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| Titel |
Data-driven time-dependent magnetofrictional modelling of coronal mass ejections and sensitivity of the modelling output to the driving electric field |
| VerfasserIn |
Erkka Lumme, Jens Pomoell, Emilia Kilpua, Erika Palmerio |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250142726
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| Publikation (Nr.) |
 EGU/EGU2017-6379.pdf |
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| Zusammenfassung |
| Determination of the magnetic structure of erupting CMEs in the corona is one
of the central open problems in CME research and in forecasting of their space
weather effects. Since routine measurements of the coronal magnetic field are not
currently available, the most promising approach to determine the magnetic structure
of an erupting CME is data-driven modelling in which available measurements
from the photosphere are used as a boundary condition. In particular, we employ
time-dependent data-driven magnetofrictional method to determine the coronal magnetic field
configuration at the time of the CME eruption. The approach is computationally
feasible yet still has sufficient physical accuracy to constrain the CME magnetic field
properties. The success of the method depends heavily on the realism of the photospheric
boundary condition, the electric field. For this purpose we have created ELECTRICIT, a
practical software toolkit for routine, faithful inversion of the electric field from
time series of photospheric magnetic field and plasma velocity measurements. In
this work we present an ensemble of magnetofrictional coronal simulations for a
single active region, driven by the electric fields inverted using ELECTRICIT and
a collection of different inversion techniques. We illustrate the feasibility of our
data-driven approach in determining the magnetic structure of an erupting CME and
study the sensitivity of the simulation output to the properties of the driving electric
field, such as the Poynting and magnetic helicity fluxes from the photosphere to the
corona.
Our data-driven modelling approach offers interesting possibilities to extend the CME
analyses in HELCATS catalogues. Using LINKCAT source region identifications our
data-driven modelling scheme can be applied to the correct active region to acquire the
magnetic structure of a given CME in the low corona. This can be then combined with the
catalogued kinematic properties of the CME to create a comprehensive description of the
eruption. |
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