New solar model maps sun more accurately by checking far-side activity

A Southwest Research Institute (SwRI)-led team has developed an improved model for predicting solar events that incorporates activity on the far side of the sun. The team studied near-simultaneous maps of the whole solar surface from 2010 to 2014, combining Earth observations with data from space-based assets showing the opposite side. The resulting framework constructs surface flux transport (SFT) models that are more complete and accurate than any previous model.

Scientists use SFT models to monitor and forecast the activity of the sun, which in turn helps them to predict space weather that can impact the Earth. The study “A Probabilistic Framework for Incorporating Helioseismic Far-Side Active Regions into SFT Models” was published this month in The Astrophysical Journal Supplement Series.

“We modeled the surface of the sun to see how the magnetic field is behaving, which helps us understand how the activity of the sun varies over solar cycles,” said Dr. Bibhuti Jha, a research scientist in SwRI’s Solar System Science and Exploration Division located in Boulder, Colorado. He is the lead author of the paper that discusses the new model. “If we can plot out the next solar cycle, we will have a better idea of how the sun is going to behave in coming years.”

The challenge of the hidden hemisphere

The far side of the sun is the hemisphere facing away from Earth at any given time. Unlike the moon, which has one side permanently facing the Earth, the sun rotates entirely on its axis around every 27 days. This means every part of the sun eventually rotates into view from Earth. However, at any given time, half of the sun is hidden from direct view.

The lack of simultaneous data from the far side of the sun has hampered earlier SFT models. In some cases, as the sun rotated, a sunspot would emerge unexpectedly from the far side, forcing quick recalculations. In the 1970s, scientists began using acoustic waves to understand internal and far-side solar activity in the same way that geologists use acoustic waves to study what is happening deep beneath the Earth’s crust.

This new field of helioseismology led to vast improvements in space weather forecasting, but even those models were sometimes hampered by bad information.

“Acoustic data can sometimes indicate an active region on the far side, but when the area comes into view, we don’t see anything. It’s almost like a false positive. We call these ghost active regions,” Jha said.

Filtering out ghost active regions

The new model developed by the SwRI team helps weed out these ghost active regions, providing a more accurate map of the entire surface of the sun at any given time.

“Before we add this far-side helioseismology data into our model, we systematically evaluate the accuracy of active regions,” said Dr. Lisa Upton, a SwRI lead scientist also in the Boulder office who co-authored the paper. “We are associating a probability with each of these active regions on the far side based on their properties.”

This probabilistic model for detecting active regions on the far side of the sun provides a practical pathway for incorporating helioseismic data into SFT models.

“This is a step toward a more realistic modeling of the magnetic field of both visible and invisible hemispheres of the sun,” Jha said.

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