
When Parker Solar Probe first crossed into the corona about 8 million miles from the Sun’s surface in 2021, it noticed the boundary of the corona was uneven and more complex than previously thought.
As it got even closer, Parker Solar Probe helped scientists pinpoint the origin of switchbacks at patches on the visible surface of the Sun where magnetic funnels form. In 2024 scientists announced that the fast solar wind — one of two main classes of the solar wind — is in part powered by these switchbacks, adding to a 50-year-old mystery.
However, it would take a closer view to understand the slow solar wind, which travels at just 220 miles per second, half the speed of the fast solar wind.
“The big unknown has been: how is the solar wind generated, and how does it manage to escape the Sun’s immense gravitational pull?” said Nour Rawafi, the project scientist for Parker Solar Probe at the Johns Hopkins Applied Physics Laboratory. “Understanding this continuous flow of particles, particularly the slow solar wind, is a major challenge, especially given the diversity in the properties of these streams — but with Parker Solar Probe, we’re closer than ever to uncovering their origins and how they evolve.”
Understanding Slow Solar Wind
The slow solar wind, which is twice as dense and more variable than fast solar wind, is important to study because its interplay with the fast solar wind can create moderately strong solar storm conditions at Earth sometimes rivaling those from CMEs.
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This artist’s concept shows a representative state of Earth’s magnetic bubble immersed in the slow solar wind, which averages some 180 to 300 miles per second. NASA’s Goddard Space Flight Center Conceptual Image Lab Prior to Parker Solar Probe, distant observations suggested there are actually two varieties of slow solar wind, distinguished by the orientation or variability of their magnetic fields. One type of slow solar wind, called Alfvénic, has small-scale switchbacks. The second type, called non-Alfvénic, doesn’t show these variations in its magnetic field.
As it spiraled closer to the Sun, Parker Solar Probe confirmed there are indeed two types. Its close-up views are also helping scientists differentiate the origins of the two types, which scientists believe are unique. The non-Alfvénic wind may come off features called helmet streamers — large loops connecting active regions where some particles can heat up enough to escape — whereas Alfvénic wind might originate near coronal holes, or dark, cool regions in the corona.
In its current orbit, bringing the spacecraft just 3.8 million miles from the Sun, Parker Solar Probe will continue to gather additional data during its upcoming passes through the corona to help scientists confirm the slow solar wind’s origins. The next pass comes Sept. 15, 2025.
“We don’t have a final consensus yet, but we have a whole lot of new intriguing data,” said Adam Szabo, Parker Solar Probe mission scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland.
By Mara Johnson-Groh
NASA’s Goddard Space Flight Center, Greenbelt, Md.
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Last Updated Jul 10, 2025 Related Terms
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By NASA
6 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
NASA instruments and aircraft are helping identify potential sources of critical minerals across vast swaths of California, Nevada, and other Western states. Pilots gear up to reach altitudes about twice as high as those of a cruising passenger jet.NASA NASA and the U.S. Geological Survey have been mapping the planets since Apollo. One team is searching closer to home for minerals critical to national security and the economy.
If not for the Joshua trees, the tan hills of Cuprite, Nevada, would resemble Mars. Scalded and chemically altered by water from deep underground, the rocks here are earthly analogs for understanding ancient Martian geology. The hills are also rich with minerals. They’ve lured prospectors for more than 100 years and made Cuprite an ideal place to test NASA technology designed to map the minerals, craters, crusts, and ices of our solar system.
Sensors that discovered lunar water, charted Saturn’s moons, even investigated ground zero in New York City were all tested and calibrated at Cuprite, said Robert Green, a senior research scientist at NASA’s Jet Propulsion Laboratory in Southern California. He’s honed instruments in Nevada for decades.
One of Green’s latest projects is to find and map rocky surfaces in the American West that could contain minerals crucial to the nation’s economy and security. Currently, the U.S. is dependent on imports of 50 critical minerals, which include lithium and rare earth elements used in everything from rechargeable batteries to medicine.
Scientists from the U.S. Geological Survey (USGS) are searching nationwide for domestic sources. NASA is contributing to this effort with high-altitude aircraft and sensors capable of detecting the molecular fingerprints of minerals across vast, treeless expanses in wavelengths of light not visible to human eyes.
The hills of Cuprite, Nevada, appear pink and tan to the eye (top image) but they shine with mica, gypsum, and alunite among other types of minerals when imaged spectroscopically (lower image). NASA sensors used to study Earth and other rocky worlds have been tested there.USGS/Ray Kokaly The collaboration is called GEMx, the Geological Earth Mapping Experiment, and it’s likely the largest airborne spectroscopic survey in U.S. history. Since 2023, scientists working on GEMx have charted more than 190,000 square miles (500,000 square kilometers) of North American soil.
Mapping Partnership Started During Apollo
As NASA instruments fly in aircraft 60,000 feet (18,000 meters) overhead, Todd Hoefen, a geophysicist, and his colleagues from USGS work below. The samples of rock they test and collect in the field are crucial to ensuring that the airborne observations match reality on the ground and are not skewed by the intervening atmosphere.
The GEMx mission marks the latest in a long history of partnerships between NASA and USGS. The two agencies have worked together to map rocky worlds — and keep astronauts and rovers safe — since the early days of the space race.
For example, geologic maps of the Moon made in the early 1960s at the USGS Astrogeology Science Center in Flagstaff, Arizona, helped Apollo mission planners select safe and scientifically promising sites for the six crewed landings that occurred from 1969 to 1972. Before stepping onto the lunar surface, NASA’s Moon-bound astronauts traveled to Flagstaff to practice fieldwork with USGS geologists. A version of those Apollo boot camps continues today with astronauts and scientists involved in NASA’s Artemis mission.
Geophysicist Raymond Kokaly, who leads the GEMx campaign for USGS, is pictured here conducting ground-based hyperspectral imaging of rock in Cuprite, Nevada, in April 2019.USGS/Todd Hoefen The GEMx mission marks the latest in a long history of partnerships between NASA and USGS. The two agencies have worked together to map rocky worlds — and keep astronauts and rovers safe — since the early days of the space race.
Rainbows and Rocks
To detect minerals and other compounds on the surfaces of rocky bodies across the solar system, including Earth, scientists use a technology pioneered by JPL in the 1980s called imaging spectroscopy. One of the original imaging spectrometers built by Robert Green and his team is central to the GEMx campaign in the Western U.S.
About the size and weight of a minifridge and built to fly on planes, the instrument is called AVIRIS-Classic, short for Airborne Visible/Infrared Imaging Spectrometer. Like all imaging spectrometers, it takes advantage of the fact that every molecule reflects and absorbs light in a unique pattern, like a fingerprint. Spectrometers detect these molecular fingerprints in the light bouncing off or emitted from a sample or a surface.
In the case of GEMx, that’s sunlight shimmering off different kinds of rocks.
Compared to a standard digital camera, which “sees” three color channels (red, green, and blue), imaging spectrometers can see more than 200 channels, including infrared wavelengths of light that are invisible to the human eye.
NASA spectrometers have orbited or flown by every major rocky body in our solar system. They’ve helped scientists investigate methane lakes on Titan, Saturn’s largest moon, and study Pluto’s thin atmosphere. One JPL-built spectrometer is currently en route to Europa, an icy moon of Jupiter, to help search for chemical ingredients necessary to support life.
“One of the cool things about NASA is that we develop technology to look out at the solar system and beyond, but we also turn around and look back down,” said Ben Phillips, a longtime NASA program manager who led GEMx until he retired in 2025.
The Newest Instrument
More than 200 hours of GEMx flights are scheduled through fall 2025. Scientists will process and validate the data, with the first USGS mineral maps to follow. During these flights, an ER-2 research aircraft from NASA’s Armstrong Flight Research Center in Edwards, California, will cruise over the Western U.S. at altitudes twice as high as a passenger jet flies.
At such high altitudes, pilot Dean Neeley must wear a spacesuit similar to those used by astronauts. He flies solo in the cramped cockpit but will be accompanied by state-of-the-art NASA instruments. In the belly of the plane rides AVIRIS-Classic, which will be retiring soon after more than three decades in service. Carefully packed in the plane’s nose is its successor: AVIRIS-5, taking flight for the first time in 2025.
Together, the two instruments provide 10 times the performance of the older spectrometer alone, but even by itself AVIRIS-5 marks a leap forward. It can sample areas ranging from about 30 feet (10 meters) to less than a foot (30 centimeters).
“The newest generation of AVIRIS will more than live up to the original,” Green said.
More About GEMx
The GEMx research project will last four years and is funded by the USGS Earth Mapping Resources Initiative. The initiative will capitalize on both the technology developed by NASA for spectroscopic imaging, as well as the agency’s expertise in analyzing the datasets and extracting critical mineral information from them.
Data collected by GEMx is available here.
News Media Contacts
Andrew Wang / Jane J. Lee
Jet Propulsion Laboratory, Pasadena, Calif.
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andrew.wang@jpl.nasa.gov / jane.j.lee@jpl.nasa.gov
Karen Fox / Elizabeth Vlock
NASA Headquarters, Washington
202-358-1600
karen.c.fox@nasa.gov / elizabeth.a.vlock@nasa.gov
Written by Sally Younger
2025-086
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Last Updated Jul 10, 2025 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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