Impact of Non-potential Coronal Boundary Conditions on Solar Wind Prediction

TL;DR

This study evaluates how replacing potential with non-potential coronal boundary conditions affects solar wind predictions at Earth, finding that non-potential models perform better during solar maximum, while potential models excel during the descending phase.

Contribution

It introduces a comparison between potential and non-potential coronal boundary conditions for solar wind prediction, highlighting their respective performances across solar cycle phases.

Findings

Non-potential models improve predictions during solar maximum.

Potential models perform better during the descending phase.

Wang-Sheeley-Arge model excels in predicting high-speed streams.

Abstract

Predictions of the solar wind at Earth are a central aspect of space weather prediction. The outcome of such a prediction, however, is highly sensitive to the method used for computing the magnetic field in the corona. We analyze the impact of replacing the potential field coronal boundary conditions, as used in operational space weather prediction tools, by non-potential conditions. For this, we compare the predicted solar wind plasma parameters with observations at 1 AU for two six-months intervals, one at solar maximum and one in the descending phase of the current cycle. As a baseline, we compare with the operational Wang-Sheeley-Arge model. We find that for solar maximum, the non-potential coronal model and an adapted solar wind speed formula lead to the best solar wind predictions in a statistical sense. For the descending phase, the potential coronal model performs best. The Wang-Sheeley-Arge model outperforms the others in predicting high speed enhancements and streamer interactions. A better parameter fitting for the adapted wind speed formula is expected to improve the performance of the non-potential model here.