During the last decades, several inversion approaches have been proposed to derive sea floor topography from satellite-based gravity data. Unfortunately, the most accurate non linear ones are based on iterative schemes that remain very time-consuming, especially if the number of topographic heights to be fitted is very important, e.g. when the oceanic domain is large and/or the gravity data is geographically dense and thus the maximum grid resolution to be accessible is high. Our strategy of computation is to decompose the total area into geographical cells that are overlapped to cancel the edge effects. The reference ocean depth given by GEBCO and the elastic thickness for regional compensation in function of the square root of the age of the oceanic crust are assumed to be constant in each cell. The initial inversion code has been translated into C++ and optimized using Armadillo software and LAPACK library to obtain a gain of speed of 1000 for a large region such as the complete North Atlantic Ocean (-54,-26,18,37). Post-fit and absolute errors are typically less than 200 m and 50 m r.m.s. respectively. These new detailed maps of bathymetry represent a precious source of information for geophysical applications.

Prediction of the trends of ice mass loss in Greenland can help for understanding what occurred during the last 20 years and in the future. The Level-2 GRACE and GRACE-FO solutions provided by the official computing centres CSR and ITSG as well as the combined products of the COST-G project give access to the spatio-temporal variations of the ice mass balance of Greenland from 2002 to present. We first reduce the GRACE data from post-glacial rebound. We propose to analyse these solutions by applying Singular Value Decomposition (SVD) and Empirical Mode Decomposition (EMD) to extract the trend. This trend is then removed from the timeseries for the Fast Fourier Transform (FFT) and 1-D Continuous Wavelet Transform (CWT) analysis. CWT and FFT analysis enable to unravel the long-term trend of the ice loss ranging from 6-9 years, as well as the annual and semi-annual part. The period of 6 to 9 years shows some correlation with meteorological and climate indexes such as North Atlantic Oscillation (NAO). The spatial component of the first SVD mode indicates that the ice melting is the most important along the west and southeast coast at the rate of -30 to -40 Gt/yr. Globally, the trend is not linear, it consist of different phases of acceleration and deceleration with rates between -60 and -340 Gt/yr.

As the Cordouan lighthouse [N45°35'11"; W1°10'24"] is constructed in the Bay of Biscay, GNSS reflectometry-monitored time series of sea level are characterized by important tidal variations for this site. However, these GNSS-R measurements are impacted by submerged sandy banks that appear at low tide and spoil the estimates of pure sea level. We propose the spatialization of the GNSS reflection points to identify the areas with sandy or rocky parts around the lighthouse. For this purpose, the surrounding of the receiving antenna is divided into juxtaposed geographical cells forming a map filled by water heights estimates according to the position of the reflection points. Water heights are determined using the method of periodogram of 1-second Signal-to-Noise-Ratio (SNR) data on a sliding elevation window of several degrees. In particular, correction of the atmospheric delay effects enables to reduce the dispersion of the water heights versus low elevations by a factor around 2. High variability (more than one meter) and higher means of water heights estimated over months in the eastern part are very consistent with the presence of the shoals, while long-term means and dispersions in cells of plain ocean are much smaller. These results are highly emphasized by the distinction between low and high tides.

While sea level variations at coastal sites can be derived from Signal-to-Noise Ratio (SNR) measurements in GNSS-R, the presence of noise, signal interruptions and unmodelled geophysical contributions still corrupt the quality of the estimates. We propose improvements in the treatment of raw SNR records for obtaining much precise sea level. We implement correction of the atmospheric delays, as well as filtering of loading displacements for producing sea level time series over several years. We also propose empirical corrections on a priori fitting parameters to absorb systematic effects from satellite elevation that spoil the sea level time series. Water height adjustment from periodogram of the windowed SNR signal requires parameters that have been fixed so far, e.g. the width of the analyzing window - or equivalently the number of SNR periods used in the adjustment. In particular, tuning of this latter critical parameter is made versus the receiving antenna height.

We propose a spatial characterization of the hydrological contributions of several climate drivers that impact continental water mass storage of Australia determined by remote sensing techniques over the period 2002 - 2021. For this purpose, the Slepian functions help for recognizing the signatures of such important changes in the varying gravity field solutions provided by GRACE and GRACE-FO satellite missions such as mascon solutions of 400-km resolution. Time series of 25 Slepian coefficients that correspond to ~99.9% of the eigenvalue spectrum are used to be analyzed and compared to the profiles of climate indexes i.e. El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and South Annular Mode (SAM). The best correlations enable to extract specific Slepian coefficients, and then reconstruct the regional hydrological structures that concern each climate driver, in particular for the southeastern basins strongly influenced by the important flooding during La Niña episode of 2010.

The AGOSTA project initially proposed by our team and lately funded by CNES TOSCA consists of developing efficient approaches to restore seafloor shape (or bathymetry), as well as lithospheric parameters such as the crust and elastic thicknesses, by combining different types of observations including gravity gradient data. As it is based on the second derivatives of the potential versus the space coordinates, gravity gradiometry provides more information inside the Earth system at short wavelengths. The GOCE mission has measured the gravity gradient components of the static field globally and give the possibility to detect more details on the structure of the lithosphere at spatial resolutions less than 200 km. We propose to analyze these satellite-measured gravity tensor components to map the undersea relief more precisely than using geoid or vertical gravity previously considered for this purpose. Inversion of vertical gravity gradient data derived from the radar altimetry technique also offers the possibility to reach greater resolutions (at least 50 km) than the GOCE mission one. The seafloor topography estimates are tested in areas well-covered by independent data for validation, such as around the Great Meteor guyot [29°57′10.6″N, 28°35′31.3″W] and New England seamount chain [37°24′N 60°00′W, 120° 10' 30.4" W] in the Atlantic Ocean as well as the Acapulco seamount [13° 36' 15.4" N, 120° 10' 30.4" W] in the Central Pacific.

We investigate the possibility to use the Low-Earth Orbiter mission well known as GRACE to detect sudden regional variations of water mass storage caused by heavy precipitation and flooding episodes caused by the passage of tropical hurricanes of categories 4-5 (from day to a week). For this purpose, daily water mass solutions are produced from along-track GRACE geopotential anomalies to catch the signatures of these intense meteorological events. These geopotential variations are derived from accurate inter-satellite K-Band Range Rate (KBRR) measurements made along the 5-second orbits by imposing the total energy conservation to the twin GRACE vehicles. The determination of these surface sources is made over a regional network of juxtaposed triangular tiles of quasi-constant areas, and they are refreshed by a Kalman filtering for integrating progressively daily geopotential observations. These latter data have been previously reduced from known gravitational effects of atmosphere and oceanic masses (including periodic tides) for isolating the continental hydrology contribution. Our estimates of regional hydrological impacts are also compared to the ones obtained by synthesis of daily degree-40 Stokes coefficients provided by ITSG, Graz.

We propose to cumulate complementary gravity data, i.e. geoid height and (radial) free-air gravity anomalies, to evaluate the 3-D shape of the sea floor more precisely. For this purpose, an Extended Kalman Filtering (EKF) scheme has been developed to construct the topographic solution by injecting gravity information progressively. The main advantage of this sequential cumulation of data is the reduction of the dimensions of the inverse problem. Non linear Newtonian operators have been re-evaluated from their original forms and elastic compensation of the topography is also taken into account. The efficiency of the method is proved by inversion of simulated gravity observations to converge to a stable topographic solution with an accuracy of only a few meters. Real geoid and gravity data are also inverted to estimate bathymetry around the New England and Great Meteor seamount chains. Error analysis consists of comparing our topographic solutions to accurate single beam ship tracks for validation.

Approaches based on Stokes coefficient filtering and « mass concentration » representations have been proposed for recovering changes of the surface water mass density from along-track accurate GRACE K-Band Range Rate (KBRR) measurements of geopotential change. The number of parameters, i.e. surface triangular tiles of water mass, to be determined remains large and the choice of the regularization strategy as the gravimetry inverse problem is non unique. In this study, we propose to use regional sets of orthogonal surface functions to image the structure of the surface water mass density variations. Since the number of coefficients of the development is largely smaller than the number of tiles, the computation of daily GRACE solutions for continental hydrology, e.g. obtained by Extended Kalman Filtering (EKF), is greatly fastened and eased by the matrix dimensions and conditioning. The proposed scheme of decomposition is applied to the African continent where it enables to very localized sources of (sub-)monthly water mass amplitudes.

The Reflected Global Navigation Satellite System (GNSS-R) is a bi-static radar system in which the receiver collect GNSS signals reflected from the Earth surface and compares them with corresponding direct signals. Measurements can be performed on the waveforms to determine the elevation of the free surface, leading to applications such as ocean altimetry, inland water level variations, soil moisture, snow depth and atmospheric water changes. This study presents the potential of in-situ GNSS-R for tidal bore detection and characterization, and compares it to high rate GNSS observations and other reference datasets. The data we used were acquired on 17th and 18th October 2016 in the Garonne River, at 126 km upstream the mouth of the Gironde estuary. We processed GNSS-based elevations from data acquired on a buoy at a 20 Hz sampling rate using differential GNSS (DGNSS) technique. Acoustic Doppler Current Profiler (ADCP) measurements as well as pressure data were used for validation purposes. These techniques show good results in estimating the amplitude of the first wave, the period of the tidal bore and the oceanic tides. All of these datasets were compared to the retrieval of GNSS-R signals above the river. We have processed the changes in water height throughout the acquisition using Larson et al. (2013) and Roussel et al. (2015) techniques. We finally separate the atmospheric component from the tidal bore and the oceanic tides ones. Larson, K. M., Löfgren, J. S., and Haas, R. (2013). Coastal sea level measurements using a single geodetic gps receiver. Advances in Space Research, 51(8):1301–1310. Roussel, N., Ramillien, G., Frappart, F. et al. (2015). Sea level monitoring and sea state estimate using a single geodetic receiver. Remote Sensing of Environment, 171:261 – 277.

In large Tropical River basins such as the Amazon, groundwater plays a major role in the water and ecological cycles with large influences on the rainforest ecosystems and climate variability. However, due to the lack of monitoring networks, Amazon groundwater storage and its variability remain poorly known. Here, we provide an unprecedented direct estimate of the spatio-temporal variations of the anomaly of groundwater storage over the period January 2003 -September 2010 in the Amazon Basin by decomposing the total terrestrial water storage measured by the Gravity Recovery and Climate Experiment (GRACE) mission into the individual contributions of other hydrological reservoirs, using multi-satellite data for the surface waters and floodplains and models outputs for the soil moisture. We show that the seasonal variations of groundwater storage represent between 20 and 35% of the terrestrial water storage seasonal volume variations of the Amazon. Larger seasonal amplitudes of groundwater storage (>450 mm) are found in the Alter do Chao and Ica aquifers in the central part of the Amazon Basin. Anomalies of groundwater storage exhibit a strong interannual variability (STD reaching 120 mm along the central corridor) during the study period in response to hydrologic variability and climatic events such as the extreme drought that occurred in 2005.

Droughts often evolve gradually and cover large areas, and therefore, affect many people and activities. This motivates developing techniques to integrate different satellite observations, to cover large areas, and understand spatial and temporal variability of droughts. In this study, we apply probabilistic techniques to generate satellite derived meteorological, hydrological, and hydro-meteorological drought indices for the world's 156 major river basins covering 2003-2016. The data includes Terrestrial Water Storage (TWS) estimates from the Gravity Recovery And Climate Experiment (GRACE) mission, along with soil moisture, precipitation, and evapotranspiration reanalysis. Different drought characteristics of trends, occurrences, areal-extent, and frequencies corresponding to 3-, 6-, 12-, and 24-month timescales are extracted from these indices. Drought evolution within selected basins of Africa, America, and Asia is interpreted. Canonical Correlation Analysis (CCA) is then applied to find the relationship between global hydro-meteorological droughts and satellite derived Sea Surface Temperature (SST) changes. This relationship is then used to extract regions, where droughts and teleconnections are strongly interrelated. Our numerical results indicate that the 3- to 6-month hydrological droughts occur more frequently than the other timescales. Longer memory of water storage changes (than water fluxes) has found to be the reason of detecting extended hydrological droughts in regions such as the Middle East and Northern Africa. Through CCA, we show that the El Niño Southern Oscillation (ENSO) has major impact on the magnitude and evolution of hydrological droughts in regions such as the northern parts of Asia and most parts of the Australian continent between 2006 and 2011, as well as droughts in the Amazon basin, South Asia, and North Africa between 2010 and 2012. The Indian ocean Dipole (IOD) and North Atlantic Oscillation (NAO) are found to have regional influence on the evolution of hydrological droughts.

This study presents the potential of GNSS Reflectometry (GNSS-R) for the monitoring of water levels in the Mekong river delta (Vietnam). A geodetic GNSS station was installed at the Tran De port, Soc Trang province, over 23-30 August 2016. The method used to retrieve water levels from GNSS-R data is based on the Interference Pattern Technic of the Signal-to-Noise Ratio (SNR). To validate our measurements, we used different radar altimetry data from Jason-2, SARAL, Jason-3 and Sentinel-3A missions during the same period for measuring sea surface height (SSH) and in-situ tide gauge station as reference for both tides and floods. The aim of this study is to evaluate the performances GNSS-R, in complex environment, for monitoring at the same time river/tide stages and the possibility to use this technique for calibration/validation of altimetry data. Early results show the good agreement between in -situ gauge and GNSS-R based estimates with correlations which reach ~ 0.85.

The emergence of quantum technologies, including cold atom based accelerometers, offers an opportunity to improve the performances of space geodesy missions. In this context, CNES initiated an assessment study called GRICE (GRadiometrie a Interferometres quantiques Correles pour l'Espace) in order to evaluate the impact of cold atom technologies to space geodesy and to the end users of the geodetic data. In this paper, we present a specific mission scenario for gravity field mapping based on a twin satellite concept. The mission uses a constellation of two satellites each equipped with a cold atom accelerometer. A laser link measures the distance between the two satellites and couples these two instruments in order to produce a correlated differential acceleration measurement. The main parameters, determining the performances of the payload, have been investigated. In addition, a preliminary study of mass, consumption and volume has been conducted to ensure the onboard feasibility of these instruments. A general study of the satellite architecture, including all the subsystems, has also been realized and is presented here.

A radial integration of spherical mass elements (i.e. tesseroids) is presented for evaluating the six components of the second-order gravity gradient (i.e. second derivatives of the Newtonian mass integral for the gravitational potential) created by an uneven spherical topography consisting of juxtaposed vertical prisms. The method uses Legendre polynomial series and takes elastic compensation of the topography by the Earth’s surface into account. The speed of computation of the polynomial series increases logically with the observing altitude from the source of anomaly. Such a forward modelling can be easily applied for reduction of observed gravity gradient anomalies by the effects of any spherical interface of density. An iterative least-squares inversion of measured gravity gradient coefficients is also proposed to estimate a regional set of juxtaposed topographic heights. Several tests of recovery have been made by considering simulated gradients created by idealistic conical and irregular Great Meteor seamount topographies, and for varying satellite altitudes and testing different levels of uncertainty. In the case of gravity gradients measured at a GOCE-type altitude of \(\sim \)300 km, the search converges down to a stable but smooth topography after 10–15 iterations, while the final root-mean-square error is \(\sim \)100 m that represents only 2 % of the seamount amplitude. This recovery error decreases with the altitude of the gravity gradient observations by revealing more topographic details in the region of survey.

As multipath effects still represent a major problem for reaching precise GNSS positioning, the mitigation of their influence has been widely investigated. Previous studies have lately proposed to use these interferences of GNSS electromagnetic waves to estimate parameters related to the reflecting surface (e.g., antenna heights, roughness...). Variations in the nature of the surface are likely to modify the properties of the reflected waves, and consequently lead to fluctuations of amplitude, phase and frequency of the signal-to-noise ratio (SNR), e.g., recorded at 1 Hz by a GNSS receiver. By analyzing the time variations of these three SNR metrics, linked to the dielectric constant of the surrounding soil, it is possible to recover the local fluctuations of the soil moisture content. The aim of our study is to validate this SNR technique in various conditions of reception and reflection. Three different configurations are under study. First, we use a static geodetic Leica AR10 antenna set up within an agricultural plot with rich clay content. Correlation between our estimates and independent soil moisture records reaches 0.95 during the 1.5 month period of measurements. The experiment is then repeated under the same conditions of reception but on another test site, presenting different conditions of reflection, namely, the surrounding soil is only sand. This leads to drastic changes of the penetration depth of the GNSS waves, and therefore different behavior of the three SNR metrics. Last, a low-cost device and airborne solution is tested for the first time, with a U-Blox antenna embedded on a UAV (Unmanned Aerial Vehicle), flying over a clay field.