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Global structure of magnetotail reconnection inferred from data mining and implications for its MHD simulations

ORAL

Abstract

Recent advances in reconstructing the Earth's magnetic field and associated currents by utilizing data mining of in situ 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. Unsurprisingly, we are able to form x-lines 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 the Earth ($\gtrsim-15R_E$), a common problem with global simulations of the Earth's magnetosphere. A consequence of reconnection taking place further in 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 near the Earth. Interestingly, as these same 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 extent of these x-lines ($\lesssim5R_E$) and their short lifespan ($\lesssim5$min), they will be difficult to observe by in situ measurements. Future work will explore time dependent resistivity to better match simulations with data mining reconstructions.

Presenters

  • Harry Arnold

    Johns Hopkins University Applied Physics Laboratory

Authors

  • Harry Arnold

    Johns Hopkins University Applied Physics Laboratory

  • Kareem Sorathia

    Johns Hopkins University Applied Physics Laboratory

  • Grant Stephens

    Johns Hopkins University Applied Physics Laboratory

  • Mikhail Sitnov

    Johns Hopkins University Applied Physics Laboratory

  • Viacheslav Merkin

    Johns Hopkins University Applied Physics Laboratory

  • Joachim Birn

    Los Alamos Space Science Institute