Public Release: 

Researcher gets $1.2 million to develop system to predict solar cycles

Georgia State University

ATLANTA--Dr. Petrus Martens, a professor in the Department of Physics and Astronomy at Georgia State University, has received a three-year, $1.2 million NASA Grand Challenge grant to develop a system to predict solar cycles and determine the long-term frequency of events such as solar flares, potentially more than a decade in advance.

Martens is collaborating with an international team of researchers from India, England, Scotland and France, as well as NASA's Ames Research Center in California's Silicon Valley and the National Solar Observatory in Tucson, Ariz.

"We think we can forecast the cycle about 11 years ahead, so one cycle," Martens said. "We will use the latest data both from ground-based observatories and spacecraft because they set the conditions for the future. We will look at previous cycles for which we have data already, feed our programs with that and see what results come out. If we can do a couple of previous cycles correctly, we think we can confidently predict the future."

The researchers are developing a computer program that can simulate data and perform data analysis. They are using existing data from the National Solar Observatory, the Solar Dynamics Observatory and the Global Oscillation Network Group.

This research area is significant because of the solar cycle's potential economic impact on the United States. According to a 2008 National Academy of Sciences' report on the societal and economic impacts of severe space weather events, the economic costs of a "severe geomagnetic storm scenario" knocking out the power grid of the United States could be an estimated $1 to $2 trillion during the first year alone, with a recovery time of four to 10 years.

The sun goes through an 11-year cycle called the solar cycle, which has periods of increasing and decreasing magnetic activity. Sunspots, or regions on the solar surface that appear dark because they are cooler than surrounding areas, occur most frequently during the peak of the cycle and result in increased magnetic activity, solar flares and coronal mass ejections, which can be hazardous to Earth.

A solar flare is a large explosion on the surface of the sun that heats material to many millions of degrees and releases huge amounts of energy in the forms of electromagnetic radiation (Gamma rays and X-rays) and energetic particles (protons and electrons), according to NASA. Solar flares can pose health hazards to astronauts and people onboard flights near the North and South poles because of exposure to radiation. They can also disrupt radio communications, the Global Positioning System and satellites.

Coronal mass ejections, which are often associated with solar flares, are huge bubbles of magnetic field and ionized gas that are ejected from the sun. They disrupt the flow of solar wind and produce disturbances that affect the Earth. They can knock out power grids and even lead to corrosion in oil pipelines, according to NASA.

Being able to predict solar cycles years ahead of time could allow governments and businesses to take preemptive measures to protect the power grid and give airlines adequate time to reroute flights near the poles. Because extended, low-solar activity during the minimum of a cycle decreases the life span of satellites, these predictions could inform the military and NASA whether they need to replace satellites sooner.

This project on the long-term prediction of solar activity is complementary to a second research effort by Martens and his close collaborator Dr. Rafal Angryk of the Computer Science Department at Georgia State. Last month, Angryk and Martens received a $1.5 million research grant from the National Science Foundation to develop tools to aid in the short-term (hours and days) prediction of individual solar flares and coronal mass ejections. For more information, visit


For additional information, please visit:

Solar Dynamics Observatory:

Global Oscillation Network Group:

National Solar Observatory:

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