Green's function of the deformation of the Earth as a result of atmospheric loading

Guo, Junyi; Li, Yuebing; Huang, Yong; Deng, H. T.; Xu, Shixin; Ning, Jinsheng

doi:10.1111/j.1365-246x.2004.02410.x

Cited by 64 publications

(73 citation statements)

References 18 publications

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“…no atmospheric and non-tidal ocean corrected, please see the Table S1). The most obvious difference between our results and Liu's work (Liu et al, 2014) is that they adopt the load Love numbers from Guo et al (2004) to transform these coefficients into vertical surface displacement estimates. We check the two results of Love numbers (ocean load and atmospheric pressure load) from Guo et al (2004), there are significant differences between ocean-load and atmospheric pressure-load Love numbers.…”

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variacontrasting

confidence: 40%

“…The most obvious difference between our results and Liu's work (Liu et al, 2014) is that they adopt the load Love numbers from Guo et al (2004) to transform these coefficients into vertical surface displacement estimates. We check the two results of Love numbers (ocean load and atmospheric pressure load) from Guo et al (2004), there are significant differences between ocean-load and atmospheric pressure-load Love numbers. Meanwhile, we compared k n Love numbers from Guo et al (2004) (work of Liu et al, 2014) and k n Love numbers from Han and Wahr (1995) (our work) with the k n Love numbers used in ADO1B products (Farrell, 1972) respectively.…”

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variacontrasting

confidence: 40%

“…The different Love numbers have caused the amplitude of the same station from Liu's GRACE-derived vertical displacements much more than GPS and our GRACE results, due to k n from atmospheric pressure-load Love numbers (Guo et al, 2004) significantly larger than Love numbers from Han and Wahr (1995) and Farrell (1972). The detailed analysis of the different Love numbers from Guo et al (2004), Han andWahr (1995), andFarrell (1972), please see the Sect. S1.…”

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

“…We check the two results of Love numbers (ocean load and atmospheric pressure load) from Guo et al (2004), there are significant differences between ocean-load and atmospheric pressure-load Love numbers. Meanwhile, we compared k n Love numbers from Guo et al (2004) (work of Liu et al, 2014) and k n Love numbers from Han and Wahr (1995) (our work) with the k n Love numbers used in ADO1B products (Farrell, 1972) respectively. The different Love numbers have caused the amplitude of the same station from Liu's GRACE-derived vertical displacements much more than GPS and our GRACE results, due to k n from atmospheric pressure-load Love numbers (Guo et al, 2004) significantly larger than Love numbers from Han and Wahr (1995) and Farrell (1972).…”

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

“…Meanwhile, we compared k n Love numbers from Guo et al (2004) (work of Liu et al, 2014) and k n Love numbers from Han and Wahr (1995) (our work) with the k n Love numbers used in ADO1B products (Farrell, 1972) respectively. The different Love numbers have caused the amplitude of the same station from Liu's GRACE-derived vertical displacements much more than GPS and our GRACE results, due to k n from atmospheric pressure-load Love numbers (Guo et al, 2004) significantly larger than Love numbers from Han and Wahr (1995) and Farrell (1972). The detailed analysis of the different Love numbers from Guo et al (2004), Han andWahr (1995), andFarrell (1972), please see the Sect.…”

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

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Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS

Wang

Chen

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. In total, 29 continuous Global Positioning System (GPS) time series data together with data from Gravity Recovery and Climate Experiment (GRACE) are analysed to determine the seasonal displacements of surface loadings in the North China Plain (NCP). Results show significant seasonal variations and a strong correlation between GPS and GRACE results in the vertical displacement component; the average correlation and weighted root-meansquares (WRMS) reduction between GPS and GRACE are 75.6 and 28.9 % respectively, when atmospheric and nontidal ocean effects were removed, but the annual peak-topeak amplitude of GPS (1.2-6.3 mm) is greater than the data (1.0-2.2 mm) derived from GRACE. We also calculate the trend rate as well as the seasonal signal caused by the mass load change from GRACE data; the rate of GRACEderived terrestrial water storage (TWS) loss (after multiplying by the scaling factor) in the NCP was 3.39 cm yr −1 (equivalent to 12.42 km 3 yr −1 ) from 2003 to 2009. For a 10-year time span (2003 to 2012), the rate loss of TWS was 2.57 cm yr −1 (equivalent to 9.41 km 3 yr −1 ), which is consistent with the groundwater storage (GWS) depletion rate (the rate losses of GWS were 2.49 and 2.72 cm yr −1 during 2003-2009 and 2003-2012 respectively) estimated from GRACE-derived results after removing simulated soil moisture (SM) data from the Global Land Data Assimilation System (GLDAS)/Noah model. We also found that GRACEderived GWS changes are in disagreement with the groundwater level changes from observations of shallow aquifers from 2003 to 2009, especially between 2010 and 2013. Although the shallow groundwater can be recharged from the annual climate-driven rainfall, the important facts indicate that GWS depletion is more serious in deep aquifers. The GRACE-derived result shows an overall uplift in the whole region at the 0.37-0.95 mm yr −1 level from 2004 to 2009, but the rate of change direction is inconsistent in different GPS stations at the −0.40-0.51 mm yr −1 level from 2010 to 2013. Then we removed the vertical rates, which are induced by TWS from GPS-derived data, to obtain the corrected vertical velocities caused by tectonic movement and human activities. The results show that there are uplift areas and subsidence areas in NCP. Almost the whole central and eastern region of NCP suffers serious ground subsidence caused by the anthropogenic-induced groundwater exploitation in the deep confined aquifers. In addition, the slight ground uplifts in the western region of NCP are mainly controlled by tectonic movement (e.g. Moho uplifting or mantle upwelling).

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Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variacontrasting

confidence: 40%

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variacontrasting

confidence: 40%

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

Section: The Loading Effects Of Non-tidal Ocean and Atmospheric Variamentioning

confidence: 99%

See 3 more Smart Citations

Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS

Wang

Chen

et al. 2017

Hydrol. Earth Syst. Sci.

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Modeling deformation induced by seasonal variations of continental water in the Himalaya region: Sensitivity to Earth elastic structure

et al. 2014

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Strong seasonal variations of horizontal and vertical positions are observed on GPS time series from stations located in Nepal, India, and Tibet (China). We show that this geodetic deformation can be explained by seasonal variations of continental water storage driven by the monsoon. For this purpose, we use satellite data from the Gravity Recovery and Climate Experiment to determine the time evolution of surface loading. We compute the expected geodetic deformation assuming a perfectly elastic Earth model. We consider Green's functions, describing the surface deformation response to a point load, for an elastic homogeneous half‐space model and for a layered nonrotating spherical Earth model based on the Preliminary Reference Earth Model and a local seismic velocity model. The amplitude and phase of the seasonal variation of the vertical and horizontal geodetic positions can be jointly adjusted only with the layered Earth model, while an elastic half‐space model fails, emphasizing the importance of using a realistic Earth elastic structure to model surface displacements induced by surface loading. We demonstrate, based on a formal inversion, that the fit to the geodetic data can be improved by adjusting the layered Earth model. Therefore, the study also shows that the modeling of geodetic seasonal variations provides a way to probe the elastic structure of the Earth, even in the absence of direct measurements of surface load variations.

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Stacking global GPS verticals and horizontals to solve for the fortnightly and monthly body tides: Implications for mantle anelasticity

et al. 2015

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The availability of long-term position measurements from permanent GPS stations distributed around the Earth makes it feasible to extract small, globally coherent, long-period geophysical signals from the data. Using 11 years of daily vertical and horizontal positions from over 600 permanent GPS stations worldwide, we solve for the amplitude and phase of the fortnightly and monthly body tides by stacking the surface displacements against spherical harmonics and isolating the fortnightly and monthly signals in the stacks. We use our solutions to help constrain the Earth's anelastic properties, which are not well understood within the tidal frequency band. Our error estimates include the effects of the following: (1) random noise across the fortnightly and monthly tidal bands; (2) fortnightly and monthly ocean tide model errors; (3) errors in the diurnal and semidiurnal ocean tide models that alias into the fortnightly and monthly frequency bands; (4) errors in the solid Earth Green's functions used to compute ocean tidal loading corrections; and (5) leakage from GPS draconitic signals at periods close to the fortnightly and monthly frequencies. The mantle anelasticity coefficients we infer from our solutions are consistent with a ω α frequency dependence of mantle Q with α in the range 0.1-0.3.

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Green's function of the deformation of the Earth as a result of atmospheric loading

Cited by 64 publications

References 18 publications

Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS

Detecting seasonal and long-term vertical displacement in the North China Plain using GRACE and GPS

Modeling deformation induced by seasonal variations of continental water in the Himalaya region: Sensitivity to Earth elastic structure

Stacking global GPS verticals and horizontals to solve for the fortnightly and monthly body tides: Implications for mantle anelasticity

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