Based on new data from an interactive tool that exploits data from the European Space Agency’s Gaia mission and other space science data sets, astronomers have created an animation to model dust in the Milky Way. The work was presented this week at the National Astronomy Meeting (NAM 2022) at the University of Warwick.

The animation shows the cumulative build-up of dust looking from Earth’s local neighbourhood to ~13000 lightyears towards the galactic centre — around 10% of the overall distance across the Milky Way. Close by, dust swirls all around but, further out, the concentration of dust along the galactic plane becomes clear. Two ‘windows’, one above and one below the galactic plane, are also revealed.

“Dust clouds are related to the formation and death of stars, so their distribution tells a story of how structures formed in the galaxy and how the galaxy evolves,” said Nick Cox, coordinator of the EXPLORE project which is developing the tools. “The maps are also important for cosmologists in revealing regions where there is no dust and we can have a clear, unobstructed view out of the Milky Way to study the Universe beyond, such as to make Deep Field observations with Hubble or the new James Webb Space Telescope.”

The tools used to create the animation combine data from the Gaia mission and the 2MASS All Sky Survey. The tools are part of a suite of applications designed to support studies of stars and galaxies, as well as lunar exploration, and have been developed through funding from the European Union’s Horizon 2020 Programme.

“State-of-the-art machine learning and visual analytics have the power to greatly enhance scientific return and discovery for space science missions, but their use is still relatively novel in the field of astronomy,” said Albert Zijlstra, of the University of Manchester and the EXPLORE project. “With a constant stream of new data, such as the recent third release of Gaia data in June 2022, we have an increasing wealth of information to mine — beyond the scope of what humans could process in a lifetime. We need tools like the ones we are developing for EXPLORE to support scientific discovery, such as by helping us to characterise properties within the data, or to pick out the most interesting or unusual features and structures.”

Video: https://youtu.be/K2hwjD5D7L0

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Shortly after sunset, pockets of super-heated gas called ‘plasma bubbles’ form in the upper atmosphere and stretch into space (up to 900km above the Earth’s surface). These bubbles start small and grow rapidly — from the size of a football pitch to that of a small country in just a couple of hours. As the bubbles grow bigger, they can prevent satellites from communicating with the Earth by blocking and warping their radio signals.

To predict plasma bubbles, a team of researchers has collated 8 years of data from the SWARM satellite mission. The spacecraft has an automatic bubble detector on-board called the Ionospheric Bubble Index. This compares changes in the density of electrons and the magnetic field strength to check if bubbles are present: a strong correlation between the two indicates the presence of a plasma bubble.

The satellite flies at an altitude of 460km (about 30x higher than a commercial plane) through the middle of most plasma bubbles. The model combines the data collection from SWARM with a machine learning approach to make predictions on the likelihood of a plasma bubble event occurring at any time.

The results show that the number of plasma bubble events varies from season to season, just like the weather, and that the number of events increases with solar activity. Despite this, the model finds location to be a far more crucial element in predicting plasma bubbles than the time of year, with most events occurring over a region in the Atlantic called the South Atlantic Anomaly. The AI model predicts events with an accuracy of 91% across different tests.

Reddy says: “Just like the weather forecast on earth, we need to be able to forecast bubbles to prevent major disruptions to satellite services. Our aim is to be able to say something like: “At 8pm tomorrow there is a 30% chance of a bubble appearing over the Horn of Africa.” This kind of information is extremely useful for spacecraft operators and for people who depend on satellite data every day, just like you and me.”

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“The forests are not keeping up with these large fires,” said study co-author James Randerson, the Ralph J. and Carol M. Cicerone Professor of Earth system science at UCI. Across the entire state, tree cover area has declined 6.7 percent since 1985. “These are big changes in less than four decades,” he said.

It’s the first time that researchers have been able to measure tree population declines in California, and attribute the changes to such pressures as wildfires, drought stress and logging.

For the study, the UCI-led team used satellite data from the USGS and NASA’s Landsat mission to study vegetation changes between 1985 and 2021. They found that one of the starkest declines in tree cover was in Southern California, where 14 percent of the tree population in local mountain ranges vanished, potentially permanently.

“The ability of forests to recover from fire appears to be dwindling in the south,” said Jonathan Wang, a postdoctoral researcher in Randerson’s research group, who led the study published in AGU Advances. “At the same time, the state’s coverage of shrubs and grasses is rising, which could foreshadow more permanent ecosystem shifts.”

The rate and scale of decline varies across the state. Tree cover in the Sierra Nevada, for instance, stayed relatively stable until around 2010, then began dropping precipitously. The 8.8 percent die-off in the Sierra coincided with a severe drought from 2012 to 2015, followed by some of the worst wildfires in the state’s history, including the Creek Fire in 2020.

Fortunately “in the north, there’s plenty of recovery after fire,” said Wang, perhaps because of the region’s higher rainfall and cooler temperatures. But even there, high fire years in 2018, 2020 and 2021 have taken a visible toll.

The tree decline has also affected carbon storage abilities in the state, said Randerson, who added that the next step is to precisely quantify the impact on forests’ ability to absorb anthropogenic carbon dioxide. Co-author Michael Goulden, a UCI professor of Earth system science and director of the Center for Ecosystem Climate Solutions, is using the data to understand how changes in forest cover are affecting water resources, carbon storage and fire behavior across the state.

“This threat to California’s climate solutions isn’t going away anytime soon,” Wang said. “We might be entering a new age of intense fire and vulnerable forests.”

Collaborators include Clarke Knight and John Battles from UC Berkeley. The research was supported by California’s Strategic Growth Council and the UC National Laboratories grant program, along with long-term funding from NASA and the U.S. Department of Energy’s Office of Science.

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