Predicting the SYM‐H Index Using the Ring Current Energy Balance Mechanism.
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| Titel: | Predicting the SYM‐H Index Using the Ring Current Energy Balance Mechanism. |
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| Autoren: | Ma, Lan, Ji, Yong, Shen, Chao, Zeng, Gang, E, Peng, Yang, YanYan, Ti, Shuo, Ahmad, Nisar |
| Quelle: | Space Weather: The International Journal of Research & Applications; Mar2025, Vol. 23 Issue 3, p1-19, 19p |
| Schlagwörter: | STANDARD deviations, SPACE environment, GEOMAGNETISM, ARTIFICIAL neural networks, MAGNETIC storms, SOLAR wind |
| Abstract: | The geomagnetic disturbance index SYM‐H is primarily determined by the total kinetic energy of ring current particles. Therefore, the energy balance mechanism of the ring current can be used to construct an SYM‐H evolution equation for prediction purposes. This study extends a modeling concept developed by Ji et al. (2023), https://doi.org/10.1029/2022ea002560 to establish an algebraic equation for predicting the SYM‐H index based on equilibrium between energy injection and ring current loss. The loss term in the model is determined by a fully connected neural network. The fundamental form of the energy injection function is derived from existing solar wind–magnetosphere energy coupling functions, with its scale factor adjusted as a free‐fitting parameter to optimize the prediction of observations. After being trained on solar wind and SYM‐H observations from 20 magnetic storms, the new model predicts the SYM‐H index well 1 hr and 2 hr in advance, with root mean square errors of 6.7 and 8.9 nT, respectively. These accuracies represent a 7% $\%$ (1‐hr model) and a 6% $\%$ (2‐hr model) improvement over the previous model. Furthermore, the scale factors for the solar wind parameters in the energy coupling function determined by the new model can be explained by the previous observations in the magnetic tail current sheet, confirming that the ring current energy primarily originates from the current sheet. The lifetime of the ring current particles, as determined by the neural network, varies with the SYM‐H index. It is approximately 6 hr for the fast recovery phase and more than 10 hr for the slow recovery phase, consistent with the dominant ring current particles changing from oxygen ions to protons during intense storms. Plain Language Summary: The energy and matter carried by the solar wind can enter the Earth's magnetosphere and induce disturbances of magnetic field near the earth. The SYM‐H index is constructed to quantify the intensity of these disturbances which is positively correlated with space weather disaster events. Therefore, predicting the SYM‐H index is of significance for space mission. This study further optimizes the algorithm for predicting the SYM‐H index based on the total kinetic energy balance mechanism of ring current and proposes a new model. The new model constructs the energy injection function of the ring current based on an empirical solar wind‐magnetosphere energy coupling function. Neural networks are used to characterize the loss process of the ring current, successfully distinguishing the fast and slow recovery phases and identifying ring current particle lifetimes, which are consistent with observations. The prediction accuracy of SYM‐H is also comparable to other neural network models, making it applicable for space weather operations and useful for studying the physical mechanisms of solar wind‐magnetosphere energy transport. Key Points: The balance mechanism of ring current particles' kinetic energy is used to construct algorithm predicting SYM‐HThe formula of energy coupling function for ring current is determinedThe lifetime of ring current particles during quiet and storm period is identified based on neural network [ABSTRACT FROM AUTHOR] |
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| Datenbank: | Complementary Index |
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