Space-Weather Utilities for Research and Forecasting (SURF): A Tool for Investigating Hydrodynamic Aspects of Solar Wind and Coronal Mass Ejection Expansion and Evolution

Abstract

We introduce Space-weather Utilities for Research and Forecasting (SURF), a flexible modelling framework for reconstructing and forecasting large-scale solar wind structure. SURF incorporates both the reduced hydrodynamic “HUXt” model and a newly developed one-dimensional, hydrodynamic solver, “hydro.”. The new solver introduces more physically consistent compression effects, while retaining the computational efficiency required for ensemble forecasting, uncertainty quantification, and large parametric studies. SURF-hydro solves the 1D Euler equations in spherical geometry using finite-volume methods with Riemann solvers and second-order spatial reconstruction. It is shown to accurately reproduce an analytical solution to pressure-driven expansion of a uniform spherical solar wind. Using 30 years of near-Earth OMNI observations, we derive empirical relations between speed, density, and temperature at 1 AU and map these back to 0.1 AU to provide non-equilibrium inner-boundary conditions for SURF-hydro (and for use with other solar wind models). This approach produces more realistic solar wind speed, density and temperature values and variability at 1 AU than simulations based on equilibrium thermodynamic relations at 0.1 AU. While magnetic pressure and tension forces are not included, SURF-hydro is also shown to reproduce the key features of coronal mass ejection (CME) expansion and evolution. For one particular example of a structured solar wind, sensitivity tests demonstrate that CME density and temperature at 0.1 AU alter 1 AU transit times and arrival speeds by 15 – 20%, highlighting a potential under-explored source of forecast uncertainty. SURF-hydro therefore provides a computationally efficient bridge between idealised models and full 3D magnetohydrodynamic simulations, enabling systematic investigation of boundary condition assumptions and CME parameter sensitivity for both research and operational space-weather forecasting.