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The discrepancy in the observed global mean sea level budget increased significantly since 2016, but the budget discrepancy over basin‐scales is unclear. In this contribution, we investigate the sea level budget discrepancies in major basins with observations from satellite altimetry, satellite gravimetry, and Argo floats. During 2016–2020, we find substantial discrepancy of 5.72 ± 0.98 mm/yr over the North Atlantic Ocean, and the basin scale discrepancies are smaller elsewhere. Our analysis suggests that three factors, including the wet tropospheric correction (WTC) effect, deep ocean warming signal, and the contemporary ocean bottom deformation (OBD), together reduce the discrepancy by only 1 mm/yr for the North Atlantic Ocean. We decompose sea level observations into the spherical harmonic domain and observe increased discrepancy in low‐degree variations of C10 and C21 since 2016. These two coefficients result in a contrasting signal between the North and South Atlantic Ocean and contribute to the large discrepancy over the North Atlantic Ocean. We further demonstrate that the C10 and C21 discrepancies are independent of the three factors. However, we find regional salinity biases in the Argo data that reduce the discrepancy for the North Atlantic Ocean. Our findings add to the debate about recent sea level budget and imply that further analysis of the Argo North Atlantic data set may be useful. Plain Language Summary: Global mean sea level rise observed by satellite altimetry was well explained by measurements from satellite gravity and Argo floats for 2003–2015. However, since 2016, a substantial portion of sea level rise is not adequately explained. This unexplained portion is defined as the sea level discrepancy. To address the discrepancy for 2016–2020, we quantify the sea level discrepancy over each of the ocean basins. We find that sea level rise is well explained over the South Atlantic Ocean, South Pacific Ocean and Indian Ocean, but a 5.7 mm/yr trend is not explained over the North Atlantic Ocean during 2016–2020. Further analysis reveals two underlying systemic discrepancies in sea level observations that produce a contrasting pattern over the North and South Atlantic Ocean and contribute to the sea level discrepancy over the North Atlantic Ocean. Biases the wet tropospheric correction (WTC), deep ocean warming, and contemporary ocean bottom deformation (OBD) do not appear to be responsible for the north‐south asymmetry. Our analysis points to a potential regional salinity bias in the North Atlantic Argo data set. Key Points: Basin‐scale discrepancies in the sea level budget are investigated using sea level observationsSea level discrepancy is substantially larger over the North Atlantic Ocean since 2016We identify a large halosteric contraction in the Argo North Atlantic data since 2016 which may be responsible for the sea level discrepancy [ABSTRACT FROM AUTHOR]

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth's surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth's surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. [ABSTRACT FROM AUTHOR]

Ocean mass increase contributes to global sea level rise, and plays an important role in understanding climate change. Here, we develop a data assimilation approach that enables the inference of ocean mass increase from global tide gauge network. This approach incorporates outputs from climate models and sea level fingerprints caused by water mass changes over land areas. The results suggest a trend of 2.15 ± 0.72 mm/yr for ocean mass increase over the period 1993–2022, which closes the global sea level budget with estimates of thermosteric sea level rise. Furthermore, the inferred ocean mass increase offers an insight into the causes of sea level rise since 1950. These findings emphasize the significance of climate models, in addition to simulating sea level changes, they contribute to understanding causes of sea level rise over the past decades. Plain Language Summary: Tide gauges record long‐term sea level changes, which encompass ocean thermal expansion and ocean mass increase due to water mass loss over global land areas. By carefully modeling these components, we can estimate the increase in global ocean mass using data from tide gauges. To this end, we construct a data assimilation approach that is driven by outputs from climate models. This approach reveals a 2.15 ± 0.72 mm/yr ocean mass trend for the satellite altimetry era, which could explain the observed global sea level rise with estimates of ocean thermal expansion. Further analysis indicates that the inferred ocean mass increase, combined along with the outputs of climate models, closely agrees with an independently reconstructed global mean sea level rise. Our findings emphasize the crucial role of climate models in comprehending the factors contributing to sea level rise over the past decades. Key Points: A data assimilation technique is driven by outputs from climate models to infer ocean mass increase from tide gaugesThe inferred ocean mass trend closes the global sea level budget over the satellite altimetry eraResults offer insights into the causes of global sea level rise since 1950 [ABSTRACT FROM AUTHOR]

Global mean sea level rise has been reconstructed using tide gauges. However, long-term sea level rise along the China coast is unclear. To address this issue, a data assimilation approach is developed to reconstruct sea level rise along the China coast from 1950 to 2020 using a global distribution of tide gauges (TGs). This approach combines climate models and sea level fingerprints. The climate models provide stereodynamic sea level changes. The sea level fingerprints include increases in ocean mass due to global ice melting and changes in water storage on land. The reconstructed global mean sea level rise agrees well with previous studies. We quantify sea level rise at 20 TGs along the China coast. The results suggest that sea level rise along the China coast (1.95±0.33 mm yr−1) is greater than the global mean (1.71±0.17 mm yr−1). We also find that China's coastal sea level rise is more than three times the global mean after 1980, increasing from 0.84±0.28 mm yr−1 for 1950–1980 to 3.12±0.21 mm yr−1 for 1980–2020. This finding implies a significant sea level acceleration along the China coast. Our results advance the understanding of long-term sea level changes along the China coast. [ABSTRACT FROM AUTHOR]

Most studies of sea level budget only indicate the stationary causes for the global mean sea level (GMSL) rise over the course of a time span of interest, providing limited information on temporary changes in the GMSL budget. In this contribution, we present an instantaneous budget of the GMSL for the period of 2003–2015, which offers new insights on the time evolution of the GMSL budget. We use a space-state model to compute the instantaneous rates of GMSL and their contributing sources (barystatic and steric contributions), to investigate the causes of the GMSL instantaneous budget, which accounts for and quantifies low-frequency variations in GMSL rise. Combining the barystatic GMSL instantaneous rates (estimated from satellite gravimetry) along with a particular choice of steric GMSL instantaneous rates (inferred from an Argo product) achieves closure of the GMSL instantaneous budget with a standard deviation of 0.4 mm yr−1. We find that the barystatic GMSL rate is primarily responsible for the striking fluctuations in the GMSL instantaneous rates between 2009 and 2015. For example, over only 20 months (July 2010 to February 2012), the GMSL (barystatic) rate increases from 0.32 (0.71) to 6.12 (4.55) mm yr−1. These strong fluctuations mainly result from hydrology and mountain glacier mass variations rather than mass loss in ice sheet, for instance, Australia slowed ∼1.2 mm yr−1 equivalent contribution to GMSL rise over the year 2010, which is approximately four times the linear rate of Antarctica mass loss. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) satellite mission has profoundly advanced our knowledge of contemporary sea level change. Owing to the coarse spatial resolution and leakage issue across the land–ocean boundary, it is challenging (even impossible) for GRACE to detect mass changes over a region smaller than its spatial resolution, especially a semi-enclosed basin (e.g., the Bohai Sea) that is adjacent to land with significant mass variation. In this contribution, the causes for the GRACE RL06 mass changes in the Bohai Sea are investigated using a reconstruction technique that is implemented with multisource data, including altimeter observations, steric estimates, and land mass changes from GRACE RL06 mascon solution. Our results by the reconstruction technique demonstrate that the GRACE annual cycles are primarily caused by water mass changes rather than sediment changes. On the other hand, the mass trends from both reconstructed signals and those observed by the GRACE RL06 spherical harmonic coefficients (SHCs) are small, ranging from − 0.38 mm/year to 0.51 mm/year (depending on different data sources). Given that our estimated accuracies are > 0.8 mm/year (the real accuracies should be larger), our reconstructed results cannot directly confirm the presence of sediment accumulation or water mass increase; however, analysis of only the altimetry data suggests the mass trends are due to water mass increase, which would amount to ~ 0.44 Gt/year. Further investigation suggests that the mass trends in the Bohai Sea suffer from a − 2.9 mm/year leakage-in effect from groundwater depletion in the North China and about 2.5 mm/year signal attenuation (resulting in a ~ 2.5 mm/year remaining trend that is roughly equivalent to the leakage-in trend, consequently leading to the small mass trend in the Bohai Sea). Our reconstruction results exemplify that elaborate data processing is necessary for specific cases. We also test whether the recently released RL06 mascon solutions that are resolved with constraints and require no further processing would improve the agreement with altimeter observations. We find that the seasonal cycles are improved relative to the RL06 SHCs; however, the rates derived from the mascon solutions cannot properly represent the altimeter-derived ocean mass estimates for the Bohai Sea, probably because the mascon solutions underestimate the rates or contain some processing artifacts. Nevertheless, the mascon solutions show enhanced signals, which offer new opportunities to investigate regional sea level change. [ABSTRACT FROM AUTHOR]

Knowledge of the coastal ocean mass variations is important for understanding the ocean climate and sea level change. However, estimates of coastal ocean mass variations have been perplexed due to poor representativeness of previous Gravity Recovery and Climate Experiment (GRACE) data across the land/ocean boundary. We here use GRACE mascon solutions to investigate the coastal ocean mass variations (within 400 km band) at global and regional scales. GRACE mascon solutions are advanced by spatial constraints and leakage correction. For the global mean, it is found that mascons ocean mass variations are in rough agreement with those inferred from satellite altimeter and an ocean analysis; the agreement is better on seasonal scales (6.4 ± 0.5 mm annual amplitude for the mascons and 7.3 ± 0.7 mm annual amplitude for the inferred); on the other hand, large differences are shown for the linear trend (2.1 ± 0.1 mm yr−1 for the mascons and 3.2 ± 0.1 mm yr−1 for the inferred), indicating that it is far from closing the coastal sea level budget. At regional scales, high consistency between mascons and the inferred is observed over two shallow areas, that is, Europe coast and East China coast, whose annual amplitudes are 24 ± 5 and 42 ± 3 mm, respectively. Ocean mass variations are not well captured by mascons over other regions (e.g. Africa coast, Indian coast and North and South America coast). Possible explanations include (1) the steric component plays a more important role in sea level, consequently resulting in weak mass signal and (2) the performance of mascons varies with locations. We find that mascon solutions show better variability (especially seasonal cycles) than do the traditional spherical harmonic coefficients, suggesting that mascons applied with spatial constraints improve the coastal ocean mass variability. [ABSTRACT FROM AUTHOR]

Ground-based GNSS-R (global navigation satellite system reflectometry) can provide the absolute vertical distance from a GNSS antenna to the reflective surface of the ocean in a common height reference frame, given that vertical crustal motion at a GNSS station can be determined using direct GNSS signals. This technique offers the advantage of enabling ground-based sea level measurements to be more accurately determined compared with traditional tide gauges. Sea level changes can be retrieved from multipath effects on GNSS, which is caused by interference of the GNSS L-band microwave signals (directly from satellites) with reflections from the environment that occur before reaching the antenna. Most of the GNSS observation types, such as pseudo-range, carrier-phase and signal-to-noise ratio (SNR), suffer from this multipath effect. In this paper, sea level altimetry determinations are presented for the first time based on geometry-free linear combinations of the carrier phase at low elevation angles from a fixed global positioning system (GPS) station. The precision of the altimetry solutions are similar to those derived from GNSS SNR data. There are different types of observation and reflector height retrieval methods used in the data processing, and to analyze the performance of the different methods, five sea level determination strategies are adopted. The solutions from the five strategies are compared with tide gauge measurements near the GPS station, and the results show that sea level changes determined from GPS SNR and carrier phase combinations for the five strategies show good agreement (correlation coefficient of 0.97-0.98 and root-mean-square error values of <0.2 m). [ABSTRACT FROM AUTHOR]