Reducing the Uncertainty in the Satellite Altimetry Estimates of Global Mean Sea Level Trends Using Highly Stable Water Vapor Climate Data Records

Barnoud, Anne; Picard, Bruno; Meyssignac, Benoît; Marti, Florence; Ablain, Michaël; Roca, Rémy

doi:10.1029/2022jc019378

Cited by 10 publications

(6 citation statements)

References 33 publications

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“…The uncertainties of the GMSL and of the GMSL trend are computed using the uncertainty budget and computational method detailed by Ablain et al (2019). Barnoud et al (2023) showed that the wet tropospheric correction (WTC) derived from the microwave radiometer (MWR) instrument on board the Jason-3 satellite, launched in 2016, is likely drifting. This drift was outlined from the comparison of Jason-3's radiometer WTC with a WTC derived from highly stable water vapour climate data records (Schröder et al, 2016) and with the radiometer's WTC from the SARAL/AltiKa and Sentinel-3A altimetry missions (Barnoud et al, 2023(Barnoud et al, , 2022.…”

Section: Altimetry-based Gmsl Datamentioning

confidence: 99%

Revisiting the global mean ocean mass budget over 2005-202

Barnoud¹,

Pfeffer²,

Cazenave

et al. 2023

Preprint

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<p>We investigate the performances of GRACE and GRACE Follow-On satellite gravimetry missions in assessing the ocean mass budget at 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 time scales. Our analyses suggest that the terrestrial water storage variations based on global hydrological model likely contributes to a large part to the misclosure of the global mean ocean mass budget at interannual time scales. 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 ORAS5 ocean reanlaysis or from CERES top of the atmosphere observations leads to closure 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.</p>

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Section: Altimetry-based Gmsl Datamentioning

confidence: 99%

Revisiting the global mean ocean mass budget over 2005-202

Barnoud¹,

Pfeffer²,

Cazenave

et al. 2023

Preprint

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“…Results by Barnoud et al. (2023) suggested that the GMSL rate increased by about 0.20 mm/yr for 1992–2021 after they used an alternative WTC data set with high quality. Taking into account the WTC effect increases the discrepancy between altimeter‐based GMSL rate and the rate of our inferred ocean mass increase + global thermosteric sea level (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…However, the evaluation presented in Table 1 has not considered the wet troposphere correction (WTC) effect on altimeter-based GMSL trend, which is shown to contribute to the GMSL rate over the altimeter era. Results by Barnoud et al (2023) suggested that the GMSL rate increased by about 0.20 mm/yr for 1992-2021 after they used an alternative WTC data set with high quality. Taking into account the WTC effect increases the discrepancy between altimeter-based GMSL rate and the rate of our inferred ocean mass increase + global thermosteric sea level (Table 1).…”

Section: Resultsmentioning

confidence: 99%

Inferring Global Ocean Mass Increase From Tide Gauges Network With Climate Models

Mu,

Huang,

et al. 2024

Geophysical Research Letters

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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.

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“…The reduction in timing error is greater than 69%. In contrast, the wet troposphere error has not changed significantly, and multiple cycles only reduce the error by 2.92%, which may be related to its characteristics of uneven temporal and spatial distribution [58]. To compare the effects of multi-cycle data on the recovery of SWOT_GGT, another experiment is conducted.…”

Section: Discussionmentioning

confidence: 99%

Expected Precision of Gravity Gradient Recovered from Ka-Band Radar Interferometer Observations and Impact of Instrument Errors

Guo,

Wan,

Wang

et al. 2024

Remote Sensing

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Full tensor of gravity gradients contains extremely large amounts of information, which is one of the most important sources for research on recovery seafloor topography and underwater matching navigation. The calculation and accuracy of the full tensor of gravity gradients are worth studying. The Ka-band interferometric radar altimeter (KaRIn) of surface water and ocean topography (SWOT) mission enables high spatial resolution of sea surface height (SSH), which would be beneficial for the calculation of gravity gradients. However, there are no clear accuracy results for the gravity gradients (the gravity gradient tensor represents the second-order derivative of the gravity potential) recovered based on SWOT data. This study evaluated the possible precision of gravity gradients using the discretization method based on simulated SWOT wide-swath data and investigated the impact of instrument errors. The data are simulated based on the sea level anomaly data provided by the European Space Agency. The instrument errors are simulated based on the power spectrum data provided in the SWOT error budget document. Firstly, the full tensor of gravity gradients (SWOT_GGT) is calculated based on deflections of the vertical and gravity anomaly. The distinctions of instrument errors on the ascending and descending orbits are also taken into account in the calculation. The precision of the Tzz component is evaluated by the vertical gravity gradient model provided by the Scripps Institution of Oceanography. All components of SWOT_GGT are validated by the gravity gradients model, which is calculated by the open-source software GrafLab based on spherical harmonic. The Tzz component has the poorest precision among all the components. The reason for the worst accuracy of the Tzz component may be that it is derived by Txx and Tyy, Tzz would have a larger error than Txx and Tyy. The precision of all components is better than 6 E. Among the various errors, the effect of phase error and KaRIn error (random error caused by interferometric radar) on the results is greater than 2 E. The effect of the other four errors on the results is about 0.5 E. Utilizing multi-cycle data for the full tensor of gravity gradients recovery can suppress the effect of errors.

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Reducing the Uncertainty in the Satellite Altimetry Estimates of Global Mean Sea Level Trends Using Highly Stable Water Vapor Climate Data Records

Cited by 10 publications

References 33 publications

Revisiting the global mean ocean mass budget over 2005-202

Revisiting the global mean ocean mass budget over 2005-202

Inferring Global Ocean Mass Increase From Tide Gauges Network With Climate Models

Expected Precision of Gravity Gradient Recovered from Ka-Band Radar Interferometer Observations and Impact of Instrument Errors

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