GRACE时变重力数据的后处理方法研究进展

Review of the Post-processing Methods on GRACE Time Varied Gravity Data

重力场是反映地球介质密度变化和在各种环境(固体地球潮汐、内部热流、固体和液体之间质量的交换、表面负荷和地震构造运动等)下动力学特征的最基本和最直接的物理量。GRACE(Gravity Recovery and Climate Experiment)卫星作为探测全球重力场的工具已经为科研工作者提供了超过10a的全球时变重力场数据。由于GRACE数据存在固有误差,GRACE数据产品需要进行后处理对局部重力场进行研究。回顾整理了GRACE数据后处理中的处理方法,包括高斯滤波法及非各向同性滤波法,位系数去相关法,主成分分析法,小波分解法,Slepian方法,以及顾及先验信息的改进算法等,并对GRACE后处理算法的后续改进和发展进行了展望。

The gravity field is a physical parameter reflecting the density change and dynamic characteristics of the earth under different circumstances including the solid earth tide,internal heat flow,mass exchange of solids and liquids,surface loads,and seismic tectonic movements.The time varied global gravity model has been provided by GRACE since 2002,but with the existing system error in GRACE and the need for focusing on local areas,post-processing is required when using GRACE products.In last decade,many algorithms have been shown to be effective.The ideas for these algorithms are reviewed in this article;a Gaussian filter with isotropic and non-isotropic types,the destriping filter,the empirical orthogonal functions method,wavelet analysis,and the Slepian function method.The future directions in post-processing algorithms are also discussed.