Comparative analysis of different environmental loading methods and their impacts on the GPS height time series

• Published in: Journal of Geodesy
• Main Authors: Jiang, Weiping, Li, Zhao, van Dam, Tonie, Ding, Wenwu
• Other Authors: ULHPC - University of Luxembourg: High Performance Computing
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer-Verlag 2013
• Subjects: Environmental loading; GGFC; QOCA; GPS height coordinate time series; Physical; chemical; mathematical & earth Sciences; Earth sciences & physical geography; Physique; chimie; mathématiques & sciences de la terre; Sciences de la terre & géographie physique; Greenland
• Online Access: https://orbilu.uni.lu/handle/10993/4978; https://doi.org/10.1007/s00190-013-0642-3

peer reviewed Three different environmental loading methods are used to estimate surface displacements and correct nonlinear variations in a set of GPS weekly height time series. Loading data are provided by (1) Global Geophysical Fluid Center (GGFC), (2) Loading Model of Quasi-Observation CombinationAnalysis software (QLM) and (3) our own daily loading time series (we call itOMDfor optimum model data). We find that OMD has the smallest scatter in height across the selected 233 globally distributed GPS reference stations, GGFC has the next smallest variability, and QLM has the largest scatter. By removing the load-induced height changes from the GPS height time series, we are able to reduce the scatter on 74, 64 and 41 % of the stations using the OMD models, the GGFC model and QLM model respectively. We demonstrate that the discrepancy between the center of earth (CE) and the center of figure (CF) reference frames can be ignored. The most important differences between the predicted models are caused by (1) differences in the hydrol- ogy data from the National Center for Atmospheric Research (NCEP) vs. those from the Global Land Data Assimilation System (GLDAS), (2) grid interpolation, and (3) whether the topographic effect is removed or not. Both QLM and GGFC are extremely convenient tools for non-specialists to use to calculate loading effects. Due to the limitation ofNCEP reanalysis hydrology data compared with theGLDAS model, theGGFCdataset is much more suitable thanQLMfor applying environmental loading corrections to GPS height time series. However, loading results for Greenland from GGFC should be discarded since hydrology data from GLDAS in this region are not accurate. The QLM model is equivalent to OMD in Greenland and, hence, could be used as a complement to the GGFC product to model the load in this region. We find that the predicted loading from all three models cannot reduce the scatter of the height coordinate for some stations in Europe.