Preprints
https://doi.org/10.5194/egusphere-2024-2956
https://doi.org/10.5194/egusphere-2024-2956
08 Oct 2024
 | 08 Oct 2024
Status: this preprint is open for discussion.

Investigation of the occurrence of significant deviations in the magnetopause location: Solar wind and foreshock effects

Niklas Grimmich, Adrian Pöppelwerth, Martin Owain Archer, David Gary Sibeck, Ferdinand Plaschke, Wenli Mo, Vicki Toy-Edens, Drew Lawson Turner, Hyangpyo Kim, and Rumi Nakamura

Abstract. The dynamic motion of the magnetopause, the boundary between the Earth's magnetic field and the interplanetary magnetic field, is mainly driven by pressure variations and changes in the interplanetary magnetic field. Common magnetopause models can predict the location of the magnetopause in response to upstream conditions from different sets of input parameters, including pressure and the interplanetary magnetic field. However, recent studies have shown that some effects of upstream conditions may still be poorly understood, as deviations between model and in situ observations beyond the expected scatter due to constant magnetopause motion are quite common. Using data from the three most recent multi-spacecraft missions to near Earth space (Cluster, THEMIS and MMS), we investigate the occurrence of these large deviations in observed magnetopause crossings from common empirical models. By comparing the results from different models, we find that the occurrence of these events appears to be model independent, suggesting that some physical processes may be missing from the models. To find these processes, we test whether the deviant magnetopause crossings are statistically associated with foreshocks and/or different solar wind types and show that in at least 50 % of cases the foreshock can be responsible for the large deviations in the magnetopause's location. In the case where the foreshock is unlikely to be responsible, two distinct classes of solar wind are found to occur most frequently in association with the occurrence of magnetopause deviations: the "fast" solar wind and the solar wind plasma associated with transients such as interplanetary coronal mass ejections. Therefore, the plasma conditions associated with these solar wind classes could be responsible for the occurrence of deviant magnetopause observations. Our results may help to develop new and more accurate models of the magnetopause, which will be needed, for example, to accurately interpret the results of the upcoming SMILE mission.

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Niklas Grimmich, Adrian Pöppelwerth, Martin Owain Archer, David Gary Sibeck, Ferdinand Plaschke, Wenli Mo, Vicki Toy-Edens, Drew Lawson Turner, Hyangpyo Kim, and Rumi Nakamura

Status: open (until 19 Nov 2024)

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Niklas Grimmich, Adrian Pöppelwerth, Martin Owain Archer, David Gary Sibeck, Ferdinand Plaschke, Wenli Mo, Vicki Toy-Edens, Drew Lawson Turner, Hyangpyo Kim, and Rumi Nakamura

Data sets

Database: Cluster Magnetopause Crossings between 2001 and 2020 Niklas Grimmich et al. https://doi.org/10.17605/OSF.IO/PXCTG

Database: THEMIS magnetopause crossings between 2007 and mid-2022 Niklas Grimmich et al. https://doi.org/10.17605/OSF.IO/B6KUX

8 years of dayside magnetospheric multiscale (MMS) unsupervised clustering plasma regions classifications Vicki Toy-Edens et al. https://doi.org/10.5281/zenodo.10491877

OMNI dataset J. King and N. Papitashvili https://spdf.gsfc.nasa.gov/pub/data/omni/omni_cdaweb/

Niklas Grimmich, Adrian Pöppelwerth, Martin Owain Archer, David Gary Sibeck, Ferdinand Plaschke, Wenli Mo, Vicki Toy-Edens, Drew Lawson Turner, Hyangpyo Kim, and Rumi Nakamura

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Short summary
The boundary of Earth's magnetic field, the magnetopause, deflects and reacts to the solar wind - the energetic particles emanating from the Sun. We find that certain types of solar wind favour the occurrence of deviations between the magnetopause locations observed by spacecraft and those predicted by models. In addition, the turbulent region in front of the magnetopause, the foreshock, has a large influence on the location of the magnetopause and thus on the accuracy of the model predictions.