Abstract :
[en] 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.
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