王乐洋, 苗威. 顾及有效角动量信息的地球自转参数中长期预报方法[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20220246
引用本文: 王乐洋, 苗威. 顾及有效角动量信息的地球自转参数中长期预报方法[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20220246
WANG Leyang, MIAO Wei. Medium-long term forecasting method for earth rotation parameters considering effective angular momentum information[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20220246
Citation: WANG Leyang, MIAO Wei. Medium-long term forecasting method for earth rotation parameters considering effective angular momentum information[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20220246

顾及有效角动量信息的地球自转参数中长期预报方法

Medium-long term forecasting method for earth rotation parameters considering effective angular momentum information

  • 摘要: 地球自转参数(earth rotation parameters,ERP)的预报精度一直是卫星自主导航和深空探测等用户们关注的焦点。为了进一步提升用户们的满意度,本文首先将激发域的有效角动量(effective angular momentum,EAM)的拟合残差序列转移到EOP域,并添加经验调节因子,构造出新的EAM拟合残差序列。然后将ERP的和新的EAM的拟合残差序列做减法,获得差异序列。最后联合差异序列和新的EAM残差序列的预报值,推出目标ERP序列的预报值。使用由最终产品数据和快速数据驱动的最小二乘外推和自回归模型(least-squaresextrapolation and autoregressive,LS+AR),后播实验从2012年初到2021年初的预报结果显示,在1-365天的预报窗口上,X方向和Y方向的调节因子均为0.7时,分别较传统方法平均提高31.86%和21.00%;日长变化的调节因子为1时,较传统方法平均提升15.01%。这用数值预报的方式验证了极移短时间尺度的大约70%高频变化由EAM激发这一已有结论,并为ERP预报研究提供了参考。

     

    Abstract: Objectives: The prediction accuracy of Earth rotation parameters (ERP), as one of the hot spots in geodetic research, has been attracting attention from users such as autonomous satellite navigation and deep space exploration. In order to further satisfy the users’ requirements, this paper combines the new effective angular momentum (EAM) data for the ERP forecast study. Methods: The EAM fitted residual series in the excitation domain is first transferred to the EOP domain, and then an empirical adjustment factor is added to construct a new EAM fitted residual series. Then the fitted residual series of ERP and the fitted residual series of the new EAM are subtracted to obtain the difference series. Using least-squares extrapolation and autoregressive (LS+AR) models driven by final product data and rapid data, forecast experiments are performed for the difference series and the new EAM residual series, respectively, and finally forecasts for the target ERP series are jointly introduced. Results: Based on hindcast experiments from the beginning of 2012 to the beginning of 2021, it is shown that an overall better result can be obtained for the adjustment factor of 0.7 in both the x-direction and y-direction at a forecast horizons of 1-365 days, with an average improvement of 31.86% and 21.00% over the traditional method, respectively; the average improvement over the traditional method was 15.01% when the adjustment factor of LOD was 1. Conclusions: This verifies the existing conclusion that about 70% of the high-frequency changes in the short time scale of polar motion are stimulated by EAM by means of numerical prediction, and provides a reference for ERP prediction research. In addition, considering time-varying periodic terms or replacing better models will also help to improve the prediction accuracy of the new method.

     

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