Gravity Recovery And Climate Experiment Mission Research Articles

Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mean climate data record (CDR v1.0), based on Global Positioning System (GPS) radio occultation (RO) data from the CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate), and Metop satellite missions. Systematic differences between RO missions, as well as differences of RO data relative to ERA-Interim reanalysis data, are quantified. The methods used to generate gridded monthly mean data are described, and the correction of monthly mean RO climatologies for sampling errors, which is essential for combining data from RO missions with different sampling characteristics, is evaluated. We find good overall agreement between the ROM SAF gridded monthly mean CDR and the ERA-Interim reanalysis, particularly in the 8–30 km height interval. Here, the differences largely reflect time-varying biases in ERA-Interim, suggesting that the RO data record has a better long-term stability than ERA-Interim. Above 30–40 km altitude, the differences are larger, particularly for the pre-COSMIC era. In the 8–30 km altitude region, the observational data record exhibits a high degree of internal consistency between the RO satellite missions, allowing us to combine data into multi-mission records. For global mean bending angle, the consistency is better than 0.04 %, for refractivity it is better than 0.05 %, and for global mean dry temperature the consistency is better than 0.15 K in this height interval. At altitudes up to 40 km, these numbers increase to 0.08 %, 0.11 %, and 0.50 K, respectively. The numbers can be up to a factor of 2 larger for certain latitude bands compared to global means. Below about 8 km, the RO mission differences are larger, reducing the possibilities to generate multi-mission data records. We also find that the residual sampling errors are about one-third of the original and that they include a component most likely related to diurnal or semi-diurnal cycles.

Surface Mass Variations from GPS and GRACE/GFO: A Case Study in Southwest China

Surface mass variations inferred from the Global Positioning System (GPS), and observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GFO) complement each other in terms of spatial and temporal coverage. This paper presents an analysis of regional surface mass variations inverted from GPS vertical displacements under different density distributions of GPS stations, and compares the GPS-derived mass variations with GRACE/GFO inversion results in spatial and temporal domains. To this end, GPS vertical displacement data from a total of 85 permanent GPS stations of the Crustal Movement Observation Network of China (CMONOC), the latest GRACE/GFO RL06 spherical harmonic (SH) solutions and GRACE RL06 mascon solutions are used to investigate surface mass variations in four regions or basins, including the Yunnan Province (YNP), Min River Basin (MRB), Jialing River Basin (JLRB), and Wu River Basin (WRB) in Southwest China. Our results showed that the spatial distributions and seasonal characteristics of GPS-derived mass change time series agree well with those from GRACE/GFO observations, especially in regions with relatively dense distributions of GPS stations (e.g., in the YNP and MRB), but there are still obvious discrepancies between the GPS and GRACE/GFO results. Scale factor methods (both basin-scaled and pixel-scaled) were employed to reduce the amplitude discrepancies between GPS and GRACE/GFO results. The results also showed that the one-year gap between the GRACE and GFO missions can be bridged by scaled GPS-derived mass change time series in the four studied regions, especially in the YNP and MRB regions (with relatively dense distributions of GPS stations).

Satellite Monitoring of Mass Changes and Ground Subsidence in Sudan’s Oil Fields Using GRACE and Sentinel-1 Data

Monitoring environmental hazards, owing to natural and anthropogenic causes, is an important issue, which requires proper data, models, and cross-validation of the results. The geodetic satellite missions, for example, the Gravity Recovery and Climate Experiment (GRACE) and Sentinel-1, are very useful in this respect. GRACE missions are dedicated to modeling the temporal variations of the Earth’s gravity field and mass transportation in the Earth’s surface, whereas Sentinel-1 collects synthetic aperture radar (SAR) data, which enables us to measure the ground movements accurately. Extraction of large volumes of water and oil decreases the reservoir pressure and form compaction and, consequently, land subsidence occurs, which can be analyzed by both GRACE and Sentinel-1 data. In this paper, large-scale groundwater storage (GWS) changes are studied using the GRACE monthly gravity field models together with different hydrological models over the major oil reservoirs in Sudan, that is, Heglig, Bamboo, Neem, Diffra, and Unity-area oil fields. Then, we correlate the results with the available oil wells production data for the period of 2003–2012. In addition, using the only freely available Sentinel-1 data, collected between November 2015 and April 2019, the ground surface deformation associated with this oil and water depletion is studied. Owing to the lack of terrestrial geodetic monitoring data in Sudan, the use of GRACE and Sentinel-1 satellite data is very valuable to monitor water and oil storage changes and their associated land subsidence over our region of interest. Our results show that there is a significant correlation between the GRACE-based GWS anomalies (ΔGWS) and extracted oil and water volumes. The trend of ΔGWS changes due to water and oil depletion ranged from –18.5 ± 6.3 to –6.2 ± 1.3 mm/year using the CSR GRACE monthly solutions and the best tested hydrological model in this study. Moreover, our Sentinel-1 SAR data analysis using the persistent scatterer interferometry (PSI) method shows a high rate of subsidence, that is, –24.5 ± 0.85, –23.8 ± 0.96, –14.2 ± 0.85, and –6 ± 0.88 mm/year over Heglig, Neem, Diffra, and Unity-area oil fields, respectively. The results of this study can help us to control the integrity and safety of operations and infrastructure in that region, as well as to study the groundwater/oil storage behavior.

Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States

The conterminous United States (CONUS) extends over a region of contrasting climates with an uneven distribution of freshwater resources. Under climate change, most predictions concur on critical disturbances in the terrestrial hydrological cycle with consequences on freshwater resources availability. In the case of the US, an exacerbation of the contrast between dry and wet regions is expected and could drastically affect local ecosystems, agriculture practices, and communities. Hence, efforts to better understand long-term spatial and temporal patterns of freshwater resources are needed to plan and anticipate responses. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite observations provide estimates of large-scale land water storage changes with an unprecedented accuracy. However, the limited lifetime and observation gaps of the GRACE mission have sparked research interest for GRACE-like data reconstruction. Hence, this study developed a predictive modeling approach to quantify monthly land liquid water equivalence thickness anomaly (LWE) using climate variables including total precipitation (PRE), number of wet day (WET), air temperature (TMP), and potential evapotranspiration (PET). The approach builds on the achievements of the GRACE mission by determining LWE footprints using a multivariate regression on principal components model with lag signals. The performance evaluation of the model with a lag signals consideration shows 0.5 ≤ R2 ≤ 0.8 for 41.2% of the CONUS. However, the model’s predictive power is unevenly distributed. The model could be useful for predicting and monitoring freshwater resources anomalies for the locations with high model performances.

Integrated study of GRACE data derived interannual groundwater storage variability over water stressed Indian regions

Groundwater serves more than 80% of agriculture and 60% of drinking water in India thus making it a demandable resource in the study area. In this study the groundwater storage change was determined by using RL05 land data product (January, 2003 to December, 2016) which was accessed from the Gravity Recovery and Climate Experiment (GRACE) satellite. Total soil moisture (up to 2m depth), canopy water storage and snow water equivalent derived from Global Land Data Assimilation System (GLDAS) NOAH was subtracted from terrestrial water storage (TWS) for extracting the groundwater component, revealing maximum groundwater storage change by −7.52 cm/year in Delhi, northern Uttar Pradesh and some parts of Haryana. In water stressed regions of India (January 2003 to December 2016) the groundwater depletion rate in the cities of Delhi, Meerut, Dehradun and Chandigarh are −3.682 ± 0.8 cm/year, −3.62 ± 0.7 cm/year, −3.1 ± 0.87 cm/year, −2.73 ± 0.6 cm/year respectively. The groundwater storage change (GWSC) depletion rate observed in Delhi, Meerut, Dehradun, Chandigarh in January 2003 to May 2010 are −3.43 ± 1.37, −3.41 ± 1.22, −3.72 ± 1.52, −3.43 ± 1.05 cm/year respectively and in August 2010 to December 2016 depletion rate is −5.53 ± 1.57, −7.12 ± 1.40, −4.98 ± 1.74,-3.92 ± 1.20 cm/year respectively. The data obtained by GRACE/GLDAS-derived total GWS (cm) and Global Positioning System (GPS)-derived vertical deformation of International GNSS services (IGS) station, at Indian Institute of Science (IISc) Bangalore (2014–2016) is correlated by 0.71. Analysis conducted in metro cities (Delhi, Chennai, Bengaluru, Kolkata and Mumbai) shows with time succession groundwater storage has suffered a major depletion in spite of quantified rainfall in these places. The GRACE-derived GWSC values agrees reasonably with in-situ well observations by Pearson's coefficient; 0.89, 0.88, 0.87 and 0.74 for Delhi, Haryana, Punjab and Uttar Pradesh thereby justifying remote sensing approach and further substantiate our research study that regional GWS mapping can be achieved by the GRACE mission rapidly and accurately.

Daily GRACE satellite data evaluate short-term hydro-meteorological fluxes from global atmospheric reanalyses

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.

Assessment of new thermospheric mass density model using NRLMSISE-00 model, GRACE, Swarm-C, and APOD observations

Thermospheric mass density estimates from in-situ observations along satellite orbits are difficult to validate due to their inherent spatiotemporal sparse nature, and difficulties related to drag-force modeling and estimation of actual mass density state. Current upper atmospheric models are unable to accurately represent the actual thermospheric variability, and in-situ observations are far to fulfill the minimum requirements in practical applications. In this manuscript, the new Thermospheric Mass Density Model (TMDM) is based on the fit of solar flux, annual, Local Solar Time (LST), and magnetospheric proxies into the Principal Component Analysis (PCA) of 13 years of accelerometer-based mass density estimates derived from the GRACE (Gravity Recovery and Climate Experiment) mission. We employ the NRLMSISE-00 model and estimates from APOD (Atmospheric density detection and Precise Orbit Determination), Swarm-C, and GRACE satellites, and assess the new model, including statistical analyses, and a Precise Orbit Determination (POD) scheme. We compare 2 years of APOD and Swarm-C estimates, and study the dynamic orbit propagation of the 3 missions under different mass density input schemes and different magnetospheric activity conditions. The results with TMDM show similar differences in the dynamically propagated orbits from NRLMSISE-00 and in-situ observations. The statistical analyses show that NRLMSISE-00 overestimates about 20%, and TMDM underestimates about 20%, the in-situ observations.

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

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.

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

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.

Total water storage variability from GRACE mission and hydrological models for a 50,000 km2 temperate watershed: the Garonne River basin (France)

Study RegionGaronne Basin, France. Study FocusThis study analyses water mass variations for the whole Garonne basin (50,000 km2 drainage area). To do so, Total Water Storage Anomalies (TWSA) from seven global solutions based on the Gravity Recovery And Climate Experiment (GRACE) satellite mission measurements (˜300 km spatial resolution) are inter-compared with TWSA from two hydrological models, SAFRAN-ISBA-MODCOU (SIM) and Soil and Water Assessment Tool (SWAT), between January 2003 and December 2010. New Hydrological Insights for the RegionDespite the small size of the Garonne basin compared to GRACE spatial resolution, good agreement between GRACE solutions and hydrological model TWSA has been found (maximum correlation coefficient ˜0.9 and Nash-Sutcliffe Efficiency, NSE, ˜0.7). These datasets showed that TWSA in the Garonne basin is mainly due to water stored in the first dozen meters of soil and in the shallow aquifer. To a smaller extent, snow also influences Garonne TWSA. Open surface water TWSA is quite small and TWSA from deep aquifer is negligible. The most important drought period occurred in 2011/2012, due to low precipitation during the two hydrological years and ETR close to previous years. Important precipitation in 2013/2014 helps to refill the water stocks. This study also showed that GRACE and models mismatches should be due to GRACE poor spatial resolution, but also to its monthly time resolution (rarely shown in previous studies).

GRACE accelerometer data transplant

In the last few months of GRACE (Gravity Recovery and Climate Experiment) mission operation, the accelerometer (ACC) aboard GRACE-B was turned off due to battery problems. In order to compute a gravity field model for these months, a data processing strategy was developed to retrieve the missing information, the so called Accelerometer data transplant. The ACC data transplant uses linear accelerations as measured by the GRACE-A accelerometer to generate the missing GRACE-B ACC data. A simple method of ACC data transplant was presented by Save et al. (2006), which only applies attitude and time correction due to orbit separation. In this paper we present an improved method of the ACC data transplant, which also includes thruster spike correction. The thruster spikes are residual linear accelerations occurring at each thruster firing caused by thruster imperfections and misbalance. We provide detailed description of the thruster spike model, which was derived analytically based on the ACC transfer function and 10 Hz ACC data. Using the transplanted ACC data we computed the gravity field models for the months with missing GRACE-B ACC data (November 2016–June 2017). We show that the gravity field model based on in the improved ACC data transplant has significantly reduced noise, especially for degrees beyond the first orbital resonance, when compared to the simple transplant method. The improved ACC transplant became therefore a part of the processing standards for the upcoming JPL RL06 gravity solution.

Sea-level fingerprints emergent from GRACE mission data

Abstract. The Gravity Recovery and Climate Experiment (GRACE) mission data have an important, if not revolutionary, impact on how scientists quantify the water transport on the Earth's surface. The transport phenomena include land hydrology, physical oceanography, atmospheric moisture flux, and global cryospheric mass balance. The mass transport observed by the satellite system also includes solid Earth motions caused by, for example, great subduction zone earthquakes and glacial isostatic adjustment (GIA) processes. When coupled with altimetry, these space gravimetry data provide a powerful framework for studying climate-related changes on decadal timescales, such as ice mass loss and sea-level rise. As the changes in the latter are significant over the past two decades, there is a concomitant self-attraction and loading phenomenon generating ancillary changes in gravity, sea surface, and solid Earth deformation. These generate a finite signal in GRACE and ocean altimetry, and it may often be desirable to isolate and remove them for the purpose of understanding, for example, ocean circulation changes and post-seismic viscoelastic mantle flow, or GIA, occurring beneath the seafloor. Here we perform a systematic calculation of sea-level fingerprints of on-land water mass changes using monthly Release-06 GRACE Level-2 Stokes coefficients for the span April 2002 to August 2016, which result in a set of solutions for the time-varying geoid, sea-surface height, and vertical bedrock motion. We provide both spherical harmonic coefficients and spatial maps of these global field variables and uncertainties therein (https://doi.org/10.7910/DVN/8UC8IR; Adhikari et al., 2019). Solutions are provided for three official GRACE data processing centers, namely the University of Texas Austin's Center for Space Research (CSR), GeoForschungsZentrum Potsdam (GFZ), and Jet Propulsion Laboratory (JPL), with and without rotational feedback included and in both the center-of-mass and center-of-figure reference frames. These data may be applied for either study of the fields themselves or as fundamental filter components for the analysis of ocean-circulation- and earthquake-related fields or for improving ocean tide models.

Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response

Abstract. The lack of direct measurement of root-zone soil moisture poses a challenge to the large-scale prediction of ecosystem response to variation in soil water. Microwave remote sensing capability is limited to measuring moisture content in the uppermost few centimetres of soil. The GRACE (Gravity Recovery and Climate Experiment) mission detected the variability in storage within the total water column. However, root-zone soil moisture cannot be separated from GRACE-observed total water storage anomalies without ancillary information on surface water and groundwater changes. In this study, GRACE total water storage anomalies and SMOS near-surface soil moisture observations were jointly assimilated into a hydrological model globally to better estimate the impact of changes in root-zone soil moisture on vegetation vigour. Overall, the accuracy of root-zone soil moisture estimates through the joint assimilation of surface soil moisture and total water storage retrievals showed improved consistency with ground-based soil moisture measurements and satellite-observed greenness when compared to open-loop estimates (i.e. without assimilation). For example, the correlation between modelled and in situ measurements of root-zone moisture increased by 0.1 (from 0.48 to 0.58) and 0.12 (from 0.53 to 0.65) on average for grasslands and croplands, respectively. Improved correlations were found between vegetation greenness and soil water storage on both seasonal variability and anomalies over water-limited regions. Joint assimilation results show a more severe deficit in soil water anomalies in eastern Australia, southern India and eastern Brazil over the period of 2010 to 2016 than the open-loop, consistent with the satellite-observed vegetation greenness anomalies. The assimilation of satellite-observed water content contributes to more accurate knowledge of soil water availability, providing new insights for monitoring hidden water stress and vegetation conditions.

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

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.

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

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

Terrestrial water storage variations and their effect on polar motion

The role of continental water in polar motion excitation can be illustrated by determining Hydrological Angular Momentum calculated from terrestrial water storage (TWS). In this paper we compare global and regional changes in TWS computed using Coupled Model Intercomparison Project Phase 5 climate models, Global Land Data Assimilation System (GLDAS) land hydrology models and observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. We also compare hydrological excitation functions derived from models with those obtained from the GRACE mission and the hydrological signal in observed polar motion excitation (the so-called geodetic residuals). The results confirm that GLDAS models of seasonal and non-seasonal TWS change are more consistent with GRACE data than climate models; on the other hand, none of the considered models are fully consistent with GRACE data or geodetic residuals. In turn, GRACE observations are most consistent with the non-seasonal hydrological signal in observed excitation. A detailed study of the contribution of different TWS components to the hydrological excitation function shows that soil moisture dominates.

On the estimation of physical height changes using GRACE satellite mission data – A case study of Central Europe

Abstract The dedicated gravity satellite missions, in particular the GRACE (Gravity Recovery and Climate Experiment) mission launched in 2002, provide unique data for studying temporal variations of mass distribution in the Earth’s system, and thereby, the geometry and the gravity fi eld changes of the Earth. The main objective of this contribution is to estimate physical height (e.g. the orthometric/normal height) changes over Central Europe using GRACE satellite mission data as well as to analyse them and model over the selected study area. Physical height changes were estimated from temporal variations of height anomalies and vertical displacements of the Earth surface being determined over the investigated area. The release 5 (RL05) GRACE-based global geopotential models as well as load Love numbers from the Preliminary Reference Earth Model (PREM) were used as input data. Analysis of the estimated physical height changes and their modelling were performed using two methods: the seasonal decomposition method and the PCA/ EOF (Principal Component Analysis/Empirical Orthogonal Function) method and the differences obtained were discussed. The main fi ndings reveal that physical height changes over the selected study area reach up to 22.8 mm. The obtained physical height changes can be modelled with an accuracy of 1.4 mm using the seasonal decomposition method.

Instrument data simulations for GRACE Follow-on: observation and noise models

Abstract. The Gravity Recovery and Climate Experiment (GRACE) mission has yielded data on the Earth's gravity field to monitor temporal changes for more than 15 years. The GRACE twin satellites use microwave ranging with micrometre precision to measure the distance variations between two satellites caused by the Earth's global gravitational field. GRACE Follow-on (GRACE-FO) will be the first satellite mission to use inter-satellite laser interferometry in space. The laser ranging instrument (LRI) will provide two additional measurements compared to the GRACE mission: interferometric inter-satellite ranging with nanometre precision and inter-satellite pointing information. We have designed a set of simulated GRACE-FO data, which include LRI measurements, apart from all other GRACE instrument data needed for the Earth's gravity field recovery. The simulated data files are publicly available via https://doi.org/10.22027/AMDC2 and can be used to derive gravity field solutions like from GRACE data. This paper describes the scientific basis and technical approaches used to simulate the GRACE-FO instrument data.

Application of the PCA/EOF method for the analysis and modelling of temporal variations of geoid heights over Poland

Temporal variations of geoid heights are vitally important in geodesy and Earth science. They are essentially needed for dynamic and kinematic updates of the static geoid model. These temporal variations, which substantially differ for different geographic locations, can successfully be determined using the Gravity Recovery And Climate Experiment (GRACE) mission data. So far, statistical decomposition methods, e.g. the Principal Component Analysis/Empirical Orthogonal Function (PCA/EOF) method, have not been implemented for the analysis and modelling of temporal mass variations within the Earth’s system over the area of Poland. The aim of this contribution is to analyse and model temporal variations of geoid heights obtained from GRACE mission data over the area of Poland using the PCA/EOF method. Temporal variations of geoid heights were obtained from the latest release, i.e. release five, of monthly GRACE-based Global Geopotential Models. They can reach the level of 10 mm. The PCA modes and their corresponding EOF loading patterns were estimated using two different algorithms. The results obtained revealed that significant part of the signal of temporal variations of geoid heights over Poland can be obtained from the first three PCA modes and EOF loading patterns. They demonstrate the suitability of the PCA/EOF method for analysing and modelling temporal variations of geoid heights over the area investigated.

Effects on Chilean Vertical Reference Frame due to the Maule Earthquake co-seismic and post-seismic effects

The Maule Earthquake (Mw=8.8) of February 27, 2010 is among the strongest earthquakes that occurred in recent years throughout the world. The crustal deformation caused by this earthquake has been widely studied using GNSS, InSAR and gravity observations. However, there is currently no estimation of the possible vertical deformations produced by co-seismic and post-seismic effects in segments of the Chilean Vertical Reference Frame (CHVRF). In this paper, we present an estimation of co-seismic and post-seismic deformations on the CHVRF using an indirect approach based on GNSS and Gravity Recovery and Climate Experiment (GRACE) data as well as by applying a trajectory model. GNSS time series were used from 10 continuous GNSS stations in the period from 2007 to 2015, as well as 28 GNSS temporary stations realized before and after the earthquake, and 34 vertical deformation vectors in the region most affected by the earthquake. We considered a set of 147 monthly solutions of spherical harmonic gravity field that were expanded up to degree, as well as order 96 of the GRACE mission provided by Center for Space Research, University of Texas at Austin (UT-CSR) process center. The magnitude of vertical deformation was estimated in part of the Chilean vertical network due to the co-seismic and post-seismic effects. Once we evaluated the hydrological effect, natural and artificial jumps, and the effect of glacial isostatic adjustment in GNSS and GRACE time series, the maximum values associated to co- and post-seismic deformations on orthometric height were found to be ∼−34cm and 5cm, respectively. Overall, the deformation caused by the Maule earthquake in orthometric heights is almost entirely explained by the variation in the ellipsoidal heights (over 85% in co-seismic jump); however, coseismic jump in the geoid reached −3.3mm, and could influence the maintenance of a modern vertical reference network in a medium to long term. We evaluated the consistency for a segment of the CHVRF after the earthquake and recommended precautions for using the CHVRF in the region.