Physics-Based Approach to Predict the Solar Activity Cycles

Kitiashvili, Irina N

关键词: SOLAR CYCLES;    SOLAR ACTIVITY;    KALMAN FILTERS;    HELIOSEISMOLOGY;    MAGNETIC FIELDS;    ACTIVITY CYCLES (BIOLOGY);    PREDICTION ANALYSIS TECHNIQUES;   

RP-ID  :  ARC-E-DAA-TN59750

学科分类：天文学(综合)

美国|英语

来源: NASA Technical Reports Server

【 摘 要 】

Observations of the complex highly non-linear dynamics of global turbulent flows and magnetic fields are currently available only from Earth-side observations. Recent progress in helioseismology has provided us some additional information about the subsurface dynamics, but its relation to the magnetic field evolution is not yet understood. These limitations cause uncertainties that are difficult take into account, and perform proper calibration of dynamo models. The current dynamo models have also uncertainties due to the complicated turbulent physics of magnetic field generation, transport and dissipation. Because of the uncertainties in both observations and theory, the data assimilation approach is natural way for the solar cycle prediction and estimating uncertainties of this prediction. I will discuss the prediction results for the upcoming Solar Cycle 25 and their uncertainties and affect of Ensemble Kalman Filter parameters to resulting predictions.