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Modeling and forecast of the polar motion excitation functions for short-term polar motion prediction

机译:短期极地运动预测的极地运动激励函数的建模和预测

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Short-term forecast of the polar motion is considered by introducing a prediction model for the excitation function that drives the polar motion dynamics. The excitation function model consists of a slowly varying trend, periodic modes with annual and several sub-annual frequencies (down to the 13.6-day fortnightly tidal period), and a transient decay function with a time constant of 1.5 days. Each periodic mode is stochastically specified using a second-order auto-regression process, allowing its frequency, phase, and amplitude to vary in time within a statistical tolerance. The model is used to time-extrapolate the excitation function series, which is then used to generate a polar motion forecast dynamically. The skills of this forecast method are evaluated by comparison to the C-04 polar motion series. Over the lead-time horizon of four months, the proposed method has performed equally well to some of the state-of-art polar motion prediction methods, none of which specifically features forecasting of the excitation function. The annual mode in the χ_2 component is energetically the most dominant periodicity. The modes with longer periods, annual and semi-annual in particular, are found to contribute more significantly to forecast accuracy than those with shorter periods.
机译:通过为驱动极性运动动力学的激励函数引入预测模型,可以考虑对极性运动进行短期预测。激励函数模型包括一个缓慢变化的趋势,具有年度频率和几个次年度频率的周期性模式(下降到13.6天的每两周潮汐期)以及一个具有1.5天时间常数的瞬态衰减函数。每个周期模式都是使用二阶自回归过程随机指定的,从而使其频率,相位和幅度在统计公差内随时间变化。该模型用于对激励函数序列进行时间外推,然后用于动态生成极运动预测。通过与C-04极地运动系列进行比较,评估了这种预测方法的技能。在四个月的交付周期内,所提出的方法与某些最新的极地运动预测方法的性能相当,其中没有一种方法特别具有对激励函数的预测功能。 χ_2分量中的年模式在能量上是最主要的周期性。与周期较短的模式相比,发现周期较长的模式(尤其是年度和半年度)对预测准确性的贡献更大。

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