14:30 〜 14:45
[PEM16-04] Effects of spheromak initial parameters on Time of Arrival of CMEs in SUSANOO-CME
キーワード：太陽風、CME、MHDシミュレーション、宇宙天気
Coronal Mass Ejections (CMEs) are impulsive ejections of plasma from the solar outer atmosphere into interplanetary space and are the primary drivers of space weather disturbances. Global heliospheric MHD models are widely used to simulate the propagation of CMEs and predict their time of arrival (ToA) to Earth. However, these models often exhibit uncertainties in ToA due to errors included in the initial parameters derived from solar observations. While some parameter surveys have been conducted to refine these initial conditions to enhance prediction accuracy, detailed parameter surveys focusing on the parameters determining the magnetic structures of CME remain insufficient.
SUSANOO-CME (Shiota & Kataoka, 2016) is a MHD model that reproduces CMEs using a spheromak. In this study, we focused on Φmag, the parameter representing the magnetic flux included in the spheromak. We performed ensemble simulations varying multiple initial parameters, including Φmag, employing SUSANOO-CME to clarify the impacts of Φmag on ToA. We then introduced 'parameter diagrams' that plot each ToA in parameter space. Our previous analysis suggested that Φmag characteristics on ToA varies depending on other initial parameters, such as the CME’s initial velocity and the ambient solar wind speed. This time, to investigate this trend in greater detail, we refined the parameter diagrams by analyzing additional fine-scale ensemble members.
We found that the parameter diagram contains specific parameter ranges for both initial CME velocities and Φmag where the ToA gradient is steep. These ranges vary depending on other parameter values and may not always exist. For example, with an initial velocity of 600 km/s, increasing Φmag by 1.0×1021 Mx from 0.50×1021 Mx resulted in a ToA difference of 13.5 hours, while increasing it from 2.5×1021 Mx resulted in a difference of only 0.7 hours. In contrast, for an initial velocity of 2200 km/s, the maximum ToA difference for a similar Φmag increment was 4 hours.
This result suggests that under certain conditions, a specific parameter can dominate ToA errors even when other parameters are precisely determined. The parameter diagrams could help identify key error sources for ToA in observed CMEs without additional calculations. This approach can also be useful for identifying key parameters in realistic probabilistic forecasting and assigning weights to ensemble members.
We also estimated ToA errors using refined parameter diagrams, assuming realistic space weather forecasting. In this analysis, we estimated Φr, the reconnection flux on the photosphere underlying the flare site, as a proxy for Φmag by utilizing the known correlation between Φr and the soft X-ray peak flux for C-, M-, and X-class flares. The results indicated that Φmag derived using this method led to ToA errors exceeding 10 hours, suggesting that the estimation of Φmag could be a limiting factor in CME forecasting. However, we consider X-ray fluence during a flare to be a more suitable parameter than flux for estimating the magnetic flux. This issue will also be discussed in this presentation.
SUSANOO-CME (Shiota & Kataoka, 2016) is a MHD model that reproduces CMEs using a spheromak. In this study, we focused on Φmag, the parameter representing the magnetic flux included in the spheromak. We performed ensemble simulations varying multiple initial parameters, including Φmag, employing SUSANOO-CME to clarify the impacts of Φmag on ToA. We then introduced 'parameter diagrams' that plot each ToA in parameter space. Our previous analysis suggested that Φmag characteristics on ToA varies depending on other initial parameters, such as the CME’s initial velocity and the ambient solar wind speed. This time, to investigate this trend in greater detail, we refined the parameter diagrams by analyzing additional fine-scale ensemble members.
We found that the parameter diagram contains specific parameter ranges for both initial CME velocities and Φmag where the ToA gradient is steep. These ranges vary depending on other parameter values and may not always exist. For example, with an initial velocity of 600 km/s, increasing Φmag by 1.0×1021 Mx from 0.50×1021 Mx resulted in a ToA difference of 13.5 hours, while increasing it from 2.5×1021 Mx resulted in a difference of only 0.7 hours. In contrast, for an initial velocity of 2200 km/s, the maximum ToA difference for a similar Φmag increment was 4 hours.
This result suggests that under certain conditions, a specific parameter can dominate ToA errors even when other parameters are precisely determined. The parameter diagrams could help identify key error sources for ToA in observed CMEs without additional calculations. This approach can also be useful for identifying key parameters in realistic probabilistic forecasting and assigning weights to ensemble members.
We also estimated ToA errors using refined parameter diagrams, assuming realistic space weather forecasting. In this analysis, we estimated Φr, the reconnection flux on the photosphere underlying the flare site, as a proxy for Φmag by utilizing the known correlation between Φr and the soft X-ray peak flux for C-, M-, and X-class flares. The results indicated that Φmag derived using this method led to ToA errors exceeding 10 hours, suggesting that the estimation of Φmag could be a limiting factor in CME forecasting. However, we consider X-ray fluence during a flare to be a more suitable parameter than flux for estimating the magnetic flux. This issue will also be discussed in this presentation.