Unprecedented images of the Sun reveal clues to one of its greatest mysteries

Image accompanying: Unprecedented images of the Sun reveal clues to one of its greatest mysteries

New observations of the Sun’s turbulent surface reveal tiny spiral structures that could help explain why its outer atmosphere is millions of degrees hotter than its surface.

image of the Sun's surfaceImage of the Sun’s surface captured by the Inouye Solar Telescope, revealing signs of what scientists call Kelvin-Helmholtz instabilities. Credit: NSF/NSO/Aura/MPS.

Astronomers have captured the most detailed images ever obtained of the Sun’s surface, revealing tiny swirls and golden bands that could provide important clues to one of the oldest mysteries in solar physics: why the Sun’s outer atmosphere, or corona, is much hotter than its visible surface.

The observations were made with the Inouye Solar Telescope in Hawaii, considered the world’s most powerful solar telescope. Researchers identified structures less than 20 kilometers across in a magnetically active region near a sunspot, reaching the instrument’s maximum resolution limit.

According to the scientists involved in the research, the images provide an unprecedented view of the turbulent motions of plasma on the solar surface. The results, published in the journal Nature, could help explain how energy is transferred through the Sun’s atmosphere and ultimately converted into heat.

Swirls may drive energy transfer

Among the most striking structures are tiny spiral-shaped features identified as signs of so-called Kelvin-Helmholtz instabilities. These occur when two layers of fluid or plasma move at different speeds, generating a type of shear that can develop into disturbances and swirling vortices.

Similar instabilities have already been observed in Earth’s oceans, lakes and clouds, as well as in the atmospheres of planets such as Jupiter and Saturn. Their apparent identification

Original Record.

This archived record authored by ‘Dainet Sierra’ at ‘METEORED (Your Weather)’ was recovered from data set:

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