Global Surface Mass Variations from Continuous GPS Observations and Satellite Altimetry Data

doi:10.3390/rs9101000

NTSC-IR

	Global Surface Mass Variations from Continuous GPS Observations and Satellite Altimetry Data
	Zhang, Xinggang 1; Jin, Shuanggen 2; Lu, Xiaochun1
	2017-10-01
发表期刊	REMOTE SENSING
ISSN	2072-4292
卷号	9 期号:10 页码:26
摘要	The Gravity Recovery and Climate Experiment (GRACE) mission is able to observe the global large-scale mass and water cycle for the first time with unprecedented spatial and temporal resolution. However, no other time-varying gravity fields validate GRACE. Furthermore, the C-20 of GRACE is poor, and no GRACE data are available before 2002 and there will likely be a gap between the GRACE and GRACE-FOLLOW-ON mission. To compensate for GRACE's shortcomings, in this paper, we provide an alternative way to invert Earth's time-varying gravity field, using a priori degree variance as a constraint on amplitudes of Stoke's coefficients up to degree and order 60, by combining continuous GPS coordinate time series and satellite altimetry (SA) mean sea level anomaly data from January 2003 to December 2012. Analysis results show that our estimated zonal low-degree gravity coefficients agree well with those of GRACE, and large-scale mass distributions are also investigated and assessed. It was clear that our method effectively detected global large-scale mass changes, which is consistent with GRACE observations and the GLDAS model, revealing the minimums of annual water cycle in the Amazon in September and October. The global mean mass uncertainty of our solution is about two times larger than that of GRACE after applying a Gaussian spatial filter with a half wavelength at 500 km. The sensitivity analysis further shows that ground GPS observations dominate the lower-degree coefficients but fail to contribute to the higher-degree coefficients, while SA plays a complementary role at higher-degree coefficients. Consequently, a comparison in both the spherical harmonic and geographic domain confirms our global inversion for the time-varying gravity field from GPS and Satellite Altimetry.
关键词	GNSS satellite altimetry time-varying gravity field mass redistribution
资助者	Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC)
DOI	10.3390/rs9101000
关键词[WOS]	SEA-LEVEL ; EARTHS OBLATENESS ; GEOCENTER MOTION ; GRAVITY-FIELD ; TIME-SERIES ; GRACE ; VARIABILITY ; REDISTRIBUTION ; INVERSION
语种	英语
资助项目	Chinese Academy of Sciences (CAS)[29Y607YR000103] ; Chinese Academy of Sciences, Russia[2BY711HZ000101] ; Chinese Academy of Sciences, Ukraine[2BY711HZ000101] ; National Natural Science Foundation of China (NSFC)[11373059] ; National Natural Science Foundation of China (NSFC)[61501430]
资助者	Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences (CAS) ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Russia ; Chinese Academy of Sciences, Ukraine ; Chinese Academy of Sciences, Ukraine ; National Natural Science Foundation of China (NSFC) ; National Natural Science Foundation of China (NSFC)
WOS研究方向	Remote Sensing
WOS类目	Remote Sensing
WOS记录号	WOS:000414650600030
出版者	MDPI AG
引用统计
文献类型	期刊论文
条目标识符	http://210.72.145.45/handle/361003/11466
专题	中国科学院国家授时中心
通讯作者	Zhang, Xinggang; Jin, Shuanggen
作者单位	1.Chinese Acad Sci, Natl Time Serv Ctr, Xian 710600, Shaanxi, Peoples R China 2.Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Xinggang,Jin, Shuanggen,Lu, Xiaochun. Global Surface Mass Variations from Continuous GPS Observations and Satellite Altimetry Data[J]. REMOTE SENSING,2017,9(10):26.
APA	Zhang, Xinggang,Jin, Shuanggen,&Lu, Xiaochun.(2017).Global Surface Mass Variations from Continuous GPS Observations and Satellite Altimetry Data.REMOTE SENSING,9(10),26.
MLA	Zhang, Xinggang,et al."Global Surface Mass Variations from Continuous GPS Observations and Satellite Altimetry Data".REMOTE SENSING 9.10(2017):26.