Driving Dynamical Inner‐Heliosphere Models With In Situ Solar Wind Observations

Abstract Accurately reconstructing the solar wind throughout the inner heliosphere is essential for understanding solar–terrestrial interactions and improving space‐weather forecasts. Conventional reconstruction methods rely on photospheric magnetic field observations and coronal models to estimate solar wind conditions near the Sun, typically at 0.1 AU. This introduces substantial uncertainty in the background flow used by heliospheric models through which coronal mass ejections (CMEs) propagate. Here we present a new approach that instead derives the inner‐boundary conditions directly from in situ solar wind observations, typically obtained near 1 AU. These observations are ballistically backmapped to 0.1 AU while accounting for both solar wind acceleration and solar rotation, and then corrected for stream‐interaction effects using a convolutional neural network trained on synthetic model data. The resulting 0.1 AU boundary conditions are used to drive the Heliospheric Upwind eXtropolation with time dependence (HUXt) model. Applied to the highly geoeffective May 2024 CME interval, this method reproduces solar wind conditions at Earth and at Solar Orbiter —on the far side of the Sun—with speed errors reduced by around 50% relative to traditional coronal‐model approaches. Although this represents a post‐event reconstruction rather than an operational forecast, the approach provides a fast, accurate, and magnetogram‐independent means of reconstructing the inner heliosphere, paving the way for improved CME analyses and future forecasting applications.