This innovative study, led by Ph.D. candidate JiaWen Yue (National Space Science Center, Chinese Academy of Sciences) and Dr. XiaoCheng Guo (National Space Science Center, Chinese Academy of Sciences), introduces a novel semi-empirical approach to simulating the Dst index—a critical metric for measuring the geomagnetic intensity of magnetic storms. By integrating empirical methods with physics-based global magnetohydrodynamic (MHD) models of Earth’s magnetosphere, the team has developed a model that outperforms traditional empirical approaches in accuracy while retaining computational efficiency.
The Dst index, widely used for decades to quantify the strength of geomagnetic storms, is influenced by complex interactions between the solar wind and Earth’s magnetosphere. Traditional empirical models, such as Burton’s, rely on statistical correlations but lack the ability to capture dynamic physical processes. Physics-based models typically require a significant amount of computational resources and pose challenges in describing ring currents. The new semi-empirical model bridges this gap by combining the strengths of both methodologies.
In this approach, the ring current contribution to the Dst index is derived from Burton’s empirical framework, while contributions from other current systems—such as the magnetotail current—are calculated using high-resolution global MHD simulations. This hybrid strategy allows the model to retain the speed of empirical methods while incorporating the physical realism of MHD simulations.
To validate the model, the team tested it against a series of recent geomagnetic storm events, comparing simulated results with observed Dst data using metrics such as correlation coefficient (CC), prediction efficiency (PE), root mean square error (RMSE), and central RMSE (CRMSE). The findings were striking: during moderate to intense geomagnetic storms, the semi-empirical model achieved significantly higher CC and PE values and lower RMSE and CRMSE compared to purely empirical models. These results demonstrate the model’s robustness in capturing both the timing and magnitude of Dst variations.
“This model provides more possibilities for space weather forecasting,” said Ph.D. candidate JiaWen Yue. “By merging empirical simplicity with MHD physics, we’ve created a tool that is both accurate and practical for space environment applications.”
Dr. XiaoCheng Guo emphasized the broader implications of the work: “The ability to simulate the Dst index within a global MHD framework opens new avenues for understanding storm-time magnetospheric dynamics. As space weather becomes an increasingly critical area of study, this semi-empirical approach offers a scalable solution for improving the accuracy and reliability of geomagnetic storm predictions.”
The study also highlights the model’s adaptability. Its modular design allows for seamless integration into existing global MHD simulation frameworks, making it a versatile tool for researchers and operational forecasters.
See the article:
A semi-empirical approach to simulating the Dst index in global MHD models of Earth’s magnetosphere
https://doi.org/10.26464/epp2025072
Earth and Planetary Physics
1-Jul-2025