scholarly journals Signal and noise in Gravity Recovery and Climate Experiment (GRACE) observed surface mass variations

2007 ◽  
Vol 112 (B8) ◽  
Author(s):  
Ernst J. O. Schrama ◽  
Bert Wouters ◽  
David A. Lavallée
Keyword(s):  
Surface Mass ◽  
Gravity Recovery

scholarly journals Accelerating changes in ice mass within Greenland, and the ice sheet’s sensitivity to atmospheric forcing

2019 ◽  
Vol 116 (6) ◽  
pp. 1934-1939 ◽  
Author(s):  
Michael Bevis ◽  
Christopher Harig ◽  
Shfaqat A. Khan ◽  
Abel Brown ◽  
Frederik J. Simons ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Climate Model ◽  
Regional Climate ◽  
Atmospheric Forcing ◽  
Surface Mass ◽  
The North ◽  
Global Positioning ◽  
The North Atlantic Oscillation ◽  
Gravity Recovery ◽  
Gps Observations

From early 2003 to mid-2013, the total mass of ice in Greenland declined at a progressively increasing rate. In mid-2013, an abrupt reversal occurred, and very little net ice loss occurred in the next 12–18 months. Gravity Recovery and Climate Experiment (GRACE) and global positioning system (GPS) observations reveal that the spatial patterns of the sustained acceleration and the abrupt deceleration in mass loss are similar. The strongest accelerations tracked the phase of the North Atlantic Oscillation (NAO). The negative phase of the NAO enhances summertime warming and insolation while reducing snowfall, especially in west Greenland, driving surface mass balance (SMB) more negative, as illustrated using the regional climate model MAR. The spatial pattern of accelerating mass changes reflects the geography of NAO-driven shifts in atmospheric forcing and the ice sheet’s sensitivity to that forcing. We infer that southwest Greenland will become a major future contributor to sea level rise.

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.

scholarly journals Recent glacier mass changes in the Gulf of Alaska region from GRACE mascon solutions

2008 ◽  
Vol 54 (188) ◽  
pp. 767-777 ◽  
Author(s):  
Scott B. Luthcke ◽  
Anthony A. Arendt ◽  
David D. Rowlands ◽  
John J. McCarthy ◽  
Christopher F. Larsen
Keyword(s):  
Region Of Interest ◽  
Gulf Of Alaska ◽  
Rate Data ◽  
Regional Patterns ◽  
Surface Mass ◽  
Range Rate ◽  
Global Sea Level ◽  
Processing Techniques ◽  
Gravity Recovery

AbstractThe mass changes of the Gulf of Alaska (GoA) glaciers are computed from the Gravity Recovery and Climate Experiment (GRACE) inter-satellite range-rate data for the period April 2003–September 2007. Through the application of unique processing techniques and a surface mass concentration (mascon) parameterization, the mass variations in the GoA glacier regions have been estimated at high temporal (10 day) and spatial (2 × 2 arc-degrees) resolution. The mascon solutions are directly estimated from a reduction of the GRACE K-band inter-satellite range-rate data and, unlike previous GRACE solutions for the GoA glaciers, do not exhibit contamination by leakage from mass change occurring outside the region of interest. The mascon solutions reveal considerable temporal and spatial variation within the GoA glacier region, with the largest negative mass balances observed in the St Elias Mountains including the Yakutat and Glacier Bay regions. The most rapid losses occurred during the 2004 melt season due to record temperatures in Alaska during that year. The total mass balance of the GoA glacier region was −84 ± 5 Gt a−1 contributing 0.23 ± 0.01 mm a−1 to global sea-level rise from April 2003 through March 2007. Highlighting the large seasonal and interannual variability of the GoA glaciers, the rate determined over the period April 2003–March 2006 is −102 ± 5 Gt a−1, which includes the anomalously high temperatures of 2004 and does not include the large 2007 winter balance-year snowfall. The mascon solutions agree well with regional patterns of glacier mass loss determined from aircraft altimetry and in situ measurements.

scholarly journals Improved GRACE regional mass balance estimates of the Greenland ice sheet cross-validated with the input–output method

2016 ◽  
Vol 10 (2) ◽  
pp. 895-912 ◽  
Author(s):  
Zheng Xu ◽  
Ernst J. O. Schrama ◽  
Wouter van der Wal ◽  
Michiel van den Broeke ◽  
Ellyn M. Enderlin
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Mass Change ◽  
Input Output ◽  
Surface Mass ◽  
Ice Cloud ◽  
The Difference ◽  
Gravity Recovery

Abstract. In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass change of the Greenland ice sheet (GrIS) and neighboring glaciated regions using a least squares inversion approach. We also consider results from the input–output method (IOM). The IOM quantifies the difference between the mass input and output of the GrIS by studying the surface mass balance (SMB) and the ice discharge (D). We use the Regional Atmospheric Climate Model version 2.3 (RACMO2.3) to model the SMB and derive the ice discharge from 12 years of high-precision ice velocity and thickness surveys. We use a simulation model to quantify and correct for GRACE approximation errors in mass change between different subregions of the GrIS, and investigate the reliability of pre-1990s ice discharge estimates, which are based on the modeled runoff. We find that the difference between the IOM and our improved GRACE mass change estimates is reduced in terms of the long-term mass change when using a reference discharge derived from runoff estimates in several subareas. In most regions our GRACE and IOM solutions are consistent with other studies, but differences remain in the northwestern GrIS. We validate the GRACE mass balance in that region by considering several different GIA models and mass change estimates derived from data obtained by the Ice, Cloud and land Elevation Satellite (ICESat). We conclude that the approximated mass balance between GRACE and IOM is consistent in most GrIS regions. The difference in the northwest is likely due to underestimated uncertainties in the IOM solutions.

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 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 Improved Estimation of Regional Surface Mass Variations from GRACE Intersatellite Geopotential Differences Using a Priori Constraints

2020 ◽  
Vol 12 (16) ◽  
pp. 2553
Author(s):  
Bo Zhong ◽  
Qiong Li ◽  
Jianli Chen ◽  
Zhicai Luo ◽  
Hao Zhou
Keyword(s):  
A Priori ◽  
Energy Balance Equation ◽  
Hydrological Models ◽  
A Priori Information ◽  
Improved Method ◽  
Surface Mass ◽  
Range Rate ◽  
Priori Information ◽  
Gravity Recovery

We presented an improved method for estimation of regional surface mass variations from the Gravity Recovery and Climate Experiment (GRACE)-derived precise intersatellite geopotential differences using a priori constraints. An alternative analytic formula was proposed to incorporate the K-band ranging (KBR) range rate into the improved energy balance equation, and precise geopotential differences were estimated from GRACE Level-1B data based on the remove-compute-restore (RCR) technique, which avoids the long-wavelength gravity signals being absorbed by empirical parameters. To reduce the ill condition for inversion of regional mass variations from geopotential differences, a priori information from hydrological models was used to construct the constraint equations, and the optimal regularization parameters were adaptively determined based on iterative least-squares estimation. To assess our improved method, a case study of regional mass variations’ inversion was carried out over South America on 2° × 2° grids at monthly intervals from January 2005 to December 2010. The results show that regional mascon solutions inverted from geopotential differences estimated by the RCR technique using hydrological models as a priori constraints can retain more signal energy and enhance regional mass variation inversion. The spatial distributions and annual amplitudes of geopotential difference-based regional mascon solutions agree well with the official GRACE mascon solutions, although notable differences exist in spatial patterns and trends, especially in small basins. In addition, our improved method can robustly estimate the mascon solutions, which are less affected by the a priori information. The results from the case study have clearly demonstrated the feasibility and effectiveness of the proposed method.

scholarly journals Improved GRACE regional mass balance estimates of the Greenland Ice Sheet cross-validated with the input-output method

2015 ◽  
Vol 9 (5) ◽  
pp. 4661-4699 ◽  
Author(s):  
Z. Xu ◽  
E. Schrama ◽  
W. van der Wal ◽  
M. van den Broeke ◽  
E. M. Enderlin
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Mass Change ◽  
Input Output ◽  
Surface Mass ◽  
Ice Cloud ◽  
The Difference ◽  
Gravity Recovery

Abstract. In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass changes of the Greenland ice sheet (GrIS) and neighbouring glaciated regions using a least-squares inversion approach. We also consider results from the input-output method (IOM) that quantifies the difference between mass input and output of the surface mass balance (SMB) components from the Regional Atmospheric Climate Model version 2 (RACMO2) and ice discharge (D) from 12 years of high-precision ice velocity and thickness surveys. We use a simulation model to quantify and correct for GRACE approximation errors in mass changes between different sub-regions of GrIS and investigate the reliability of pre-1990s ice discharge estimates based on modelled runoff. We find that the difference between IOM and our improved GRACE mass change estimates is reduced in terms of the long-term mass changes when using runoff-based discharge estimates in several sub-areas. In most regions our GRACE and IOM solutions are consistent with other studies, but differences remain in the northwestern GrIS. We verify the GRACE mass balance in that region by considering several different GIA models and mass change estimates derived from the Ice, Cloud and land Elevation satellite (ICEsat). We conclude that the remaining differences between GRACE and IOM are likely due to underestimated uncertainties in the IOM solutions.

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