This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Science seems like a straightforward endeavor. You come up with a hypothesis, collect data to prove or disprove it, and analyze that data to see whether the hypothesis is right.
But anyone who actually does science will tell you that it is often not that straightforward. One of the most common complexities is data analysis. A new paper in Nature suggests that one such complexity, known as regression to the mean, might be causing us to massively underestimate how severe solar storms can be.
The interaction between the solar wind and Earth's magnetosphere can be thought of as a giant dynamo. The combination of solar wind and magnetic field drives high-speed plasma and electric currents into the upper atmosphere, particularly around the polar caps (hence the appearance of auroras). Scientists typically track this dynamo effect using the Polar Cap Index (PCI).
One thing has been clear for decades: For moderate solar activity, there is a clear linear relationship between solar wind electric fields and the electric response measured on Earth. However, for stronger storms, that relationship breaks down as Earth's response seems to "saturate"—that is, cap out at a certain level below what would otherwise be expected. But we never really understood why.
According to the new paper by Dr. Nithin Sivadas and their co-authors at NASA's Goddard Space Flight Center, that saturation might simply be an illusion caused by how we measure the strength of solar storms. They noted that most solar wind measurements come from satellites like WIND, ACE or DSCOVR, all of which are located at the L1 Earth–Sun Lagrange point—which means they are 1.5 million km (930,000 miles) closer to the sun than Earth is.
That distance introduces a great deal of uncertainty. The timing of wind propagation varies, making precise timing difficult. The wind itself can change in the intervening 1.5 million km (930,000 miles), and shock fronts can introduce "heteroskedastic noise"—that is, random errors that grow larger in extreme events.
Extract — continue reading at the source.
