# Evaluation of the Consistency of Three GRACE Gap-Filling Data
## 2 Materials and Methods
### View of EWH Results of SHCs in the Space Domain  
In the section, we give a perspective on the characteristics of different datasets when applied to study miscellaneous signals. The five sites given in Figure 4f cover three categories: Polar ice melting in Greenland (Figure 4a) and Antarctica (Figure 4b), terrestrial water storage changes in north India (Figure 4c) and the Amazon (Figure 4d), and seismic activity in eastern Japan (Figure 4e). Two types of EWH results were calculated from SHCs: EWH with d/o up to 60 and EWH with d/o up to 12 (to account for the limited spatial resolution of QF). As the effect of glacial isostatic adjustment (GIA) affects only linear trends, it was not considered here. It should be noted that the SSA data used the original GRACE observations for the period outside the gaps. Sites a and b are located in Greenland and Antarctica, respectively, where the polar ice sheets are melting rapidly as the global temperature rises in this century [44]. In Greenland (Figure 4a) and Antarctica (Figure 4b), the EWH series of SSA, IGG, and QF truncated to d/o 12 consistently reflect the long-term losses in the polar ice sheet mass, but IGG shows stronger volatility relative to the other two, especially in Antarctica. The volatility in IGG is more evident when referring to the d/o 60 results. Furthermore, it is shown that all three datasets have the potential to reconstruct the stable seasonal variation in Greenland during the gap months. Figure 3: Logarithmic (base 10) variances versus degree of SHCs of the IGG, QF, and SSA data during the 11-month gap (July 2017–May 2018). (**a–k**) denote the time series from July 2017 to May 2018, respectively. Sites c and d are located in northern India and the Amazon basin, respectively, two hotspots for research on changes in terrestrial water storage. Figure 4c illustrates the differences in the abilities of these data to monitor the serious groundwater depletion in north India [45]. It is obvious that the EWH results with d/o up to 12 failed to detect this long-term groundwater signal due to the low spatial resolution. The EWH results of IGG and SSA with d/o up to 60 can essentially capture this signal. However, there was a certain difference between SSA and IGG after August 2016, when the declining trend of IGG was significantly smaller than that of SSA. Since IGG did not use GRACE data after August 2016, we speculated that IGG may have underestimated the EWH trend in this region after 2016. The Amazon Basin has the world's greatest variations in water storage due to enormous precipitation, and its interannual variability in water storage is also influenced by El Nino Southern Oscillation (ENSO) events [46]. Figure 4d shows that the EWH series of SSA, IGG, and QF are in good agreement with each other, and all can reflect seasonal and interannual water storage changes in the Amazon Basin. It has been verified that GRACE is capable of observing the co-seismic and post-seismic signals caused by giant subduction earthquakes [47; 48]. Figure 4e illustrates the differences in the abilities of these data to monitor the gravity field signal of the M 9.0 earthquake in eastern Japan on 11 March 2011. It can be found that the EWH results with d/o up to 12 are not capable of monitoring the co-seismic or post-seismic signals. The EWH results of IGG and SSA with d/o up to 60 can essentially reflect the co-seismic signal and the post-seismic signal before August 2016. Furthermore, the SSA data connects the GRACE and GRACE-FO results seamlessly and roughly accurately depicts the gradual and persistent  
Figure 4: EWH time series from five sites in well-studied regions: (**a**) Greenland, (**b**) Antarctica, (**c**) north India, (**d**) Amazon, (**e**) eastern Japan. Subplot (**f**) shows the locations of these five sites. The gray ribbons represent the data gaps. post-seismic adjustment signal. Unfortunately, the IGG data appears to fail to reflect the persistent post-seismic adjustment signal after August 2016.