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The non‐closure of the global sea level budget, detected since 2017, stimulates the need to better understand limitations of satellite altimetry and gravimetry measurements, and breakdown in situ measurement contributions and gaps. Here, temperature and salinity profiles collected in the subtropical Northwest Atlantic Ocean between 2017 and 2022 by Deep Argo floats are used to partition steric sea level variability into contributions as a function of depth. Interannual steric sea level variability near the surface is of the same order of magnitude over the western boundary and abyssal plain, but fluctuations below 2,000 m over the western boundary are seven times larger and seem affected by local wind forcing. This analysis demonstrates how Deep Argo enables new evaluation of regional sea level budgets and comparison to geodetic products. Differences between float measurements and GLORYS12 highlight the need for more deep‐ocean measurements that can be assimilated in the development of ocean reanalysis products.

We investigate the performances of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite gravimetry missions in assessing the ocean mass budget at the global scale over 2005–2020. For that purpose, we focus on the last years of the record (2015–2020) when GRACE and GRACE Follow-On faced instrumental problems. We compare the global mean ocean mass estimates from GRACE and GRACE Follow-On to the sum of its contributions from Greenland, Antarctica, land glaciers, terrestrial water storage and atmospheric water content estimated with independent observations. Significant residuals are observed in the global mean ocean mass budget at interannual timescales. Our analyses suggest that the terrestrial water storage variations based on global hydrological models likely contribute in large part to the misclosure of the global mean ocean mass budget at interannual timescales. We also compare the GRACE-based global mean ocean mass with the altimetry-based global mean sea level corrected for the Argo-based thermosteric contribution (an equivalent of global mean ocean mass). After correcting for the wet troposphere drift of the radiometer on board the Jason-3 altimeter satellite, we find that mass budget misclosure is reduced but still significant. However, replacing the Argo-based thermosteric component by the Ocean Reanalysis System 5 (ORAS5) or from the Clouds and the Earth's Radiant Energy System (CERES) top of the atmosphere observations significantly reduces the residuals of the mass budget over the 2015–2020 time span. We conclude that the two most likely sources of error in the global mean ocean mass budget are the thermosteric component based on Argo and the terrestrial water storage contribution based on global hydrological models. The GRACE and GRACE Follow-On data are unlikely to be responsible on their own for the non-closure of the global mean ocean mass budget.

Closure of the regional sea level trend budget is investigated over the 2004–2022 time span by comparing trend patterns from the satellite altimetry-based sea level with the sum of contributions, i.e. the thermosteric, halosteric, manometric and GRD (gravitational, rotational, and deformational fingerprints due to past and ongoing land ice melt) components. The thermosteric and halosteric components are based on Argo data (down to 2000 m). For the manometric component, two approaches are considered: one using GRACE/GRACE Follow-On satellite gravimetry data and the other using ocean reanalyses-based sterodynamic sea level data corrected for local steric effects. For the latter, six different ocean reanalyses are considered, including two reanalyses that do not assimilate satellite altimetry data. The results show significantly high residuals in the North Atlantic for both approaches. In a few other regions, small-scale residuals of smaller amplitude are observed and attributed to the finer resolution of altimetry data compared to the coarser resolution of data sets used for the components. The observed strong residual signal in the North Atlantic points to Argo-based salinity errors in this region. However, it is not excluded that other factors also contribute to the reported non-closure of the budget in this area.

The Earth energy imbalance (EEI) at the top of the atmosphere is responsible for the accumulation of heat in the climate system. Monitoring the EEI is therefore necessary to better understand the Earth's warming climate. Measuring the EEI is challenging as it is a globally integrated variable whose variations are small (0.5–1 W m−2) compared to the amount of energy entering and leaving the climate system (∼340 W m−2). Since the ocean absorbs more than 90 % of the excess energy stored by the Earth system, estimating the ocean heat content (OHC) change provides an accurate proxy of the EEI. This study provides a space geodetic estimation of the OHC changes at global and regional scales based on the combination of space altimetry and space gravimetry measurements. From this estimate, the global variations in the EEI are derived with realistic estimates of its uncertainty. The mean EEI value is estimated at +0.74±0.22 W m−2 (90 % confidence level) between August 2002 and August 2016. Comparisons against estimates based on Argo data and on CERES measurements show good agreement within the error bars of the global mean and the time variations in EEI. Further improvements are needed to reduce uncertainties and to improve the time series, especially at interannual timescales. The space geodetic OHC-EEI product (version 2.1) is freely available at https://doi.org/10.24400/527896/a01-2020.003 (Magellium/LEGOS, 2020).

Five successive reference missions, TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, and more recently Sentinel-6 Michael Freilich, have ensured the continuity and stability of the satellite altimetry data record. Tandem flight phases have played a key role in verifying and ensuring the consistency of sea level measurements between successive altimetry reference missions and thus the stability of sea level measurements. During a tandem flight phase, two successive reference missions follow each other on an identical ground track at intervals of less than 1 min. Observing the same ocean zone simultaneously, the differences in sea level measurements between the two altimetry missions mainly reflect their relative errors. Relative errors are due to instrumental differences related to altimeter characteristics (e.g., altimeter noise) and processing of altimeter measurements (e.g., retracking algorithm), precise orbit determination, and mean sea surface. Accurate determination of systematic instrumental differences is achievable by averaging these relative errors over periods that exceed 100 d. This enables for the precise calibration of the two altimeters. The global mean sea level offset between successive altimetry missions can be accurately estimated with an uncertainty of about ±0.5 mm ([16 %–84 %] confidence level). Nevertheless, it is only feasible to detect instrumental drifts in the global mean sea level exceeding 1.0 to 1.5 mm yr−1 due to the brief duration of the tandem phase (9 to 12 months). This study aims to propose a novel cross-validation method with a better ability to assess the instrumental stability (i.e., instrumental drifts in the global mean sea level trends). It is based on the implementation of a second tandem flight phase between two successive satellites a few years after the first one. Calculating sea level differences during the second tandem phase provides an accurate evaluation of relative errors between the two successive altimetry missions. With a second tandem phase that is long enough, the systematic instrumental differences in sea level will be accurately reevaluated. The idea is to calculate the trend between the systematic instrumental differences made during the two tandem phases. The uncertainty in the trend is influenced by the length of each tandem phase and the time intervals between the two tandem phases. Our findings show that assessing the instrumental stability with two tandem phases can achieve an uncertainty below ±0.1 mm yr−1 ([16 %–84 %] confidence level) at the global scale for time intervals between the two tandem phases that are higher than 4 years or more and where each tandem phase lasts at least 4 months. On regional scales, the gain is greater, with an uncertainty of ±0.5 mm yr−1 ([16 %–84 %] confidence level) for spatial scales of about 1000 km or more. With regard to the scenario foreseen for the second phase between Jason-3 and Sentinel-6 Michael Freilich planned for early 2025, 2 years and 9 months after the end of the first tandem phase, the instrumental stability could be assessed with an uncertainty of ±0.14 mm yr−1 on the global scale and ±0.65 mm yr−1 for spatial scales of about 1000 km ([16 %–84 %] confidence level). In order to achieve a larger benefit from the use of this novel cross-validation method, this involves regularly implementing double tandem phases between two successive altimetry missions in the future.

An instrumental drift in the point target response (PTR) parameters has been detected on the Copernicus Sentinel-3A altimetry mission. It will affect the accuracy of sea level sensing, which could result in errors in sea level change estimates of a few tenths of a millimeter per year. In order to accurately evaluate this drift, a method for detecting global and regional mean sea level relative drifts between two altimetry missions is implemented. Associated uncertainties are also accurately calculated thanks to a detailed error budget analysis. A drift on both Sentinel-3A (S3A) and Sentinel-3B (S3B) global mean sea level (GMSL) is detected with values significantly higher than expected. For S3A, the relative GMSL drift detected is 1.0 mm yr−1 with Jason-3 and 1.3 mm yr−1 with SARAL/AltiKa. For S3B, the relative GMSL drift detected is −3.4 mm yr−1 with Jason-3 and −2.2 mm yr−1 with SARAL/AltiKa. The drift detected at global level does not show detectable regional variations above the uncertainty level of the proposed method. The investigations led by the altimeter experts can now explain the origin of this drift for S3A and S3B. The ability of the implemented method to detect a sea level drift with respect to the length of the common period is also analyzed. We find that the minimum detectable sea level drift over a 5-year period is 0.3 mm yr−1 at the global scale and 1.5 mm yr−1 at the 2400 km regional scale. However, these levels of uncertainty do not meet the sea level stability requirements for climate change studies.