Abstract
We apply multi-channel singular spectrum analysis (MSSA) to infer the main spatiotemporal modes of mass variability in North America derived from GRACE monthly gravity field data. MSSA is a data-adaptive method for analyzing time lagged maps of variability on regional and global scales. The method proves useful in studying the annual and long-term continental water mass variations and the secular deformation signal associated with glacial isostatic adjustment (GIA) of the Earth.
We study the capabilities of the MSSA method using simulated spatiotemporal data series and address issues such as lag-window length, spectral mixing, and significance of the extracted modes. We investigate two cases using the GRACE RL-04 data. We analyze water mass variations derived from the GRACE data (corrected for GIA) and compare our results with the main modes extracted from the GLDAS/Noah and WGHM continental water storage models. Good agreement between the annual amplitudes exists in the Cordillera region, the WGHM model being closer to GRACE compared to GLDAS/Noah. Furthermore, we model the North American GIA signal using the GRACE data corrected for hydrology. Two peak signals are observed west (9–11 mm/year uplift rate) and southeast (11–13 mm/year) of Hudson Bay in agreement with the multi-dome geometry of the North American ice sheet in the ICE-5G model.
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Acknowledgements
The authors gratefully acknowledge R. Peltier for the GIA model, M. Rodell for the GLDAS model and P. Döll and Dr. Fiedler for the WGHM model. The two anonymous reviewers are acknowledged for their very helpful comments. Financial support is provided by GEOIDE NCE and NSERC, Canada.
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Rangelova, E., van der Wal, W., Sideris, M.G., Wu, P. (2010). Spatiotemporal Analysis of the GRACE-Derived Mass Variations in North America by Means of Multi-Channel Singular Spectrum Analysis. In: Mertikas, S. (eds) Gravity, Geoid and Earth Observation. International Association of Geodesy Symposia, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10634-7_72
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DOI: https://doi.org/10.1007/978-3-642-10634-7_72
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