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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 October 2019) | Viewed by 67452

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Special Issue Editors

Dr. Thomas Gruber

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Guest Editor

Institute of Astronomical and Physical Geodesy, School for Engineering and Design, Technical University of Munich, 80333 Munich, Germany
Interests: gravity field missions; gravity field modelling; height systems; mass distribution and transport
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Annette Eicker

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Guest Editor

HafenCity University Hamburg
Interests: satellite gravity missions; hydrology; climate research; data assimilation
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Frank Flechtner

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Guest Editor

Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum - GFZ
Interests: satellite gravity missions; time-variable gravity fields

Special Issue Information

Dear Colleagues,

During the last two decades, satellite gravimetry has become a new remote sensing technique providing a detailed global picture of the physical structure of the Earth. For the first time, with the CHAMP, GRACE, and GOCE missions, mass irregularities and the transport of mass in the Earth system could be systematically observed and monitored from space. A wide range of Earth science disciplines and operational observing systems benefit from these observations and have been enabled to improve their models and to get new insights into processes of the Earth system (e.g., water cycle, continental hydrology, ocean modelling, ice sheet and glacier melting, lithosphere modelling). Recently, because of the success of these missions, GRACE Follow-On was launched in order to continue the time series of mass transport observations, which is needed to disentangle the effects of anthropogenic and natural sources of climate change on the Earth system. The value of satellite gravimetry has been acknowledged by the international Earth science community in various resolutions and, in the meantime, this procedure is regarded as a new remote-sensing tool, providing information that is complementary to other remote-sensing techniques. In order to secure sustained observations of mass distribution and mass transport on a long-term basis, space agencies and the Earth science community are currently planning future satellite gravimetry mission concepts enabling higher accuracy and better spatial and temporal resolution. This Special Issue is calling for contributions about observation techniques, data processing, and achievements obtained with satellite gravimetry missions so far. In addition, the first results of the GRACE Follow-On mission and future concepts of satellite constellations for monitoring the mass distribution of the Earth shall be addressed. Potential topics of the Special Issue include, but are not limited to:

CHAMP, GRACE, GRACE Follow-On, and GOCE data analysis, including instrument performance
Techniques for gravity field modelling with satellite data
Current and future concepts for satellite gravimetry
New observation techniques in satellite gravimetry
Satellite gravity field models (mean field and time series) and their validation
Time series of mass transport in the Earth system
Applications of satellite gravimetry in Earth sciences

Dr. Thomas Gruber
Prof. Dr. Annette Eicker
Prof. Dr. Frank Flechtner
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

GRACE and GRACE Follow-On Mission
GOCE Mission
Next-Generation Gravity Field Missions
Current and future observation concepts and Instruments
Gravity Field Modelling
Geoid, Mass distribution
Mass transport in the Earth system
Applications in Earth sciences (hydrology, glaciology, oceanography, solid Earth, and others)

Published Papers (13 papers)

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Research

28 pages, 3444 KiB

Open AccessArticle

An Assessment of the GOCE High-Level Processing Facility (HPF) Released Global Geopotential Models with Regional Test Results in Turkey

by Bihter Erol, Mustafa Serkan Işık and Serdar Erol

Remote Sens. 2020, 12(3), 586; https://doi.org/10.3390/rs12030586 - 10 Feb 2020

Cited by 10 | Viewed by 3924

Abstract

The launch of dedicated satellite missions at the beginning of the 2000s led to significant improvement in the determination of Earth gravity field models. As a consequence of this progress, both the accuracies and the spatial resolutions of the global geopotential models increased. However, the spectral behaviors and the accuracies of the released models vary mainly depending on their computation strategies. These strategies are briefly explained in this article. Comprehensive quality assessment of the gravity field models by means of spectral and statistical analyses provides a comparison of the gravity field mapping accuracies of these models, as well as providing an understanding of their progress. The practical benefit of these assessments by means of choosing an optimal model with the highest accuracy and best resolution for a specific application is obvious for a broad range of geoscience applications, including geodesy and geophysics, that employ Earth gravity field parameters in their studies. From this perspective, this study aims to evaluate the GOCE High-Level Processing Facility geopotential models including recently published sixth releases using different validation methods recommended in the literature, and investigate their performances comparatively and in addition to some other models, such as GOCO05S, GOGRA04S and EGM2008. In addition to the validation statistics from various countries, the study specifically emphasizes the numerical test results in Turkey. It is concluded that the performance improves from the first generation RL01 models toward the final RL05 models, which were based on the entire mission data. This outcome was confirmed when the releases of different computation approaches were considered. The accuracies of the RL05 models were found to be similar to GOCO05S, GOGRA04S and even to RL06 versions but better than EGM2008, in their maximum expansion degrees. Regarding the results obtained from these tests using the GPS/leveling observations in Turkey, the contribution of the GOCE data to the models was significant, especially between the expansion degrees of 100 and 250. In the study, the tested geopotential models were also considered for detailed geoid modeling using the remove-compute-restore method. It was found that the best-fitting geopotential model with its optimal expansion degree (please see the definition of optimal degree in the article) improved the high-frequency regional geoid model accuracy by almost 15%. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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19 pages, 6235 KiB

Open AccessArticle

Next-Generation Gravity Missions: Sino-European Numerical Simulation Comparison Exercise

by Roland Pail, Hsien-Chi Yeh, Wei Feng, Markus Hauk, Anna Purkhauser, Changqing Wang, Min Zhong, Yunzhong Shen, Qiujie Chen, Zhicai Luo, Hao Zhou, Bingshi Liu, Yongqi Zhao, Xiancai Zou, Xinyu Xu, Bo Zhong, Roger Haagmans and Houze Xu

Remote Sens. 2019, 11(22), 2654; https://doi.org/10.3390/rs11222654 - 13 Nov 2019

Cited by 17 | Viewed by 3575

Abstract

Temporal gravity retrieval simulation results of a future Bender-type double pair mission concept, performed by five processing centers of a Sino-European study team, have been inter-compared and assessed. They were computed in a synthetic closed-loop simulation world by five independent software systems applying different gravity retrieval methods, but were based on jointly defined mission scenarios. The inter-comparison showed that the results achieved a quite similar performance. Exemplarily, the root mean square (RMS) deviations of global equivalent water height fields from their true reference, resolved up to degree and order 30 of a 9-day solution, vary in the order of 10% of the target signal. Also, co-estimated independent daily gravity fields up to degree and order 15, which have been co-estimated by all processing centers, do not show large differences among each other. This positive result is an important pre-requisite and basis for future joint activities towards the realization of next-generation gravity missions. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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22 pages, 3188 KiB

Open AccessEditor’s ChoiceArticle

The GFZ GRACE RL06 Monthly Gravity Field Time Series: Processing Details and Quality Assessment

by Christoph Dahle, Michael Murböck, Frank Flechtner, Henryk Dobslaw, Grzegorz Michalak, Karl Hans Neumayer, Oleh Abrykosov, Anton Reinhold, Rolf König, Roman Sulzbach and Christoph Förste

Remote Sens. 2019, 11(18), 2116; https://doi.org/10.3390/rs11182116 - 11 Sep 2019

Cited by 79 | Viewed by 8579

Abstract

Time-variable gravity field models derived from observations of the Gravity Recovery and Climate Experiment (GRACE) mission, whose science operations phase ended in June 2017 after more than 15 years, enabled a multitude of studies of Earth’s surface mass transport processes and climate change. The German Research Centre for Geosciences (GFZ), routinely processing such monthly gravity fields as part of the GRACE Science Data System, has reprocessed the complete GRACE mission and released an improved GFZ GRACE RL06 monthly gravity field time series. This study provides an insight into the processing strategy of GFZ RL06 which has been considerably changed with respect to previous GFZ GRACE releases, and modifications relative to the precursor GFZ RL05a are described. The quality of the RL06 gravity field models is analyzed and discussed both in the spectral and spatial domain in comparison to the RL05a time series. All results indicate significant improvements of about 40% in terms of reduced noise. It is also shown that the GFZ RL06 time series is a step forward in terms of consistency, and that errors of the gravity field coefficients are more realistic. These findings are confirmed as well by independent validation of the monthly GRACE models, as done in this work by means of ocean bottom pressure in situ observations and orbit tests with the GOCE satellite. Thus, the GFZ GRACE RL06 time series allows for a better quantification of mass changes in the Earth system. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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19 pages, 17866 KiB

Open AccessArticle

Improved Estimates of Geocenter Variability from Time-Variable Gravity and Ocean Model Outputs

by Tyler C. Sutterley and Isabella Velicogna

Remote Sens. 2019, 11(18), 2108; https://doi.org/10.3390/rs11182108 - 10 Sep 2019

Cited by 5 | Viewed by 3245

Abstract

Geocenter variations relate the motion of the Earth’s center of mass with respect to its center of figure, and represent global-scale redistributions of the Earth’s mass. We investigate different techniques for estimating of geocenter motion from combinations of time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On missions, and bottom pressure outputs from ocean models. Here, we provide self-consistent estimates of geocenter variability incorporating the effects of self-attraction and loading, and investigate the effect of uncertainties in atmospheric and oceanic variation. The effects of self-attraction and loading from changes in land water storage and ice mass change affect both the seasonality and long-term trend in geocenter position. Omitting the redistribution of sea level affects the average annual amplitudes of the x, y, and z components by 0.2, 0.1, and 0.3 mm, respectively, and affects geocenter trend estimates by 0.02, 0.04 and 0.05 mm/yr for the the x, y, and z components, respectively. Geocenter estimates from the GRACE Follow-On mission are consistent with estimates from the original GRACE mission. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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14 pages, 5346 KiB

Open AccessArticle

A New Approach to Earth’s Gravity Field Modeling Using GPS-Derived Kinematic Orbits and Baselines

by Xiang Guo and Qile Zhao

Remote Sens. 2019, 11(14), 1728; https://doi.org/10.3390/rs11141728 - 21 Jul 2019

Cited by 6 | Viewed by 2967

Abstract

Earth’s gravity field recovery from GPS observations collected by low earth orbiting (LEO) satellites is a well-established technique, and kinematic orbits are commonly used for that purpose. Nowadays, more and more satellites are flying in close formations. The GPS-derived kinematic baselines between them can reach millimeter precision, which is more precise than the centimeter-level kinematic orbits. Thus, it has long been expected that the more precise kinematic baselines can deliver better gravity field solutions. However, this expectation has not been met yet in practice. In this study, we propose a new approach to gravity field modeling, in which kinematic orbits of the reference satellite and baseline vectors between the reference satellite and its accompanying satellite are jointly inverted. To validate the added value, data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used. We derive kinematic orbits and inter-satellite baselines of the twin GRACE satellites from the GPS data collected in the year of 2010. Then two sets of monthly gravity field solutions up to degree and order 60 are produced. One is derived from kinematic orbits of the twin GRACE satellites (‘orbit approach’). The other is derived from kinematic orbits of GRACE A and baseline vectors between GRACE A and B (‘baseline approach’). Analysis of observation postfit residuals shows that noise in the kinematic baselines is notably lower than the kinematic orbits by 50, 47 and 43% for the along-track, cross-track and radial components, respectively. Regarding the gravity field solutions, analysis in the spectral domain shows that noise of the gravity field solutions beyond degree 10 can be significantly reduced when the baseline approach is applied, with cumulative errors up to degree 60 being reduced by 34%, when compared to the orbit approach. In the spatial domain, the recovered mass changes with the baseline approach are more consistent with those inferred from the K-Band Ranging based solutions. Our results demonstrate that the proposed baseline approach is able to provide better gravity field solutions than the orbit approach. The findings may facilitate, among others, bridging the gap between GRACE and GRACE Follow-On satellite mission. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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19 pages, 11120 KiB

Open AccessArticle

GOCE-Derived Coseismic Gravity Gradient Changes Caused by the 2011 Tohoku-Oki Earthquake

by Xinyu Xu, Hao Ding, Yongqi Zhao, Jin Li and Minzhang Hu

Remote Sens. 2019, 11(11), 1295; https://doi.org/10.3390/rs11111295 - 30 May 2019

Cited by 2 | Viewed by 3085

Abstract

In contrast to most of the coseismic gravity change studies, which are generally based on data from the Gravity field Recovery and Climate Experiment (GRACE) satellite mission, we use observations from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) Satellite Gravity Gradient (SGG) mission to estimate the coseismic gravity and gravity gradient changes caused by the 2011 Tohoku-Oki Mw 9.0 earthquake. We first construct two global gravity field models up to degree and order 220, before and after the earthquake, based on the least-squares method, with a bandpass Auto Regression Moving Average (ARMA) filter applied to the SGG data along the orbit. In addition, to reduce the influences of colored noise in the SGG data and the polar gap problem on the recovered model, we propose a tailored spherical harmonic (TSH) approach, which only uses the spherical harmonic (SH) coefficients with the degree range 30–95 to compute the coseismic gravity changes in the spatial domain. Then, both the results from the GOCE observations and the GRACE temporal gravity field models (with the same TSH degrees and orders) are simultaneously compared with the forward-modeled signals that are estimated based on the fault slip model of the earthquake event. Although there are considerable misfits between GOCE-derived and modeled gravity gradient changes (ΔV_xx, ΔV_yy, ΔV_zz, and ΔV_xz), we find analogous spatial patterns and a significant change (greater than 3σ) in gravity gradients before and after the earthquake. Moreover, we estimate the radial gravity gradient changes from the GOCE-derived monthly time-variable gravity field models before and after the earthquake, whose amplitudes are at a level over three times that of their corresponding uncertainties, and are thus significant. Additionally, the results show that the recovered coseismic gravity signals in the west-to-east direction from GOCE are closer to the modeled signals than those from GRACE in the TSH degree range 30–95. This indicates that the GOCE-derived gravity models might be used as additional observations to infer/explain some time-variable geophysical signals of interest. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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22 pages, 14105 KiB

Open AccessArticle

SLR, GRACE and Swarm Gravity Field Determination and Combination

by Ulrich Meyer, Krzysztof Sosnica, Daniel Arnold, Christoph Dahle, Daniela Thaller, Rolf Dach and Adrian Jäggi

Remote Sens. 2019, 11(8), 956; https://doi.org/10.3390/rs11080956 - 22 Apr 2019

Cited by 58 | Viewed by 5959

Abstract

Satellite gravimetry allows for determining large scale mass transport in the system Earth and to quantify ice mass change in polar regions. We provide, evaluate and compare a long time-series of monthly gravity field solutions derived either by satellite laser ranging (SLR) to geodetic satellites, by GPS and K-band observations of the GRACE mission, or by GPS observations of the three Swarm satellites. While GRACE provides gravity signal at the highest spatial resolution, SLR sheds light on mass transport in polar regions at larger scales also in the pre- and post-GRACE era. To bridge the gap between GRACE and GRACE Follow-On, we also derive monthly gravity fields using Swarm data and perform a combination with SLR. To correctly take all correlations into account, this combination is performed on the normal equation level. Validating the Swarm/SLR combination against GRACE during the overlapping period January 2015 to June 2016, the best fit is achieved when down-weighting Swarm compared to the weights determined by variance component estimation. While between 2014 and 2017 SLR alone slightly overestimates mass loss in Greenland compared to GRACE, the combined gravity fields match significantly better in the overlapping time period and the RMS of the differences is reduced by almost 100 Gt. After 2017, both SLR and Swarm indicate moderate mass gain in Greenland. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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20 pages, 6113 KiB

Open AccessArticle

The Rapid and Steady Mass Loss of the Patagonian Icefields throughout the GRACE Era: 2002–2017

by Andreas Richter, Andreas Groh, Martin Horwath, Erik Ivins, Eric Marderwald, José Luis Hormaechea, Raúl Perdomo and Reinhard Dietrich

Remote Sens. 2019, 11(8), 909; https://doi.org/10.3390/rs11080909 - 14 Apr 2019

Cited by 61 | Viewed by 4606

Abstract

We use the complete gravity recovery and climate experiment (GRACE) Level-2 monthly time series to derive the ice mass changes of the Patagonian Icefields (Southern Andes). The glacial isostatic adjustment is accounted for by a regional model that is constrained by global navigation satellite systems (GNSS) uplift observations. Further corrections are applied concerning the effect of mass variations in the ocean, in the continental water storage, and of the Antarctic ice sheet. The 161 monthly GRACE gravity field solutions are inverted in the spatial domain through the adjustment of scaling factors applied to a-priori ice mass change patterns based on published remote sensing results for the Southern and Northern Patagonian Icefields, respectively. We infer an ice mass change rate of −24.4 ± 4.7 Gt/a for the Patagonian Icefields between April 2002 and June 2017, which corresponds to a contribution to the eustatic sea level rise of 0.067 ± 0.013 mm/a. Our time series of monthly ice mass changes reveals no indication for an acceleration in ice mass loss. We find indications that the Northern Patagonian Icefield contributes more to the integral ice loss than previously assumed. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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23 pages, 7356 KiB

Open AccessEditor’s ChoiceArticle

Downscaling GRACE TWSA Data into High-Resolution Groundwater Level Anomaly Using Machine Learning-Based Models in a Glacial Aquifer System

by Wondwosen M. Seyoum, Dongjae Kwon and Adam M. Milewski

Remote Sens. 2019, 11(7), 824; https://doi.org/10.3390/rs11070824 - 05 Apr 2019

Cited by 79 | Viewed by 8894

Abstract

With continued threat from climate change and human impacts, high-resolution and continuous hydrologic data accessibility has a paramount importance for predicting trends and availability of water resources. This study presents a novel machine learning (ML)-based downscaling algorithm that produces a high spatial resolution groundwater level anomaly (GWLA) from the Gravity Recovery and Climate Experiment (GRACE) data by utilizing the relationship between Terrestrial Water Storage Anomaly (TWSA) from GRACE and other land surface and hydro-climatic variables (e.g., vegetation coverage, land surface temperature, precipitation, streamflow, and in-situ groundwater level data). The predicted downscaled GWLA data were tested using monthly in-situ groundwater level observations. Of the 32 groundwater monitoring wells available in the study site, 21 wells were used to develop the ML-based downscaling model, while the remaining 11 wells were used to assess the performance of the ML-based downscaling model. The test results showed that the model satisfactorily reproduces the spatial and temporal variation of the GWLA in the area, with acceptable correlation coefficient and Nash-Sutcliffe Efficiency values of ~0.76 and ~0.45, respectively. GRACE TWSA was the most influential predictor variable in the models, followed by stream discharge and soil moisture storage. Though model limitations and uncertainty could exist due to high spatial heterogeneity of the geologic materials and omission of human impact (e.g., abstraction), the significance of the result is undeniable, particularly in areas where in-situ well measurements are sparse. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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18 pages, 5822 KiB

Open AccessArticle

Gravity Field Recovery Using High-Precision, High–Low Inter-Satellite Links

by Markus Hauk and Roland Pail

Remote Sens. 2019, 11(5), 537; https://doi.org/10.3390/rs11050537 - 05 Mar 2019

Cited by 12 | Viewed by 5159

Abstract

Past temporal gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE), as well as current solutions from GRACE Follow-On, suffer from temporal aliasing errors due to undersampling of the signal to be recovered (e.g., hydrology), which arise in terms of stripes caused by the north–south observation direction. In this paper, we investigate the potential of the proposed mass variation observing system by high–low inter-satellite links (MOBILE) mission. We quantify the impact of instrument errors of the main sensors (inter-satellite link and accelerometer) and high-frequency tidal and non-tidal gravity signals on achievable performance of the temporal gravity field retrieval. The multi-directional observation geometry of the MOBILE concept with a strong dominance of the radial component result in a close-to-isotropic error behavior, and the retrieved gravity field solutions show reduced temporal aliasing errors of at least 30% for non-tidal, as well as tidal, mass variation signals compared to a low–low satellite pair configuration. The quality of the MOBILE range observations enables the application of extended alternative processing methods leading to further reduction of temporal aliasing errors. The results demonstrate that such a mission can help to get an improved understanding of different components of the Earth system. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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17 pages, 6435 KiB

Open AccessArticle

Combination Analysis of Future Polar-Type Gravity Mission and GRACE Follow-On

by Yufeng Nie, Yunzhong Shen and Qiujie Chen

Remote Sens. 2019, 11(2), 200; https://doi.org/10.3390/rs11020200 - 21 Jan 2019

Cited by 8 | Viewed by 3787

Abstract

Thanks to the unprecedented success of Gravity Recovery and Climate Experiment (GRACE), its successive mission GRACE Follow-On (GFO) has been in orbit since May 2018 to continue measuring the Earth’s mass transport. In order to possibly enhance GFO in terms of mass transport estimates, four orbit configurations of future polar-type gravity mission (FPG) (with the same payload accuracy and orbit parameters as GRACE, but differing in orbit inclination) are investigated by full-scale simulations in both standalone and jointly with GFO. The results demonstrate that the retrograde orbit modes used in FPG are generally superior to prograde in terms of gravity field estimation in the case of a joint GFO configuration. Considering the FPG’s independent capability, the orbit configurations with 89- and 91-degree inclinations (namely FPG-89 and FPG-91) are further analyzed by joint GFO monthly gravity field models over the period of one-year. Our analyses show that the FPG-91 basically outperforms the FPG-89 in mass change estimates, especially at the medium- and low-latitude regions. Compared to GFO & FPG-89, about 22% noise reduction over the ocean area and 17% over land areas are achieved by the GFO & FPG-91 combined model. Therefore, the FPG-91 is worthy to be recommended for the further orbit design of FPGs. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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23 pages, 6396 KiB

Open AccessArticle

High-Resolution Mass Trends of the Antarctic Ice Sheet through a Spectral Combination of Satellite Gravimetry and Radar Altimetry Observations

by Ingo Sasgen, Hannes Konrad, Veit Helm and Klaus Grosfeld

Remote Sens. 2019, 11(2), 144; https://doi.org/10.3390/rs11020144 - 14 Jan 2019

Cited by 21 | Viewed by 6302

Abstract

Time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions and satellite altimetry measurements from CryoSat-2 enable independent mass balance estimates of the Earth’s glaciers and ice sheets. Both approaches vary in terms of their retrieval principles and signal-to-noise characteristics. GRACE/GRACE-FO recovers the gravity disturbance caused by changes in the mass of the entire ice sheet with a spatial resolution of 300 to 400 km. In contrast, CryoSat-2measures travel times of a radar signal reflected close to the ice sheet surface, allowing changes of the surface topography to be determined with about 5 km spatial resolution. Here, we present a method to combine observations from the both sensors, taking into account the different signal and noise characteristics of each satellite observation that are dependent on the spatial wavelength. We include uncertainties introduced by the processing and corrections, such as the choice of the re-tracking algorithm and the snow/ice volume density model for CryoSat-2, or the filtering of correlated errors and the correction for glacial-isostatic adjustment (GIA) for GRACE. We apply our method to the Antarctic ice sheet and the time period 2011–2017, in which GRACE and CryoSat-2 were simultaneously operational, obtaining a total ice mass loss of 178 ± 23 Gt yr⁻¹. We present a map of the rate of mass change with a spatial resolution of 40 km that is evaluable across all spatial scales, and more precise than estimates based on a single satellite mission. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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24 pages, 10463 KiB

Open AccessArticle

Hydrologic Mass Changes and Their Implications in Mediterranean-Climate Turkey from GRACE Measurements

by Gonca Okay Ahi and Shuanggen Jin

Remote Sens. 2019, 11(2), 120; https://doi.org/10.3390/rs11020120 - 10 Jan 2019

Cited by 23 | Viewed by 5369

Abstract

Water is arguably our most precious resource, which is related to the hydrological cycle, climate change, regional drought events, and water resource management. In Turkey, besides traditional hydrological studies, Terrestrial Water Storage (TWS) is poorly investigated at a continental scale, with limited and sparse observations. Moreover, TWS is a key parameter for studying drought events through the analysis of its variation. In this paper, TWS variation, and thus drought analysis, spatial mass distribution, long-term mass change, and impact on TWS variation from the parameter scale (e.g., precipitation, rainfall rate, evapotranspiration, soil moisture) to the climatic change perspective are investigated. GRACE (Gravity Recovery and Climate Experiment) Level 3 (Release05-RL05) monthly land mass data of the Centre for Space Research (CSR) processing center covering the period from April 2002 to January 2016, Global Land Data Assimilation System (GLDAS: Mosaic (MOS), NOAH, Variable Infiltration Capacity (VIC)), and Tropical Rainfall Measuring Mission (TRMM-3B43) models and drought indices such as self-calibrating Palmer Drought Severity (SCPDSI), El Niño–Southern Oscillation (ENSO), and North Atlantic Oscillation (NAO) are used for this purpose. Turkey experienced serious drought events interpreted with a significant decrease in the TWS signal during the studied time period. GRACE can help to better predict the possible drought nine months before in terms of a decreasing trend compared to previous studies, which do not take satellite gravity data into account. Moreover, the GRACE signal is more sensitive to agricultural and hydrological drought compared to meteorological drought. Precipitation is an important parameter affecting the spatial pattern of the mass distribution and also the spatial change by inducing an acceleration signal from the eastern side to the western side. In Turkey, the La Nina effect probably has an important role in the meteorological drought turning into agricultural and hydrological drought. Full article

(This article belongs to the Special Issue Remote Sensing by Satellite Gravimetry)

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