Improved baseline method for time-variable gravity field recovery

doi:10.11947/j.AGCS.2026.20250515

Abstract

Abstract:

To address the challenge of suppressing high-frequency errors in high-precision time-variable gravity field inversion, this paper investigates and develops the baseline method. An improved baseline inversion model is constructed by introducing a decorrelation method to optimize observation error processing and adopting a short-term time-variable parameter estimation strategy to enhance time-variable signal capture capability. The study focuses on comparing its performance with the traditional short-arc method in terms of spectral response and noise control. Based on 2021 GRACE-FO real data, monthly gravity field models up to degrees 60, 96, and 120 are derived. Results indicate that in the low-frequency band (below degree 30), both methods achieve comparable accuracy. However, in the mid-to-high frequency range (above degree 30), the improved baseline method significantly outperforms the short-arc method; notably, its cumulative geoid height error at degree 120 is reduced by approximately 8 cm, demonstrating superior capability in suppressing high-frequency noise. Furthermore, the model derived from the improved baseline method (referred to as the Baseline model) is validated against the CSR RL06.3 model released by Center for Space Research, University of Texas at Austin, the HUST-Grace2024 model released by Huazhong University of Science and Technology, and the Tongji-Grace2022 model released by Tongji University. The comparison reveals that the Baseline model achieves better overall accuracy above degree 60. The global equivalent water height derived from the Baseline model exhibits a more reasonable spatial distribution with less striping noise. Specifically, its RMSE over the ocean is significantly lower than that of the CSR RL06.3, HUST-Grace2024, and Tongji-Grace2022 models, and its signal-to-noise ratio is superior to these models, demonstrating optimal high-frequency noise suppression capability. The study concludes that the improved baseline method, through the combined enhancements of decorrelation processing and short-term time-variable parameterization, effectively improves the accuracy and stability of gravity field models in mid-to-high frequency bands, providing an effective approach for constructing high-resolution and high-reliability time-variable gravity field products.

Key words: improved baseline method, short-arc method, GRACE-FO, time-variable gravity field

CLC Number:

P228

Xiaolei YANG, Yun XIAO, Liqing YANG, Xiaodong HONG, Enze GUO, Han WANG. Improved baseline method for time-variable gravity field recovery[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(4): 708-720.

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References 25

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力模型	数据说明
静态重力场模型	GOCO06S
地球自转	IERS 2010
固体潮汐	IERS 2010
海洋潮汐	FES2014b
固体极潮	IERS 2010
海洋极潮	Desai 2004
大气潮汐	AOD1B RL06
大气和海洋去混频模型	AOD1B RL06
月球太阳行星星历表	JPL DE432
相对论效应	IERS 2010
卫星初始状态	位置和速度、局部参数、每弧段估计
加速度计尺度	全填充尺度矩阵、局部参数、每月估计
加速度计偏差	常数、局部参数、每天估计
天线相位中心变化	估计y和z轴方向参数、局部参数、每月估计
短时变参数	40阶次，局部参数，每天估计
时变重力场	60、96、120阶次，全局参数，每月估计

月份	模型	累计误差/cm			精度提升/（%）
月份	模型	60阶	96阶	120阶	60阶	96阶	120阶
4月	Baseline	2.16	4.32	11.87	3.57	32.81	33.28
4月	Short-arc	2.24	6.43	17.79	—	—	—
8月	Baseline	2.20	3.99	10.34	6.38	38.14	44.97
8月	Short-arc	2.35	6.45	18.79	—	—	—

时间	模型	RMSE/cm	RMSE降低比率/（%）	信噪比	信噪比提升比率/（%）
2021年8月	CSR RL06.3	12.94	29.52	1.84	29.35
	HUST-Grace2024	10.62	14.12	2.15	10.70
	Tongji-Grace2022	11.01	17.17	2.09	13.88
	Baseline模型	9.12	—	2.38	—
2021年9月	CSR RL06.3	13.12	26.98	1.89	26.46
	HUST-Grace2024	11.26	14.92	2.02	18.32
	Tongji-Grace2022	10.88	11.95	2.11	13.27
	Baseline模型	9.58	—	2.39	—