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| Titel |
Implementing sequential data assimilation in a flux-transport solar dynamo model for reconstructing meridional flow |
| VerfasserIn |
M. Dikpati, J. Anderson |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250069014
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| Zusammenfassung |
| Data assimilation in atmospheric and oceanic models started about 40 years ago, but
that in solar models has started only recently. We develop here a sequential data
assimilation approach for the application in a flux-transport solar dynamo model, with the
motivation of building a better tool for predicting global solar cycle features, such as
amplitude, duration and shape of a cycle. A key ingredient in flux-transport type dynamo
models is meridional circulation. Time-variation of this flow plays a crucial role in
determining the duration, onset and peak timings, rise and decline patterns of a
solar cycle. We generate artificial data of magnetic flux from our flux-transport
dynamo model with a time-varying meridional flow, and use that as the observational
proxy for a solar cycle. We then sequentially assimilate these data into our dynamo
model, and implement an Ensemble Kalman Filter using the framework of Data
Assimilation Research Testbed (DART) developed at IMAGe/NCAR, to reconstruct the
time-variation in this flow. The reconstructed flow reveals this is a very powerful
technique and can be applied for building a sophisticated predictive tool for simulating
the shape, rise and fall patterns of a cycle, if the flow variation is known apriori. |
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