[1] We present a method of directly estimating surface mass anomalies at regional scales using satellite-to-satellite K-band Ranging (KBR) data from the Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission. Geopotential differences based primarily on KBR measurement are derived using a modified energy integral method with an improved method to calibrate accelerometer measurements. Surface mass anomalies are computed based on a downward continuation process, with optimal regularization parameters estimated using the L-curve criterion method. We derive the covariance functions in both space- and space-time domains and use them as light constraints in the regional gravity estimation process in the Amazon basin study region. The space-time covariance function has a time-correlation distance of 1.27 months, which is evident that observations between neighboring months are correlated and the correlation should be taken into account. However, most of the current GRACE solutions did not consider such temporal correlations. In our study, the artifact in the regional gravity solution is mitigated by using the covariance functions. The averaged commission errors are estimated to be only 6.86% and 5.85% for the solutions based on the space-covariance function (SCF) and the space-time covariance function (STCF), respectively. Our regional gravity solution in the Amazon basin study region, which requires no further post-processing, shows enhanced regional gravity signatures, reduced gravity artifacts, and the gravity solution agrees with NASA/GSFC's GRACE MASCON solution to about 1 cm RMS in terms of water thickness change over the Amazon basin study region. The regional gravity solution also retains the maximum signal energy while suppressing the short wavelength errors.

[1] The Gravity Recovery And Climate Experiment (GRACE) mission has been providing high quality observations since its launch in 2002. Over the years, fruitful achievements have been obtained and the temporal gravity field has revealed the ongoing geophysical, hydrological and other processes. These discoveries help the scientists better understand various aspects of the Earth. However, errors exist in high degree and order spherical harmonics, which need to be processed before use. Filtering is one of the most commonly used techniques to smooth errors, yet it attenuates signals and also causes leakage of gravity signal into surrounding areas. This paper reports a new method to estimate the true mass change on the grid (expressed in equivalent water height or surface density). The mass change over the grid can be integrated to estimate regional or global mass change. This method assumes the GRACE-observed apparent mass change is only caused by the mass change on land. By comparing the computed and observed apparent mass change, the true mass change can be iteratively adjusted and estimated. The problem is solved with nonlinear programming (NLP) and yields solutions which are in good agreement with other GRACE-based estimates.

[1] Operational analyses from the U.S. National Centers for Environmental Prediction (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) provide, among other quantities, atmospheric surface pressure. This field is especially useful for data processing and interpretation of altimeter and gravity satellite missions like Jason-1 and GRACE (Gravity Recovery and Climate Experiment). Quantitative use of this pressure field, however, requires knowledge of its uncertainties. To assess these uncertainties, we compare NCEP and ECMWF analyses of surface pressure to an extensive set of surface barometric observations for the period 2001–2005, both land- and ocean-based, as well as to each other. Differences between each analysis and the observations are quite similar, indicating that both analyses generally fit the station observations equally well. Such differences, including both bias and variance about the bias, are largest over parts of the Southern Ocean, and over Asia, central Africa, and Antarctica. These bias and variance differences between the NCEP and ECMWF surface pressure fields change only slightly over the period of study. More importantly, though, such differences are substantially smaller than those found by previous studies for an earlier period (1993–1995), suggesting recent improvements in both analyses. The largest differences are found over high latitudes, particularly over Antarctica, and in the respective winter hemisphere. Much of the differences occur on rapid timescales, though with a significant portion at timescales longer than 1–2 months. The potential impact of such uncertainties on de-aliasing and interpreting sea level and gravity data from altimeter and GRACE missions is discussed.

[1] Land water storage plays a fundamental role in the West African water cycle and has an important impact on climate and on the natural resources of this region. However, measurements of land water storage are scarce at regional and global scales and especially in poorly instrumented endorheic regions, such as most of the Sahel, where little useful information can be derived from river flow measurements and basin water budgets. The Gravity Recovery and Climate Experiment (GRACE) satellite mission provides an accurate measurement of the terrestrial gravity field variations from which land water storage variations can be derived. However, their retrieval is not straightforward, and different methods are employed, which results in different water storage GRACE products. On the other hand, water storage can be estimated by land surface modeling forced with observed or satellite-based boundary conditions, but such estimates can be highly model dependent. In this study, land water storage by six GRACE products and soil moisture estimations by nine land surface models (run within the framework of the African Monsoon Multidisciplinary Analysis Land Surface Intercomparison Project (ALMIP)) are evaluated over West Africa, with a particular focus on the Sahelian area. The water storage spatial distribution, including zonal transects, its seasonal cycle, and its and interannual variability, are analyzed for the years 2003–2007. Despite the nonnegligible differences among the various GRACE products and among the different models, a generally good agreement between satellite and model estimates is found over the West Africa study region. In particular, GRACE data are shown to reproduce well the water storage interannual variability over the Sahel for the 5 year study period. The comparison between satellite estimates and ALMIP results leads to the identification of processes needing improvement in the land surface models. In particular, our results point out the importance of correctly simulating slow water reservoirs as well as evapotranspiration during the dry season for accurate soil moisture modeling over West Africa.

[1] In recent publications, a new basin-scale dataset of monthly variations in terrestrial water storage (BSWB) was derived for the ERA40 time period (1958–2002) using an atmospheric-terrestrial water-balance approach (Seneviratne et al., 2004; Hirschi et al., 2006). Here, we test the feasibility of using ECMWF operational forecast analyses – available for the recent time period in near real time – instead of reanalysis data for the derivation of these estimates. Our results suggest that the moisture flux convergence from the ECMWF operational forecast analysis is generally consistent with ERA40 in the investigated regions, including 35 mid-latitude river basins and domains. For ten domains with recent streamflow measurements, water-balance estimates of monthly terrestrial water storage variations derived using the ECMWF operational forecast data are compared with estimates from the Gravity Recovery and Climate Experiment (GRACE). In general the atmospheric-terrestrial water-balance estimates show more geographical detail than the analyzed standard resolution GRACE products.

[1] High-degree and high-order spherical harmonics of time-variable gravity fields observed by the Gravity Recovery and Climate Experiment (GRACE) gravity mission are dominated by noise. We develop two smoothing methods that suppress these high-degree and high-order errors with results superior to more commonly used Gaussian smoothing. These optimized smoothing methods considerably improve signal-to-noise levels of GRACE terrestrial water storage estimates relative to residual signal and noise over the oceans and show significantly better spatial resolution and lower leakage error. On the basis of analysis using an advanced land surface model, the equivalent spatial resolution from these optimized smoothing estimates is about 500 km, compared to the roughly 800–1000 km Gaussian smoothing that is required to suppress high-degree noise in the GRACE fields.

We have analysed satellite altimetry data from the ERS-2, ENVISAT and Topex/Poseidon satellites to construct water level time series over a 8-year period (from April 1996 to April 2004) over the lower Mekong River basin. The study area includes the Tonle Sap Lake, seasonally inundated areas and several branches of the hydrographic network of the Mekong delta. We found a very strong seasonal signal over the main river north of 13°N, the Tonle Sap Lake and Tonle Sap River, with amplitudes reaching 8-10 meters annually. We also found a clear interannual signal in altimetry-derived water level time-series. For example, year 1999 had weak floods (around 6 m amplitude), contrasting with year 2000 during which strong flood was noticed (around 10 m amplitude). Southward, we also observed large seasonal fluctuations (2-3 m) over inundated floodplains, as identified using satellite imagery data from the SPOT-4 Vegetation instrument. Depending on the location, quite different annual amplitudes were observed, the closer to the Mekong mouth, the smaller the signal (less than 0.5 m seasonal amplitude). Using NDVI (Normalized Difference Vegetation Index) data from the Vegetation instrument, we studied the seasonal extent of flood plains in the delta. Then combining the areal extent of floods with water levels estimated from the ERS-2/ENVISAT data, we computed maps of monthly surface water volume change over six successive years (1998-2003), the period of availability of the NDVI data. Averaged over the lower Mekong basin, this surface water volume change was then compared to the total (i.e., surface plus underground) water volume change inferred from the GRACE satellite. They exhibit in phase fluctuations.

We estimate terrestrial water storage variations using time variable gravity changes observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during the first 2 years of the mission. We examine how treatment of low-degree gravitational changes and geocenter variations affect GRACE based estimates of basin-scale water storage changes, using independently derived low-degree harmonics from Earth rotation (EOP) and satellite laser ranging (SLR) observations. GRACE based water storage changes are compared with estimates from NASA's Global Land Data Assimilation System (GLDAS). Results from the 22 GRACE monthly gravity solutions, covering the period April 2002 to July 2004, show remarkably good agreement with GLDAS in the Mississippi, Amazon, Ganges, Ob, Zambezi, and Victoria basins. Combining GRACE observations with EOP and SLR degree-2 spherical harmonic coefficient changes and SLR observed geocenter variations significantly affects and apparently improves the estimates, especially in the Mississippi, Ob, and Victoria basins.

We derive the mass balance of Greenland ice sheet from the Gravity Recovery and Climate Experiment (GRACE) for the period January 2003–October 2014. We have found an ice mass loss with peak amplitude of −15 cm/yr in the southeastern and northwestern parts, and an acceleration of −2.5 cm/yr2 in the southwestern region. Global warming is a well-known suspected triggering factor of ice melting. We use MODIS-derived Ice Surface Temperature (IST), and continuous and cross wavelet transforms have been determined to investigate the common power and relative phase between GRACE derived time-series of ice mass changes and IST time-series. Results indicate a high common power between the two time-series for the whole study period, but with different time patterns.

Time-varying gravity field and surface density distribution on and around Chinese Mainland are calculated by the GRACE satellite gravity data. Time series of gravity changes at typical locations are also obtained. At the same time, time series of displacements at GPS fiducial stations of WUSH, LHAS, KUNM and LUZH are obtained in the regional reference frame. Results from GRACE gravity observations indicate that there was significant negative gravity change along the Himalaya arc after the Sumatra earthquake, particularly during the period of 2006 to 2008. Meanwhile there was also obvious negative gravity change along the northwestern boundary of the Xiyu block. While there appeared an arc with positive gravity change along the northern and eastern boundaries of the Tibetan plateau in 2007. And positive gravity change was remarkable in the southern and middle segments of the North-South seismic belt in 2008. This trend of gravity variation after the Sumatra earthquake began to change only after the Wenchuan earthquake. Displacements at four GPS stations recorded co-seismic signals of the great Sumatra earthquake, and then the horizontal displacement vectors at WUSH, LHAS and KUNM showed significant changes in their general trend until the occurrence of the Ms8.0 Wenchuan earthquake. The changes in the ground mass in the Tibetan plateau and its surrounding areas as revealed by the GRACE satellites have provided new observation approach and data for the explanation of the dynamic mechanism of the Wenchuan earthquake. A preliminary explanation and discussion on the characteristics of the time variable changes in the gravity field observed by GRACE and the dynamic mechanism of the Wenchuan earthquake are presented in this paper by combining the features of regional tectonic movements and displacements of GPS observations.

This study presents the first direct comparison of terrestrial water storage estimates from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to in situ hydrological observations. Monthly anomalies of total water storage derived from GRACE gravity fields are compared with combined soil moisture and groundwater measurements from a network of observing sites in Illinois. This comparison is achieved through the use of a recently developed filtering technique designed to selectively remove correlated errors in the GRACE spectral coefficients. Application of this filter significantly improves the spatial resolution of the GRACE water storage estimates, and produces a time series which agrees quite well (RMS difference = 20.3 mm) with the in situ measurements averaged over an area of ∼280,000 km2.

This review surveys the basic theories, observational methods, satellite algorithms, and land surface models for terrestrial evapotranspiration, E (or λE, i.e., latent heat flux), including a long‐term variability and trends perspective. The basic theories used to estimate E are the Monin‐Obukhov similarity theory (MOST), the Bowen ratio method, and the Penman‐Monteith equation. The latter two theoretical expressions combine MOST with surface energy balance. Estimates of E can differ substantially between these three approaches because of their use of different input data. Surface and satellite‐based measurement systems can provide accurate estimates of diurnal, daily, and annual variability of E. But their estimation of longer time variability is largely not established. A reasonable estimate of E as a global mean can be obtained from a surface water budget method, but its regional distribution is still rather uncertain. Current land surface models provide widely different ratios of the transpiration by vegetation to total E. This source of uncertainty therefore limits the capability of models to provide the sensitivities of E to precipitation deficits and land cover change.

The measurement of total basin discharge along coastal regions is necessary for understanding the hydrological and oceanographic issues related to the water and energy cycles. However, only the observed streamflow (gauge-based observation) is used to estimate the total fluxes from the river basin to the ocean, neglecting the portion of discharge that infiltrates to underground and directly discharges into the ocean. Hence, the aim of this study is to assess the total discharge of the Yangtze River (Chang Jiang) basin. In this study, we explore the potential response of total discharge to changes in precipitation (from the Tropical Rainfall Measuring Mission—TRMM), evaporation (from four versions of the Global Land Data Assimilation—GLDAS, namely, CLM, Mosaic, Noah and VIC), and water-storage changes (from the Gravity Recovery and Climate Experiment—GRACE) by using the terrestrial water budget method. This method has been validated by comparison with the observed streamflow, and shows an agreement with a root mean square error (RMSE) of 14.30 mm/month for GRACE-based discharge and 20.98 mm/month for that derived from precipitation minus evaporation (P − E). This improvement of approximately 32% indicates that monthly terrestrial water-storage changes, as estimated by GRACE, cannot be considered negligible over Yangtze basin. The results for the proposed method are more accurate than the results previously reported in the literature.

The essence of this paper is to undertake an investigation of the recent Canadian Prairie drought by employing total water storage anomalies obtained from gravity recovery and climate experiment (GRACE) remote sensing satellite mission. In order to successfully retrieve average terrestrial water storages from gravity measurements, a necessary procedure is to undertake the transformation of the GRACE geopotential spherical harmonic coefficients into spatially varying time series of geopotential heights that were subsequently converted into water equivalent amounts. These obtained GRACE-based total water storages were thereafter validated using storages estimated from the atmospheric-based water balance P - E computation in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Canada. Interestingly, the results from this study corroborate the potential of GRACE-based technique as a veritable tool for the characterization of the 2002/2003 Canadian Prairie droughts. Especially, this approach would prove resourceful for other regions globally where soil moisture availability is sparing or worst still, inexistent thereby making such studies impossible.

The change of water resources under global warming is one of the most important issues faced by national economy and social development. Accurate estimation and analysis of Terrestrial Water Storage Anomaly (TWSA) are important for understanding global and regional water cycle process. Gravity Recovery and Climate Experiment (GRACE) satellite data is used to inverse water storage change in China and the correlation between it and precipitation from Tropical Rainfall Measuring Mission (TRMM) is also analyzed. The study shows that GRACE TWSA and TRMM precipitation are consistent and linear. In the best regression model, R2 and RMSE are 0.8025 and 11.1469 respectively, which suggests that precipitation is the source of water supply and also the main impact of water storage change.

Summary Retrieval of the terrestrial moisture storage dataset from the Gravity Recovery and Climate Experiment (GRACE) satellite remote sensing system is possible when the catchment of interest is of large spatial scale. These dataset are of paramount importance for the estimation of the total storage deficit index (TSDI), which enables the characterization of a particular drought event from the perspective of the terrestrial moisture storage over that catchment. Incidentally, the GRACE gravity signal over the 13,000 km 2 Upper Assiniboine River Basin on the drought-prone Canadian Prairie is so poor therefore making the computation of the total storage deficit index for this basin infeasible. Consequently, the estimation of the terrestrial moisture storage from other reliable sources becomes imperative in order to enable the computation of the TSDI over this basin. This study explores the utilization of the Variable Infiltration Capacity (VIC) model, a physically based, spatially distributed hydrologic model to simulate the total moisture storage over the Upper Assiniboine River Basin which was then employed in the estimation of the TSDI over this basin for subsequent characterization of the recent Prairie-wide drought. Interestingly, the temporal patterns in the computed TSDI from the VIC model reveal a strong resemblance with the same drought characterization undertaken over the larger adjacent Saskatchewan River Basin, which was accomplished utilizing terrestrial moisture storage from the GRACE-based approach. Additionally, these independent techniques employed in the characterization of the last Prairie drought over the two adjacently situated basins resulted in similar drought severity classification from the standpoint of the total moisture storage deficits over these basins. This study has therefore shown that in the computation of the total storage deficit index over small-scale catchments during anomalous climatic conditions that propagate extreme dryness through the terrestrial hydrologic systems, simulations of the total water storage from a structurally sound model such as the VIC model could be resourceful for the computation of the monthly total storage deficit index if no constraint is placed on the availability of accurate meteorological forcing.

Since its launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided a global mapping of the time-variations of the Earth’s gravity field. Tiny variations of gravity from monthly to decadal time scales are mainly due to redistributions of water mass inside the surface fluid envelops of our planet (i.e., atmosphere, ocean and water storage on continents). In this article, we present a review of the major contributions of GRACE satellite gravimetry in global and regional hydrology. To date, many studies have focused on the ability of GRACE to detect, for the very first time, the time-variations of continental water storage (including surface waters, soil moisture, groundwater, as well as snow pack at high latitudes) at the unprecedented resolution of ~400–500 km. As no global complete network of surface hydrological observations exists, the advances of satellite gravimetry to monitor terrestrial water storage are significant and unique for determining changes in total water storage and water balance closure at regional and continental scales.

Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

SUMMARY We present a new non-isotropic Gaussian filter for smoothing mass changes computed from Gravity Recovery and Climate Experiment (GRACE) L2 products and a new method to reduce land–ocean signal leakage caused by Gaussian smoothing. The kernel of our non-isotropic filter is the product of two Gaussian functions with distinct latitudinal and longitudinal smoothing radii. When expressed as number of kilometres at the Earth’s surface, the longitudinal smoothing radius, defined as a fixed longitude interval, is longer at the equator, and shorter at higher latitude. This is principally in accordance with the resolution of the GRACE data, and permits us to produce homogeneously smoothed results without excessive smoothing in latitudinal direction. This filter is not applicable in polar regions, where we choose to use the classical isotropic Gaussian filter. A smoothing radius choice scheme is proposed for the two filters to mesh seamlessly. In our leakage reduction method, the inputs are the mass change data after smoothing using a Gaussian filter. Along coasts where mass change signal on land is far larger than that over ocean (or signal over ocean is reduced to a very small magnitude by removing a model beforehand, and adding the model back afterwards), our method approximately recovers a smoothed mass change signal over both land and ocean sides as if a regional Gaussian filter with the same smoothing radius were applied over land and ocean separately, in which no signal leakages appear. The side lobe problem does not appear in our approach. Our leakage reduction method could also be used to study mass changes within a region where signal is far larger than that in surrounding regions, or where signal in surrounding regions could be reduced to very low magnitude by removing a model.

SUMMARY This paper investigates the precision of the estimation of geophysical fluid load deformation computed from GRACE space gravity, GPS vertical displacement and geophysical fluids models [Global Circulation Models (GCMs) for ocean, atmosphere and hydrology], using the three-cornered hat method. This method allows the estimation of the variance of the errors of each technique, when the same quantity is monitored by three instruments with independent errors.Appliedonanetworkofstations,severalpointsofviewcanbeconsidered:thetechnique level(inordertodeterminetheerrorofeachtechnique:GRACE,GPSandGCMs),thesolution level(allowingtocomparetheprecisionofthesametechniquewhendifferentstrategies/models are used), and the station level (in order to emphasize local anomalies and geographical patterns). In particular, our results show a precision of the loading vertical displacement at the level of 1 mm when using GRACE or the fluid models, and of 2 mm using GPS. We do not find significant differences between the precision of different solutions of the same techniques, even when there are strong differences in the data processing.