谷歌浏览器插件
订阅小程序
在清言上使用

The New AFRGDB_V2.2 Gravity Database for Africa

Pure and Applied Geophysics(2020)

引用 2|浏览11
暂无评分
摘要
The primary task of the IAG Sub-Commission on Gravity and Geoid in Africa is the development of the vertical reference surface (the geoid) for the entire African continent. For the practical solution of this boundary value problem, the available, arbitrarily distributed boundary data (gravity values) must be interpolated onto a regular grid for numerical reasons. In this paper it is explained in detail how to create this grid from the irregularly distributed point-gravity data. It is worth mentioning that this gravity database is not only used for geoid computation; it is also a stand-alone product used in earth sciences, as it reflects interesting geophysical signals. The gravity data available in this project are land and shipborne point gravity values as well as altimetry-derived gravity anomaly data. One challenge of preparing the homogeneous grid of gravity anomalies is caused by the inhomogeneous distribution of the observations and a lot of data gaps, especially on land. At these data gaps, gravity anomalies are provided on a so-called underlying grid from the GOCE DIR_R5 global reference model. One challenge in the framework of the least-squares prediction technique used is the determination of an empirical covariance function representing the behaviour of the irregularly distributed data points and the individual weights of the land, shipborne, and altimetry data and the underlying grid entering the process. A sophisticated filtering of the available gravity data is carried out to meet this challenge. The preprocessed data from the remove step are predicted to an equiangular $$5^{'} \times 5^{'}$$ grid. Finally, a consistent restore step leads to the AFRGDB_V2.2 gravity database. The precision of the developed gravity database has been studied to assess the quality of the new product. The new AFRGDB_V2.2 gravity database is compared to the preceding one (AFRGDB_V2.0), which was generated using the window remove-restore technique.
更多
查看译文
关键词
Africa,RTM reduction technique,gravity database,geoid determination,unequal weight least-squares prediction
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要