Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS

Fritsche, Mathias; Döll, Petra; Dietrich, Reinhard

doi:10.1016/j.jog.2011.04.001

Cited by 50 publications

(28 citation statements)

References 34 publications

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“…Regarding the stacked power spectra of the ATML, a sudden drop at frequencies higher than 40 cpy can be seen, indicating an autoregressive behavior. This result confirms the findings of earlier studies [19,26,35]. Likewise, the frequency characteristics of NTOL's stacked power spectra also follow an autoregressive process.…”

Section: Stacked Power Spectra Analysissupporting

confidence: 91%

“…With regard to hydrological loading (HYDL), van Dam et al [25] investigated the height time series of 147 GPS stations and found significant reductions of scatter at 92 stations after HYDL correction. Fritsche et al [26] performed a quantitative analysis of 208 stations worldwide. They found that displacements due to HYDL predicted with the WaterGAP Global Hydrology Model (WGHM) are slightly overestimated on average.…”

Section: Introductionmentioning

confidence: 99%

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Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Peng

Jiang

et al. 2018

Remote Sensing

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Mass redistribution of the atmosphere, oceans, and terrestrial water storage generates crustal displacements which can be predicted by environmental loading models and observed by the Global Positioning System (GPS). In this paper, daily height time series of 235 GPS stations derived from a homogeneously reprocessed Crustal Movement Observation Network of China (CMONOC) and corresponding loading displacements predicted by the Deutsche GeoForschungsZentrum (GFZ) are compared to assess the effects of loading corrections on the nonlinear variations of GPS time series. Results show that the average root mean square (RMS) of vertical displacements due to atmospheric, nontidal oceanic, hydrological, and their combined effects are 3.2, 0.6, 2.7, and 4.0 mm, respectively. Vertical annual signals of loading and GPS are consistent in amplitude but different in phase systematically. The average correlation coefficient between loading and GPS height time series is 0.6. RMS of the GPS height time series are reduced by 20% on average. Moreover, an investigation of 208 CMONOC stations with observing time spans of~4.6 years shows that environmental loading corrections lead to an overestimation of the GPS velocity uncertainty by about 1.4 times on average. Nevertheless, by using a common mode component filter through principal component analysis, the dilution of velocity precision due to environmental loading corrections can be compensated.

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Section: Stacked Power Spectra Analysissupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Peng

Jiang

et al. 2018

Remote Sensing

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“…Alternatively, hydrological models can be calibrated (Werth and Güntner, 2010;Lo et al, 2010) and evaluated using GRACE data (Alkama et al, 2010), or GRACE-based water storage variations can be integrated into models via data assimilation (Zaitchik et al, 2008). The same is true for geodetic measurements such as GPS, which are impacted by deformations caused by large-scale continental water mass variations (Fritsche et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Impact of water withdrawals from groundwater and surface water on continental water storage variations

Döll

Hoffmann-Dobrev

Portmann

et al. 2012

Journal of Geodynamics

596

408

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“…Previous research has confirmed the strong correlation between Continental Water Storage (CWS) induced vertical surface displacement and the global positioning system (GPS) height time series (van Dam et al 2001(van Dam et al , 2007Tregoning et al 2009;Fritsche et al 2012). This environmentally driven displacement adds noise to the GPS data being used for geodynamic investigations, such as postglacial rebound, sea level rise, etc.…”

Section: Introductionmentioning

confidence: 88%

Quality Evaluation of the Weekly Vertical Loading Effects Induced from Continental Water Storage Models

Dam

Collilieux

et al. 2015

International Association of Geodesy Symposia

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To remove continental water storage (CWS) signals from the GPS data, CWS mass models are needed to obtain predicted surface displacements. We compared weekly GPS height time series with five CWS models: (1) the monthly and (2) three-hourly Global Land Data Assimilation System (GLDAS); (3) the monthly and (4) one-hourly ModernEra Retrospective Analysis for Research and Applications (MERRA); (5) the six-hourly National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) global reanalysis products (NCEP-R-2). We find that of the 344 selected global IGS stations, more than 77% of stations have their weighted root mean square (WRMS) reduced in the weekly GPS height by using both the GLDAS and MERRA CWS products to model the surface displacement, and the best improvement concentrate mainly in North America and Eurasia. We find that the one-hourly MERRA-Land dataset is the most appropriate product for modeling weekly vertical surface displacement caused by CWS variations. The threehourly GLDAS data ranks the second, while the GLDAS and MERRA monthly products rank the third. The higher spatial resolution MERRA product improves the performance of the CWS model in reducing the scatter of the GPS height by about 2-6% compared with the GLDAS. Under the same spatial resolution, the higher temporal resolution could also improve the performance by almost the same magnitude. We also confirm that removing the ATML and NTOL effects from the weekly GPS height would remarkably improve the performance of CWS model in correcting the GPS height by at least 10%, especially for coastal and island stations. Since the GLDAS product has a much greater latency than the MERRA product, MERRA would be a better choice to model surface displacements from CWS. Finally, we find that the NCEP-R-2 data is not sufficiently precise to be used for this application. Further work is still required to determine the reason.

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Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS

Cited by 50 publications

References 34 publications

Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Influences of Environmental Loading Corrections on the Nonlinear Variations and Velocity Uncertainties for the Reprocessed Global Positioning System Height Time Series of the Crustal Movement Observation Network of China

Impact of water withdrawals from groundwater and surface water on continental water storage variations

Quality Evaluation of the Weekly Vertical Loading Effects Induced from Continental Water Storage Models

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