海底地形高次项对海面重力信息影响分析

Influence Analysis of High-order Seafloor Topography on Sea Surface Gravity Information

为了尽可能利用海面重力数据所含地形相关信息,提升依据重力数据反演海底地形结果质量,选择南中国海为试验海区,详细研讨了频率域不同阶次海底地形正演恢复海面重力异常和重力异常垂直梯度在不同海底地形环境下的影响。数值分析试验结果表明,一次项海底地形正演结果对重力信息贡献起主要作用,随着海底地形阶次的增加,相应阶次海底地形正演海面重力信息的幅度不断减弱;海底地形起伏剧烈且起伏幅度较大海区,高阶次海面重力异常和重力异常垂直梯度变化明显,而地形平坦海区正演的海面重力信息变化微弱;重力异常垂直梯度相比重力异常对海底地形高频部分更加敏感,在试验海区依据海面重力数据反演海底地形过程中,若输入数据源为重力异常,建议顾及至二次项海底地形,若输入数据源为重力异常垂直梯度,建议顾及至三次项或者四次项海底地形,从而尽可能利用海面重力数据所包含信息。

Objectives: In order to make the best use of seafloor topographic information contained in gravity data and improve the quality of seafloor topographic inversion results based on gravity data, the South China Sea is selected as the experimental sea area.Methods: The effects of different order seafloor in frequency domain are discussed in detail when recovering the gravity anomaly and vertical gravity gradient anomaly in different seafloor topographic environments.Results: The results of numerical analysis and experiment show that the results of one-time seafloor topographic play a major role in the contribution of gravity information. With the increase of the order of seafloor topography, the amplitude of gravity information decreases continuously. The high order gravity anomaly/vertical gravity gradient anomaly varies obviously in the sea area where the seafloor topography fluctuates sharply and its amplitude is larger, while gravity information varies slightly in the flat sea area. The vertical gravity gradient anomaly is more sensitive to high frequency part of seafloor topography than gravity anomaly.Conclusions: In the process of inversion of seafloor topography based on gravity data, if the input data source is gravity anomaly, it is suggested that the second term of seafloor topography should be taken into account. If the input data source is vertical gravity gradient anomaly, it is suggested that the third term or the fourth term of seafloor topography should be taken into account so as to make full use of the information contained in gravity data.