Space Weather Predictions with Data-driven Models of the Solar Atmosphere and Inner Heliosphere: Importance of Uncertainty Quantification

The solar wind (SW) emerging from the Sun is the main driving mechanism of solar events which may lead to geomagnetic storms that are the primary causes of space weather (SWx) disturbances that affect the magnetic environment of Earth and may have hazardous effects on the space-borne and ground-based technological systems as well as human health. The connection of the ambient interplanetary magnetic field to CME-related shocks and impulsive solar flares determines where solar energetic particles propagate. Therefore, modeling stream interaction background and ICME propagating through it on the basis of observational data is a key area of research in solar and heliospheric physics. Such modeling should necessarily be built on physically-consistent connections between eruptive events, magnetic phenomena on the Sun, and SW structures in the solar atmosphere and inner heliosphere (IHS). We discuss our team’s efforts in the development of a new data-driven, time-dependent chain of open-source models of the solar corona and inner heliosphere to predict the SW properties at Earth’s orbit. The new models are providing more accurate solutions and are scalable on massively parallel systems. These include (1) a flux transport model; (2) a potential field solver, (3) the Wang-Sheeley-Arge model with its ensemble capabilities, and (4) a Reynolds-averaged MHD SW model based on modern computational methods. The latter component is based on the Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) capabilities and takes advantage of the publicly available Chombo adaptive mesh refinement framework for solving partial differential equations, now with the application of mapped grids, e.g., cubed spheres. In addition, the newest release of Chombo allows us to perform AMR simulations with the 4-th order of accuracy in space and time — a feature of substantial importance for SWx simulations. We have extend and made publicly available the Predictive Science Incorporated (PSI) Potential Filed Solver (POT3D) code, which scales well on massively parallel systems and GPUs. POT3D is now being used in our ensemble runs using the input from the Open Flux Transport (OFT) model. Validation studies for the combination of OFT, POT3D, and WSA models are presented. We particularly investigate the physics of evolution, eruption and propagation of ICMEs. We apply our flux-rope-based CME models, which depend on their observations-derived direction, tilt, shape, speed, mass, poloidal and toroidal magnetic fluxes, and helicity sign. Quantified uncertainties are presented of the CME dependence on the choice of its parameters.