NASA Science Flights Venture to Improve Severe Winter Weather Warnings

A team of NASA scientists deployed on an international mission designed to better understand severe winter storms. The North American Upstream Feature-Resolving and Tropopause Uncertainty Reconnaissance Experiment, or NURTURE, is an airborne campaign that uses a suite of remote sensing instruments to collect atmospheric data on winter weather with a goal of improving the models that feed storm forecasts. This combination of instruments will also serve as a proxy to demonstrate the potential to collect similar observations from space.

On Jan. 24, the research team departed from NASA’s Langley Research Center in Hampton, Virginia, aboard the center’s Gulfstream III aircraft (G-III) en route to Goose Bay, Canada.  For nearly a month, the plane will be making flights stretching from the Northern Atlantic Ocean over Canada through the Northeast United States, measuring moisture, clouds, and ozone as winter storms develop.

The second phase of the campaign, scheduled to fly out of Langley next year, will serve as the inaugural mission of NASA’s new airborne science laboratory, a Boeing 777 These flights will cover a larger range of 3,100 miles (5,000 kilometers) and use a larger suite of instruments. Researchers will collect detailed observations of the atmosphere over Europe, Greenland, the North Atlantic Ocean, Canada, the majority of  of the U.S., and much of the Arctic Ocean.

“Part of NASA’s role is to leverage our expertise and resources for the benefit of humankind – with innovation always being at our core,” said Will McCarty, weather program manager and program scientist at NASA’s Headquarters in Washington. “The NURTURE campaign is doing exactly that by outfitting our aircraft with one-of-a-kind instruments designed to put our science data into action to understand dangerous weather events before, and as they form.”

As the NASA G-III flies over Canada, a parallel companion mission led by a team of international partners called the North Atlantic Waveguide, Dry Intrusion, and Downstream Impact Campaign (NAWDIC) will be operating out of Shannon, Ireland. Meanwhile, a third airborne mission led by the National Oceanic and Atmospheric Administration (NOAA) will be studying how moisture is transported from the tropics to the Western U.S. By combining the data collected during these campaigns, scientists will be able to track weather systems as they interact and intersect globally to understand the large-scale flows and small-scale features that drive high-impact winter weather events. 

“These storms are not forecasted very accurately,” said Amin Nehrir, a research scientist at NASA Langley and co-investigator for the NURTURE mission. “Space observations of high latitudes in the Arctic lack the sensitivity needed to gather accurate data in such a dry, atmospheric environment. In lower latitudes, we benefit from observations from radiosondes, surface networks, and satellite observations. We are using cutting-edge technology beyond those that we have in space to get a better snapshot of atmospheric dynamics.”

Examples of severe winter weather events include cold air outbreaks, windstorms, hazardous seas, snow and ice storms, sea ice breakup, and extreme precipitation. Data from the NURTURE mission will be used to inform first responders, decision makers, and the public sooner while also demonstrating the potential for NASA’s remote weather sensor capabilities to be developed for use on future space-based missions.

“Effects from severe weather have significant costs that threaten lives and national security by destabilizing supply chains and damaging infrastructure,” said Steven Cavallo, principal investigator for NURTURE and lead scientist at the University of Oklahoma, School of Meteorology.

The NURTURE mission is funded by NASA’s Earth Science Division and managed by researchers at NASA Langley and NASA Ames in collaboration with the University of Oklahoma.

To learn more about NURTURE, visit:

https://espo.nasa.gov/nurture

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Webb Data Reveals Dark Matter

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Webb Data Reveals Dark Matter

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Webb Data Reveals Dark Matter

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This image from NASA’s James Webb Space Telescope, containing nearly 800,000 galaxies, is overlaid with a map of dark matter, represented in blue. Brighter blue areas indicate a higher density of dark matter. Researchers used Webb data to find the dark matter — which is invisible — via its gravitational influence on regular matter.

The area of sky shown here is 0.54 square degrees (about 2½ times the size of the full Moon) and located in the constellation Sextans. Webb’s Near-Infrared Camera (NIRCam) peered at this region for a total of about 255 hours. 

Dark matter doesn’t emit, reflect, absorb, or even block light, and is therefore not visible to the human eye or traditional telescopes. But it does interact with the universe through gravity, and large clumps or clusters of dark matter have enough mass to curve space itself. Light traveling to Earth from distant galaxies becomes slightly distorted as it passes through the curved fabric of spacetime. In some cases, the warping is significant enough that it is apparent to the naked eye, almost as if the galaxy were being viewed through a warped windowpane, an effect called strong gravitational lensing. In the case of the dark matter map shown here, scientists inferred dark matter’s distribution by relying instead on an effect called weak gravitational lensing, which leads to much more subtle distortions of the light from thousands of galaxies.  

The dark matter in this area of sky was also mapped in 2007 using data from NASA’s Hubble Space Telescope. The Webb map contains about 10 times more galaxies than do maps of the area made by ground-based observatories and twice as many as Hubble’s map. It reveals new clumps of dark matter and captures a higher-resolution view compared to the Hubble map. 

Both the Hubble and Webb dark matter maps are part of a project called the Cosmic Evolution Survey (COSMOS). The full COSMOS “field” is 2 square degrees (about 10 times the size of the full Moon) and has been imaged by at least 15 telescopes in space and on the ground. Observing the same region with many different telescopes allows scientists to combine complementary views to understand how galaxies grow and how dark matter influences their evolution. Only Webb and Hubble data have been used to map dark matter in the region.

To refine measurements of the distance to many galaxies for the map, the team used Webb’s Mid-Infrared Instrument (MIRI), designed and managed through launch by the agency’s Jet Propulsion Laboratory, along with other space- and ground-based telescopes. The wavelengths that MIRI detects also make it adept at detecting galaxies obscured by cosmic dust clouds. 

The James Webb Space Telescope is solving mysteries in our solar system, looking beyond to distant worlds around other stars, and probing the mysterious structures and origins of our universe and our place in it. Webb is an international program led by NASA with its partners, ESA (European Space Agency) and CSA (Canadian Space Agency).

Webb’s MIRI was developed through a 50-50 partnership between NASA and ESA. A division of Caltech in Pasadena, California, JPL led the U.S. contribution to MIRI. JPL also led development of MIRI’s cryocooler, done in collaboration with Northrop Grumman in Redondo Beach, California, and NASA’s Goddard Space Flight Center in Greenbelt, Maryland.

To learn more about Webb, visit: https://science.nasa.gov/webb

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AI Unlocks Hundreds of Cosmic Anomalies in Hubble Archive

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AI Unlocks Hundreds of Cosmic Anomalies in Hubble Archive

A team of astronomers has employed a cutting-edge, artificial intelligence-assisted technique to uncover rare astronomical phenomena within archived data from NASA’s Hubble Space Telescope. The team analyzed nearly 100 million image cutouts from the Hubble Legacy Archive, each measuring just a few dozen pixels (7 to 8 arcseconds) on a side. They identified more than 1,300 objects with an odd appearance in just two and a half days — more than 800 of which had never been documented in scientific literature.

Most of the anomalies were galaxies undergoing mergers or interactions, which exhibit unusual morphologies or trailing, elongated streams of stars and gas. Others were gravitational lenses, where the gravity of a foreground galaxy distorts spacetime and bends light from a background galaxy into arcs or rings. Additional discoveries included galaxies with massive star-forming clumps, jellyfish-looking galaxies with gaseous “tentacles,” and edge-on planet-forming disks in our own galaxy resembling hamburgers. Remarkably, several dozen objects defied existing classification schemes entirely.

Identifying such a diverse array of rare objects within the vast and growing repository of Hubble and other telescope data presents a formidable challenge. Never in the history of astronomy has such a volume of observational data been available for analysis.

To address this challenge, researchers David O’Ryan and Pablo Gómez of ESA (the European Space Agency) developed an AI tool capable of inspecting millions of astronomical images in a fraction of the time required by human experts. Their neural network, named AnomalyMatch, was trained to detect rare and unusual objects by recognizing patterns in data — mimicking the way the human brain processes visual information.

“Archival observations from the Hubble Space Telescope now span 35 years, offering a rich dataset in which astrophysical anomalies may be hidden,” said David O’Ryan, lead author of the study published in Astronomy & Astrophysics.

Traditionally, anomalous images are discovered through manual inspection or serendipitous observation. While expert astronomers excel at identifying unusual features, the sheer volume of Hubble data makes comprehensive manual review impractical. Citizen science initiatives have helped expand the scope of data analysis, but even these efforts fall short when faced with archives as extensive as Hubble’s or those from wide-field survey telescopes like Euclid, an ESA mission with NASA contributions.

The work by O’Ryan and Gómez represents a significant advancement. By applying AnomalyMatch to the Hubble Legacy Archive, they conducted the first systematic search for astrophysical anomalies across the entire dataset. After the algorithm flagged likely candidates, the researchers manually reviewed the top-rated sources and confirmed more than 1,300 as true anomalies.

“This is a powerful demonstration of how AI can enhance the scientific return of archival datasets,” Gómez said. “The discovery of so many previously undocumented anomalies in Hubble data underscores the tool’s potential for future surveys.”

Hubble is just one of many astronomical archives poised to benefit from AI-driven analysis. Facilities such as NASA’s upcoming Nancy Grace Roman Space Telescope, a well as ESA’s Euclid and the National Science Foundation and Department of Energy’s Vera C. Rubin Observatory, will generate unprecedented volumes of data. Tools like AnomalyMatch will be essential for navigating this data deluge, enabling astronomers to uncover new and unexpected phenomena — and perhaps even objects never before seen in the universe.

The Hubble Space Telescope has been operating for over three decades and continues to make ground-breaking discoveries that shape our fundamental understanding of the universe. Hubble is a project of international cooperation between NASA and ESA. NASA’s Goddard Space Flight Center in Greenbelt, Maryland, manages the telescope and mission operations. Lockheed Martin Space, based in Denver, also supports mission operations at Goddard. The Space Telescope Science Institute in Baltimore, which is operated by the Association of Universities for Research in Astronomy, conducts Hubble science operations for NASA.

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