A new study from the Hebrew University of Jerusalem challenges a long-held assumption in climate science by showing that aerosols—tiny particles suspended in the atmosphere—can either warm or cool the climate, depending on the time scale considered.
Led by Prof. Guy Dagan of the Fredy and Nadine Herrmann Institute of Earth Sciences, the research reveals that aerosol-cloud interactions can produce opposite climate effects in the short and long term. The findings, published in Nature Communications, offer a new explanation for why aerosols remain one of the largest sources of uncertainty in climate projections.
Aerosols come from a variety of natural and human-made sources, including air pollution, wildfires, sea spray and dust. Scientists have long known that these particles influence how clouds form and how much heat Earth retains, but accurately estimating their overall impact on climate has proved difficult.
Freshwater from melting Antarctic glaciers may be influencing the Southern Ocean in ways scientists have largely overlooked. New research, published in Frontiers in Marine Science, has found that glacial meltwater is not confined to the ocean’s surface, as previously assumed, but can also be detected much deeper in coastal waters along the Western Antarctic Peninsula.
The findings suggest that meltwater from glaciers is being transported and stored tens of meters below the surface, where it could alter ocean circulation, affect the movement of heat and nutrients, and influence how the region responds to climate change.
A circle running along the 27° east and 153° west meridians divides the globe into two halves with equal reflectivity – and this may have implications for solar geoengineering schemes
Storm Dave, which swept across northern Europe over the Easter weekend, is an example of what new research from the University of Gothenburg has revealed. Spring storms forming over the North Atlantic have become more common than they were 80 years ago, and this is due to climate change.
In the Northern Hemisphere, storm seasons follow a seasonal cycle. Storms are weakest and least frequent in summer and most intense in winter. As a result of global warming, storm patterns and their course have changed, and several studies have indicated that winter storms appear to be occurring more frequently and with even greater intensity.
New research from a team of scientists led by Cornell is transforming how researchers understand one of the atmosphere’s most abundant and least understood constituents: mineral dust.
Mineral dust, composed of tiny particles lifted from arid regions including the Sahara, Middle East and East Asia, plays a complex role in Earth’s climate system. These particles both scatter and absorb radiation, influence cloud formation and even fertilize ecosystems. But until recently, scientists lacked reliable global data on the surface soils’ mineral composition, particularly on the prevalence of light-absorbing iron oxides.
Using high-resolution data from a NASA mission aboard the International Space Station, the team has reduced long-standing uncertainty about how airborne dust particles affect Earth’s energy balance through interactions with sunlight. The findings are published in the journal Nature Geoscience.
Antimatter propulsion could be the fastest engine ever built. We explore how antimatter rockets work, their extreme energy density, and whether they could power humanity’s first true interstellar spacecraft.
Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthur. Watch my exclusive video Surviving a New Ice Age: https://nebula.tv/videos/isaacarthur–… SFIA Merchandise: https://isaac-arthur-shop.fourthwall… 🌐 Visit our Website: http://www.isaacarthur.net ❤️ Support us on Patreon: / isaacarthur ⭐ Support us on Subscribestar: https://www.subscribestar.com/isaac-a… 👥 Facebook Group: / 1,583,992,725,237,264 📣 Reddit Community: / isaacarthur 🐦 Follow on Twitter / X: / isaac_a_arthur 💬 SFIA Discord Server: / discord Credits: Antimatter Propulsion — Extended Edition Written, Produced & Narrated by: Isaac Arthur Edited by: Thomas Owens & Merv Johnson II Graphics: Jeremy Jozwik, Ken York YD Visual, Sergio Botero Select imagery/video supplied by Getty Images Music Courtesy of Epidemic Sound http://epidemicsound.com/creator Markus Junnikkala, “A Fleet Behind the Moon” Phase Shift, “Forest Night” Kai Engel, “Endless Story About Sun and Moon” Chris Zabriskie, “Unfoldment, Revealment”, “A New Day in a New Sector” Taras Harkavyi, “Alpha and…” Stellardrone, “Red Giant”, “Billions and Billions”
🛒 SFIA Merchandise: https://isaac-arthur-shop.fourthwall… 🌐 Visit our Website: http://www.isaacarthur.net. ❤️ Support us on Patreon: / isaacarthur. ⭐ Support us on Subscribestar: https://www.subscribestar.com/isaac-a… 👥 Facebook Group: / 1583992725237264 📣 Reddit Community: / isaacarthur. 🐦 Follow on Twitter / X: / isaac_a_arthur. 💬 SFIA Discord Server: / discord. Credits: Antimatter Propulsion — Extended Edition. Written, Produced & Narrated by: Isaac Arthur. Edited by: Thomas Owens & Merv Johnson II Graphics: Jeremy Jozwik, Ken York YD Visual, Sergio Botero. Select imagery/video supplied by Getty Images. Music Courtesy of Epidemic Sound http://epidemicsound.com/creator. Markus Junnikkala, \
Whether the dust borne on the violent winds of a tornado or the sugar grains in a swirled cup of coffee, the behavior of particles carried along in turbulence is subject to some similarities—all of them difficult to predict at scale. As described in a recent publication in the Proceedings of the National Academy of Sciences, a research team led by Los Alamos National Laboratory scientists has developed a first-of-its-kind machine learning framework that models chaotic particle motions in a turbulent flow.
“Modeling turbulence is a big, open problem, and it’s probably the hardest problem in classical physics,” said Daniel Livescu, Los Alamos scientist and one of the leaders of the work. “A subset of that challenge is modeling particle motions within turbulence. To meet that challenge, our artificial intelligence approach offers an innovative theoretical construct tested with a real-world application.”
The team has developed and applied the first data-driven, auto-regressive machine learning framework to capture the dynamics of turbulence at scale. The research demonstrates that machine learning can overcome longstanding barriers in modeling chaotic particle motions.
Natural geological processes have been regulating Earth’s climate for millions of years. Accelerated versions of these processes are now being promoted as technologies to draw down carbon from the atmosphere—and some are rapidly moving from concept to real-world deployments.
Two such technologies are known as enhanced weathering, which speeds up the chemical breakdown of certain rocks, and ocean alkalinity enhancement, which increases the ocean’s natural ability to remove carbon dioxide from the air.
On May 21, ground controllers powered down NASA’s AWE (Atmospheric Waves Experiment) instrument, bringing the data collection phase of the mission to a successful and scheduled end, surpassing its planned two-year mission.
Installed on the exterior of the International Space Station since November 2023, AWE studied atmospheric gravity waves, which are giant ripples in the atmosphere caused by strong winds flowing over tall mountains or by violent weather events, such as tornadoes, thunderstorms, and hurricanes.
The AWE instrument looked for these waves in colorful bands of light in Earth’s atmosphere, called airglow. AWE investigated how atmospheric gravity waves propagate upward to space and contribute to space weather—conditions in space that can disrupt satellites, as well as navigation and communications signals.
