Estimation of mass change trends in the Earth’s system on the basis of GRACE satellite data, with application to Greenland

Siemes, Christian; Ditmar, Pavel; Riva, Riccardo; Slobbe, Cornelis; Liu, X. L.; Farahani, H. Hashemi

doi:10.1007/s00190-012-0580-5

Cited by 32 publications

(25 citation statements)

References 36 publications

(78 reference statements)

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“…Since this study was completed, a new release was made of GRACE data, version RL05, and products from three groups are available [from the Jet Propulsion Laboratory, as given by Landerer and Swenson (2012); University of Texas, as given by Tapley et al (2004); and German Research Center for Geosciences (GFZ) Potsdam, as given by Siemes et al (2013)]. Since this study was completed, a new release was made of GRACE data, version RL05, and products from three groups are available [from the Jet Propulsion Laboratory, as given by Landerer and Swenson (2012); University of Texas, as given by Tapley et al (2004); and German Research Center for Geosciences (GFZ) Potsdam, as given by Siemes et al (2013)].…”

Section: Discussionmentioning

confidence: 99%

Regional Energy and Water Cycles: Transports from Ocean to Land

Trenberth

Fasullo

2013

Journal of Climate

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The flows of energy and water from ocean to land are examined in the context of the land energy and water budgets, for land as a whole and for continents. Most atmospheric reanalyses have large errors of up to 15 W m 22 in the top-of-atmosphere (TOA) energy imbalance, and none include volcanic eruptions. The flow of energy from ocean to land is more reliable as it relies on analyzed wind, temperature, and moisture fields. It is examined for transports of the total, latent energy (LE), and dry static energy (DSE) to land as a whole and as zonal means. The net convergence of energy onto land is balanced by the loss of energy at TOA, measured by Clouds and the Earth's Radiant Energy System (CERES), and again there are notable discrepancies. Only the ECMWF Interim Re-Analysis (ERA-I) is stable and plausible. Strong compensation between variations in LE and DSE transports onto land means that their sum is more stable over time, and the net transport of energy onto land is largely that associated with the hydrological cycle (LE). A more detailed examination is given of the energy and water budgets for Eurasia, North and South America, Australia, and Africa, making use of Gravity Recovery and Climate Experiment (GRACE) data for water storage on land and data on river discharge into the ocean. With ERA-I, the new land estimates for both water and energy are closer to achieving balances than in previous studies. As well as the annual means, the mean annual cycles are examined in detail along with uncertainty sampling estimates, but the main test used here is that of closure.

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Section: Discussionmentioning

confidence: 99%

Regional Energy and Water Cycles: Transports from Ocean to Land

Trenberth

Fasullo

2013

Journal of Climate

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“…The "true" signal over these areas is also defined as the yearly mass variation. It is generated using the available optimally filtered trend over 2003-2008 based on the Delft Mass Transport (DMT) model (Siemes et al 2013). 3.1.2.2 AOD noise AOD noise refers to errors in the background models, which are used to reduce non-tidal mass transport in the atmosphere and ocean.…”

Section: Signal Leakagementioning

confidence: 99%

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Ran

Ditmar

Klees

et al. 2017

J Geod

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We present an improved mascon approach to transform monthly spherical harmonic solutions based on GRACE satellite data into mass anomaly estimates in Greenland. The GRACE-based spherical harmonic coefficients are used to synthesize gravity anomalies at satellite altitude, which are then inverted into mass anomalies per mascon. The limited spectral content of the gravity anomalies is properly accounted for by applying a low-pass filter as part of the inversion procedure to make the functional model spectrally consistent with the data. The full error covariance matrices of the monthly GRACE solutions are properly propagated using the law of covariance propagation. Using numerical experiments, we demonstrate the importance of a proper data weighting and of the spectral consistency between functional model and data. The developed methodology is applied to process real GRACE level-2 data (CSR RL05). The obtained mass anomaly estimates are integrated over five drainage systems, as well as over entire Greenland. We find that the statistically optimal data weighting reduces random noise by 35-69%, depending on the drainage system. The obtained mass anomaly time-series are de-trended to eliminate the contribution of ice discharge and are compared with detrended surface mass balance (SMB) time-series computed with the Regional Atmospheric Climate Model (RACMO 2.3). We show that when using a statistically optimal data weighting in GRACE data processing, the discrepancies between GRACE-based estimates of SMB and modelled SMB are reduced by 24-47%.B J. Ran

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“…The river basin boundaries used in this study are taken from the website http://hydro.iis.u-tokyo.ac.jp/~taikan/TRIPDATA/TRIPDATA.html. As regards Greenland, it is known that the mass changes there show seasonal variations superimposed by a strong negative long‐term trend (e.g., Ran et al, ; Schrama et al, ; Siemes et al, ; Velicogna & Wahr, ). The selected regions show different levels of errors in GRACE data as can be seen in Figure .…”

Section: Resultsmentioning

confidence: 99%

Improvements in the Monthly Gravity Field Solutions Through Modeling the Colored Noise in the GRACE Data

et al. 2018

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The Gravity Recovery And Climate Experiment (GRACE) mission has achieved a quantum leap in knowledge of the Earth's gravity field. However, current gravity field solutions still cannot reach the prelaunch baseline accuracy. One of the reasons for that is the presence of colored noise in GRACE data, which is typically ignored in the classical dynamic approach to gravity field modeling. In this research, we propose to account for colored noise in the classical dynamic approach by applying the frequency‐dependent data weighting (FDDW) scheme, so that enhanced estimates of gravity field solutions are produced. The monthly solutions are compared with those produced using the standard least squares adjustment without a data weighting scheme. The comparison is performed in both spectral and spatial domains, showing the positive effect of the FDDW scheme in all considered cases. For instance, the cumulative geoid height errors up to degree 96 are reduced by 18%. In the spatial domain, the FDDW scheme lowers noise level in mass changes over the oceans, Mississippi river basin, and Greenland by 20, 38, and 23%, respectively, when compared to the without a data weighting scheme. In addition, the consistency of mass changes over the Mississippi and Congo river basins with those inferred from the state‐of‐the‐art hydrology model WaterGAP is substantially improved when the FDDW scheme is applied. These results indicate that modeling colored noise in the GRACE data allows to significantly improve the recovered monthly solutions. This finding is likely applicable also to the GRACE Follow‐On mission.

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Estimation of mass change trends in the Earth’s system on the basis of GRACE satellite data, with application to Greenland

Cited by 32 publications

References 36 publications

Regional Energy and Water Cycles: Transports from Ocean to Land

Regional Energy and Water Cycles: Transports from Ocean to Land

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Improvements in the Monthly Gravity Field Solutions Through Modeling the Colored Noise in the GRACE Data

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