We analyze three substorms that occur on (1) 9 March 2008 05:14 UT, (2) 26 February 2008 04:05 UT, and (3) 26 February 2008 04:55 UT. Using ACE solar wind velocity and interplanetary magnetic field
The auroral substorm has been extensively studied over the last six decades. However, our understanding of its driving mechanisms is still limited and so is our ability to accurately forecast its onset. In this study, we present the first deep learning‐based approach to predict the onset of a magnetic substorm, defined as the signature of the auroral electrojets in ground magnetometer measurements. Specifically, we use a time history of solar wind speed (
- NSF-PAR ID:
- 10456287
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Space Weather
- Volume:
- 17
- Issue:
- 11
- ISSN:
- 1542-7390
- Page Range / eLocation ID:
- p. 1534-1552
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract B z values, we calculate the rectified (southwardB z ) solar wind voltage propagated to the magnetosphere. The solar wind conditions for the two events were vastly different, 300 kV for 9 March 2008 substorm, compared to 50 kV for 26 February 2008. The voltage is input to a nonlinear physics‐based model of the magnetosphere called WINDMI. The output is the westward auroral electrojet current which is proportional to the auroral electrojet (AL) index from World Data Center for Geomagnetism Kyoto and the SuperMAG auroral electrojet index (SML). Substorm onset times are obtained from the superMAG substorm database, Pu et al. (2010,https://doi.org/10.1029/2009JA014217 ), Lui (2011,https://doi.org/10.1029/2010JA016078 ) and synchronized to Time History of Events and Macroscale Interactions during Substorms satellite data. The timing of onset, model parameters, and intermediate state space variables are analyzed. The model onsets occurred about 5 to 10 min earlier than the reported onsets. Onsets occurred when the geotail current in the WINDMI model reached a critical threshold of 6.2 MA for the 9 March 2008 event, while, in contrast, a critical threshold of 2.1 MA was obtained for the two 26 February 2008 events. The model estimates 1.99 PJ of total energy transfer during the 9 March 2008 event, with 0.95 PJ deposited in the ionosphere. The smaller events on 26 February 2008 resulted in a total energy transfer of 0.37 PJ according to the model, with 0.095 PJ deposited in the ionosphere. -
more » « less
Abstract We model lower band chorus observations from the DEMETER satellite using daily and hourly autoregressive‐moving average transfer function (ARMAX) equations. ARMAX models can account for serial autocorrelation between observations that are measured close together in time and can be used to predict a response variable based on its past behavior without the need for recent data. Unstable distributions of radiation belt source electrons (tens of keV) and the substorm activity (SMEd from the SuperMAG array) that is thought to inject these electrons were both statistically significant explanatory variables in a daily ARMAX model describing chorus. Predictions from this model correlated well with observations in a hold‐out test data set (validation correlation of 0.675). Source electron flux was most influential when observations came from the same day or the day before the chorus measurement, with effects decaying rapidly over time. Substorms were more influential when they occurred on previous days, presumably due to their injecting source electrons from the plasma sheet. A daily ARMAX model with interplanetary magnetic field (IMF)|
B |, IMFB z , and solar wind pressure as inputs instead of those given above was somewhat less predictive of chorus (r =0.611). An hourly ARMAX model with only solar wind and IMF inputs was even less successful, with a validation correlation of 0.502. -
more » « less
Abstract In this paper, we present a case study of the radial interplanetary magnetic field (IMF
B x )‐induced asymmetric solar wind‐magnetosphere‐ionosphere (SW‐M‐I) coupling between the northern and southern polar caps using ground‐based and satellite‐based data. Under prolonged conditions of strong earthward IMF on 5 March 2015, we find significant discrepancies between polar cap north (PCN) and polar cap south (PCS) magnetic indices with a negative bay‐like change in the PCN and a positive bay‐like change in the PCS. The difference between these indices (PCN‐PCS) reaches a minimum of −1.63 mV/m, which is approximately three times higher in absolute value than the values for most of the time on this day (within ±0.5 mV/m). The high‐latitude plasma convection also shows an asymmetric feature such that there exists an additional convection cell near the noon sector in the northern polar cap, but not in the southern polar cap. Meanwhile, negative bays in the north‐south component of ground magnetic field perturbations (less than 50 nT) observed in the nightside auroral region of the Northern Hemisphere are accompanied with the brightening and widening of the nightside auroral oval in the Southern Hemisphere, implying a weak, but clear energy transfer to the nightside ionosphere of both hemispheres. After the hemispheric asymmetries in the polar caps disappear, a substorm onset takes place. All these observations indicate that IMFB x ‐induced single lobe reconnection that occurred in the Northern Hemisphere plays an important role in hemispheric asymmetry in the energy transfer from the solar wind to the polar cap through the magnetosphere. -
more » « less
Abstract The coupling function monitors solar wind driving of geomagnetic activity. Magnetic indices, including the polar cap (PC) index, the auroral lower (AL) index, and the midlatitude positive bay index (MPB), provide measures of the magnetospheric response. Sharp changes in these are associated with the onset of a substorm and a maximum in coupling. Many reinterpret this association as evidence that northward turnings of the interplanetary magnetic field (IMF) trigger onset. We investigate this hypothesis using a list of over 100,000 negative bay onsets. When data are available, we calculate coupling and its time derivatives. From these, we construct ensembles of data segments centered on the onsets.`For all lists, a pulse occurs 20 min before onset and appears to trigger onset. By correlating the average derivative with every event in the ensemble, we conclude that a pulse of either sign precedes 40% of all onsets. More than half of the triggered onsets display a positive pulse, and slightly fewer show a negative pulse. Substorms following a positive pulse are stronger than those after a negative pulse. The pulse is usually hidden by noise, but ensemble averaging and correlation analysis can detect the pulse in the coupling data.
-
more » « less
Abstract Substorm‐type evolution of the Earth's magnetosphere is investigated by mining more than two decades (1995–2017) of spaceborne magnetometer data from multiple missions including the first two years (2016‐2017) of the Magnetospheric MultiScale mission. This investigation reveals interesting features of plasma evolution distinct from ideal magnetohydrodynamics (MHD) behavior: X‐lines, thin current sheets, and regions with the tailward gradient of the equatorial magnetic field
B z . X‐lines are found to form mainly beyond 20R E , but for strong driving, with the solar wind electric field exceeding ∼5mV/m, they may come closer. For substorms with weaker driving, X‐lines may be preceded by redistribution of the magnetic flux in the tailwardB z gradient regions, similar to the magnetic flux release instability discovered earlier in PIC and MHD simulations as a precursor mechanism of the reconnection onset. Current sheets in the growth phase may be as thin as 0.2R E , comparable to the thermal ions gyroradius, and at the same time, as long as 15R E . Such an aspect ratio is inconsistent with the isotropic force balance for observed magnetic field configurations. These findings can help resolve kinetic mechanisms of substorm dipolarizations and adjust kinetic generalizations of global MHD models of the magnetosphere. They can also guide and complement microscale analysis of nonideal effects.
