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The Gravity Recovery Object Oriented Programming System (GROOPS) is a software toolkit written in C++ that enables the user to perform core geodetic tasks. Key features of the software include gravity field recovery from satellite and terrestrial data, the determination of satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. Next to raw data processing, GROOPS is capable to operate on time series and spatial data to directly analyze and visualize the computed data sets. Most tasks and algorithms are (optionally) parallelized through the Message Passing Interface, thus the software enables a smooth transition from single-CPU desktop computers to large distributed computing environments for resource intensive tasks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of the software is freely available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and step-by-step installation instructions.
Torsten Mayer-Gürr; Saniya Behzadpour; Annette Eicker; Matthias Ellmer; Beate Koch; Sandro Krauss; Christian Pock; Daniel Rieser; Sebastian Strasser; Barbara Süsser-Rechberger; Norbert Zehentner; Andreas Kvas. GROOPS: A software toolkit for gravity field recovery and GNSS processing. Computers & Geosciences 2021, 155, 104864 .
AMA StyleTorsten Mayer-Gürr, Saniya Behzadpour, Annette Eicker, Matthias Ellmer, Beate Koch, Sandro Krauss, Christian Pock, Daniel Rieser, Sebastian Strasser, Barbara Süsser-Rechberger, Norbert Zehentner, Andreas Kvas. GROOPS: A software toolkit for gravity field recovery and GNSS processing. Computers & Geosciences. 2021; 155 ():104864.
Chicago/Turabian StyleTorsten Mayer-Gürr; Saniya Behzadpour; Annette Eicker; Matthias Ellmer; Beate Koch; Sandro Krauss; Christian Pock; Daniel Rieser; Sebastian Strasser; Barbara Süsser-Rechberger; Norbert Zehentner; Andreas Kvas. 2021. "GROOPS: A software toolkit for gravity field recovery and GNSS processing." Computers & Geosciences 155, no. : 104864.
Observations of changes in terrestrial water storage (TWS) obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models, spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighbouring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology-related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes and reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a relocation of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction, RECOG-EQ, includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above Mw9. We discuss that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available on an open-access basis via the Pangaea database (RECOG-LR: Deggim et al., 2020a, https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al., 2020b, https://doi.org/10.1594/PANGAEA.921923).
Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. Earth System Science Data 2021, 13, 2227 -2244.
AMA StyleSimon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. Earth System Science Data. 2021; 13 (5):2227-2244.
Chicago/Turabian StyleSimon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2021. "RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes." Earth System Science Data 13, no. 5: 2227-2244.
The Gravity Recovery Object Oriented Programming System (GROOPS) is a software package written in C++ that enables the user to perform core geodetic tasks. The software features gravity field recovery from satellite and terrestrial data, the determination of low-earth-orbiting satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of GROOPS is released under the GPL v3 license and is available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and installation instructions for different platforms. In this contribution we give a software overview and present results of different applications and data sets computed with GROOPS.
Andreas Kvas; Saniya Behzadpour; Annette Eicker; Matthias Ellmer; Beate Koch; Sandro Krauss; Christian Pock; Daniel Rieser; Sebastian Strasser; Barbara Suesser-Rechberger; Norbert Zehentner; Torsten Mayer-Guerr. GROOPS: An open-source software package for GNSS processing and gravity field recovery. 2021, 1 .
AMA StyleAndreas Kvas, Saniya Behzadpour, Annette Eicker, Matthias Ellmer, Beate Koch, Sandro Krauss, Christian Pock, Daniel Rieser, Sebastian Strasser, Barbara Suesser-Rechberger, Norbert Zehentner, Torsten Mayer-Guerr. GROOPS: An open-source software package for GNSS processing and gravity field recovery. . 2021; ():1.
Chicago/Turabian StyleAndreas Kvas; Saniya Behzadpour; Annette Eicker; Matthias Ellmer; Beate Koch; Sandro Krauss; Christian Pock; Daniel Rieser; Sebastian Strasser; Barbara Suesser-Rechberger; Norbert Zehentner; Torsten Mayer-Guerr. 2021. "GROOPS: An open-source software package for GNSS processing and gravity field recovery." , no. : 1.
The Global Positioning System (GPS) measures surface displacements in response to time-varying terrestrial water mass variations. Components of surface water storage include water in lakes and reservoirs, snow, and soil moisture. Groundwater depletion or recharge will also contribute to the overall water storage. Understanding the nature of the observed GPS displacements related to the continental water variations is important to help identify which compartment in the total water storage controls the water changes in any particular region. In this study, we demonstrate the potential of GPS to observe the surface displacements induced by groundwater variations in France. In-situ groundwater observations from boreholes in France are used to be compared with GPS displacements. Groundwater data are processed to obtain the Equivalent Water Height (EWH) and used to forward model surface deformation. Displacements predicted using EWH variations from the WaterGAP Global Hydrology Model (WGHM) will also be compared to the GPS displacements.
Anita Thea Saraswati; Kuei-Hua Hsu; Tonie van Dam; Annette Eicker. Surface deformations observed by GPS and its relation to groundwater variations in France. 2021, 1 .
AMA StyleAnita Thea Saraswati, Kuei-Hua Hsu, Tonie van Dam, Annette Eicker. Surface deformations observed by GPS and its relation to groundwater variations in France. . 2021; ():1.
Chicago/Turabian StyleAnita Thea Saraswati; Kuei-Hua Hsu; Tonie van Dam; Annette Eicker. 2021. "Surface deformations observed by GPS and its relation to groundwater variations in France." , no. : 1.
Climate change will affect terrestrial water storage (TWS) during the next decades by impacting the seasonal cycle, interannual variations, and long-term linear trends. But how exactly will the variability change in the future? Reliable projections are needed not only for sensible water management but also as input for long-term performance studies of possible Next Generation Gravity Missions (NGGMs).
In this contribution, an ensemble of climate model projections provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6) covering the years 2002 – 2100 is utilized to assess possible changes in TWS variability. To demonstrate performance and identify shortcomings of the models we first compare modeled TWS to globally observed TWS from the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) in the time span 2002 – 2020. We then analyze changes in the variability of TWS from model projections until the end of the century and the consensus on such changes within the model ensemble.
Based on these projections, we find that present-day GRACE accuracies are sufficient to detect amplitude and phase changes in the seasonal cycle in one third of the land surface after 30 years of observation, whereas a five times more accurate NGGM mission could resolve such changes almost everywhere outside the most arid landscapes of our planet. We also select one individual model experiment out of the CMIP6 ensemble that closely matches both GRACE observations and the multi-model median of all CMIP6 realizations. This model run might serve as basis for multi-decadal satellite mission performance studies to demonstrate the suitability of NGGM satellite missions to monitor long-term climate variations in the terrestrial water cycle.
Laura Jensen; Annette Eicker; Henryk Dobslaw; Roland Pail. Land Water Storage Variabilities in GRACE and Climate Models – How do they compare and which future changes can we expect? 2021, 1 .
AMA StyleLaura Jensen, Annette Eicker, Henryk Dobslaw, Roland Pail. Land Water Storage Variabilities in GRACE and Climate Models – How do they compare and which future changes can we expect? . 2021; ():1.
Chicago/Turabian StyleLaura Jensen; Annette Eicker; Henryk Dobslaw; Roland Pail. 2021. "Land Water Storage Variabilities in GRACE and Climate Models – How do they compare and which future changes can we expect?" , no. : 1.
The Combination Service for Time-variable Gravity Fields (COST-G) of the International Association of Geodesy (IAG) provides combined monthly gravity fields of its associated and partner Analysis Centers (ACs). In November 2020, the combination of monthly GRACE-FO gravity fields started its operational mode, providing consolidated L2 (spherical harmonics) and L3 (gridded and post- processed) products with a latency of currently 3 months. We present an overview and quality assessment of the available products.
COST-G aims at the extension of its service to include further GRACE and GRACE-FO analysis centers. In January 2020 a collaboration with representatives of five Chinese ACs was initiated, who provided GRACE time-series according to the COST-G requirements. We present the results of a test combination with the Chinese AC models, including comparison and quality assessment of all contributing time-series and validation of the combined gravity fields.
Ulrich Meyer; Martin Lasser; Adrian Jäggi; Christoph Dahle; Frank Flechtner; Andreas Kvas; Saniya Behzadpour; Torsten Mayer-Gürr; Jean-Michel Lemoine; Igor Koch; Jakob Flury; Stephane Bourgogne; Andreas Groh; Annette Eicker; Christoph Förste; Zhicai Luo; Jiangjun Ran; Yunzhong Shen; Qile Zhao; Wei Feng; Cost-G Team. Combination Service for Time-variable Gravity Fields (COST-G): operational GRACE-FO combination and validation of Chinese GRACE time-series. 2021, 1 .
AMA StyleUlrich Meyer, Martin Lasser, Adrian Jäggi, Christoph Dahle, Frank Flechtner, Andreas Kvas, Saniya Behzadpour, Torsten Mayer-Gürr, Jean-Michel Lemoine, Igor Koch, Jakob Flury, Stephane Bourgogne, Andreas Groh, Annette Eicker, Christoph Förste, Zhicai Luo, Jiangjun Ran, Yunzhong Shen, Qile Zhao, Wei Feng, Cost-G Team. Combination Service for Time-variable Gravity Fields (COST-G): operational GRACE-FO combination and validation of Chinese GRACE time-series. . 2021; ():1.
Chicago/Turabian StyleUlrich Meyer; Martin Lasser; Adrian Jäggi; Christoph Dahle; Frank Flechtner; Andreas Kvas; Saniya Behzadpour; Torsten Mayer-Gürr; Jean-Michel Lemoine; Igor Koch; Jakob Flury; Stephane Bourgogne; Andreas Groh; Annette Eicker; Christoph Förste; Zhicai Luo; Jiangjun Ran; Yunzhong Shen; Qile Zhao; Wei Feng; Cost-G Team. 2021. "Combination Service for Time-variable Gravity Fields (COST-G): operational GRACE-FO combination and validation of Chinese GRACE time-series." , no. : 1.
The dynamic global water cycle is of ecological and societal importance as it affects the availability of freshwater resources and influences extreme events such as floods and droughts. This work is set in the frame of the GlobalCDA Research Unit, which has the goal of developing a calibration/data assimilation approach (C/DA) to improve the quantification of freshwater resources by combining the global hydrological model WaterGAP with geodetic (GRACE, altimetry) and remote sensing data. This presentation focuses on the validation of the C/DA results using an independent in-situ groundwater data set based on ~1500 monitoring boreholes in France.
The resulting validation data set is applied to independently assess the output of several C/DA experiments: data assimilation using different combinations of the available geodetic and remote sensing data sets and different methods of model calibration, based on either an ensemble Kalman filter approach or a Pareto-optimal calibration algorithm.
To further understand in-situ groundwater and WaterGAP data set, we subtract the coherent signals using Empirical orthogonal function (EOF). Over 85% variances can be explained by the first 3 EOFs for both data sets.
Kuei-Hua Hsu; Laurent Longuevergne; Annette Eicker; Mehedi Hasan; Andreas Güntner; Olga Engels; Kerstin Schulze; Jürgen Kusche. Using high-resolution groundwater data for the validation of a global hydrological model: evaluating WaterGAP and calibration/data assimilation (C/DA) performance over France. 2021, 1 .
AMA StyleKuei-Hua Hsu, Laurent Longuevergne, Annette Eicker, Mehedi Hasan, Andreas Güntner, Olga Engels, Kerstin Schulze, Jürgen Kusche. Using high-resolution groundwater data for the validation of a global hydrological model: evaluating WaterGAP and calibration/data assimilation (C/DA) performance over France. . 2021; ():1.
Chicago/Turabian StyleKuei-Hua Hsu; Laurent Longuevergne; Annette Eicker; Mehedi Hasan; Andreas Güntner; Olga Engels; Kerstin Schulze; Jürgen Kusche. 2021. "Using high-resolution groundwater data for the validation of a global hydrological model: evaluating WaterGAP and calibration/data assimilation (C/DA) performance over France." , no. : 1.
Knowledge of the variances and covariances of gridded terrestrial water storage anomalies (TWS) as observed with GRACE and GRACE-FO is crucial for many applications thereof. For example, data assimilation into different models, trend estimations, or combinations with other data set require reliable estimations of the variances and covariances. Today, the Level-2 Stokes coefficients are provided with formal variance-covariance matrices which can yield variance-covariance matrices of the gridded data after a labourious variance propagation through all post-processing steps, including filtering and spherical harmonic synthesis. Unfortunately, this is beyond the capabilities of many, if not most, users.
This is why, we developed a spatial covariance model for gridded TWS data. The covariance model results in non-homogeneous, non-stationary, and anisotropic covariances. This model also accommodates a wave-like behaviour in latitudinal-directed correlations caused by residual striping errors. The model is applied to both VDK3 filtered GFZ RL06 and ITSG-Grace2018 TWS data.
With thus derived covariances it is possible to estimate the uncertainties of mean TWS time series for any arbitrary region such as river basins. On the other hand, such time series uncertainties can also be derived from the afore mentioned formal covariance matrices. Here, only the formal covariance matrices of ITSG-Grace2018 are used which are also filtered with the VDK3 filter. All together, we are able to compare globally the time series uncertainties of both the modelled and formal approach. Further, the modelled uncertainties are compared to empirical standard deviations in arid regions in the Arabian, Sahara, and Gobi desert where residual hydrological signal can be neglected. Both in the temporal and spatial domain they show a very satisfying agreement proving the usefulness of the covariance model for the users.
Eva Boergens; Andreas Kvas; Henryk Dobslaw; Annette Eicker; Christoph Dahle; Frank Flechtner. Uncertainties of TWS Time Series for Arbitrary Regions - Modelled vs. Formal Covariances. 2021, 1 .
AMA StyleEva Boergens, Andreas Kvas, Henryk Dobslaw, Annette Eicker, Christoph Dahle, Frank Flechtner. Uncertainties of TWS Time Series for Arbitrary Regions - Modelled vs. Formal Covariances. . 2021; ():1.
Chicago/Turabian StyleEva Boergens; Andreas Kvas; Henryk Dobslaw; Annette Eicker; Christoph Dahle; Frank Flechtner. 2021. "Uncertainties of TWS Time Series for Arbitrary Regions - Modelled vs. Formal Covariances." , no. : 1.
Information on water storage changes in the soil can be obtained on a global scale from different types of satellite observations. While active or passive microwave remote sensing is limited to investigating the upper few centimeters of the soil, satellite gravimetry is sensitive to variations in the full column of terrestrial water storage (TWS) but cannot distinguish between storage variations occurring in different soil depths. Jointly analyzing both data types promises interesting insights into the underlying hydrological dynamics and may enable a better process understanding of water storage change in the subsurface.
In this study, we aim at investigating the global relationship of (1) several satellite soil moisture (SM) products and (2) non-standard daily TWS data from the GRACE and GRACE-FO satellite gravimetry missions on different time scales. We decompose the data sets into different temporal frequencies from seasonal to sub-monthly signals and carry out the comparison with respect to spatial patterns and temporal variability. Level-3 (Surface SM up to 5 cm depth) and Level-4 (Root-Zone SM up to 1 m depth) data sets of the SMOS and SMAP missions as well as the ESA CCI data set are used in this investigation.
Since a direct comparison of the absolute values is not possible due to the different integration depths of the two data sets (SM and TWS), we will analyze their relationship using Pearson’s pairwise correlation coefficient. Furthermore, a time-shift analysis is carried out by means of cross-correlation to identify time lags between SM and TWS data sets that indicate differences in the temporal dynamics of SM storage change in varying depth layers.
Daniel Blank; Annette Eicker; Laura Jensen; Andreas Güntner. Joint analysis of remotely sensed soil moisture and water storage variations from satellite gravimetry. 2021, 1 .
AMA StyleDaniel Blank, Annette Eicker, Laura Jensen, Andreas Güntner. Joint analysis of remotely sensed soil moisture and water storage variations from satellite gravimetry. . 2021; ():1.
Chicago/Turabian StyleDaniel Blank; Annette Eicker; Laura Jensen; Andreas Güntner. 2021. "Joint analysis of remotely sensed soil moisture and water storage variations from satellite gravimetry." , no. : 1.
The Gravity Recovery Object Oriented Programming System (GROOPS) is a software toolkit written in C++ that enables the user to perform core geodetic tasks. Key features of the software include gravity field recovery from satellite and terrestrial data, the determination of satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. Next to raw data processing, GROOPS is capable to operate on time series and spatial data to directly analyze and visualize the computed data sets. Most tasks and algorithms are (optionally) parallelized through the Message Passing Interface, thus the software enables a smooth transition from single-CPU desktop computers to large distributed computing environments for resource intensive tasks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of the software is freely available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and step-by-step installation instructions.
Torsten Mayer-Gürrid; Saniya BehzadpouriD; Annette EickeriD; Matthias Ellmer; Beate Koch; Sandro KraussiD; Christian Pock; Daniel Rieser; Sebastian StrasseriD; Barbara Suesser-Rechberger; Norbert Zehentner; Andreas KvasiD. GROOPS: A software toolkit for gravity field recovery and GNSS processing. 2020, 1 .
AMA StyleTorsten Mayer-Gürrid, Saniya BehzadpouriD, Annette EickeriD, Matthias Ellmer, Beate Koch, Sandro KraussiD, Christian Pock, Daniel Rieser, Sebastian StrasseriD, Barbara Suesser-Rechberger, Norbert Zehentner, Andreas KvasiD. GROOPS: A software toolkit for gravity field recovery and GNSS processing. . 2020; ():1.
Chicago/Turabian StyleTorsten Mayer-Gürrid; Saniya BehzadpouriD; Annette EickeriD; Matthias Ellmer; Beate Koch; Sandro KraussiD; Christian Pock; Daniel Rieser; Sebastian StrasseriD; Barbara Suesser-Rechberger; Norbert Zehentner; Andreas KvasiD. 2020. "GROOPS: A software toolkit for gravity field recovery and GNSS processing." , no. : 1.
Climate change will affect the terrestrial water cycle during the next decades by impacting the seasonal cycle, interannual variations, and long-term linear trends of water stored at or beyond the surface. Since 2002, terrestrial water storage (TWS) has been globally observed by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO). Next Generation Gravity Missions (NGGMs) are planned to extend this record in the near future. Based on a multi-model ensemble of climate model output provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6) covering the years 2002–2100, we assess possible changes in TWS variability with respect to present-day conditions to help defining scientific requirements for NGGMs. We find that present-day GRACE accuracies are sufficient to detect amplitude and phase changes in the seasonal cycle in a third of the land surface, whereas a five times more accurate double-pair mission could resolve such changes almost everywhere outside the most arid landscapes of our planet. We also select one individual model experiment out of the CMIP6 ensemble that closely matches both GRACE observations and the multi-model median of all CMIP6 realizations, which might serve as basis for satellite mission performance studies extending over many decades to demonstrate the suitability of NGGM satellite missions to monitor long-term climate variations in the terrestrial water cycle.
Laura Jensen; Annette Eicker; Henryk Dobslaw; Roland Pail. Emerging Changes in Terrestrial Water Storage Variability as a Target for Future Satellite Gravity Missions. Remote Sensing 2020, 12, 3898 .
AMA StyleLaura Jensen, Annette Eicker, Henryk Dobslaw, Roland Pail. Emerging Changes in Terrestrial Water Storage Variability as a Target for Future Satellite Gravity Missions. Remote Sensing. 2020; 12 (23):3898.
Chicago/Turabian StyleLaura Jensen; Annette Eicker; Henryk Dobslaw; Roland Pail. 2020. "Emerging Changes in Terrestrial Water Storage Variability as a Target for Future Satellite Gravity Missions." Remote Sensing 12, no. 23: 3898.
Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes". 2020, 1 .
AMA StyleSimon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes". . 2020; ():1.
Chicago/Turabian StyleSimon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2020. "Supplementary material to "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes"." , no. : 1.
Observations of changes in terrestrial water storage obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighboring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions. In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes & reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a re-location of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction RECOG-EQ includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above 9 Mw. We can show that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, even in neighboring river basins, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available as open access via the Pangea database (RECOG-LR: Deggim et al. (2020a) https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al. (2020b, under revision), https://doi.pangaea.de/10.1594/PANGAEA.921923).
Simon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. 2020, 1 -30.
AMA StyleSimon Deggim, Annette Eicker, Lennart Schawohl, Helena Gerdener, Kerstin Schulze, Olga Engels, Jürgen Kusche, Anita T. Saraswati, Tonie van Dam, Laura Ellenbeck, Denise Dettmering, Christian Schwatke, Stefan Mayr, Igor Klein, Laurent Longuevergne. RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes. . 2020; ():1-30.
Chicago/Turabian StyleSimon Deggim; Annette Eicker; Lennart Schawohl; Helena Gerdener; Kerstin Schulze; Olga Engels; Jürgen Kusche; Anita T. Saraswati; Tonie van Dam; Laura Ellenbeck; Denise Dettmering; Christian Schwatke; Stefan Mayr; Igor Klein; Laurent Longuevergne. 2020. "RECOG RL01: Correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes." , no. : 1-30.
We present the operational GRACE-FO combined time-series of monthly gravity fields of the Combination Service for Time-variable Gravity fields (COST-G) of the International Association of Geodesy (IAG). COST-G_GRACE-FO_RL01_operational is combined at AIUB and relies on operational monthly solutions of the COST-G Analysis Centers GFZ, GRGS, IfG, LUH and AIUB and the associated Analysis Centers CSR and JPL. All COST-G Analysis Centers have passed a benchmark test to ensure consistency between the different processing approaches and all of the contributing time-series undergo a strict quality control focusing on the signal content in river basins and polar regions with pronounced changes in ice mass to uncover any regularization that may bias the combination.
The combination is performed by variance component estimation on the solution level, the relative monthly weights thus providing valuable and independent insight into the consistency and noise levels of the individual monthly contributions. The combined products then are validated internally in terms of noise, approximated by the non-secular, non-seasonal variability over the oceans. Once they have passed this quality control the combined gravity fields are assessed by an external board of experts who evaluate them in terms of orbit predictions, lake altimetry, river hydrology or oceanography.
Ulrich Meyer; Martin Lasser; Adrian Jäggi; Frank Flechtner; Christoph Dahle; Torsten Mayer-Gürr; Andreas Kvas; Saniya Behzadpour; Jean-Michel Lemoine; Stephane Bourgogne; Igor Koch; Andreas Groh; Christoph Förste; Annette Eicker; Benoit Meyssignac. Combination Service for Time-variable Gravity Field Solutions (COST-G) – GRACE-FO operational combination. 2020, 1 .
AMA StyleUlrich Meyer, Martin Lasser, Adrian Jäggi, Frank Flechtner, Christoph Dahle, Torsten Mayer-Gürr, Andreas Kvas, Saniya Behzadpour, Jean-Michel Lemoine, Stephane Bourgogne, Igor Koch, Andreas Groh, Christoph Förste, Annette Eicker, Benoit Meyssignac. Combination Service for Time-variable Gravity Field Solutions (COST-G) – GRACE-FO operational combination. . 2020; ():1.
Chicago/Turabian StyleUlrich Meyer; Martin Lasser; Adrian Jäggi; Frank Flechtner; Christoph Dahle; Torsten Mayer-Gürr; Andreas Kvas; Saniya Behzadpour; Jean-Michel Lemoine; Stephane Bourgogne; Igor Koch; Andreas Groh; Christoph Förste; Annette Eicker; Benoit Meyssignac. 2020. "Combination Service for Time-variable Gravity Field Solutions (COST-G) – GRACE-FO operational combination." , no. : 1.
Reliable predictions of terrestrial water storage (TWS) changes for the next couple of years would be extremely valuable for, e.g., agriculture and water management. In contrast to long-term projections of future climate conditions, so-called decadal predictions do not depend on prescribed CO2 scenarios but provide unconditional forecasts similar to numerical weather models. Therefore, opposed to climate projections, decadal predictions (or hindcasts, if run for the past) can directly be compared to observations. Here, we evaluate decadal hindcasts of TWS related variables from an ensemble of 5 coupled CMIP5 climate models against a TWS data set based on GRACE satellite observations.
Since data from the CMIP5 models and GRACE is jointly available in only 9 years, we access a GRACE-like reconstruction of TWS derived from precipitation and temperature data sets (Humphrey and Gudmundsson, 2019), which expands the analysis time-frame to 41 years. The skill of the decadal hindcasts is assessed by means of anomaly correlations and root-mean-square deviations (RMSD) for the yearly global average and aggregated over different climate zones. Furthermore, we compute global maps of correlation and RMSD.
We find that at least for the first two prediction years the decadal model experiments clearly outperform the classical climate projections, regionally even for the third year. We can thereby demonstrate that the observation type “terrestrial water storage” as available from the GRACE and GRACE-FO missions is suitable as additional data set in the validation and/or calibration of climate model experiments.
Laura Jensen; Annette Eicker; Tobias Stacke; Henryk Dobslaw. Evaluation of land water storage prediction skill in CMIP5 decadal hindcasts by means of a GRACE-based data set. 2020, 1 .
AMA StyleLaura Jensen, Annette Eicker, Tobias Stacke, Henryk Dobslaw. Evaluation of land water storage prediction skill in CMIP5 decadal hindcasts by means of a GRACE-based data set. . 2020; ():1.
Chicago/Turabian StyleLaura Jensen; Annette Eicker; Tobias Stacke; Henryk Dobslaw. 2020. "Evaluation of land water storage prediction skill in CMIP5 decadal hindcasts by means of a GRACE-based data set." , no. : 1.
The application of GRACE and GRACE-FO observed gridded terrestrial water storage data (TWS) often requires realistic assumptions of the data variances and covariances. Such covariances are, e.g., needed for data assimilation in various models or combinations with other data sets. The formal variance-covariance matrices now provided with the Stokes coefficients can yield such spatial variances and covariances after variance propagating them through the various post-processing steps, including the filtering, and spherical harmonic synthesis. However, a rigorous variance propagation to the TWS grids is beyond the capabilities of most non-geodetic users.
That is why we developed a new spatial covariance model for global TWS grids. This covariance model is non-stationary (time-depending), non-homogeneous (location-depending), and anisotropic (direction-depending). Additionally, it allows latitudinal wave-like correlations caused by residual striping errors. The model is tested for both GFZ RL06 Level-3 TWS data as provided via the GravIS portal (gravis.gfz-potsdam.de) and ITSG-Grace2018 GravIS-like processed Level-3 TWS data. The model parameters are fitted to empirical correlations derived from both TWS fields. Both data sets yield the same model parameters within the uncertainty of the parameter estimation.
Now, the covariance model derived thereof can be used to estimate uncertainties of mean TWS time series of arbitrary regions such as river basins. Here, we use a global basin segmentation covering all continents. At the same time, such regional uncertainties can be derived from formal variance-covariance matrices as well. To this end, the formal ITSG-Grace2018 variance-covariance matrices of the spherical harmonic coefficients are used. Thus, the modelled and formal basin uncertainties can be compared against each other globally, both spatially and temporally. Further, external validation investigates the usefulness of the basin uncertainties for applications such as data assimilation into hydrological models. Our results show a high agreement between the modelled and the formal basin uncertainties proving our approach of modelled covariance to be a suitable surrogate for the formal variance-covariance matrices.
Eva Boergens; Andreas Kvas; Henryk Dobslaw; Annette Eicker; Christoph Dahle; Frank Flechtner. Uncertainties of Terrestrial Water Storage Anomalies for Global Basins – A Comparison Between Modelled and Formal Covariances. 2020, 1 .
AMA StyleEva Boergens, Andreas Kvas, Henryk Dobslaw, Annette Eicker, Christoph Dahle, Frank Flechtner. Uncertainties of Terrestrial Water Storage Anomalies for Global Basins – A Comparison Between Modelled and Formal Covariances. . 2020; ():1.
Chicago/Turabian StyleEva Boergens; Andreas Kvas; Henryk Dobslaw; Annette Eicker; Christoph Dahle; Frank Flechtner. 2020. "Uncertainties of Terrestrial Water Storage Anomalies for Global Basins – A Comparison Between Modelled and Formal Covariances." , no. : 1.
Changes in terrestrial water storage as observed by the satellite gravity mission GRACE (Gravity Recovery and Climate Experiment) represent a new and completely independent way to constrain the net flux imbalance in atmospheric reanalyses. In this study daily GRACE gravity field changes are used for the first time to investigate high-frequency hydro-meteorological fluxes over the continents. Band-pass filtered water fluxes are derived from GRACE water storage time series by first applying a numerical differentiation filter and subsequent high-pass filtering to isolate fluxes at periods between 5 and 30 days corresponding to typical time-scales of weather system persistence at moderate latitudes. By comparison with the latest atmospheric reanalysis ERA5 of the European Centre for Medium-Range Weather Forecasts (ECWMF) we show that daily GRACE gravity field models contain realistic high-frequency water flux information. Furthermore, GRACE-derived water fluxes can clearly identify improvements realized within ERA5 over its direct predecessor ERA-Interim particularly in equatorial and temperate climate zones. The documented improvements are in good agreement with rain gauge validation, but GRACE also identifies three distinct regions (Sahel Zone, Okavango Catchment, Kimberley Plateau) with a slight degradation of net-fluxes in ERA5 with respect to ERA-Interim, thereby highlighting the potentially added value of non-standard daily GRACE gravity series for hydro-meteorological monitoring purposes.
Annette Eicker; Laura Jensen; Viviana Wöhnke; Henryk Dobslaw; Andreas Kvas; Torsten Mayer-Gürr; Robert Dill. Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses. Scientific Reports 2020, 10, 1 -10.
AMA StyleAnnette Eicker, Laura Jensen, Viviana Wöhnke, Henryk Dobslaw, Andreas Kvas, Torsten Mayer-Gürr, Robert Dill. Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses. Scientific Reports. 2020; 10 (1):1-10.
Chicago/Turabian StyleAnnette Eicker; Laura Jensen; Viviana Wöhnke; Henryk Dobslaw; Andreas Kvas; Torsten Mayer-Gürr; Robert Dill. 2020. "Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses." Scientific Reports 10, no. 1: 1-10.
Over the recent years, the computation of temporally high-resolution (daily) GRACE gravity field solutions has advanced as an alternative to the processing of monthly models. In this presentation we will show that recent processing improvements incorporated in the latest version of daily gravity field models (ITSG-Grace2018) now allow for the investigation of water flux signals on the continents down to time scales of a few days.
Time variations in terrestrial water storage derived from GRACE can be related to atmospheric net-fluxes of precipitation (P), evapotranspiration (E) and lateral runoff (R) via the terrestrial water balance equation, which makes GRACE a new and completely independent data set for constraining hydro-meteorological observations and the output of atmospheric reanalyses.
In our study, band-pass filtered water fluxes are derived from the daily GRACE water storage time series by first applying a numerical differentiation filter and subsequent high-pass filtering to isolate fluxes at periods between 5 and 30 days. We can show that on these time scales GRACE is able to identify quality differences between different global reanalyses, e.g. the improvements in the latest reanalysis ERA5 of the European Centre for Medium-Range Weather Forecasts (ECWMF) over its direct predecessor ERA-Interim.
We can further demonstrate that only the very recent progress in GRACE data processing has enabled the use of daily GRACE time series for such an evaluation of high-frequency atmospheric fluxes. The accuracy of the previous daily GRACE time series ITSG-Grace2016 would not have been sufficient to carry out such an assessment.
Annette Eicker; Laura Jensen; Viviana Wöhnke; Andreas Kvas; Henryk Dobslaw; Torsten Mayer-Gürr; Robert Dill. Can daily GRACE gravity field models be used to evaluate short-term hydro-meteorological signals over the continents? 2020, 1 .
AMA StyleAnnette Eicker, Laura Jensen, Viviana Wöhnke, Andreas Kvas, Henryk Dobslaw, Torsten Mayer-Gürr, Robert Dill. Can daily GRACE gravity field models be used to evaluate short-term hydro-meteorological signals over the continents? . 2020; ():1.
Chicago/Turabian StyleAnnette Eicker; Laura Jensen; Viviana Wöhnke; Andreas Kvas; Henryk Dobslaw; Torsten Mayer-Gürr; Robert Dill. 2020. "Can daily GRACE gravity field models be used to evaluate short-term hydro-meteorological signals over the continents?" , no. : 1.
Coupled climate models participating in the CMIP5 (Coupled Model Intercomparison Project Phase 5) exhibit a large inter‐model spread in the representation of long‐term trends in soil moisture and snow in response to anthropogenic climate change. We evaluate long‐term (1861/01‐2099/12) water storage trends from 21 CMIP5 models against observed trends in terrestrial water storage (TWS) obtained from 14 years (2002/04‐2016/08) of the GRACE (Gravity Recovery And Climate Experiment) satellite mission. This is complicated due to the incomplete representation of TWS in CMIP5 models and interannual climate variability masking long‐term trends in observations. We thus evaluate first the spread in projected trends among CMIP5 models and identify regions of broad model consensus. Second, we assess the extent to which these projected trends are already present during the historical period (1861/01‐2016/08) and thus potentially detectable in observational records available today. Third, we quantify the degree to which 14‐year tendencies can be expected to represent long‐term trends, finding that regional long‐term trends start to emerge from interannual variations after just 14 years while stable global trend patterns are detectable after 30 years. We classify regions of strong model consensus into areas where 1) climate‐related TWS changes are supported by the direction of GRACE trends, 2) mismatch of trends hints at possible model deficits, 3) the short observation time span and/or anthropogenic influences prevent reliable conclusions about long‐term wetting or drying. We thereby demonstrate the value of satellite observations of water storage to further constrain the response of the terrestrial water cycle to climate change.
L. Jensen; A. Eicker; H. Dobslaw; T. Stacke; V. Humphrey. Long‐Term Wetting and Drying Trends in Land Water Storage Derived From GRACE and CMIP5 Models. Journal of Geophysical Research: Atmospheres 2019, 124, 9808 -9823.
AMA StyleL. Jensen, A. Eicker, H. Dobslaw, T. Stacke, V. Humphrey. Long‐Term Wetting and Drying Trends in Land Water Storage Derived From GRACE and CMIP5 Models. Journal of Geophysical Research: Atmospheres. 2019; 124 (17-18):9808-9823.
Chicago/Turabian StyleL. Jensen; A. Eicker; H. Dobslaw; T. Stacke; V. Humphrey. 2019. "Long‐Term Wetting and Drying Trends in Land Water Storage Derived From GRACE and CMIP5 Models." Journal of Geophysical Research: Atmospheres 124, no. 17-18: 9808-9823.
The GRACE satellites provide signals of total terrestrial water storage (TWS) variations over large spatial domains at seasonal to inter-annual timescales. While the GRACE data have been extensively and successfully used to assess spatio-temporal changes in TWS, little effort has been made to quantify the relative contributions of snowpacks, soil moisture, and other components to the integrated TWS signal across northern latitudes, which is essential to gain a better insight into the underlying hydrological processes. Therefore, this study aims to assess which storage component dominates the spatio-temporal patterns of TWS variations in the humid regions of northern mid- to high latitudes. To do so, we constrained a rather parsimonious hydrological model with multiple state-of-the-art Earth observation products including GRACE TWS anomalies, estimates of snow water equivalent, evapotranspiration fluxes, and gridded runoff estimates. The optimized model demonstrates good agreement with observed hydrological spatio-temporal patterns and was used to assess the relative contributions of solid (snowpack) versus liquid (soil moisture, retained water) storage components to total TWS variations. In particular, we analysed whether the same storage component dominates TWS variations at seasonal and inter-annual temporal scales, and whether the dominating component is consistent across small to large spatial scales. Consistent with previous studies, we show that snow dynamics control seasonal TWS variations across all spatial scales in the northern mid- to high latitudes. In contrast, we find that inter-annual variations of TWS are dominated by liquid water storages at all spatial scales. The relative contribution of snow to inter-annual TWS variations, though, increases when the spatial domain over which the storages are averaged becomes larger. This is due to a stronger spatial coherence of snow dynamics that are mainly driven by temperature, as opposed to spatially more heterogeneous liquid water anomalies, that cancel out when averaged over a larger spatial domain. The findings first highlight the effectiveness of our model–data fusion approach that jointly interprets multiple Earth observation data streams with a simple model. Secondly, they reveal that the determinants of TWS variations in snow-affected northern latitudes are scale-dependent. In particular, they seem to be not merely driven by snow variability, but rather are determined by liquid water storages on inter-annual timescales. We conclude that inferred driving mechanisms of TWS cannot simply be transferred from one scale to another, which is of particular relevance for understanding the short- and long-term variability of water resources.
Tina Trautmann; Sujan Koirala; Nuno Carvalhais; Annette Eicker; Manfred Fink; Christoph Niemann; Martin Jung. Understanding terrestrial water storage variations in northern latitudes across scales. Hydrology and Earth System Sciences 2018, 22, 4061 -4082.
AMA StyleTina Trautmann, Sujan Koirala, Nuno Carvalhais, Annette Eicker, Manfred Fink, Christoph Niemann, Martin Jung. Understanding terrestrial water storage variations in northern latitudes across scales. Hydrology and Earth System Sciences. 2018; 22 (7):4061-4082.
Chicago/Turabian StyleTina Trautmann; Sujan Koirala; Nuno Carvalhais; Annette Eicker; Manfred Fink; Christoph Niemann; Martin Jung. 2018. "Understanding terrestrial water storage variations in northern latitudes across scales." Hydrology and Earth System Sciences 22, no. 7: 4061-4082.