Improving Ambient Solar Wind Modeling and Prediction

The solar wind is a stream of charged particles that constantly emanates from the Sun into our solar system, reaching speeds of up to 800 km/s. The interaction of the solar wind with Earth's magnetosphere continually leads to increased geomagnetic activity. In addition to the beautiful northern lights, geomagnetic storms can have severe consequences for our modern civilization. Technological infrastructure on the surface and in orbit such as power grids, air traffic, GPS, and radio communication are affected. Knowledge of the structure of the solar wind is therefore critical for successful space research.

In this project, we will study the question of how we can accurately model the large-scale structure of the solar wind in our solar system. Here we will develop new approaches to improve the boundary conditions of state-of-the-art solar wind codes. To validate and quantify our progress, we will focus on the comparison of model solutions with solar wind measurements from current space missions such as BepiColombo and Solar Orbiter. This project will provide a better understanding of the sources of the solar wind flow, give insight into the physical condition of the solar wind in our solar system, and improve the boundary conditions of large-scale solar wind models.

Figure 1: In Reiss+ [2019] and Reiss+ [2020] we have developed a framework that combines various reduced physics-based models to predict space weather conditions at Earth. This figure shows the solution of the WSA-THUX model combination for modeling the solar wind speed in the inner heliosphere. The framework is based on the established Wang-Sheeley-Arge Model [Wang & Sheeley, 1990; Riley+ 2001; Arge+ 2003], and a modified version of the Heliospheric Upwind eXtrapolation (HUX) model [Riley & Lionello, 2011] that bridges the gap between ballistic mapping and MHD modeling.


Figure 2: We are interested in reduced physics-based solar wind models for two reasons. On one hand, these models have proven to be the most reliable and robust approach for predicting solar wind conditions at Earth [Reiss+ 2016, Bailey+ 2021]. On the other hand, their computational efficiency makes them well-suited for studying the parameter settings of models that specify the solar wind conditions at the inner boundary of heliospheric MHD codes, as shown in this figure [Reiss+ 2020].





Team
PI: Martin A. Reiss
Postdoc: Satabdwa Majumdar
Master's student: N.N.
Duration: 04/2022 – 03/2027
Link to FWF project page: P 34437





Acknowledgements: This research is funded by the Austrian Science Fund (FWF) [P 34437].