Volcanic layers beneath the moon's surface revealed in radar data

Newly processed radar data from the moon's surface and revealed more details about the volcanic layers beneath it and their age.

Published Thu, Dec 2 2021 7:17 AM CST   |   Updated Thu, Dec 23 2021 2:12 PM CST

Using radar data from China's Chang'e 3 mission in 2013, researchers are learning more about the stratified layers of the lunar surface.

Volcanic layers beneath the moon's surface revealed in radar data 01 | TweakTown.com

Volcanic activity on the moon has deposited lava rock on its surface throughout its history. With time, these rocks break down into dust and soil, called regolith, from space weathering and asteroid impacts. Layers of this material have been buried beneath the lunar surface over time as this cycle repeats.

"Using careful data processing, we found interesting new evidence that this buried layer, called paleoregolith, may be much thicker than previously expected. These layers have been undisturbed since their formation and could be important records for determining early asteroid impact and volcanic history of the moon," said Tieyuan Zhu, assistant professor of geophysics at Penn State.

Researchers identified from the first direct ground radar measurements made by the Chang'e 3 mission a layer of paleoregolith roughly 16 to 30 feet (4.8 to 9.1 meters) thick, between two layers of lava rock thought to be 2.3 and 3.6 billion years old. Scientists say this suggests that the paleoregolith formed significantly faster than the previous estimate of 6.5 feet (1.8 meters) per billion years.

"Lunar scientists count craters on the moon and use computer models to determine the rate that regolith is produced. Our findings provide a constraint on what happened between two and three billion years ago. This is the very unique contribution of this work," Zhu said.

The team used changes in polarity of the electromagnetic pulses as they traveled down through the lava rock and the paleoregolith to distinguish between the layers, gleaning new insight from the older data. The team is working on machine learning technology that may help process this data and similar in the future.

You can read more from their study published in Geophysical Research Letters here.

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NEWS SOURCES:doi.org, phys.org

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