Variationen in der Zusammensetzung des Sonnenwindes als Tracer für seinen solaren Ursprung
Zusammenfassung der Projektergebnisse
The solar wind, a stream of charged particles constantly emitted from the Sun, originates from different solar source regions which are reflected in different properties of the solar wind. For the fast component of the solar wind, the source regions have been identified as coronal holes, but the source of the slow solar wind is still under debate. Locating the solar source regions of slow solar wind is one of the major science goals of ESA’s Solar Orbiter and contributing to this was the aim of the proposal. In particular, Solar Orbiter relies on correlating in situ measurements of the solar wind with remote-sensing observations of potential source regions of the slow solar wind by comparing observations of elemental composition. In preparation of the data analysis of the Solar Orbiter, we based our work on measurements with the Solar Wind Ion Composition Spectrometer (SWICS) onboard the Advanced composition Explorer (ACE) and investigated the elemental composition of the solar wind on various time scales. We focused on the low first-ionization-potential (FIP) elements Mg, Si, and Fe, since they are often treated as interchangeable in the literature because this is predicted by the prevalent theories of the elemental composition in the solar wind. We found that both on short and long time scales the assumption that the low FIP elements Mg, Si, and Fe can be treated as interchangeable is not valid. Thus, correlating in-situ observations of the elemental abundance with remote-sensing measurements of solar source regions can only be successful if the same elements are compared with each other. This is highly relevant for Solar Orbiter, since due to different instrumental properties of the heavy ion sensor (HIS) and the Spectral Imaging of the Coronal Environment (SPICE) instrument, Fe is favoured by HIS and Mg ions by SPICE. Nevertheless, our findings indicate that comparisons between in-situ and remote-sensing data need to be made individually for each element. While Solar Orbiter was launched in February 2020, the remote-sensing instruments have only just become operational at the time of writing this final report. The nominal science phase of the mission will only start in March 2022, the current cruise phase was always planned for commissioning activities with the in-situ instruments in science mode but did start later than assumed when writing the proposal for this work. This delay was due to several issues with the spacecraft and the payload. The Solar Wind Analyzer on Solar Orbiter has encountered a number of difficulties, and HIS sensor is only now achieving the high voltages needed for its nominal operation. The work performed in this proposal will serve as a valuable reference for future work and we plan to continue it. Further, we found that analysing the correlation of high time-resolution time series of different elements in the solar wind demands a particular high data quality which exceeds the capabilities of the currently available ACE/SWICS data sets. Therefore, we concluded that a thorough reanalysis of the ACE/SWICS data is necessary before a formal publication of part of our work. This re-analysis of the ACE/SWICS data is a time consuming process and is still ongoing. Our findings emphasized the importance of correctly identifying different types of solar wind. Therefore, we diverted some of our effort to the task of solar wind classification. This effort led to a machine learning based approach which provides an independent and objective perspective to solar wind classification. In addition, we developed a simplification of a pre-existing solar wind classification that requires no magnetic field observations. Our method has the distinct advantage that this classification can be applied directly to the data from the Solar and Heliospheric Observatory (SOHO) which is not equipped with a magnetometer.
Projektbezogene Publikationen (Auswahl)
- (2018). Disparity among low first ionization potential elements. Astronomy & Astrophysics, 619:A79
Heidrich-Meisner, V., Berger, L., and Wimmer-Schweingruber, R. F.
(Siehe online unter https://doi.org/10.1051/0004-6361/201833454) - (2018). Solar wind classification via k-means clustering algorithm. In Machine learning techniques for space weather, pages 397–424. Elsevier
Heidrich-Meisner, V. and Wimmer-Schweingruber, R. F.
(Siehe online unter https://doi.org/10.1016/B978-0-12-811788-0.00016-0) - (2020). An elliptic expansion of the potential field source surface model. Astronomy & Astrophysics, 638:A109
Kruse, M., Heidrich-Meisner, V., Wimmer-Schweingruber, R., and Hauptmann, M.
(Siehe online unter https://doi.org/10.1051/0004-6361/202037734) - (2020). Proton-proton collisional age to order solar wind types. Astronomy & Astrophysics, 636:A103
Heidrich-Meisner, V., Berger, L., and Wimmer-Schweingruber, R. F.
(Siehe online unter https://doi.org/10.1051/0004-6361/201937378) - (2021). Evaluation of a potential field source surface model with elliptical source surfaces via ballistic back mapping of in situ spacecraft data. Astronomy & Astrophysics, 645:A83
Kruse, M., Heidrich-Meisner, V., and Wimmer-Schweingruber, R.
(Siehe online unter https://doi.org/10.1051/0004-6361/202039120) - (2021). Kinetic Physics with Solar Wind Heavy Ions Measured at 1 AU. PhD thesis
Janitzek, N. et al.
