Refined Modeling of Geoeffective Fast Halo CMEs During Solar Cycle 24

被引:2
|
作者
Yordanova, E. [1 ]
Temmer, M. [2 ]
Dumbovic, M. [3 ]
Scolini, C. [4 ]
Paouris, E. [5 ,6 ]
Werner, A. L. E. [1 ]
Dimmock, A. P. [1 ]
Sorriso-Valvo, L. [1 ,7 ,8 ]
机构
[1] Swedish Inst Space Phys, Uppsala, Sweden
[2] Graz Univ, Inst Phys, Graz, Austria
[3] Univ Zagreb, Fac Geodesy, Hvar Observ, Zagreb, Croatia
[4] Royal Observ Belgium, Brussels, Belgium
[5] George Mason Univ, Dept Phys & Astron, Fairfax, VA USA
[6] Johns Hopkins Univ, Appl Phys Lab, Laurel, MD USA
[7] CNR, Inst Plasma Sci & Technol ISTP, Bari, Italy
[8] KTH Royal Inst Technol, Sch Elect Engn & Comp Sci, Space & Plasma Phys, Stockholm, Sweden
关键词
halo CME; background solar wind; CME arrival time; CME impact speed; space weather forecast; CORONAL MASS EJECTIONS; WIND PREDICTION; ARRIVAL-TIME; EARTH; VALIDATION; SUN;
D O I
10.1029/2023SW003497
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
The propagation of geoeffective fast halo coronal mass ejections (CMEs) from solar cycle 24 has been investigated using the European Heliospheric Forecasting Information Asset (EUHFORIA), ENLIL, Drag-Based Model (DBM) and Effective Acceleration Model (EAM) models. For an objective comparison, a unified set of a small sample of CME events with similar characteristics has been selected. The same CME kinematic parameters have been used as input in the propagation models to compare their predicted arrival times and the speed of the interplanetary (IP) shocks associated with the CMEs. The performance assessment has been based on the application of an identical set of metrics. First, the modeling of the events has been done with default input concerning the background solar wind, as would be used in operations. The obtained CME arrival forecast deviates from the observations at L1, with a general underestimation of the arrival time and overestimation of the impact speed (mean absolute error [MAE]: 9.8 +/- 1.8-14.6 +/- 2.3 hr and 178 +/- 22-376 +/- 54 km/s). To address this discrepancy, we refine the models by simple changes of the density ratio (dcld) between the CME and IP space in the numerical, and the IP drag (gamma) in the analytical models. This approach resulted in a reduced MAE in the forecast for the arrival time of 8.6 +/- 2.2-13.5 +/- 2.2 hr and the impact speed of 51 +/- 6-243 +/- 45 km/s. In addition, we performed multi-CME runs to simulate potential interactions. This leads, to even larger uncertainties in the forecast. Based on this study we suggest simple adjustments in the operational settings for improving the forecast of fast halo CMEs. Coronal mass ejections (CMEs) are massive explosions of magnetized plasma hurled into the interplanetary space. The ones traveling directly toward or away from the observer's line of sight are called halo CMEs because of their appearance as a ringlike white light feature surrounding the occulting disk in the coronagraph instruments monitoring the Sun. Because of their course of propagation, the Earth-directed halo CMEs are more likely to strongly disturb the geomagnetic field and subsequently trigger intense geomagnetic storms. Therefore the accurate prediction of halo CMEs arrival at Earth is critically important to mitigate their hazardous effects on human technology in space and on the ground. This work attempts to investigate the performance of several models for CME propagation for a selected set of fast Earth-directed halo CMEs. A refinement in the modeling input was implemented that lead to a significant improvement in the forecast for the halo CME arrivals. A unified small sample of fast halo coronal mass ejection (CME) events have been modeled and their forecast have been compared with an identical set of metricsThe default model inputs in European Heliospheric Forecasting Information Asset (EUHFORIA), ENLIL, Drag-Based Model (DBM) and Effective Acceleration Model (EAM) resulted in underestimated CME arrival time and overestimated CME impact speedAn improved CME prediction has been achieved by adjusting the input parameters drag (gamma) and density ratios (dcld) in the models
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页数:22
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