Common mode error in Antarctic GPS coordinate time series on its effect on bedrock-uplift estimates

Common mode error in Antarctic GPS coordinate time series on its effect on bedrock-uplift estimates Summary Spatially-correlated common mode error always exists in regional, or-larger, GPS networks. We applied independent component analysis (ICA) to GPS vertical coordinate time series in Antarctica from 2010 to 2014 and made a comparison with the principal component analysis (PCA). Using PCA/ICA, the time series can be decomposed into a set of temporal components and their spatial responses. We assume the components with common spatial responses are common mode error (CME). An average reduction of ∼40% about the RMS values was achieved in both PCA and ICA filtering. However, the common mode components obtained from the two approaches have different spatial and temporal features. ICA time series present interesting correlations with modeled atmospheric and non-tidal ocean loading displacements. A white noise (WN) plus power law noise (PL) model was adopted in the GPS velocity estimation using maximum likelihood estimation (MLE) analysis, with ∼55% reduction of the velocity uncertainties after filtering using ICA. Meanwhile, spatiotemporal filtering reduces the amplitude of PL and periodic terms in the GPS time series. Finally, we compare the GPS uplift velocities, after correction for elastic effects, with recent models of glacial isostatic adjustment (GIA). The agreements of the GPS observed velocities and four GIA models are generally improved after the spatiotemporal filtering, with a mean reduction of ∼0.9 mm/yr of the WRMS values, possibly allowing for more confident separation of various GIA model predictions. Satellite geodesy, Time series analysis, Space geodetic surveys, Antarctica © The Author(s) 2018. Published by Oxford University Press on behalf of The Royal Astronomical Society This article is published and distributed under the term of oxford University Press, standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geophysical Journal International Oxford University Press

Common mode error in Antarctic GPS coordinate time series on its effect on bedrock-uplift estimates

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Publisher
Oxford University Press
Copyright
© The Author(s) 2018. Published by Oxford University Press on behalf of The Royal Astronomical Society
ISSN
0956-540X
eISSN
1365-246X
D.O.I.
10.1093/gji/ggy217
Publisher site
See Article on Publisher Site

Abstract

Summary Spatially-correlated common mode error always exists in regional, or-larger, GPS networks. We applied independent component analysis (ICA) to GPS vertical coordinate time series in Antarctica from 2010 to 2014 and made a comparison with the principal component analysis (PCA). Using PCA/ICA, the time series can be decomposed into a set of temporal components and their spatial responses. We assume the components with common spatial responses are common mode error (CME). An average reduction of ∼40% about the RMS values was achieved in both PCA and ICA filtering. However, the common mode components obtained from the two approaches have different spatial and temporal features. ICA time series present interesting correlations with modeled atmospheric and non-tidal ocean loading displacements. A white noise (WN) plus power law noise (PL) model was adopted in the GPS velocity estimation using maximum likelihood estimation (MLE) analysis, with ∼55% reduction of the velocity uncertainties after filtering using ICA. Meanwhile, spatiotemporal filtering reduces the amplitude of PL and periodic terms in the GPS time series. Finally, we compare the GPS uplift velocities, after correction for elastic effects, with recent models of glacial isostatic adjustment (GIA). The agreements of the GPS observed velocities and four GIA models are generally improved after the spatiotemporal filtering, with a mean reduction of ∼0.9 mm/yr of the WRMS values, possibly allowing for more confident separation of various GIA model predictions. Satellite geodesy, Time series analysis, Space geodetic surveys, Antarctica © The Author(s) 2018. Published by Oxford University Press on behalf of The Royal Astronomical Society This article is published and distributed under the term of oxford University Press, standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Geophysical Journal InternationalOxford University Press

Published: May 29, 2018

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