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Erschienen in:
Current Status of MHD Simulations for Space Weather Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

7. Data-Driven MHD Modeling of Solar Wind

verfasst von : Xueshang Feng

Erschienen in: Magnetohydrodynamic Modeling of the Solar Corona and Heliosphere

Verlag: Springer Singapore

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Abstract

Solar wind is rather than of steady state, but physically dynamic corresponding to the solar rotation, solar mass flow and solar magnetic field evolution. In fact, solar wind is constantly time varying. Data-driven modeling of solar wind here means to use continuously time-varying solar observations as input to drive models to produce solar wind background and reproduce eruptive process of solar active region, instead of using one instantaneous cadence of observation as input. The latter is in contrast called data-constrained modeling. The idea of data-driven modeling is to let continuously observed data and MHD evolve to produce what is happening next. This chapter describes how to use the global photospheric field maps generated by the solar surface flux Transport (SFT) model for long-interval synoptic data products or time interpolation for short-interval synoptic data products as input to drive the CESE-MHD coronal and solar wind model.

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Vorheriges Kapitel AMR Implementation of 3D SIP-CESE MHD Model on Six-Component Overset Grid System
Nächstes Kapitel Coronal Force-Free Field Extrapolations
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Metadaten
Titel
Data-Driven MHD Modeling of Solar Wind
verfasst von
Xueshang Feng
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Magnetohydrodynamic Modeling of the Solar Corona and Heliosphere

Print ISBN: 978-981-13-9080-7

Electronic ISBN: 978-981-13-9081-4

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-13-9081-4_7

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