Kp Index Simulation Based on Global MHD Modelof Earth's Magnetosphere

We present a comprehensive methodology for Kp index calculation based on the PPMLR(Piecewise Parabolic Method with Linear Reconstruction) global MHD simulation model, which simulates Earth's dynamics in the solar wind-magnetosphere-ionosphere interaction system. The Kp index is a widely used geomagnetic activity indicator crucial for space weather monitoring and forecasting. Accurate understanding and prediction of geomagnetic activity levels are essential for space weather operational services, satellite operations, and power grid management. Global MHD simulations provide a physics-based approach to model ground magnetic disturbances driven by the complex Earth's magnetospheric system under varying solar wind conditions. In this work, we first conduct a comprehensive validation of the PPMLR-MHD model by comparing simulated magnetic disturbances with observational data from SuperMAG ground-based magnetometer stations distributed across both hemispheres. The model successfully reproduces the spatial and temporal variations of geomagnetic disturbances during different geomagnetic activity levels, including quiet periods and storm events. This validation confirms the capability of this global magnetohydrodynamic model to capture the physical processes of the coupled system. Subsequently, we apply a normalization method to the model-generated global ground magnetic disturbances at the standard station locations provided by ISGI (International Service of Geomagnetic Indices). A weighted averaging procedure based on longitudinal distribution is then employed to derive unique global Kp index values for each three-hour interval, following the standard Kp determination methodology. Detailed comparison with observed Kp indices demonstrates that our methodology successfully captures both the trends and magnitudes of Kp variations throughout different phases of geomagnetic activity, indicating significant potential for operational space weather forecasting based on global magnetospheric simulations.