Home Application of singular spectrum analysis in reconstruction of the annual signal from GRACE
Article
Licensed
Unlicensed Requires Authentication

Application of singular spectrum analysis in reconstruction of the annual signal from GRACE

  • Chuandong Zhu ORCID logo EMAIL logo , Wei Zhan , Jinzhao Liu and Ming Chen
Published/Copyright: April 22, 2020
Become an author with De Gruyter Brill

Abstract

The mixture effect of the long-term variations is a main challenge in single channel singular spectrum analysis (SSA) for the reconstruction of the annual signal from GRACE data. In this paper, a nonlinear long-term variations deduction method is used to improve the accuracy of annual signal reconstructed from GRACE data using SSA. Our method can identify and eliminate the nonlinear long-term variations of the equivalent water height time series recovered from GRACE. Therefore the mixture effect of the long-term variations can be avoided in the annual modes of SSA. For the global terrestrial water recovered from GRACE, the peak to peak value of the annual signal is between 1.4 cm and 126.9 cm, with an average of 11.7 cm. After the long-term and the annual term have been deducted, the standard deviation of residual time series is between 0.9 cm and 9.9 cm, with an average of 2.1 cm. Compared with the traditional least squares fitting method, our method can reflect the dynamic change of the annual signal in global terrestrial water, more accurately with an uncertainty of between 0.3 cm and 2.9 cm.

Award Identifier / Grant number: 41804010

Award Identifier / Grant number: 41704084

Award Identifier / Grant number: 2018YFC1503606

Funding statement: This research is financially supported by the National Natural Science Foundation of China, No. 41804010, 41704084; Science for Earthquake Resilience, No. XH194204Y; National Key Research and Development Program of China, No. 2018YFC1503606.

Acknowledgment

We acknowledge the CSR, JPL and GFZ for providing the GRACE data. We thank the editor and anonymous reviewers for their insightful comments, which help to improve the quality of this paper.

  1. Author contributions: CDZ contributed to the design of the study, data processing, analysis of results, and manuscript writing. WZ and JZL contributed to the analysis of results. MC contributed to reviewing and editing the manuscript.

  2. Conflict of interest: All the authors declare no competing financial and non-financial interests.

References

[1] Tapley B D, Bettadpur S, Ries J C, et al. GRACE measurements of mass variability in the Earth system. Science, 2004, 305(5683): 503–505.10.1126/science.1099192Search in Google Scholar PubMed

[2] Tapley B D, Watkins M M, Flechtner F, et al. Contributions of GRACE to understanding climate change. Nature climate change, 2019, 9(5): 358–369.10.1038/s41558-019-0456-2Search in Google Scholar PubMed PubMed Central

[3] Scanlon B R, Zhang Z, Rateb A, et al. Tracking seasonal fluctuations in land water storage using global models and GRACE satellites. Geophysical Research Letters, 2019, 46(10): 5254–5264.10.1029/2018GL081836Search in Google Scholar

[4] Dam T V, Wahr J, Lavallée J. A comparison of annual vertical crustal displacements from GPS and Gravity Recovery and Climate Experiment (GRACE) over Europe. Journal of Geophysical Research: Solid Earth, 2007, 112.10.1029/2006JB004335Search in Google Scholar

[5] Fu Y, Freymueller J. Seasonal and long-term vertical deformation in the Nepal Himalaya constrained by GPS and GRACE measurements. J Geophys Res, 2012, 117(B3): B03407.10.1029/2011JB008925Search in Google Scholar

[6] Chanard K, Avouac J P, Ramillien G, et al. Modeling deformation induced by seasonal variations of continental water in the Himalaya region: Sensitivity to Earth elastic structure. J Geophys Res, 2014, 119(6): 5097–5113.10.1002/2013JB010451Search in Google Scholar

[7] Wang L S, Chen C, Du J S. Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS. Hydrol Earth Syst Sci, 2017, 21(6): 2905–2922.10.5194/hess-21-2905-2017Search in Google Scholar

[8] Zhan W, Li F, Hao W F, et al. Regional characteristics and influencing factors of seasonal vertical crustal motions in Yunnan, China. Geophys J Int, 2017, 210(3): 1295–1304.10.1093/gji/ggx246Search in Google Scholar

[9] Jiang W, Yuan P, Chen H, et al. Annual variations of monsoon and drought detected by GPS: A case study in Yunnan, China. Scientific Reports, 2017, 7(1): 5874.10.1038/s41598-017-06095-1Search in Google Scholar PubMed PubMed Central

[10] Pan Y, Shen W B, Shum C K, et al. Spatially varying surface seasonal oscillations and 3-D crustal deformation of the Tibetan Plateau derived from GPS and GRACE data. Earth and Planetary Science Letters, 2018, 502: 12–22.10.1016/j.epsl.2018.08.037Search in Google Scholar

[11] Yan J, Dong D D, Roland B, et al. Separation of Sources of Seasonal Uplift in China Using Independent Component Analysis of GNSS Time Series. Journal of Geophysical Research: Solid Earth, 2019.10.1029/2019JB018139Search in Google Scholar

[12] Wang X, Cheng Y, Wu S, et al. An enhanced singular spectrum analysis method for constructing nonsecular model of GPS site movement. Journal of Geophysical Research: Solid Earth, 2016, 121(3): 2193–2211.10.1002/2015JB012573Search in Google Scholar

[13] Yue D, Xu C, et al. Monte Carlo SSA to detect time-variable seasonal oscillations from GPS-derived site position time series. Tectonophysics International Journal of Geotectonics & the Geology & Physics of the Interior of the Earth, 2015.Search in Google Scholar

[14] Gruszczynska M, Klos A, Gruszczynski M, et al. Investigation of time-changeable seasonal components in the GPS height time series: A case study for Central Europe. Acta Geodyn. Geomater, 2016, 13(3(183)): 281–289.10.13168/AGG.2016.0010Search in Google Scholar

[15] Li Z, Yue J, Li W, et al. Investigating mass loading contributes of annual GPS observations for the Eurasian plate. Journal of geodynamics, 2017, 111.10.1016/j.jog.2017.07.001Search in Google Scholar

[16] Klos A, Bos M S, Bogusz J. Detecting time-varying seasonal signal in GPS position time series with different noise levels. GPS Solutions, 2018, 22(1): 21.10.1007/s10291-017-0686-6Search in Google Scholar

[17] Khazraei S M, Amiri-Simkooei A R. On the application of Monte Carlo singular spectrum analysis to GPS position time series. Journal of Geodesy, 2019.10.1007/s00190-019-01253-xSearch in Google Scholar

[18] Velicogna I. Measurements of Time-Variable Gravity Show Mass Loss in Antarctica. Science, 2006, 311(5768): 1754–1756.10.1126/science.1123785Search in Google Scholar PubMed

[19] Chen J L, Wilson C R, Blankenship D, et al. Accelerated Antarctic ice loss from satellite gravity measurements. Nature Geoscience, 2009, 2(12): 859–862.10.1038/ngeo694Search in Google Scholar

[20] Chen J L, Wilson C R, Tapley B D. Interannual variability of Greenland ice losses from satellite gravimetry. Journal of Geophysical Research: Solid Earth, 2011, 116(B7).10.1029/2010JB007789Search in Google Scholar

[21] Ogawa R, Chao B F, Heki K. Acceleration Signal in GRACE Time-variable Gravity in Relation to Interannual Hydrological Changes. Geophysical Journal International, 2011, 184(2): 673–679.10.1111/j.1365-246X.2010.04843.xSearch in Google Scholar

[22] Rangelova E, Sideris M G, Kim J W. On the Capabilities of the Multi-channel Singular Spectrum Method for Extracting the Main Periodic and Non-periodic Variability from Weekly GRACE data. Journal of Geodynamics, 2012, 54(2): 64–78.10.1016/j.jog.2011.10.006Search in Google Scholar

[23] Guo J, Li W, Chang X, et al. Terrestrial Water Storage Changes over Xinjiang Extracted by Combining Gaussian filter and Multichannel Singular Spectrum Analysis from GRACE. Geophysical Journal International, 2018, 213(1): 397–407.10.1093/gji/ggy006Search in Google Scholar

[24] Prevost P, Chanard K, Fleitout L, et al. Data-adaptive spatio-temporal filtering of GRACE data. Geophysical Journal International, 2019, 219(3): 2034–2055.10.1093/gji/ggz409Search in Google Scholar

[25] Linage C, Kim H, Famiglietti J S, et al. Impact of Pacific and Atlantic Sea Surface Temperatures on Interannual and Decadal Variations of GRACE Land Water Storage in Tropical South America. Journal of Geophysical Research: Atmospheres, 2013, 118(19): 10,811–10,829.10.1002/jgrd.50820Search in Google Scholar

[26] Ghil M, Allen M R, Dettinger M D, et al. Advanced Spectral Methods for Climatic Time Series. Reviews of geophysics, 2002, 40(1): 3-1–3-41.10.1029/2000RG000092Search in Google Scholar

[27] Groth A, Ghil M. Multivariate singular spectrum analysis and the road to phase synchronization. Physical Review E, 2011, 84(3): 036206.10.1103/PhysRevE.84.036206Search in Google Scholar PubMed

[28] Chen Q, van Dam T, Sneeuw N, et al. Singular spectrum analysis for modeling seasonal signals from GPS time series. Journal of Geodynamics, 2013, 72: 25–35.10.1016/j.jog.2013.05.005Search in Google Scholar

[29] Swenson S, Chambers D, Wahr J. Estimating Geocenter Variations from a Combination of GRACE and Ocean Model Output. Journal of Geophysical Research: Solid Earth, 2008, 113(B8): B08410.10.1029/2007JB005338Search in Google Scholar

[30] Cheng M, Tapley B D. Variations in the Earth’s oblateness during the past 28 years. Journal of Geophysical Research: Solid Earth, 2004, 109(B9).10.1029/2004JB003028Search in Google Scholar

[31] Wahr J, Molenaar M, Bryan F. Time Variability of the Earth’s Gravity Field: Hydrological and Oceanic Effects and Their Possible Detection Using GRACE. Journal of Geophysical Research: Solid Earth, 1998, 103(B12): 30205–30229.10.1029/98JB02844Search in Google Scholar

[32] Swenson S, Wahr J. Post-processing Removal of Correlated Errors in GRACE Data. Geophysical Research Letters, 2006, 33(L08): 402–405.10.1029/2005GL025285Search in Google Scholar

[33] Chen J L, Wilson C R, Tapley B D, et al. GRACE Detects Coseismic and Postseismic Deformation from the Sumatra-Andaman Earthquake. Geophysical Research Letters, 2007, 34(13): L13302.10.1029/2007GL030356Search in Google Scholar

[34] Schoellhamer D H. Singular spectrum analysis for time series with missing data. Geophysical Research Letters, 2001, 28(16): 3187–3190.10.1029/2000GL012698Search in Google Scholar

[35] Kondrashov D, Ghil M. Spatio-temporal filling of missing points in geophysical data sets. Nonlinear Processes in Geophysics, 2006, 13(2): 151–159.10.5194/npg-13-151-2006Search in Google Scholar

[36] Vautard R, Yiou P, Ghil M. Singular-spectrum analysis: A toolkit for short, noisy chaotic signals. Physica D: Nonlinear Phenom, 1992, 58(1–4): 95–126.10.1016/0167-2789(92)90103-TSearch in Google Scholar

[37] Plaut G, Vautard R. Spells of Low-frequency Oscillations and Weather Regimes in the Northern Hemisphere. Journal of the Atmospheric Sciences, 1994, 51(2): 210–236.10.1175/1520-0469(1994)051<0210:SOLFOA>2.0.CO;2Search in Google Scholar

[38] Bettadpur S. Level-2 Gravity Field Product User Handbook. The GRACE Project (Jet Propulsion Laboratory, Pasadena, CA, 2003), 2007.Search in Google Scholar

[39] Ferreira V G, Montecino H D C, Yakubu C I, et al. Uncertainties of the Gravity Recovery and Climate Experiment time-variable gravity-field solutions based on three-cornered hat method. Journal of Applied Remote Sensing, 2016, 10(1): 015015.10.1117/1.JRS.10.015015Search in Google Scholar

Received: 2020-02-07
Accepted: 2020-04-11
Published Online: 2020-04-22
Published in Print: 2020-07-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 27.10.2025 from https://www.degruyterbrill.com/document/doi/10.1515/jag-2020-0005/html
Scroll to top button