Accurate, short-term predictions of Earth orientation parameters (EOP) are needed for many real-time applications including precise tracking and navigation of interplanetary spacecraft, climate forecasting, and disaster prevention. Out of the EOP, the LOD (length of day), which represents the changes in the Earth’s rotation rate, is the most challenging to predict since it is largely affected by the torques associated with changes in atmospheric circulation. In this study, the combination of Copula-based analysis and singular spectrum analysis (SSA) method is introduced to improve the accuracy of the forecasted LOD. The procedure operates as follows: First, we derive the dependence structure between LOD and the Z component of the effective angular momentum (EAM) arising from atmospheric, hydrologic, and oceanic origins (AAM + HAM + OAM). Based on the fitted theoretical Copula, we then simulate LOD from the Z component of EAM data. Next, the difference between LOD time series and its Copula-based estimation is modeled using SSA. Multiple sets of short-term LOD prediction have been done based on the IERS 05 C04 time series to assess the capability of our hybrid model. The results illustrate that the proposed method can efficiently predict LOD.

中文翻译：

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一种改进LOD超短期预测的新混合方法

许多实时应用都需要对地球定向参数 (EOP) 进行准确的短期预测，包括行星际航天器的精确跟踪和导航、气候预测和灾害预防。在 EOP 中，代表地球自转速率变化的 LOD（日长）是最具挑战性的预测，因为它在很大程度上受到与大气环流变化相关的扭矩的影响。在这项研究中，引入了基于 Copula 的分析和奇异谱分析 (SSA) 方法的结合，以提高预测 LOD 的准确性。该过程操作如下：首先，我们推导出 LOD 与由大气、水文和海洋起源 (AAM + HAM + OAM) 产生的有效角动量 (EAM) 的 Z 分量之间的依赖结构。基于拟合的理论 ​​Copula，我们然后从 EAM 数据的 Z 分量模拟 LOD。接下来，使用 SSA 对 LOD 时间序列与其基于 Copula 的估计之间的差异进行建模。基于 IERS 05 C04 时间序列进行了多组短期 LOD 预测，以评估我们混合模型的能力。结果表明，所提出的方法可以有效地预测 LOD。