Joint Reprocessing of Shipborne Gravity Anomalies Based on MultiSources:A Case Study of the Gulf of Mexico
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摘要: 船载重力异常数据对于海洋重力场模型的构建起着至关重要的作用。虽然现有的船载重力异常数据在当初获取时已经经过重力测量常规改正、测量环境动态效应改正等处理,但是船载重力异常数据跨度时间较长,测量机构、所使用的重力仪与参考基准均不尽相同,体现出一种多来源的特性;同时受到当时测量技术与数据处理技术的限制,获得的数据质量参差不齐,含有较大的误差,很难被直接应用。针对此问题,本文构建了一种多来源船载重力异常数据的联合再处理方法,分别从粗差剔除、长波误差改正、交叉点平差与系统误差补偿等方面对航线进行精化处理。以墨西哥湾为例,在美国国家环境信息中心(NationalCenters for Environmental Information,NCEI)获取该区域的船载重力异常数据,首先通过对比参考重力场对粗差航线及剩余航线粗差点进行剔除;其次基于正常重力公式推导的二次多项式模型对测线长波误差进行改正;最后基于交叉点不符值,通过交叉点条件平差与构建混合多项式模型相结合的方法对航线观测值进行误差推估与系统误差补偿。经过一系列联合处理方法之后,船载重力异常交叉点不符值的均方根(RMS)由原始数据的12.1mGal减少至3.7mGal,与重力异常模型SIO V32.1的残差RMS由精化前的6.62mGal减少至3.91mGal。最后对两组航线数据与模型的差值做频率域分析,结果表明误差的功率谱密度在各频率域上都得到明显减弱。以上结果均表明经过本文联合处理方法之后,船载数据质量得到了明显改善,该方法可用于进一步优化全球船载重力异常数据,从而为高精度的海洋重力场模型构建提供可靠数据集。Abstract: Objectives: Shipborne gravity anomaly data plays a crucial role in the construction of marine gravity field models. Although the existing shipborne gravity anomaly data have undergone conventional gravity measurement corrections and dynamic environmental effect corrections at the time of acquisition, the data span a long time period, involve multiple measurement agencies, gravity instruments, and reference frames, and thus exhibit a multi-source characteristic. Furthermore, due to the limitations of measurement and data processing techniques at the time of acquisition, the quality of the data varies and contains significant errors, making direct application difficult. Methods: In this study, a joint reprocessing method for multi-source shipborne gravity anomaly data is proposed, which refines the ship tracks through outlier elimination, long-wavelength error correction, intersection point adjustment, and systematic error compensation. First, rough tracks and remaining rough points were eliminated by comparing them with the reference gravity field; second, a quadratic polynomial model derived from the normal gravity formula was used to correct the long-wavelength error of the survey lines; finally, the error estimation and systematic error compensation of the observed values were performed through intersection point condition adjustment and the construction of a mixed polynomial model. Results: Taking the Gulf of Mexico as an example, shipborne gravity anomaly data in this region were obtained from the National Centers for Environmental Information (NCEI). After a series of joint processing methods, the root mean square (RMS) of crossover differences is reduced from 12.1mGal to 3.7mGal, and the residual RMS of gravity anomaly model SIO V32.1 is reduced from 6.62mGal before refinement to 3.91mGal. The difference between the two sets of ship tracks and the model was analyzed in the frequency domain, and the power spectral density of the error was significantly reduced in all frequency domains. Conclusions: As this study combined shipborne gravity data from different periods for joint processing, the final processing results have a certain gap compared to the precision of modern high-precision shipborne gravity measurements. However, overall, the accuracy of shipborne data has been significantly improved, which greatly enhances the utilization rate of shipborne data. This method can be used to further optimize global shipborne gravity anomaly data, providing a reliable dataset for constructing high-precision ocean gravity field models.
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