[1]ZHAN Wei,LI Jingwei.Extraction and Analysis of the Common-mode Component of GNSS Time Series in Yunnan[J].Journal of Seismological Research,2021,44(01):56-63.
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Extraction and Analysis of the Common-mode Component of GNSS Time Series in Yunnan
Journal of Seismological Research[ISSN 1000-0666/CN 53-1062/P] Volume:
44
Number of periods:
2021 01
Page number:
56-63
Column:
Public date:
2021-01-15
- Title:
- Extraction and Analysis of the Common-mode Component of GNSS Time Series in Yunnan
- Keywords:
- time series; common mode component; evaluation of two methods; stacking method; principal component analysis
- CLC:
- P315.73
- DOI:
- -
- Abstract:
- For the accurate acquisition of the common-mode component(CMC),two commonly used methods are selected,namely the stacking method and the principal component analysis(PCA)method. Then,based on the vertical time series of 31 continuous GNSS stations in the period 2011-2018 in Yunnan,the effects of the two methods are evaluated. The results show that:①Due to the good spatial consistency of the vertical nonlinear motion in Yunnan(the average correlation coefficient between stations is 0.88),the CMCs obtained by the two methods are relatively close. ②The extracted CMCs are consistent with the vertical time series given by the global hydrological mass loading model and the atmospheric mass loading model(the correlation coefficients are both 0.9),which indicates that the main components of the CMCs are the non-tectonic,vertical,crustal movement induced by the variations of surface loading.③The CMC cannot be fully represented by the periodic model,for it also contains information such as inter-annual variation. ④The spatial filtering effect of the two methods is very close to the average WRMS Reduction Ratio of 0.70. The spatial filtering effects of the stations were significantly and positively correlated with the inter-station correlation coefficients. Since the stacking method requires relatively low data-integrity rate,it is suggested to use the stacking method when there are few continuous GNSS stations or a lot of missing data. The PCA method is recommended in areas with dense continuous GNSS network and high data-integrity rate,which shows the difference in the amplitude of the movement from year to year.
- References:
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Last Update:
2021-01-15