摘要
针对GRACE卫星仅能探测到大空间尺度的重力变化,提出利用卫星测高数据反演高空间分辨率的海洋时变重力.首先将CryoSat-2卫星测高数据按月分组,基于每组海面高数据计算沿轨剩余大地水准面梯度和格网剩余垂线偏差,然后利用逆Vening-Meinesz公式反演月重力异常,最后基于全部月重力异常数据计算格网大小为3′的CryoSat-2时变重力.以孟加拉湾及其周边海域为例,在2011年2月—2020年4月间,CryoSat-2时变重力的周年振幅和周年相位分别为(0.10±0.03)μGal和98.84°±0.43°,同期GRACE数据的周年振幅和周年相位分别为(0.66±0.05)μGal和93.52°±0.08°,两者的周年信号基本一致;CryoSat-2和GRACE时变重力的线性趋势分别为(0.02±0.01)和(0.09±0.01)μGal/a,均表现为增长.结果表明:3′×3′格网的CryoSat-2时变重力能够反映出研究海域重力变化的季节性信号和长期趋势,验证了利用卫星测高数据反演高空间分辨率海洋时变重力的可行性.
Aiming at the GRACE satellites can only detect gravity variation at a large spatial scale,using altimetry data to derive high spatial resolution time-varying marine gravity was proposed.Firstly,the CryoSat-2 altimetry data were grouped by month,and the residual along-track geoid gradients and gridded deflections of the vertical were calculated based on each group of sea surface heights.Then the inverse Vening-Meinesz formula was used to derive monthly gravity anomalies data.Finally,the CryoSat-2 timevarying gravity with a grid size of 3′ were calculated based on all monthly gravity anomalies data.The Bay of Bengal and adjoining areas was selected as the study area,from February 2011 to April 2020,the annual amplitude and annual phase of CryoSat-2 timevarying gravity are(0.10±0.03) μGal and 98.84°±0.43°,the GRACE data for the same period are(0.66±0.05) μGal and 93.52°±0.08°,which show that their annual signals are consistent.In addition,the linear trend of CryoSat-2 and GRACE time-varying gravity is(0.02±0.01) and(0.09±0.01) μGal/year,both of which show growth.The results show that the CryoSat-2 time-varying gravity data with a grid size of 3’ can reflect the seasonal signals and long-term trend in the study area,the feasibility of deriving high spatial resolution time-varying marine gravity from altimetry data is verified.
作者
郭金运
朱风顺
刘新
常晓涛
GUO Jinyun;ZHU Fengshun;LIU Xin;CHANG Xiaotao(College of Geodesy and Geomatics,Shandong University of Science and Technology,Qingdao 266590,Shandong China;Land Satellite Remote Sensing Application Center of MNR,Beijing 100048,China)
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2023年第3期85-91,99,共8页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(42174041,41774001)
国家测绘自主可控专项(816-517)
山东科技大学科研创新团队支持计划资助项目(2014TDJH101)。
