scholarly journals Geophysical interpretation of GPS loading deformation over western Europe using GRACE measurements

2016 ◽  
Vol 59 (5) ◽  
Author(s):  
Songyun Wang ◽  
Jianli Chen ◽  
Jin Li ◽  
Xiaogong Hu ◽  
Shengnan Ni
Keyword(s):  
Western Europe ◽  
International Gnss Service ◽  
Satellite Gravity ◽  
Surface Mass ◽  
Grace Data ◽  
Surface Displacements ◽  
Residual Series ◽  
Vertical Displacements ◽  
Gravity Recovery ◽  
Improved Accuracy

<p>We analyze more than 10 years of Global Positioning System (GPS) height residuals and vertical displacements predicted from surface mass loading observed by the Gravity Recovery and Climate Experiment (GRACE) for 36 International GNSS Service (IGS) stations over Europe. Seasonal surface displacements, mostly due to atmospheric and hydrological loading, are significant in both GPS and GRACE measurements. With an extended time period, our new analysis based on release 05 GRACE data from Center for Space Research (CSR) shows considerably improved agreement between GPS and GRACE than that from previous studies, for not only annual but also interannual signals. The GPS height residual series at most stations exhibit reduced weighted root-mean-squares (WRMS) after removing GRACE-derived vertical displacements, which is attributed to improved accuracy of both GPS and GRACE data products. Furthermore, we demonstrate the necessity of reducing leakage bias in GRACE estimates for the study of surface loading deformation using GRACE satellite gravity observations.</p>

scholarly journals A framework for deriving drought indicators from the Gravity Recovery and Climate Experiment (GRACE)

2020 ◽  
Vol 24 (1) ◽  
pp. 227-248 ◽  
Author(s):  
Helena Gerdener ◽  
Olga Engels ◽  
Jürgen Kusche
Keyword(s):  
Hydrological Cycle ◽  
Water Storage ◽  
Synthetic Data ◽  
Satellite Gravity ◽  
Spatially Correlated ◽  
Grace Data ◽  
Spatial Noise ◽  
Drought Indicators ◽  
Gravity Recovery ◽  
Linear Trends

Abstract. Identifying and quantifying drought in retrospective is a necessity for better understanding drought conditions and the propagation of drought through the hydrological cycle and eventually for developing forecast systems. Hydrological droughts refer to water deficits in surface and subsurface storage, and since these are difficult to monitor at larger scales, several studies have suggested exploiting total water storage data from the GRACE (Gravity Recovery and Climate Experiment) satellite gravity mission to analyze them. This has led to the development of GRACE-based drought indicators. However, it is unclear how the ubiquitous presence of climate-related or anthropogenic water storage trends found within GRACE analyses masks drought signals. Thus, this study aims to better understand how drought signals propagate through GRACE drought indicators in the presence of linear trends, constant accelerations, and GRACE-specific spatial noise. Synthetic data are constructed and existing indicators are modified to possibly improve drought detection. Our results indicate that while the choice of the indicator should be application-dependent, large differences in robustness can be observed. We found a modified, temporally accumulated version of the Zhao et al. (2017) indicator particularly robust under realistic simulations. We show that linear trends and constant accelerations seen in GRACE data tend to mask drought signals in indicators and that different spatial averaging methods required to suppress the spatially correlated GRACE noise affect the outcome. Finally, we identify and analyze two droughts in South Africa using real GRACE data and the modified indicators.

scholarly journals An ice flow modeling perspective on bedrock adjustment patterns of the Greenland ice sheet

2012 ◽  
Vol 6 (6) ◽  
pp. 1263-1274 ◽  
Author(s):  
M. Olaizola ◽  
R. S. W. van de Wal ◽  
M. M. Helsen ◽  
B. de Boer
Keyword(s):  
Mass Balance ◽  
Maximum Yield ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Elastic Response ◽  
Delayed Response ◽  
Surface Mass ◽  
Grace Data ◽  
Grace Satellites ◽  
Gravity Recovery

Abstract. Since the launch in 2002 of the Gravity Recovery and Climate Experiment (GRACE) satellites, several estimates of the mass balance of the Greenland ice sheet (GrIS) have been produced. To obtain ice mass changes, the GRACE data need to be corrected for the effect of deformation changes of the Earth's crust. Recently, a new method has been proposed where ice mass changes and bedrock changes are simultaneously solved. Results show bedrock subsidence over almost the entirety of Greenland in combination with ice mass loss which is only half of the currently standing estimates. This subsidence can be an elastic response, but it may however also be a delayed response to past changes. In this study we test whether these subsidence patterns are consistent with ice dynamical modeling results. We use a 3-D ice sheet–bedrock model with a surface mass balance forcing based on a mass balance gradient approach to study the pattern and magnitude of bedrock changes in Greenland. Different mass balance forcings are used. Simulations since the Last Glacial Maximum yield a bedrock delay with respect to the mass balance forcing of nearly 3000 yr and an average uplift at present of 0.3 mm yr−1. The spatial pattern of bedrock changes shows a small central subsidence as well as more intense uplift in the south. These results are not compatible with the gravity based reconstructions showing a subsidence with a maximum in central Greenland, thereby questioning whether the claim of halving of the ice mass change is justified.

Estimating the changes in the Moho interface beneath the Tibetan Plateau based on GRACE data

2020 ◽  
Author(s):  
Weilong Rao ◽  
Wenke Sun
Keyword(s):  
Mass Transfer ◽  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Moho Interface ◽  
Grace Data ◽  
Surface Displacements ◽  
Crustal Uplift ◽  
Gravity Recovery ◽  
Earth Dynamics ◽  
Land Water

&lt;p&gt;&amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160;The Tibetan Plateau (TP) experiences complex mass transfer and redistribution due to the effects from internal earth dynamics and external climate change, such as, land water change, crustal uplift, surface denudation, and Moho interface change. These phenomenas are accompanied by the gravity field change and could be observed by the Gravity Recovery and Climate Experiment (GRACE). This study applies GRACE data to estimate the corresponding mass changes expressed by water equivalent height (EWH) anomaly of the TP. In addition, we use ICESat data and hydrological models to estimate the effects of hydrological factors (lake, glaciers, snow, soil moisture, and groundwater), to separate them from the comprehensive mass field to obtain the tectonic information. The total hydrological contribution to the average EWH change is -0.30&amp;#177;0.21 cm/yr. We further estimate the rates of tectonic uplift and denudation based on GNSS and denudation, with results of 0.71&amp;#177;0.46 mm/yr and 0.38&amp;#177;0.10 mm/yr, respectively. Removing the effects of hydrological change, surface displacements and GIA from the GRACE data, we obtain the EWH change contributed from interior mass change of 0.21&amp;#177;0.27 cm/yr, which is equivalent to a mean Moho interface uplift rate of 3.63&amp;#177;4.32 mm/yr. Final results show that the crustal thickness of the northern TP is thinning because of the upwelling of Moho interface and the southern TP is thickening along with Moho deepening, coinciding with the tomographic results.&lt;/p&gt;&lt;p&gt;Key words: the Tibetan plateau, mass transfer, land water change, Moho interface change, GRACE&lt;/p&gt;

scholarly journals Quantifying the resolution level where the GRACE satellites can separate Greenland's glacial mass balance from surface mass balance

2015 ◽  
Vol 9 (1) ◽  
pp. 1315-1343
Author(s):  
J. A. Bonin ◽  
D. P. Chambers
Keyword(s):  
Mass Balance ◽  
Gravity Measurement ◽  
Surface Mass Balance ◽  
Satellite Gravity ◽  
Surface Mass ◽  
Grace Data ◽  
Resolution Level ◽  
Grace Satellites ◽  
Grace Satellite ◽  
Gravity Mission

Abstract. Mass change over Greenland can be caused by either changes in the glacial mass balance (GMB) or the precipitation-based surface mass balance (SMB). The GRACE satellite gravity mission cannot directly separate the two physical causes because it measures the sum of the entire mass column with limited spatial resolution. We demonstrate one theoretical way to indirectly separate SMB from GMB with GRACE, using a least squares inversion technique with knowledge of the location of the glacier. However, we find that the limited 60 × 60 spherical harmonic representation of current GRACE data does not provide sufficient resolution to adequately accomplish the task. We determine that at a maximum degree/order of 90 × 90 or above, a noise-free gravity measurement could theoretically separate the SMB from GMB signals. However, current GRACE satellite errors are too large at present to separate the signals. A noise reduction of a factor of 9 at a resolution of 90 × 90 would provide the accuracy needed for the interannual SMB and GMB to be accurately separated.

scholarly journals Quantifying the resolution level where the GRACE satellites can separate Greenland's glacial mass balance from surface mass balance

2015 ◽  
Vol 9 (5) ◽  
pp. 1761-1772 ◽  
Author(s):  
J. A. Bonin ◽  
D. P. Chambers
Keyword(s):  
Mass Balance ◽  
Gravity Measurement ◽  
Surface Mass Balance ◽  
Satellite Gravity ◽  
Surface Mass ◽  
Grace Data ◽  
Resolution Level ◽  
Grace Satellites ◽  
Grace Satellite ◽  
Gravity Mission

Abstract. Mass change over Greenland can be caused by either changes in the glacial dynamic mass balance (DMB) or the surface mass balance (SMB). The GRACE satellite gravity mission cannot directly separate the two physical causes because it measures the sum of the entire mass column with limited spatial resolution. We demonstrate one theoretical way to indirectly separate cumulative SMB from DMB with GRACE, using a least squares inversion technique with knowledge of the location of the glaciers. However, we find that the limited 60 × 60 spherical harmonic representation of current GRACE data does not provide sufficient resolution to adequately accomplish the task. We determine that at a maximum degree/order of 90 × 90 or above, a noise-free gravity measurement could theoretically separate the SMB from DMB signals. However, current GRACE satellite errors are too large at present to separate the signals. A noise reduction of a factor of 10 at a resolution of 90 × 90 would provide the accuracy needed for the interannual cumulative SMB and DMB to be accurately separated.

scholarly journals Constrained Linear Deconvolution of GRACE Anomalies to Correct Spatial Leakage

2020 ◽  
Vol 12 (11) ◽  
pp. 1798
Author(s):  
Ki-Weon Seo ◽  
Seokhoon Oh ◽  
Jooyoung Eom ◽  
Jianli Chen ◽  
Clark R. Wilson
Keyword(s):  
Climate Forcing ◽  
Mass Change ◽  
Data Types ◽  
Surface Mass ◽  
Grace Data ◽  
Mass Redistribution ◽  
Grace Satellites ◽  
Earth’S Climate ◽  
Gravity Recovery ◽  
Mass Loads

Time-varying gravity observed by the Gravity Recovery and Climate Experiment (GRACE) satellites measures surface water and ice mass redistribution driven by weather and climate forcing and has emerged as one of the most important data types in measuring changes in Earth’s climate. However, spatial leakage of GRACE signals, especially in coastal areas, has been a recognized limitation in quantitatively assessing mass change. It is evident that larger terrestrial signals in coastal regions spread into the oceans and vice versa and various remedies have been developed to address this problem. An especially successful one has been Forward Modeling but it requires knowledge of geographical locations of mass change to be fully effective. In this study, we develop a new method to suppress leakage effects using a linear least squares operator applied to GRACE spherical harmonic data. The method is effectively a constrained deconvolution of smoothing inherent in GRACE data. It assumes that oceanic mass changes near the coast are negligible compared to terrestrial changes, with additional spatial regularization constraints. Some calibration of constraint weighting is required. We apply the method to estimate surface mass loads over Australia using both synthetic and real GRACE data. Leakage into the oceans is effectively suppressed and when compared with mascon solutions there is better performance over interior basins.

scholarly journals A framework for deriving drought indicators from GRACE

2019 ◽  
Author(s):  
Helena Gerdener ◽  
Olga Engels ◽  
Jürgen Kusche
Keyword(s):  
Hydrological Cycle ◽  
Water Storage ◽  
Synthetic Data ◽  
Satellite Gravity ◽  
Spatially Correlated ◽  
Grace Data ◽  
Spatial Noise ◽  
Drought Indicators ◽  
Gravity Recovery ◽  
Hydrological Droughts

Abstract. Identifying and quantifying drought in retrospective is a necessity for better understanding drought conditions and the propagation of drought through the hydrological cycle, and eventually for developing forecast systems. Hydrological droughts refer to water deficits in surface and subsurface storage, and since these are difficult to monitor at larger scales, several studies have suggested to exploit total water storage data from the GRACE (Gravity Recovery and Climate Experiment) satellite gravity mission to analyse them. This has led to the development of GRACE-based drought indicators. However, it is unclear how the ubiquitous presence of climate-related or anthropogenic water storage trends, which has been found from GRACE analyses, masks drought signals. Thus, this study aims at a better understanding of how drought signals, in the presence of trends and GRACE-specific spatial noise, propagate through GRACE drought indicators. Synthetic data are constructed and existing indicators are modified to possibly improve drought detection. Our results indicate that while the choice of the indicator should be application dependent, larger differences in robustness can be observed. We found a modified, temporally accumulated version of the Zhao et al. (2017) indicator in particular robust under realistic simulations. We show that trends and accelerations seen in GRACE data tend to mask drought signals in indicators, and that different spatial averaging methods required to suppress the spatially correlated GRACE noise affect the outcome. Finally, we identify and analyse two droughts in South Africa using real GRACE data and the modified indicators.

scholarly journals Study of water storage variations at the Pantanal wetlands area from GRACE monthly mass grids

2019 ◽  
Vol 9 (1) ◽  
pp. 133-143
Author(s):  
Ayelen Pereira ◽  
Cecilia Cornero ◽  
Ana C. O. C. Matos ◽  
M. Cristina Pacino ◽  
Denizar Blitzkow
Keyword(s):  
Water Mass ◽  
Spatial Scales ◽  
Water Storage ◽  
Transport Processes ◽  
Satellite Gravity ◽  
The North ◽  
Paraguay River ◽  
Gravity Recovery ◽  
Grace Mission ◽  
Phase Differences

Abstract The continental water storage is significantly in-fluenced by wetlands, which are highly affected by climate change and anthropogenic influences. The Pantanal, located in the Paraguay river basin, is one of the world’s largest and most important wetlands because of the environmental biodiversity that represents. The satellite gravity mission GRACE (Gravity Recovery And Climate Experiment) provided until 2017 time-variable Earth’s gravity field models that reflected the variations due to mass transport processes-like continental water storage changes-which allowed to study environments such as wetlands, at large spatial scales. The water storage variations for the period 2002-2016, by using monthly land water mass grids of Total Water Storage (TWS) derived from GRACE solutions, were evaluated in the Pantanal area. The capability of the GRACE mission for monitoring this particular environment is analyzed, and the comparison of the water mass changes with rainfall and hydrometric heights data at different stations distributed over the Pantanal region was carried out. Additionally, the correlation between the TWS and river gauge measurements, and the phase differences for these variables, were also evaluated. Results show two distinct zones: high correlations and low phase shifts at the north, and smaller correlation values and consequently significant phase differences towards the south. This situation is mainly related to the hydrogeological domains of the area.

scholarly journals Spatio-Temporal Patterns of Mass Changes in Himalayan Glaciated Region from EOF Analyses of GRACE Data

2021 ◽  
Vol 13 (2) ◽  
pp. 265
Author(s):  
Harika Munagapati ◽  
Virendra M. Tiwari
Keyword(s):  
Temperature Anomaly ◽  
Mass Gain ◽  
Snow Accumulation ◽  
Empirical Orthogonal Functions ◽  
Total Water ◽  
Orthogonal Functions ◽  
Grace Data ◽  
Grace Satellite ◽  
Spatio Temporal ◽  
Gravity Recovery

The nature of hydrological seasonality over the Himalayan Glaciated Region (HGR) is complex due to varied precipitation patterns. The present study attempts to exemplify the spatio-temporal variation of hydrological mass over the HGR using time-variable gravity from the Gravity Recovery and Climate Experiment (GRACE) satellite for the period of 2002–2016 on seasonal and interannual timescales. The mass signal derived from GRACE data is decomposed using empirical orthogonal functions (EOFs), allowing us to identify the three broad divisions of HGR, i.e., western, central, and eastern, based on the seasonal mass gain or loss that corresponds to prevailing climatic changes. Further, causative relationships between climatic variables and the EOF decomposed signals are explored using the Granger causality algorithm. It appears that a causal relationship exists between total precipitation and total water storage from GRACE. EOF modes also indicate certain regional anomalies such as the Karakoram mass gain, which represents ongoing snow accumulation. Our causality result suggests that the excessive snowfall in 2005–2008 has initiated this mass gain. However, as our results indicate, despite the dampening of snowfall rates after 2008, mass has been steadily increasing in the Karakorum, which is attributed to the flattening of the temperature anomaly curve and subsequent lower melting after 2008.

scholarly journals The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

2021 ◽  
Vol 13 (2) ◽  
pp. 235
Author(s):  
Natthachet Tangdamrongsub ◽  
Michal Šprlák
Keyword(s):  
Data Assimilation ◽  
Gravity Data ◽  
Regional Scale ◽  
Vertical Motion ◽  
Vertical Displacement ◽  
Spatial Coverage ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Gravity Recovery ◽  
Central South

The vertical motion of the Earth’s surface is dominated by the hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into the regional geophysical process. Although the Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across the globe, posing a challenge to obtaining accurate deformation information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO)) have been successfully used to improve the spatial coverage. While combining model estimates and GRACE/GRACE-FO data via the GRACE/GRACE-FO data assimilation (DA) framework can potentially improve the accuracy and resolution of deformation estimates, the approach has rarely been considered or investigated thus far. This study assesses the performance of vertical displacement estimates from GRACE/GRACE-FO, the PCRaster Global Water Balance (PCR-GLOBWB) hydrology model, and the GRACE/GRACE-FO DA approach (assimilating GRACE/GRACE-FO into PCR-GLOBWB) in CSEA, where measurements from six GPS sites are available for validation. The results show that GRACE/GRACE-FO, PCR-GLOBWB, and GRACE/GRACE-FO DA accurately capture regional-scale hydrologic- and flood-induced vertical displacements, with the correlation value and RMS reduction relative to GPS measurements up to 0.89 and 53%, respectively. The analyses also confirm the GRACE/GRACE-FO DA’s effectiveness in providing vertical displacement estimates consistent with GRACE/GRACE-FO data while maintaining high-spatial details of the PCR-GLOBWB model, highlighting the benefits of GRACE/GRACE-FO DA in data-sparse regions.

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