Members Can Post Anonymously On This Site
-
Similar Topics
-
By NASA
An unexpectedly strong solar storm rocked our planet on April 23, 2023, sparking auroras as far south as southern Texas in the U.S. and taking the world by surprise.
Two days earlier, the Sun blasted a coronal mass ejection (CME) — a cloud of energetic particles, magnetic fields, and solar material — toward Earth. Space scientists took notice, expecting it could cause disruptions to Earth’s magnetic field, known as a geomagnetic storm. But the CME wasn’t especially fast or massive, and it was preceded by a relatively weak solar flare, suggesting the storm would be minor. But it became severe.
Using NASA heliophysics missions, new studies of this storm and others are helping scientists learn why some CMEs have more intense effects — and better predict the impacts of future solar eruptions on our lives.
During the night of April 23 to 24, 2023, a geomagnetic storm produced auroras that were witnessed as far south as Arizona, Arkansas, and Texas in the U.S. This photo shows green aurora shimmering over Larimore, North Dakota, in the early morning of April 24. Copyright Elan Azriel, used with permission Why Was This Storm So Intense?
A paper published in the Astrophysical Journal on March 31 suggests the CME’s orientation relative to Earth likely caused the April 2023 storm to become surprisingly strong.
The researchers gathered observations from five heliophysics spacecraft across the inner solar system to study the CME in detail as it emerged from the Sun and traveled to Earth.
They noticed a large coronal hole near the CME’s birthplace. Coronal holes are areas where the solar wind — a stream of particles flowing from the Sun — floods outward at higher than normal speeds.
“The fast solar wind coming from this coronal hole acted like an air current, nudging the CME away from its original straight-line path and pushing it closer to Earth’s orbital plane,” said the paper’s lead author, Evangelos Paouris of the Johns Hopkins Applied Physics Laboratory in Laurel, Maryland. “In addition to this deflection, the CME also rotated slightly.”
Paouris says this turned the CME’s magnetic fields opposite to Earth’s magnetic field and held them there — allowing more of the Sun’s energy to pour into Earth’s environment and intensifying the storm.
The strength of the April 2023 geomagnetic storm was a surprise in part because the coronal mass ejection (CME) that produced it followed a relatively weak solar flare, seen as the bright area to the lower right of center in this extreme ultraviolet image of the Sun from NASA’s Solar Dynamics Observatory. The CMEs that produce severe geomagnetic storms are typically preceded by stronger flares. However, a team of scientists think fast solar wind from a coronal hole (the dark area below the flare in this image) helped rotate the CME and made it more potent when it struck Earth. NASA/SDO Cool Thermosphere
Meanwhile, NASA’s GOLD (Global-scale Observations of Limb and Disk) mission revealed another unexpected consequence of the April 2023 storm at Earth.
Before, during, and after the storm, GOLD studied the temperature in the middle thermosphere, a part of Earth’s upper atmosphere about 85 to 120 miles overhead. During the storm, temperatures increased throughout GOLD’s wide field of view over the Americas. But surprisingly, after the storm, temperatures dropped about 90 to 198 degrees Fahrenheit lower than they were before the storm (from about 980 to 1,070 degrees Fahrenheit before the storm to 870 to 980 degrees Fahrenheit afterward).
“Our measurement is the first to show widespread cooling in the middle thermosphere after a strong storm,” said Xuguang Cai of the University of Colorado, Boulder, lead author of a paper about GOLD’s observations published in the journal JGR Space Physics on April 15, 2025.
The thermosphere’s temperature is important, because it affects how much drag Earth-orbiting satellites and space debris experience.
“When the thermosphere cools, it contracts and becomes less dense at satellite altitudes, reducing drag,” Cai said. “This can cause satellites and space debris to stay in orbit longer than expected, increasing the risk of collisions. Understanding how geomagnetic storms and solar activity affect Earth’s upper atmosphere helps protect technologies we all rely on — like GPS, satellites, and radio communications.”
Predicting When Storms Strike
To predict when a CME will trigger a geomagnetic storm, or be “geoeffective,” some scientists are combining observations with machine learning. A paper published last November in the journal Solar Physics describes one such approach called GeoCME.
Machine learning is a type of artificial intelligence in which a computer algorithm learns from data to identify patterns, then uses those patterns to make decisions or predictions.
Scientists trained GeoCME by giving it images from the NASA/ESA (European Space Agency) SOHO (Solar and Heliospheric Observatory) spacecraft of different CMEs that reached Earth along with SOHO images of the Sun before, during, and after each CME. They then told the model whether each CME produced a geomagnetic storm.
Then, when it was given images from three different science instruments on SOHO, the model’s predictions were highly accurate. Out of 21 geoeffective CMEs, the model correctly predicted all 21 of them; of 7 non-geoeffective ones, it correctly predicted 5 of them.
“The algorithm shows promise,” said heliophysicist Jack Ireland of NASA’s Goddard Space Flight Center in Greenbelt, Maryland, who was not involved in the study. “Understanding if a CME will be geoeffective or not can help us protect infrastructure in space and technological systems on Earth. This paper shows machine learning approaches to predicting geoeffective CMEs are feasible.”
The white cloud expanding outward in this image sequence is a coronal mass ejection (CME) that erupted from the Sun on April 21, 2023. Two days later, the CME struck Earth and produced a surprisingly strong geomagnetic storm. The images in this sequence are from a coronagraph on the NASA/ESA (European Space Agency) SOHO (Solar and Heliospheric Observatory) spacecraft. The coronagraph uses a disk to cover the Sun and reveal fainter details around it. The Sun’s location and size are indicated by a small white circle. The planet Jupiter appears as a bright dot on the far right. NASA/ESA/SOHO Earlier Warnings
During a severe geomagnetic storm in May 2024 — the strongest to rattle Earth in over 20 years — NASA’s STEREO (Solar Terrestrial Relations Observatory) measured the magnetic field structure of CMEs as they passed by.
When a CME headed for Earth hits a spacecraft first, that spacecraft can often measure the CME and its magnetic field directly, helping scientists determine how strong the geomagnetic storm will be at Earth. Typically, the first spacecraft to get hit are one million miles from Earth toward the Sun at a place called Lagrange Point 1 (L1), giving us only 10 to 60 minutes advanced warning.
By chance, during the May 2024 storm, when several CMEs erupted from the Sun and merged on their way to Earth, NASA’s STEREO-A spacecraft happened to be between us and the Sun, about 4 million miles closer to the Sun than L1.
A paper published March 17, 2025, in the journal Space Weather reports that if STEREO-A had served as a CME sentinel, it could have provided an accurate prediction of the resulting storm’s strength 2 hours and 34 minutes earlier than a spacecraft could at L1.
According to the paper’s lead author, Eva Weiler of the Austrian Space Weather Office in Graz, “No other Earth-directed superstorm has ever been observed by a spacecraft positioned closer to the Sun than L1.”
Earth’s Lagrange points are places in space where the gravitational pull between the Sun and Earth balance, making them relatively stable locations to put spacecraft. NASA By Vanessa Thomas
NASA’s Goddard Space Flight Center, Greenbelt, Md.
View the full article
-
By NASA
Ozone high in the stratosphere protects us from the Sun’s ultraviolet light. But ozone near the ground is a pollutant that harms people and plants. The San Joaquin Valley has some of the most polluted air in the country, and NASA scientists with the new Ozone Where We Live (OWWL) project are working to measure ozone and other pollutants there. They need your help!
Do you live or work in Bakersfield, CA? Sign up to host an ozone sensor! It’s like a big lunch box that you place in your yard, but it’s not packed with tuna and crackers. It’s filled with sensors that measure temperature and humidity and sniff out dangerous gases like methane, carbon monoxide, carbon dioxide, and of course, ozone.
Can you fly a plane? Going to the San Joaquin Valley? Sign up to take an ozone sensor on your next flight! You can help measure ozone levels in layers of the atmosphere that are hard for satellites to investigate. Scientists will combine the data you take with data from NASA’s TEMPO satellite to improve air quality models and measurements within the region. Find out more here or email: Emma.l.yates@nasa.gov
Join the Ozone Where We Live (OWWL) project and help NASA scientists protect the people of the San Joaquin Valley! Credit: Emma Yates Share
Details
Last Updated Jun 24, 2025 Related Terms
Citizen Science Earth Science Division Tropospheric Emissions: Monitoring of Pollution (TEMPO) Explore More
4 min read c-FIRST Team Sets Sights on Future Fire-observing Satellite Constellations
Article
3 weeks ago
2 min read Summer Students Scan the Radio Skies with SunRISE
Article
4 weeks ago
2 min read Space Cloud Watch Needs Your Photos of Night-Shining Clouds
Article
1 month ago
View the full article
-
By NASA
3 min read
Help Classify Galaxies Seen by NASA’s James Webb Space Telescope!
The Galaxy Zoo classification interface shows you an image from NASA’s Webb telescope and asks you questions about it. Image credit: Galaxy Zoo, Zooniverse. Inset galaxy: NASA/STScI/CEERS/TACC/S. Finkelstein/M. Bagley/Z. Levay/A. Pagan NASA needs your help identifying the shapes of thousands of galaxies in images taken by our James Webb Space Telescope with the Galaxy Zoo project. These classifications will help scientists answer questions about how the shapes of galaxies have changed over time, what caused these changes, and why. Thanks to the light collecting power of Webb, there are now over 500,000 images of galaxies on website of the Galaxy Zoo citizen science project—more images than scientists can classify by themselves.
“This is a great opportunity to see images from the newest space telescope,” said volunteer Christine Macmillan from Aberdeen, Scotland. “Galaxies at the edge of our universe are being seen for the first time, just as they are starting to form. Just sign up and answer simple questions about the shape of the galaxy that you are seeing. Anyone can do it, ages 10 and up!”
As we look at more distant objects in the universe, we see them as they were billions of years ago because light takes time to travel to us. With Webb, we can spot galaxies at greater distances than ever before. We’re seeing what some of the earliest galaxies ever detected look like, for the first time. The shapes of these galaxies tell us about how they were born, how and when they formed stars, and how they interacted with their neighbors. By looking at how more distant galaxies have different shapes than close galaxies, we can work out which processes were more common at different times in the universe’s history.
At Galaxy Zoo, you’ll first examine an image from the Webb telescope. Then you will be asked several questions, such as ‘Is the galaxy round?’, or ‘Are there signs of spiral arms?’. If you’re quick, you may even be the first person to see the galaxies you’re asked to classify.
“I’m amazed and honored to be one of the first people to actually see these images! What a privilege!” said volunteer Elisabeth Baeten from Leuven, Belgium.
Galaxy Zoo is a citizen science project with a long history of scientific impact. Galaxy Zoo volunteers have been exploring deep space since July 2007, starting with a million galaxies from a telescope in New Mexico called the Sloan Digital Sky Survey and then, moving on to images from space telescopes like NASA’s Hubble Space Telescope and ESA (European Space Agency)’s Euclid telescope. The project has revealed spectacular mergers, taught us about how the black holes at the center of galaxies affect their hosts, and provided insight into how features like spiral arms form and grow.
Now, in addition to adding new data from Webb, the science team has incorporated an AI algorithm called ZooBot, which will sift through the images first and label the ‘easier ones’ where there are many examples that already exist in previous images from the Hubble Space Telescope. When ZooBot is not confident on the classification of a galaxy, perhaps due to complex or faint structures, it will show it to users on Galaxy Zoo to get their human classifications, which will then help ZooBot learn more. Working together, humans and AI can accurately classify limitless numbers of galaxies. The Galaxy Zoo science team acknowledges support from the International Space Sciences Institute (ISSI), who provided funding for the team to get together and work on Galaxy Zoo. Join the project now.
Share
Details
Last Updated Apr 29, 2025 Related Terms
Astrophysics Division Citizen Science Get Involved James Webb Space Telescope (JWST) Explore More
2 min read Hubble Visits Glittering Cluster, Capturing Its Ultraviolet Light
Article
4 days ago
5 min read Eye on Infinity: NASA Celebrates Hubble’s 35th Year in Orbit
Article
6 days ago
3 min read Nine Finalists Advance in NASA’s Power to Explore Challenge
Article
6 days ago
View the full article
-
By NASA
Explore This Section Science Science Activation 2025 Aviation Weather Mission:… Overview Learning Resources Science Activation Teams SME Map Opportunities More Science Activation Stories Citizen Science 2 min read
2025 Aviation Weather Mission: Civil Air Patrol Cadets Help Scientists Study the Atmosphere with GLOBE Clouds
The Science Activation Program’s NASA Earth Science Education Collaborative (NESEC) is working alongside the Civil Air Patrol (CAP) to launch the 2025 Aviation Weather Mission. The mission will engage cadets (students ages 11-20) and senior members to collect aviation-relevant observations including airport conditions, Global Learning and Observations to Benefit the Environment (GLOBE) Cloud observations, commercial aircraft information (including registration number and altitude), and satellite collocations provided by the NASA GLOBE Clouds team at NASA Langley Research Center. This mission results from a highly successful collaboration between NESEC and CAP as cadets and senior members collected cloud, air temperature, and land cover observations during the partial and total solar eclipses in 2023 and 2024, engaging over 400 teams with over 3,000 cadets and over 1,000 senior members in every state, Washington DC, and Puerto Rico.
The 2025 Aviation Weather Mission will take place from April through July 2025, collecting observations over two 4-hour periods while practicing additional skills, such as flight tracking, orienteering, and data management. So far, over 3,000 cadets in 46 wings (states) have signed up to participate.
Science Activation recently showed support for this mission through a letter of collaboration sent to CAP Major General Regena Aye in early February. NASA GLOBE Clouds and GLOBE Observer are part of the NASA Earth Science Education Collaborative (NESEC), which is led by the Institute for Global Environmental Strategies (IGES) and supported by NASA under cooperative agreement award number NNX16AE28A. NESEC is part of NASA’s Science Activation Portfolio. Learn more about how Science Activation 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
Cadets from the Virginia wing making cloud observations as they prepare for the 2025 Aviation Weather Mission. Share
Details
Last Updated Mar 04, 2025 Editor NASA Climate Editorial Team Location NASA Langley Research Center Related Terms
Science Activation Clouds Opportunities For Students to Get Involved Weather and Atmospheric Dynamics Explore More
2 min read Sharing PLANETS Curriculum with Out-of-School Time Educators
Article
1 week ago
3 min read Eclipses to Auroras: Eclipse Ambassadors Experience Winter Field School in Alaska
Article
2 weeks ago
2 min read An Afternoon of Family Science and Rocket Exploration in Alaska
Article
3 weeks ago
Keep Exploring Discover More Topics From NASA
James Webb Space Telescope
Webb is the premier observatory of the next decade, serving thousands of astronomers worldwide. It studies every phase in the…
Perseverance Rover
This rover and its aerial sidekick were assigned to study the geology of Mars and seek signs of ancient microbial…
Parker Solar Probe
On a mission to “touch the Sun,” NASA’s Parker Solar Probe became the first spacecraft to fly through the corona…
Juno
NASA’s Juno spacecraft entered orbit around Jupiter in 2016, the first explorer to peer below the planet’s dense clouds to…
View the full article
-
By NASA
An image of a coastal marshland combines aerial and satellite views in a technique similar to hyperspectral imaging. Combining data from multiple sources gives scientists information that can support environmental management.John Moisan When it comes to making real-time decisions about unfamiliar data – say, choosing a path to hike up a mountain you’ve never scaled before – existing artificial intelligence and machine learning tech doesn’t come close to measuring up to human skill. That’s why NASA scientist John Moisan is developing an AI “eye.”
Oceanographer John MoisanNASA Moisan, an oceanographer at NASA’s Wallops Flight Facility near Chincoteague, Virginia, said AI will direct his A-Eye, a movable sensor. After analyzing images his AI would not just find known patterns in new data, but also steer the sensor to observe and discover new features or biological processes.
“A truly intelligent machine needs to be able to recognize when it is faced with something truly new and worthy of further observation,” Moisan said. “Most AI applications are mapping applications trained with familiar data to recognize patterns in new data. How do you teach a machine to recognize something it doesn’t understand, stop and say ‘What was that? Let’s take a closer look.’ That’s discovery.”
Finding and identifying new patterns in complex data is still the domain of human scientists, and how humans see plays a large part, said Goddard AI expert James MacKinnon. Scientists analyze large data sets by looking at visualizations that can help bring out relationships between different variables within the data.
Infrared images like this one from a marsh area on the Maryland/Virginia Eastern Shore coastal barrier and back bay regions reveal clues to scientists about plant health, photosynthesis, and other conditions that affect vegetation and ecosystems.John Moisan It’s another story to train a computer to look at large data streams in real time to see those connections, MacKinnon said. Especially when looking for correlations and inter-relationships in the data that the computer hasn’t been trained to identify.
Moisan intends first to set his A-Eye on interpreting images from Earth’s complex aquatic and coastal regions. He expects to reach that goal this year, training the AI using observations from prior flights over the Delmarva Peninsula. Follow-up funding would help him complete the optical pointing goal.
“How do you pick out things that matter in a scan?” Moisan asked. “I want to be able to quickly point the A-Eye at something swept up in the scan, so that from a remote area we can get whatever we need to understand the environmental scene.”
Moisan’s on-board AI would scan the collected data in real-time to search for significant features, then steer an optical sensor to collect more detailed data in infrared and other frequencies.
Thinking machines may be set to play a larger role in future exploration of our universe. Sophisticated computers taught to recognize chemical signatures that could indicate life processes, or landscape features like lava flows or craters, might offer to increase the value of science data returned from lunar or deep-space exploration.
Today’s state-of-the-art AI is not quite ready to make mission-critical decisions, MacKinnon said.
“You need some way to take a perception of a scene and turn that into a decision and that’s really hard,” he said. “The scary thing, to a scientist, is to throw away data that could be valuable. An AI might prioritize what data to send first or have an algorithm that can call attention to anomalies, but at the end of the day, it’s going to be a scientist looking at that data that results in discoveries.”
Share
Details
Last Updated Feb 10, 2025 Related Terms
Goddard Space Flight Center Artificial Intelligence (AI) Goddard Technology People of Goddard Technology Wallops Flight Facility Keep Exploring Discover More Topics From NASA
Missions
Humans in Space
Climate Change
Solar System
View the full article
-
-
Check out these Videos
Recommended Posts
Join the conversation
You can post now and register later. If you have an account, sign in now to post with your account.
Note: Your post will require moderator approval before it will be visible.