High accuracy vertical gradient of gravity anomaly model determined from SWOT/KaRIn altimetry data during scientific phase

doi:10.11947/j.AGCS.2025.20240520

Abstract

Abstract:

Satellite altimetry is a crucial technique for determining the marine vertical gradient of gravity anomaly. One-dimensional altimetry data suffer from large sampling intervals, sparse across-track data, and low precision. In comparison, the surface water and ocean topography (SWOT) altimetry satellite provides two-dimensional wide-range ocean information, achieving higher spatial resolution and accuracy in sea surface height measurements. Therefore, this paper presents a vertical gradient of gravity anomaly (SWOT_VGGA) model based on SWOT sea surface height data from cycles 1 to 20. The remove-restore technique was employed as the processing strategy, selecting XGM2019e_2159 as the reference gravity field model. The deflection of vertical was computed by combining along-track, cross-track, and diagonal-track altimetry data through least squares collocation. Based on the deflection of the vertical and the reference gravity field, the SWOT_VGGA model was obtained. This study focused on the Philippine Sea, with the vertical gravity gradient anomaly from SIO V32.1 employed as the reference. The results show an 8.25 E consistency between the SWOT_VGGA and SIO_curv_32.1 models, confirming the reliability of SWOT-derived vertical gradient of gravity anomaly from one year of SWOT altimetry data. Additionally, the model consistency was assessed across varying water depths, distances, and seafloor slope angles. Furthermore, the multi-cycle model exhibited better consistency than the single-cycle model. Specifically, the discrepancy between its 1~10 and 11~20 cycle subsets was only 1.81 E. This demonstrates that the data quality of the SWOT satellite exhibits stability across different cycles, making it suitable for inverting high-precision marine gravity information.

Key words: SWOT altimetry satellite, sea surface height, deflection of the vertical, vertical gradient of gravity anomaly, remove-restore method

CLC Number:

P223

Shaoshuai YA, Xin LIU, Ruichen ZHOU, Zhen LI, Shaofeng BIAN, Jinyun GUO. High accuracy vertical gradient of gravity anomaly model determined from SWOT/KaRIn altimetry data during scientific phase[J]. Acta Geodaetica et Cartographica Sinica, 2025, 54(9): 1583-1595.

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周期	数量	最大值	最小值	均值	标准差	均方根
1～20	1 442 392	0.061	－0.061	0.000	0.016	0.016
5	1 278 929	0.203	－0.203	0.002	0.059	0.059
10	1 332 836	0.183	－0.183	0.003	0.053	0.053
13	1 303 739	0.202	－0.202	－0.001	0.059	0.059
20	1 234 200	0.194	－0.194	0.000	0.058	0.058

不同分量	最大值	最小值	均值	标准差	均方根
北分量	80.86	－62.76	0.02	1.93	1.93
东分量	132.62	－67.95	0.05	2.53	2.53

不同水深/m	最大值/E	最小值/E	均值/E	标准差/E	均方根/E
（0，1000]	358.06	－373.53	－0.24	16.22	16.22
（1000，2000]	193.31	－391.04	0.30	12.94	12.95
（2000，3000]	144.86	－75.15	－0.13	9.05	9.05
（3000，4000]	80.89	－56.94	0.04	7.26	7.26
（4000，5000]	70.61	－41.99	0.08	5.90	5.90
（5000，∞）	42.52	－43.61	0.19	4.92	4.93

离岸距离/km	最大值/E	最小值/E	均值/E	标准差/E	均方根/E
（0，50]	358.06	－391.04	0.44	18.93	18.93
（50，100]	154.91	－228.64	0.03	8.19	8.19
（100，150]	65.81	－79.51	0.05	6.94	6.95
（150，200]	62.85	－55.56	0.05	6.48	6.48
（200，250]	56.06	－44.07	0.03	6.22	6.22
（250，300]	43.61	－71.04	0.02	6.16	6.16
（300，∞）	94.65	－76.67	0.02	5.74	5.74

坡角/（°）	最大值/E	最小值/E	均值/E	标准差/E	均方根/E
[0，2]	358.06	－274.77	0.15	7.00	7.00
（2，4]	273.40	－228.53	0.05	8.00	8.00
（4，6]	278.89	－316.45	－0.03	9.11	9.11
（6，8]	222.55	－253.63	－0.10	9.77	9.77
（8，10]	220.55	－248.45	－0.01	10.55	10.55
（10，∞）	211.07	－391.04	－0.10	11.97	11.97