Data-driven magnetohydrodynamic models are computational frameworks that utilize real observational data to simulate and predict the behavior of plasma in astrophysical contexts, particularly in the solar and heliospheric environment. These models integrate empirical measurements from spacecraft and ground-based observations to enhance the accuracy of simulations regarding solar phenomena such as solar flares, coronal mass ejections, and solar wind dynamics. By using data from various sources, these models can better represent the complexities of magnetic fields and fluid dynamics in space plasmas.
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