Byron D. Tapley

A model of ocean tides is generally used to remove the dynamic tidal signal in satellite gravimetric observations, such as GRACE(‐FO). Model imperfections can cause stripes and long period aliasing errors in monthly gravity solutions. Recent developments in ocean tide modeling have substantially improved accuracy at high latitudes and in shallow water regions. In this study, we compared the 8 major tidal constituents from three recent ocean tide models, namely EOT20, FES22 and GOT5.6, as well as GOT4.8, using 13‐year long GRACE ranging observations. The improvements of the three recent models are significant, showing more than 2 postfit variance reduction. Among them, GOT5.6 generally performs the best in terms of postfit variance reduction (11% vs. GOT4.8) and residual ocean tide fitting, particularly near West Antarctica. The residual ocean mass RMS, computed from monthly gravity solutions using GOT5.6, is on average 1 mm (GOT4.8), 0.3 mm (EOT20) and 0.1 mm (FES22) smaller. These results make it our preferred model for the upcoming GRACE(‐FO) Release 07 (RL07) re‐processing. Regarding implementation, utilizing the minor tides in GOT5.6 and long period tides in FES22 as well as considering geographically varying seawater density can further enhance model performance (denoted GOT5.6p3), which on average reduces the residual ocean mass RMS by an additional 7%. Notably, using lateral varying seawater density largely reduces the anomalous M ₂ residuals in the North Atlantic Ocean. We anticipate that GOT5.6p3 will substantially reduce stripes and aliasing errors in forthcoming RL07 monthly solutions. The improvements will also benefit GOCE reprocessing and GRACE(‐FO) sub‐monthly solutions.

More than 24 years of time-variable gravity observations from the GRACE and GRACE-FO missions have greatly advanced our quantitative understanding of mass redistribution within the Earth system, including terrestrial hydrology, ocean mass variability, cryospheric change, solid Earth processes, and climate-driven signals. The GRACE and GRACE-FO datasets are currently undergoing RL07 reprocessing at the Center for Space Research (CSR) to further reduce noise and systematic errors, improve solution consistency, and establish a uniform long-term archival record that supports multi-decadal mass change analyses across the GRACE and GRACE Follow-On missions.The RL07 reprocessing includes a complete reanalysis of Level-1B observations, updates to reference frames and background geophysical models, and a series of improvements to orbit determination and gravity field recovery. Key enhancements include improved treatment of GNSS and K-band ranging observations, refined instrument error calibration, and updated processing and stochastic modeling strategies. In parallel, a new generation of CSR mascon solutions is produced using methodologies fully consistent with the RL07 framework. This paper describes the major upgrades implemented in the CSR RL07 reprocessing of GRACE and GRACE-FO data and assesses their impact on solution stability, noise characteristics, and the fidelity of time-variable gravity signals. Relative to CSR RL06, the RL07 solutions exhibit more than a 35% reduction in noise, quantified as root-mean-square (RMS) variability over the oceans, which translates directly into a substantial improvement in the realized spatial resolution of GRACE and GRACE-FO mass change estimates.

We will present the GRACE-FO Level-2 and Level-3 products currently produced at the CSR as part of the SDS effort, in particular the changes related to the latest releases RL06.2 and RL06.3. We will provide a quality assesment of the gravity products through the usual metrics. Finally, we will offer a status report on the efforts conducted towards the RL07 reprocessing of the GRACE/GRACE-FO data and mean fields.

GRACE observations revealed that rapid mass loss in the West Antarctic Ice Sheet (WAIS) abruptly paused in 2015, followed by a much lower rate of mass loss ( 21.3±5.7 Gt‧yr-1) until the decommissioning of GRACE in 2017. The critical 1-year GRACE inter-mission data gap raises the question of whether the reduced mass loss rate persists. The Swarm gravimetry data, which have a lower resolution, show good agreement with GRACE/GRACE-FO observations during the overlapping period, i.e. high correlation (0.78) and consistent trend estimates. Swarm data efficiently bridge the GRACE/GRACE-FO data gap and reveal that WAIS has returned to the rapid mass loss state (  161.5±48.4  Gt‧yr-1) that prevailed prior to 2015 during the GRACE inter-mission data gap. The changes in precipitation patterns, driven by the climate cycles, further explain and confirm the dramatic shifts in the WAIS mass loss regime implied by the Swarm observations.

GRACE observations revealed that rapid mass loss in the West Antarctic Ice Sheet (WAIS) abruptly paused in 2015, followed by a much lower rate of mass loss ( Gt yr⁻¹) until the decommissioning of GRACE in 2017. The critical 1‐year GRACE intermission data gap raises the question of whether the reduced mass loss rate persists. The Swarm gravimetry data, which have a lower resolution, show good agreement with GRACE/GRACE‐FO observations during the overlapping period, i.e., high correlation (0.78) and consistent trend estimates. Swarm data efficiently bridge the GRACE/GRACE‐FO data gap and reveal that WAIS has returned to the rapid mass loss state ( Gt yr⁻¹) that prevailed prior to 2015 during the GRACE intermission data gap. The changes in precipitation patterns, driven by the climate cycles, further explain and confirm the dramatic shifts in the WAIS mass loss regime implied by the Swarm observations.

We carry out a comprehensive error assessment of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) Release‐6 (RL06) solutions from the Center for Space Research (CSR) at the University of Texas at Austin, NASA Jet Propulsion Laboratory (JPL), and Geoforschungszentrum (GFZ). The study covers the period April 2002 to August 2020 and uses two different methods, one based upon open ocean residuals (OOR) and the other a Three‐Cornered Hat (TCH) calculation. General results from the two methods are similar. With 300 km Gaussian smoothing OOR RMS errors for CSR, JPL, and GFZ solutions are ∼2.01, 3.19, and 3.67 cm, respectively. With additional decorrelation filtering OOR RMS values are reduced to ∼1.24, 1.53, and 1.69 cm, respectively. TCH analysis also shows that CSR has the lowest noise levels with similar RMS values, and additional decorrelation filtering reduces error levels. TCH may underestimate errors if there are common errors among geophysical background models. Errors in GFO's first two years (25 solutions for 2018.06 to 2020.08) are comparable to those of GRACE when zonal degree 2 and 3 coefficients are replaced by Satellite Laser Ranging estimates. The OOR method reveals mismodeled intra‐seasonal dynamic ocean signals associated with the Argentine Gyre during de‐aliasing, while the TCH method shows differences between ocean tide models near Australia and Antarctica. Both OOR and TCH RMS analysis offer a means to assess the noise level of GRACE/GFO estimated mass change. The actual uncertainty of GRACE/GFO estimate averaged (or totaled) over a given region is also affected by other error sources.

Satellite altimeter sea surface heights, in combination with Argo ocean temperature and salinity observations, provide an independent measure of global mean ocean mass (GMOM) change. Over the period January 2005 to April 2020, GMOM rates observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) range from 1.88 ± 0.10 to 2.63 ± 0.10 mm/year, compared to 2.85 ± 0.37 mm/year from Altimeter‐Argo. Over much of the GRACE era, GRACE GMOM estimates agree well with Altimeter‐Argo over a broadband of frequencies. However, during the late stage of the GRACE mission (after August 2016) and into the GFO era, differences between GRACE/GFO and Altimeter‐Argo GMOM estimates become substantially larger and systematic, which may be related to the single accelerometer mode of operation during late‐stage GRACE and GFO missions and/or errors of Argo and altimeter data.

River runoff is estimated as a water budget residual using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage time series, ERA5 reanalysis data, and precipitation observations for January 2003 through December 2015 for the Obidos upstream drainage basin and for the entire Amazon basin. Estimated runoff based on the water budget agrees remarkably well with in situ gauge observations at Obidos, especially at seasonal time scales, with nearly perfect phase agreement but slightly larger seasonal amplitude. The discrepancy in the seasonal amplitude may be attributed to underestimation of river gauge runoff during the wet season when water overflows the riverbanks. The ERA5 model appears to overestimate long‐term mean evapotranspiration in the Amazon by ~2 cm/month based on comparisons with precipitation and runoff observations. Using precipitation data based on satellites and gauge observations relative to gauge observations alone improved agreement between water budget runoff estimates and in situ runoff observations. Seasonal variations in ERA5‐simulated runoff are about twice as large as those from in situ observations and show a large phase lag as well. Water budget‐based runoff for the entire Amazon (~7,200 km³ averaged over the 13‐year period) is significantly larger than observed runoff (~5,700 km³) at Obidos and notably larger than previous estimates for the entire Amazon. These differences may be partly related to submarine runoff from the Amazon basin that cannot be captured by surface gauges.

Global mean ocean mass change derived from the Gravity Recovery and Climate Experiment (GRACE) gravity solutions generally agrees well with ocean mass change inferred from satellite altimeter sea surface height and Argo floats observations during the period January 2005 to December 2015. However, there is a systematic annual phase lag (~10°) between GRACE and Altimeter‐Argo estimates. This phase lag is attributed to the enforced mass conservation in GRACE gravity solutions, in which the ΔC₀₀ coefficients (representing changes in total Earth mass) are set to zero. After a correct implementation of global mass conservation by removing global mean atmospheric mass from the GRACE solutions using atmospheric model predictions, the annual phase lag is nearly completely gone, yielding significantly improved agreement between GRACE and Altimeter‐Argo estimates. In addition, retaining GRACE ΔJ₂ coefficients provides better GRACE ocean mass estimates at both seasonal and long‐term time scales.