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Paper: |
Implementation of Data Assimilation Methods for Dynamo Models to Predict Solar Activity |
Volume: |
416, Solar-Stellar Dynamos as Revealed by Helio- and Asteroseismology: GONG 2008/SOHO 21 |
Page: |
511 |
Authors: |
Kitiashvili I.; Kosovichev, A. |
Abstract: |
Cyclic variations of solar activity are a result of a complicated dynamo process in the convection zone. Despite the regular cyclic variations of solar activity, the chaotic variations of sunspot number from cycle to cycle are difficult to predict. The main reasons are the imperfect dynamo models and deficiency of the necessary observational data. Data assimilation methods iterate observational data and models for possible efficient and accurate estimations of physical properties, which cannot be observed directly. We apply the Ensemble Kalman Filter method for assimilation of the sunspot data into a non-linear mean-field dynamo model, which takes into variations of magnetic helicity and parameters of the solar convection zone from helioseismology. We present the results of application of this data assimilation method for representation of the solar cycles and prediction of variations of the sunspot number, and discuss potentials of data assimilation methods for solar dynamo modeling. |
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