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

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关注的焦点。为了进一步提升用户的满意度,首先将激发域的有效角动量(effective angular momentum,EAM)的拟合残差序列卷积到大地测量观测域,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和新的EAM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ERP数据驱动的最小二乘外推和自回归(the least square extrapolation and autoregressive,LS+AR)模型,从2012年初到2021年初的预报实验结果显示,在1~365 d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%。这用数值预报的方式验证了极移短时间尺度的约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。

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 usersrequirements,we combine the new effective angular momentum(EAM)data for the ERP prediction study.Methods:The EAM fitted residual series in the excitation domain is first transferred to the geodetic observation domain,and 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 the least square extrapolation and autoregressive(LS+AR)models driven by ERP data,prediction experiments are performed for the difference series and the new EAM residual series,respectively,and finally predictions for the target ERP series are jointly introduced.Results:Based on 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 prediction 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 is 15%when the adjustment factor of length of day is 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.