UT1-UTC Prediction Based On The Earth’s Fluid Effective Angular Momentum Function

UT1-UTC is an important part of the Earth orientation parameters and one of the key parameters for the conversion between the international celestial reference frame and the international Earth reference frame.In the fields of deep space exploration and satellite navigation,high-precision UT1-UTC prediction has important scientific significance and engineering application value.The change of UT1-UTC is affected by many excitation factors,including atmospheric surface pressure and atmospheric wind,seafloor pressure and ocean currents,land water distribution and sea level change.In recent years,the excitation function has been applied to the prediction of UT1-UTC.At present,there is less research on using the Earth’s fluid effective angular momentum function to improve the prediction of Earth orientation parameters in China,and there is still a certain gap between the prediction level and the international level.In order to improve the accuracy of UT1-UTC autonomous prediction,this study draws on the prediction method of the Geo Forschungs Zentrum(Dill et al.,2019),and integrates the Earth’s fluid effective angular momentum function into the UT1-UTC prediction.The extrapolation method of autoregressive model is explored and improved,and significantly improved the prediction accuracy of UT1-UTC in the short and medium term of 15-90 days.The research content of this study mainly includes the following aspects.(1)The paper firstly summarizes the domestic and foreign research on UT1-UTC prediction,and reviews some important UT1-UTC prediction methods and measurement methods,and the excitation mechanism of UT1-UTC changes on different time scales.Then,a detailed formula and explanation of the Liouville equation,which describes the geophysical and geodynamic mathematical description of the Earth’s fluid effective angular momentum function and the UT1-UTC change,is given.Starting with the Euler equation of non rigid Earth rotation,the mathematical expression of the influence of angular momentum change caused by relative motion and material redistribution on Earth rotation under the condition of non rigid Earth is derived,and the Liouville equation is further derived,which makes mathematical preparations for the coding of prediction program.(2)In this study,the Earth’s fluid effective angular momentum function(including the effective angular momentum function of atmosphere,ocean,hydrosphere and sea level)is introduced and analyzed in detail.On this basis,the UT1-UTC prediction algorithm and code based on the least square combined with autoregressive model of Earth’s fluid effective angular momentum are completed,and the UT1-UTC prediction method is improved and optimized.The main innovations of this paper are:Piecewise prediction of UT1-UTC is performed using a combination of least squares and autoregressive model.The paper divides the forecast span from 1 to 90 days into multiple prediction stages.For different UT1-UTC prediction stages,different autoregressive model orders are selected to achieve optimal prediction results.The paper conducts 526 UT1-UTC prediction experiments from 1 to 90 days and compares them with IERS EOP C04,IERS Bulletin A,Dill and traditional least squares combined with autoregressive model.The results show that 63.35% and 61.43% of the UT1-UTC prediction results from 1 to 10 days and 11 to 40 days are better than the IERS prediction,respectively.The mean absolute error of the UT1-UTC prediction on the first and sixth days are reduced by 23.81% and 36.84% compared with IERS,respectively.On the whole,the prediction method proposed in this paper is more suitable for short-term UT1-UTC prediction,and for medium and long-term prediction,by adopting a piecewise prediction strategy,it also has a good effect.(3)This paper makes a further research on the evaluation method of UT1-UTC prediction.In addition to the general mean absolute error,it also tries to use the root mean square error,median absolute error,maximum absolute error and absolute difference of prediction error to compare and evaluate different prediction methods.The results show that under all the above evaluation indicators,the prediction method of this paper can obtain results equivalent to the IERS prediction.The maximum absolute error is the largest absolute value of the prediction error under the same forecast span for many times,which indicates the worst forecasting situation of the prediction method and reflects the robustness of the prediction algorithm.On the 6th,30 th,and 90 th days of the forecast span,the maximum absolute errors of the UT1-UTC prediction in this paper are 0.601 ms,8.034 ms,23.363 ms,and the maximum absolute errors of the IERS UT1-UTC prediction are 1.550 ms,9.251 ms,and 29.179 ms,respectively.The results show that in the worst case of forecasting,the UT1-UTC prediction in the paper is still better than the IERS prediction,and the stability of the prediction method is also better than IERS.The python language UT1-UTC prediction program developed based on the research results of the paper has completed the deployment and routine operation of the Linux server environment,and has performed well in the second EOPPCC held by IERS recently.