Speaker
Description
Modeling extreme storm response on the ground, for the purpose of preparing for a worst-case scenario, sometimes takes the form of scaling up observed ground response from historical storms. This approach assumes that a simple scaling of the ground response can capture the complexities and non-linearities inherent in the solar wind-magnetosphere interaction. As part of the Solar Tsunamis project, which brings together both space and ground researchers, we test the level of utility of this assumption using the Space Weather Modeling Framework (SWMF) and the solar wind observations from the Gannon storm of May 2024. We scale the solar wind drivers by factors of 1.5, 2, and 3 and run the SWMF with each set of scaled drivers. We then compare the ground magnetometer predictions from running the model with the original solar wind and scale those predictions by the same set of factors. From this set of comparisons we present two primary findings. First, we demonstrate that scaling the solar wind drivers and scaling the ground predictions produce significantly different results. Second, we find that low latitude magnetic indexes such as Dst and SMR, which have long been used to measure storm intensity, exhibit an unusual behavior akin to saturation for the 2x and 3x simulation runs, indicating that for a truly "extreme" storm the magnetosphere enters a state not hitherto observed. This result calls for careful consideration of how we use magnetic indexes to describe storms and demonstrates that our understanding of a worst-case scenario may be severely limited by kind of storms experienced by humanity so far.
