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

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Abstract

Three different environmental loading methods are used to estimate surface displacements and correct non-linear 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 Combination Analysis software (QLM) and (3) our own daily loading time series (we call it OMD for 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 hydrology 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 of NCEP reanalysis hydrology data compared with the GLDAS model, the GGFC dataset is much more suitable than QLM for 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.

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Notes

  1. http://geophy.uni.lu/ggfc-about/products.html.

  2. http://www.esrl.noaa.gov/psd/data/gidded/data.ncep.reanalysis.surface.html.

  3. http://ecco.jpl.nasa.gov/thredds/las/kf080/catalog.html.

  4. http://www.esrl.noaa.gov/psd/data/gidded/data.ncep.reanalysis.surfaceflux.html.

  5. http://www-gpsg.mit.edu/~tah/MIT_IGS_AAC/index2.html.

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Acknowledgments

We thank the GGFC and NRCan for making the global loading and IGS station coordinate time series freely available. We thank D. N. Dong for providing the QOCA software. Figures in this paper are plotted with the GMT and MATLAB software. This research is supported by the National Natural Science Foundation of China (41074022), the National 863 program of China (2012AA12A209), together with the Independent Research Project of Wuhan University (3103002).

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Authors and Affiliations

  1. GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan, 430079, Hubei, China

    Weiping Jiang

  2. School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan, 430079, Hubei, China

    Zhao Li

  3. Faculté des Sciences, de la Technologieet de la Communication, University of Luxembourg, 6, rue Richard Coudenhove-Kalergi, L-1359, Luxembourg

    Tonie van Dam

  4. Institute of Geodesy and Geophysics, Chinese Academy of Sciences, 340 XuDong Road, Wuhan, 430077, Hubei, China

    Wenwu Ding

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  1. Weiping Jiang
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Correspondence to Weiping Jiang.

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Jiang, W., Li, Z., van Dam, T. et al. Comparative analysis of different environmental loading methods and their impacts on the GPS height time series. J Geod 87, 687–703 (2013). https://doi.org/10.1007/s00190-013-0642-3

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