Himanshu Save

High‐resolution CSR GRACE RL05 mascons

The determination of the gravity model for the Gravity Recovery and Climate Experiment (GRACE) is susceptible to modeling errors, measurement noise, and observability issues. The ill-posed GRACE estimation problem causes the unconstrained GRACE RL05 solutions to have north-south stripes. We discuss the development of global equal area mascon solutions to improve the GRACE gravity information for the study of Earth surface processes. These regularized mascon solutions are developed with a 1° resolution using Tikhonov regularization in a geodesic grid domain. These solutions are derived from GRACE information only, and no external model or data is used to inform the constraints. The regularization matrix is time variable and will not bias or attenuate future regional signals to some past statistics from GRACE or other models. The resulting Center for Space Research (CSR) mascon solutions have no stripe errors and capture all the signals observed by GRACE within the measurement noise level. The solutions are not tailored for specific applications and are global in nature. This study discusses the solution approach and compares the resulting solutions with postprocessed results from the RL05 spherical harmonic solutions and other global mascon solutions for studies of Arctic ice sheet processes, ocean bottom pressure variation, and land surface total water storage change. This suite of comparisons leads to the conclusion that the mascon solutions presented here are an enhanced representation of the RL05 GRACE solutions and provide accurate surface-based gridded information that can be used without further processing.

Reducing errors in the GRACE gravity solutions using regularization

The nature of the gravity field inverse problem amplifies the noise in the GRACE data, which creeps into the mid and high degree and order harmonic coefficients of the Earth’s monthly gravity fields provided by GRACE. Due to the use of imperfect background models and data noise, these errors are manifested as north-south striping in the monthly global maps of equivalent water heights. In order to reduce these errors, this study investigates the use of the L-curve method with Tikhonov regularization. L-curve is a popular aid for determining a suitable value of the regularization parameter when solving linear discrete ill-posed problems using Tikhonov regularization. However, the computational effort required to determine the L-curve is prohibitively high for a large-scale problem like GRACE. This study implements a parameter-choice method, using Lanczos bidiagonalization which is a computationally inexpensive approximation to L-curve. Lanczos bidiagonalization is implemented with orthogonal transformation in a parallel computing environment and projects a large estimation problem on a problem of the size of about 2 orders of magnitude smaller for computing the regularization parameter. Errors in the GRACE solution time series have certain characteristics that vary depending on the ground track coverage of the solutions. These errors increase with increasing degree and order. In addition, certain resonant and near-resonant harmonic coefficients have higher errors as compared with the other coefficients. Using the knowledge of these characteristics, this study designs a regularization matrix that provides a constraint on the geopotential coefficients as a function of its degree and order. This regularization matrix is then used to compute the appropriate regularization parameter for each monthly solution. A 7-year time-series of the candidate regularized solutions (Mar 2003–Feb 2010) show markedly reduced error stripes compared with the unconstrained GRACE release 4 solutions (RL04) from the Center for Space Research (CSR). Post-fit residual analysis shows that the regularized solutions fit the data to within the noise level of GRACE. A time series of filtered hydrological model is used to confirm that signal attenuation for basins in the Total Runoff Integrating Pathways (TRIP) database over 320 km radii is less than 1 cm equivalent water height RMS, which is within the noise level of GRACE.

Hydrologic implications of GRACE satellite data in the Colorado River Basin

Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km3 during 1986–1990 and by 102 km3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km3) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.

Global evaluation of new GRACE mascon products for hydrologic applications

Recent developments in mascon (mass concentration) solutions for GRACE (Gravity Recovery and Climate Experiment) satellite data have significantly increased the spatial localization and amplitude of recovered terrestrial Total Water Storage anomalies (TWSA); however, land hydrology applications have been limited. Here we compare TWSA from April 2002 through March 2015 from (1) newly released GRACE mascons from the Center for Space Research (CSR-M) with (2) NASA JPL mascons (JPL-M), and with (3) CSR Tellus gridded spherical harmonics rescaled (sf) (CSRT-GSH.sf) in 176 river basins, ∼60% of the global land area. Time series in TWSA mascons (CSR-M and JPL-M) and spherical harmonics are highly correlated (rank correlation coefficients mostly >0.9). The signal from long-term trends (up to ±20 mm/yr) is much less than that from seasonal amplitudes (up to 250 mm). Net long-term trends, summed over all 176 basins, are similar for CSR and JPL mascons (66–69 km3/yr) but are lower for spherical harmonics (∼14 km3/yr). Long-term TWSA declines are found mostly in irrigated basins (−41 to −69 km3/yr). Seasonal amplitudes agree among GRACE solutions, increasing confidence in GRACE-based seasonal fluctuations. Rescaling spherical harmonics significantly increases agreement with mascons for seasonal fluctuations, but less for long-term trends. Mascons provide advantages relative to spherical harmonics, including (1) reduced leakage from land to ocean increasing signal amplitude, and (2) application of geophysical data constraints during processing with little empirical postprocessing requirements, making it easier for nongeodetic users. Results of this product intercomparison should allow hydrologists to better select suitable GRACE solutions for hydrologic applications.

Long‐term and seasonal Caspian Sea level change from satellite gravity and altimeter measurements

We examine recent Caspian Sea level change by using both satellite radar altimetry and satellite gravity data. The altimetry record for 2002–2015 shows a declining level at a rate that is approximately 20 times greater than the rate of global sea level rise. Seasonal fluctuations are also much larger than in the world oceans. With a clearly defined geographic region and dominant signal magnitude, variations in the sea level and associated mass changes provide an excellent way to compare various approaches for processing satellite gravity data. An altimeter time series derived from several successive satellite missions is compared with mass measurements inferred from Gravity Recovery and Climate Experiment (GRACE) data in the form of both spherical harmonic (SH) and mass concentration (mascon) solutions. After correcting for spatial leakage in GRACE SH estimates by constrained forward modeling and accounting for steric and terrestrial water processes, GRACE and altimeter observations are in complete agreement at seasonal and longer time scales, including linear trends. This demonstrates that removal of spatial leakage error in GRACE SH estimates is both possible and critical to improving their accuracy and spatial resolution. Excellent agreement between GRACE and altimeter estimates also provides confirmation of steric Caspian Sea level change estimates. GRACE mascon estimates (both the Jet Propulsion Laboratory (JPL) coastline resolution improvement version 2 solution and the Center for Space Research (CSR) regularized) are also affected by leakage error. After leakage corrections, both JPL and CSR mascon solutions also agree well with altimeter observations. However, accurate quantification of leakage bias in GRACE mascon solutions is a more challenging problem.

Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data

Significance We increasingly rely on global models to project impacts of humans and climate on water resources. How reliable are these models? While past model intercomparison projects focused on water fluxes, we provide here the first comprehensive comparison of land total water storage trends from seven global models to trends from Gravity Recovery and Climate Experiment (GRACE) satellites, which have been likened to giant weighing scales in the sky. The models underestimate the large decadal (2002–2014) trends in water storage relative to GRACE satellites, both decreasing trends related to human intervention and climate and increasing trends related primarily to climate variations. The poor agreement between models and GRACE underscores the challenges remaining for global models to capture human or climate impacts on global water storage trends. Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002–2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤−0.5 km3/y) and increasing (≥0.5 km3/y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km3/y, whereas most models estimate decreasing trends (−71 to 11 km3/y). Land water storage trends, summed over all basins, are positive for GRACE (∼71–82 km3/y) but negative for models (−450 to −12 km3/y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated.

Quantifying temporal variations in water resources of a vulnerable middle eastern transboundary aquifer system

Department of Civil and Environmental Engineering, University of Rhode Island, Kingston, RI, USA Faculty of Engineering, Radiation Protection and Training Centre, King Abdulaziz University, Jeddah, Saudi Arabia Department of Geosciences, Western Michigan University, Kalamazoo, MI, USA Department of Geology, Faculty of Science, Suez Canal University, Ismailia, Egypt Center for Space Research, University of Texas at Austin, Austin, TX, USA Correspondence Ali S. Akanda, Civil and Environmental Engineering, University of Rhode Island, 1 Lippitt Road, Kingston, RI 02881, USA. Email: akanda@uri.edu Funding information National Aeronautics and Space Administration, Grant/Award Number: Health and Air Quality grant/ (NNX15AF71G)

Assessing modern river sediment discharge to the ocean using satellite gravimetry

Recent acceleration of sand extraction for anthropic use threatens the sustainability of this major resource. However, continental erosion and river transport, which produce sand and sediment in general, lack quantification at the global scale. Here, we develop a new geodetic method to infer the sediment discharge to ocean of the world’s largest rivers. It combines the spatial distribution of modern sedimentation zones with new high-resolution (~170 km) data from the Gravity Recovery and Climate Experiment (GRACE) mission launched in 2002. We obtain sediment discharges consistent with in situ measurements for the Amazon, Ganges-Brahmaputra, Changjiang, Indus, and Magdalena rivers. This new approach enables to quantitatively monitor the contemporary erosion of continental basins drained by rivers with large sediment discharges and paves the way toward a better understanding of how natural and anthropic changes influence landscape dynamics.Measuring rivers’ sediment discharge is critical to assess continental erosion and landscape dynamics, yet it remains a challenging task. Here the authors show that GRACE satellite helps quantifying river sediment discharge by measuring the increment in gravitational attraction due to sediment accumulation.

Determination of Center-of-Mass of Gravity Recovery and Climate Experiment Satellites

The Gravity Recovery and Climate Experiment (GRACE)mission, launched on 17March 2002, uses radiometric tracking between twin, coorbiting satellites in a polar 500-km-alt orbit, in order to make detailed measurements of Earth’s gravity field. Thesemeasurements have led to significant, new insights into climate-drivenmass transport in the Earth system. A key element of the GRACE scientific measurement suite is the high-precision accelerometer required to measure the nongravitational accelerations acting on the GRACE satellites. To avoid contamination of nongravitational acceleration measurements, the GRACE mission requires the proof mass of the accelerometer to be positioned within 100 m (0.1 mm) of the center-of-mass of satellite. This is accomplished using a dedicated center-of-mass calibration maneuver every few months. This paper describes the GRACE center-of-mass calibration maneuver design and implementation details and presents the data analysis used to routinely measure the center-of-mass offset. Using external validation and internal consistency checks, we show that the GRACE satellite center-of-mass offset is being measured routinely to approximately 25 to 40 m precision along the three satellite axes.