Modiri Sadegh, Belda Santiago, Hoseini Mostafa, Heinkelmann Robert, Ferrándiz José M, Schuh Harald
1GFZ German Research Centre for Geosciences, Potsdam, Germany.
2Institute for Geodesy and Geoinformation Science, Technische Universität Berlin, Berlin, Germany.
J Geod. 2020;94(2):23. doi: 10.1007/s00190-020-01354-y. Epub 2020 Feb 5.
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 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 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.
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与导航、气候预测以及灾害预防。在地球定向参数中，日长（LOD）代表地球自转速率的变化，由于它在很大程度上受与大气环流变化相关的扭矩影响，因此是最难预测的。在本研究中，引入了基于Copula的分析与奇异谱分析（SSA）方法的组合，以提高预测日长的准确性。该过程如下：首先，我们推导日长与大气、水文和海洋来源（大气角动量 + 水文角动量 + 海洋角动量）产生的有效角动量（EAM）分量之间的依赖结构。基于拟合的理论Copula，然后我们从EAM数据分量模拟日长。接下来，使用奇异谱分析对日长时间序列与其基于Copula的估计之间的差异进行建模。基于国际地球自转服务组织（IERS）05 C04时间序列进行了多组日长短期预测，以评估我们的混合模型的能力。结果表明，所提出的方法能够有效地预测日长。
