Japan Geoscience Union Meeting 2023

Presentation information

[J] Online Poster

P (Space and Planetary Sciences ) » P-EM Solar-Terrestrial Sciences, Space Electromagnetism & Space Environment

[P-EM16] Heliosphere and Interplanetary Space

Tue. May 23, 2023 10:45 AM - 12:15 PM Online Poster Zoom Room (2) (Online Poster)

convener:Kazumasa Iwai(Institute for Space–Earth Environmental Research (ISEE), Nagoya University), Yasuhiro Nariyuki(Faculty of Education, University of Toyama), Masaki N Nishino(Japan Aerospace Exploration Agency, Institute of Space and Astronautical Science), Ken Tsubouchi(University of Electro-Communications)

On-site poster schedule(2023/5/22 17:15-18:45)

10:45 AM - 12:15 PM

[PEM16-P04] Evaluation of Uncertainty in Arrival Time of CME given by initial parameters in the SUSANOO-CME Model

*Hirofumi Isogai1,2, Munetoshi Tokumaru2, Kazumasa Iwai2, Ken'ichi Fujiki2 (1.Nagoya University graduate school of science, 2.Institute for Space-Earth Environmental Research, Nagoya Universiy)


Keywords:Solar Wind, CME, Space Weather, MHD Simulation

An interplanetary disturbance associated with a transient solar plasma ejection, called Coronal Mass Ejection (CME), sometimes arrives at Earth with a strong southward magnetic field. It is concerned that various communication infrastructure and electrical systems can be damaged through magnetospheric disturbances. In order to predict the time of arrival (ToA) of the CME accurately in advance of their arrival to the Earth, global heliospheric MHD models have been applied to forecast the ToA. Today, some space weather forecast models have been developed and operated such as WSA-ENLIL (Riley et al., 2018), EUHFORIA (Pomoell & Poedts, 2018) and SUSANOO-CME (Shiota & Kataoka, 2016). In many of these models, the ToA is known to be sensitive to the initial parameters of the injected CME. Some particularly important CME parameters in several models have been investigated by ensemble modeling (e.g., May et al., 2015; Riley et al, 2018, 2021). These models often reproduce CMEs using cone models that do not include magnetic field structures. SUSANOO-CME is a forecast model that includes CMEs using spheromak-type flux ropes. In several cases, such as the series of CME events observed in October-November 2003 (Halloween event), this model could explain observed CME propagation (Shiota et al. 2016). However, there are some parameters, such as magnetic flux, that are difficult to observe and therefore whose initial parameters have not been adequately validated. It has been suggested that additional variables in models that include magnetic flux rope structures can cause additional ToA uncertainty (Riley et al., 2021). Quantitative estimations of the contribution of CME parameters to the ToA in SUSANOO-CME are needed for more accurate forecast modeling.
In this study, we aim to quantitatively estimate the contribution of CME parameters to the ToA, such as the magnetic flux in SUSANOO-CME and constrain the parameters by comparing them with solar observation data and interplanetary scintillation (IPS) data derived by ISEE, Nagoya University. As a preliminary analysis, we analyzed simulation results of CMEs associated with the M1.0 flare on March 28, 2022. Ten CMEs with five different initial velocities (600, 700, 800, 900, and 1000 km/s) and two magnetic fluxes (2×1021 Mx and 3×1021 Mx) were injected into the background solar wind with the same conditions, and in-situ data were synthesized at the Earth position from each simulation result. We found that the CME with an initial speed of 1000 km/s arrives about 4-5 h earlier than that of with an initial speed of 600 km/s, while the ToA changes about 6 hours between the two simulations with the same initial speed and the magnetic flux of 2×1021 Mx and 3×1021 Mx. This result suggests that at least the magnetic flux is a sensitive parameter to ToA. From the viewpoint of actual forecasting, it is important to quantify the ToA variation within the error range of

the initial parameters expected by the observations. Therefore, the range of initial parameters should be estimated more accurately in the future.