Medium- and Long-Term Prediction of Polar Motion Using Weighted Least Squares Extrapolation and Vector Autoregressive Modeling

Figure 1.

Figure 2.

Figure 3.

Maximum absolute differences (in mas) between the pole coordinate observations and their predictions up to different prediction ranges

Prediction technology	xp					yp
	10 d	30 d	150 d	270 d	365 d	10 d	30 d	150 d	270 d	365 d
LS+AR	11.28	29.31	67.22	74.84	77.03	9.76	19.66	64.78	73.86	84.96
WLS+VAR (equal weights)	10.63	21.22	51.89	65.71	69.16	8.65	14.16	47.69	71.76	76.66
WLS+VAR (piecewise weights)	11.07	23.57	46.11	61.05	64.70	9.17	13.24	47.29	63.55	70.80

Mean absolute errors (in mas) for different prediction ranges by the LS+AR and WLS+VAR

Prediction technology	xp					yp
	10 d	30 d	150 d	270 d	365 d	10 d	30 d	150 d	270 d	365 d
LS+AR	2.93	7.71	21.83	24.57	30.86	1.94	5.43	21.90	24.04	27.90
WLS+VAR (equal weights)	2.90	7.15	15.22	20.35	22.69	1.79	4.27	15.91	22.88	23.40
WLS+VAR (piecewise weights)	2.87	7.03	13.97	18.47	20.52	1.81	4.41	15.41	21.17	21.82

Mean absolute errors (in mas) for different prediction ranges by the WLS+VAR and participants in the 1st EOP PCC

Prediction technology	xp					yp
	10 d	30 d	150 d	270 d	365 d	10 d	30 d	150 d	270 d	365 d
LS+AR (Kosek 051)	3.56	9.52	21.16	23.85	19.78	2.01	6.08	25.65	21.86	28.91
LS+AR (Kalarus 061)	3.33	8.78	19.36	17.46	14.50	1.83	5.01	21.28	25.10	21.32
AR (Zotov 091)	4.17	9.31	—	—	—	2.30	5.64	—	—	—
Neural networks (Zotov 093)	4.21	11.51	—	—	—	2.14	6.08	—	—	—
WLS+VAR (piecewise weights)	3.49	9.20	21.13	29.67	28.04	1.89	5.84	23.18	27.58	32.55