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Synergy of Observations and Dynamo Models to Understand and Predict Solar Activity CyclesThe long-standing problem of understanding the evolution of the global magnetic fields that drive solar activity through different temporal scales is becoming more tractable because, in addition to 400 years of sunspot records, we now have almost 4 solar cycles of magnetic field observations. These observations allow us to discern physical connections between dynamo model variables and observations using data assimilation analysis. In particular, the Ensemble Kalman Filter approach takes into account uncertainties in both observations and modeling and allows us to make reliable forecasts of solar cycle activity by using a relatively simple non-linear dynamical model of the solar dynamo. To expand this approach for more complex 2D and 3D dynamo modeling, it is necessary to decompose the observed synoptic magnetograms into poloidal and toroidal field components. In this presentation I will present initial results on magnetogram decomposition and assimilation of magnetogram data into dynamo modeling.
Document ID
Acquisition Source
Ames Research Center
Document Type
Kitiashvili, Irina N.
(Bay Area Environmental Research Inst. Moffett Field, CA, United States)
Date Acquired
April 30, 2019
Publication Date
December 10, 2018
Subject Category
Solar Physics
Report/Patent Number
Meeting Information
Meeting: American Geophysical Union Fall Meeting (AGU 2018)
Location: Washington, DC
Country: United States
Start Date: December 10, 2018
End Date: December 14, 2018
Sponsors: American Geophysical Union (AGU)
Funding Number(s)
Distribution Limits
Public Use Permitted.
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