## 3 Results and Discussions
### Consistency Analysis between GNSS, GRACE and GGFC
#### 3.1.4 Remaining Disagreements between GNSS and GRACE or GGFC  
After subtracting GRACE or GGFC modeled non-tidal deformations from IG2 solutions, seasonal signals still occur in the GNSS corrected by GRACE solutions and GNSS corrected by GGFC solutions, indicating the disagreement existing among the different techniques. There are two main error sources leading to the disagreement.  
Firstly, there are shortcomings in the inversion process for both GRACE and GGFC models. The spatial resolutions, with about 300 km for GRACE and 2.5\({}^{\circ}\) grid for GGFC, denote that the two types of models have difficulties in distinguishing the surface mass loading appearing in small regional areas. The research of [20] demonstrated that the GRACE VDs from different institutes and different approaches are highly consistent. The incorporation of the degree 1 surface load coefficients from the GNSS deformations into GRACE computations can further improve comparisons. The GRACE follow-on plan also has great potential to correct the non-tidal loading in GNSS time series more effectively. For all GGFC datasets, ATML is modeled using input from the NCEP surface pressure grids, NTOL is modeled using the ECCO data as input, and CWS is modeled using the GLDAS data soil moisture and snow water equivalent. Both the original loading data and interpolation can introduce errors, especially for stations on ocean islands or small peninsulas where the physically expected loading signals are very small.  
Secondly, GNSS signals not only contain the impacts of hydrology, non-tidal atmosphere, ocean tides, but also GNSS technique-related errors in data processing, such as processing noise effect, local multipath, and orbital errors. Previous researches have investigated the signals related to possible aspects in GNSS data processing, such as the draconitic errors caused by solar radiation pressure [34], satellite constellation and local multipath effects [33], unmodelled high frequency signals caused by S1 and S2 atmospheric pressure tides loading [48], subdaily EOP model, the effect of the thermal expansion of monuments and nearby bedrock [49]. The results indicate that the effect of these errors or mismodeling errors is related to seasonal signals in GNSS coordinate time series, but are not significant enough when comparing to the residuals between GNSS and GRACE/GMs data, and investigations on the ideal model for the effect of the mismodeling errors on GNSS data processing are still ongoing [48; 49; 50; 51; 52]. By the start of October 2019, the IGS ACs had begun the third reanalysis of the full history of GNSS data collected by the IGS global network since 1994 in a fully consistent way using the latest models and methodology.  
However, it is difficult to provide the accurate/precise amplitudes of the above sources right now. In the following section, we do not try to declare the exact effects of the above options, but introduce one further aspect that reflects the total effect of the related errors, that is the noise in the coordinate time series [53; 54; 55]. GNSS measurements of position are temporally and spatially correlated rather than simply independent observations. The temporally correlated process for noise might characterize localized, random motions of the geodetic monument, the analysis errors in GNSS data processing, and the non-tidal loading effects. Therefore, we can adopt the noise characteristics as an indicator to decide which type of the non-tidal loading interpretation is better for the global IG2 coordinate time series.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Index** & **Monthly Solutions** & **Weekly Solutions** \\ \hline Annual amplitudes and phases & 2.6 mm/176.9\({}^{\circ}\) & 2.6 mm/167.5\({}^{\circ}\) \\ Stations with WRMS reduction & 74\% & 73\% \\ Mean values of WRMS variations & \(-\)5.6\% & \(-\)5.4\% \\ Correlation coefficients & 0.45 & 0.44 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistical results of the GNSS and GGFC with different sampling rates.