Hydrological loading induced vertical displacements from GPS and GRACE
4.7 Discussion and summary
1 10 20 30 40 46
No. of stations
IG IGD AG AGD DDK Regularization
BELE BOAV BOGA POVE NAUS CUIB AREQ BOGT BOMJ BUEN CALI CHPI CART CUCU GVAL IMPZ KOUR MABA MAPA MARA MCLA NEVA PERA PMB1 POPA PPTE QUI1 RECF RIOB RIOD ROJI SAGA SALU SAMA SRNW SRZN TOGU TOPL TUNA UBER UNSA VALL VICO VIVI BRAZ FLOR
−1.0 0.0 0.1 0.3 0.5 0.7 1.0
WRMS reduction wrt. GPS
Figure 4.22:The same as Fig.4.15but forWRMSreduction ratio at the seasonal signal level.
reduction ratio. These statistics indicate the strong agreements between the GPSobserved dis-placements and the estimated deformations fromGRACE at the seasonal level in the Amazon area. However, attentions should be paid on selecting the stations properly to make use of the seasonal displacements derived fromGRACEfor additional purposes, e.g. the aforementioned regional reference frame issue (Zou et al.,2013).
In addition, statistics shown in Table4.4confirms the conclusion of the best filter in the Amazon area. The regularization filter with λ = 4 outperforms other filtering schemes in both the monthly time series and the seasonal signals.
4.7 Discussion and summary 85
GPSdatasets from two study areas, i.e. the Europe area and the Amazon area. Strong correla-tions betweenGPSandGRACEare obtained in both areas. In Europe, all considered 40GPSsites have observed positiveWRMSreduction with respect to previous studies (e.g.,van Dam et al., 2007;Tregoning et al.,2009) which is a consequence of improvedGPSandGRACE data. In the Amazon area, high correlations,WRMSreductions andNSEvalues are observed in theGPSsites located in the central Amazon area. While for the sites located close to the coast, poor statistics are shown possibly in part due to the high impact of non-tidal oceanic loading effects, which are not accounted for in the GPS time series. The non-tidal oceanic loading induced displace-ments computed over 46GPSsites in the Amazon area using theECCOmodel show a meanRMS
value of 0.36 mm. What’s more, GRACE senses less hydrological loading information close to the coastline that the inland, which could also be attributed to poor statistics for stations close to the coast.
At the seasonal level, the agreements between GPS and GRACE are significant in both areas which might indicate the potential usage of the GRACE derived displacements for correcting hydrological loading signals buried in theGPStime series.
Concerning the effects of different filtering schemes used in this chapter, like other studies regarding GRACE filtering comparison (e.g.,Werth et al., 2009;Steffen et al.,2010), no single filtering scheme can produce consistent good results over the two different study areas. In view of singleGPS site, different filtering schemes can produce significant differences, for example, differentDDKfilters can produce a difference up to 19% atNAUSin terms of theWRMSreduction value. The differences will be even larger when comparing among all the considered filters.
However, it is not possible to tune filtering schemes for each site separately. Considering the mean performances, the used filters do not produce as big differences as single GPS station.
Nevertheless, the optimal filters for both areas are obtained and several common features of filters for the two study areas are observed.
In the deterministic filter group, we arrive at the same conclusion asKing et al.(2006) that a smoothing radius around 500 km reaches best performance if only the isotropic Gaussian filter is applied. However, this is not true when combined with the destriping filter. The advantage of combining the destriping filter with the isotropic Gaussian filter is demonstrated in both study areas. It is highly recommended to use the Gaussian filter with a low smoothing radius, e.g. around 300 km, combined with the destriping filter, which produces consistent good re-sults in both the Europe area and the Amazon area with respect to other deterministic filtering scenarios. The performance of the anisotropic Gaussian filter decreases with increasing the smoothing radius. Besides, the anisotropic Gaussian filter only shows its better performance as opposed to the Gaussian filter at low smoothing radii. However, this point is not held when they are combined with the destriping filter. In view of the performance of all deterministic filters, the study concludes the optimal filtering scheme in this filter group is the combination of the Gaussian filter of a low smoothing radius with the destriping filter.
In the stochastic filter group, the DDK 1 filter displays better performance in the Europe area while the regularization filter ofλ=4 stands out in the Amazon area. These two filter schemes outperform other filters respectively in the two study areas. It is shown that the performance of the DDK filters depends on the study area. The DDK 1 and DDK 2 which show good per-formances in the Europe area turn out to be inferior to other DDK filters in the Amazon area.
While in the regularization filter group, the parameterλ=4 turns out to produce consistently better and reliable results.
In view of both the deterministic filters and the stochastic filters, the stochastic filter generally demonstrates better performance in both study areas.
It is worth mentioning that the DDK 5 filter produces the highest spatial resolution deforma-tion maps in both study areas. However, the high spatial resoludeforma-tion in grids does not help to improve the consistency between theGPS-observed and the GRACE-derived vertical displace-ments. We attribute this phenomenon to the fact that GPS measurements are point samples whileGRACEprovides low spatial resolution products, which leads to the agreement between theGPS-observed and theGRACE-derived vertical deformations depending highly on the dis-tribution of theGPSsites.
In conclusion, the study in this chapter presents results and experiences regarding evaluating different filtering schemes when comparingGPSandGRACE, which could serve as a reference for future studies concerning GPS and GRACE comparison. In addition, the GRACE follow-on missifollow-on, which is simply a copy of the GRACE mission, is planned to be launched in 2017 (Sheard et al.,2012; Flechtner et al., 2014b). The conclusions and experiences obtained from the study in this chapter could be possibly applied in the products delivered by the GRACE
follow-on mission in the future.
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