84 citations · 780 across the 23 of their papers we have counts for
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Machine learning for predicting the Bz magnetic field component from upstream in situ observations of solar coronal mass ejections
Martin A. Reiss, Christian Möstl, Rachel L. Bailey +6
Predicting the Bz magnetic field embedded within ICMEs, also known as the Bz problem, is a key challenge in space weather forecasting. We study the hypothesis that upstream in situ…
In situ multi-spacecraft and remote imaging observations of the first CME detected by Solar Orbiter and BepiColombo
E. E. Davies, C. Möstl, M. J. Owens +20
On 2020 April 19 a coronal mass ejection (CME) was detected in situ by Solar Orbiter at a heliocentric distance of about 0.8 AU. The CME was later observed in situ on April 20th by…
Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
Tanja Amerstorfer, Jürgen Hinterreiter, Martin A. Reiss +8
In this study, we evaluate a coronal mass ejection (CME) arrival prediction tool that utilizes the wide-angle observations made by STEREO's heliospheric imagers (HI). The unsurpass…
Using gradient boosting regression to improve ambient solar wind model predictions
R. L. Bailey, M. A. Reiss, C. N. Arge +7
Studying the ambient solar wind, a continuous pressure-driven plasma flow emanating from our Sun, is an important component of space weather research. The ambient solar wind flows…
Forecasting the Ambient Solar Wind with Numerical Models. II. An Adaptive Prediction System for Specifying Solar Wind Speed Near the Sun
Martin A. Reiss, Peter J. MacNeice, Karin Muglach +8
The ambient solar wind flows and fields influence the complex propagation dynamics of coronal mass ejections in the interplanetary medium and play an essential role in shaping Eart…