Data Mining Inspired Localized Resistivity in Global MHD Simulations of the Magnetosphere

Recent advances in reconstructing Earth’s magnetic field and associated currents by utilizing data mining of in situ magnetometer observations in the magnetosphere have proven remarkably accurate at reproducing observed ion diffusion regions. We investigate the effect of placing regions of localized resistivity in global simulations of the magnetosphere at specific locations inspired by the data mining results for the substorm occurring on July 6, 2017. When explicit resistivity is included, the simulation forms an x-line at the same time and location as the MMS observation of an ion diffusion region at 15:35 UT on that day. Without this explicit resistivity, reconnection forms later in the substorm and far too close to Earth ($\gtrsim-15R_E$), a common problem with global simulations of Earth’s magnetosphere. A consequence of reconnection taking place farther down the tail due to localized resistivity is that the reconnection outflows transport magnetic flux Earthward and thus prevent the current sheet from thinning enough for reconnection to take place nearer Earth. As these flows rebound tailward from the inner magnetosphere, they can temporarily and locally (in the dawn-dusk direction) stretch the magnetic field allowing for small scale x-lines to form in the near Earth region. Due to the narrow cross-tail extent of these x-lines ($\lesssim5R_E$) and their short lifespan ($\lesssim5$min), they would be difficult to observe with in situ measurements. Future work will explore time-dependent resistivity using 5 minute cadence data mining reconstructions.