Using Data Assimilation Methods for Modeling and Predicting Solar Activity Cycles

Details Using Data Assimilation Methods for Modeling and Predicting Solar Activity Cycles Using Data Assimilation Methods for Modeling and Predicting Solar Activity Cycles

Dec 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008agufmsh13a1506k&link_type=abstract

American Geophysical Union, Fall Meeting 2008, abstract #SH13A-1506

Physics

7536 Solar Activity Cycle (2162), 7544 Stellar Interiors And Dynamo Theory

Scientific paper

Modern data assimilation methods allow us to adapt a model to observations by estimating the true state of a system and taking into account uncertainties in the data and the model. The Ensemble Kalman Filter (EnKF) method provides an effective data assimilation for models of nonlinear dynamics. It is based on analysis of an ensemble of model solutions. We implement the EnKF method for modeling the 11-year sunspot number variations. Using this approach we propose a new physics-based method for predicting for the strength of the solar sunspot cycles. For the initial modeling of the sunspot number we use a dynamo model of Kleeorin and Ruzmaikin dynamo model in a low-mode approximation. The model includes the Parker's dynamo equations and an equation for conservation of the magnetic helicity. Also, we accept Bracewell's suggestion to relate the toroidal magnetic field, B, to the sunspot number, W,in the form of a three-halfs law: W ~ B3/2. We investigate non-linear solutions of the dynamo model and find periodic and chaotic solutions for the convection zone parameters, which represent basic properties of the solar cycles, such as the mean profile of solar cycle and the relationship between the cycle amplitude and the growth and decay times. By applying the EnKF method to the non-linear periodic solutions we reproduce the annual variations of the sunspot number and investigate the predictive capabilities. For testing we calculate forecasts for the 10 previous cycles and find a reasonable agreement with the observations. The calculations of the forecast of the upcoming solar cycle 24 indicate that this cycle will be weaker than the previous one, with the maximum sunspot number of about 80. This investigation shows that data assimilation methods may be useful for evaluating solar dynamo models and for forecasting solar activity.

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