Analysis of the interannual variability in satellite gravity solutions: detection of climate modes fingerprints in water mass displacements across continents and oceans

Pfeffer, Julia; Cazenave, Anny; Barnoud, Anne

doi:10.1007/s00382-021-05953-z

Cited by 21 publications

(25 citation statements)

References 117 publications

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“…The dominant influence of ENSO and PDO indices with Pacific and Indian Ocean sea level agrees with other works (e.g. Zhang and Church, 2012;Hamlington et al, 2019;Wang et al, 2021;Pfeffer et al, 2018Pfeffer et al, , 2022. In the North Atlantic Ocean, our approach finds a stronger relationship between sea-level variability and AMOC, followed by the AO.…”

Section: Sources Of Decadal Variability and Caveatssupporting

confidence: 91%

“…a ridge regression. A least absolute shrinkage and selection operator (LASSO) regression approach has been successfully applied to steric sea-level change (Pfeffer et al, 2018) and ocean mass change (Pfeffer et al, 2022) associated with climate variability on inter-annual and longer timescales. This approach relies on the user determining an appropriate penalty term, typically by a cross-validation.…”

Section: Methodsmentioning

confidence: 99%

“…Sea-level variability related (linearly) to climate indices shows larger correlation coefficients at coastal locations in tide gauge data than in open-ocean altimetry (Wang et al, 2021). Statistically significant relationships between the steric and manometric components of sea level and climate variability have been identified from models, reanalyses, and geodetic observations (Pfeffer et al, 2018(Pfeffer et al, , 2022. These works validate model and reanalyses data sets for sealevel studies and identify regions of the global ocean with explainable, climate-driven, inter-annual to decadal variability, masking anthropogenically driven changes and modifying coastal flood risk about the long-term trend on decadal periods.…”

Section: Introductionmentioning

confidence: 99%

“…Hamlington et al, 2013;Hamlington et al, 2020c) and regionally from climate variability dominated by atmosphere-ocean interactions (e.g. Zhang and Church, 2012;Pfeffer et al, 2018;Richter et al, 2020;Hamlington et al, 2020b;Wang et al, 2021;Pfeffer et al, 2022) and intrinsic, oceanic variability in eddy-rich regions (Sérazin et al, 2016). Understanding the driving mechanisms behind local, decadal sea-level change could lead to improved short-to medium-term forecasts of coastal sea-level change.…”

Section: Introductionmentioning

confidence: 99%

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Attributing decadal climate variability in coastal sea-level trends

2022

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Abstract. Decadal sea-level variability masks longer-term changes due to natural and anthropogenic drivers in short-duration records and increases uncertainty in trend and acceleration estimates. When making regional coastal management and adaptation decisions, it is important to understand the drivers of these changes to account for periods of reduced or enhanced sea-level change. The variance in decadal sea-level trends about the global mean is quantified and mapped around the global coastlines of the Atlantic, Pacific, and Indian oceans from historical CMIP6 runs and a high-resolution ocean model forced by reanalysis data. We reconstruct coastal, sea-level trends via linear relationships with climate mode and oceanographic indices. Using this approach, more than one-third of the variability in decadal sea-level trends can be explained by climate indices at 24.6 % to 73.1 % of grid cells located within 25 km of a coast in the Atlantic, Pacific, and Indian oceans. At 10.9 % of the world's coastline, climate variability explains over two-thirds of the decadal sea-level trend. By investigating the steric, manometric, and gravitational components of sea-level trend independently, it is apparent that much of the coastal ocean variability is dominated by the manometric signal, the consequence of the open-ocean steric signal propagating onto the continental shelf. Additionally, decadal variability in the gravitational, rotational, and solid-Earth deformation (GRD) signal should not be ignored in the total. There are locations such as the Persian Gulf and African west coast where decadal sea-level variability is historically small that are susceptible to future changes in hydrology and/or ice mass changes that drive intensified regional GRD sea-level change above the global mean. The magnitude of variance explainable by climate modes quantified in this study indicates an enhanced uncertainty in projections of short- to mid-term regional sea-level trend.

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Section: Sources Of Decadal Variability and Caveatssupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Attributing decadal climate variability in coastal sea-level trends

2022

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“…Vishwakarma et al, 2021), ice sheet melting (e.g. Velicogna et al, 2020;Shepherd et al, 2021), interannual variability of water mass transport (Pfeffer et al, 2022), variations of Earth's energy imbalance (Hakuba et al, 2021;Marti et al, 2022). Ensuring the stability of GRACE and GRACE-FO data is therefore very important for climate and hydrological applications.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the global mean ocean mass budget over 2005–2020

Barnoud

Pfeffer²,

Cazenave³

et al. 2022

Preprint

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Abstract. We investigate the continuity and stability of GRACE and GRACE Follow-On satellite gravimetric missions by assessing the ocean mass budget at global scale over 2005–2020, focusing on the last years of the record (2015–2020) when GRACE and GRACE Follow-On faced instrumental problems. For that purpose, 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 and terrestrial water storage estimated with independent observations. A significant residual trend of -1.60 ± 0.36 mm/yr over 2015–2018 is observed. We also compare the gravimetry-based global mean ocean mass with the altimetry-based global mean sea level corrected for the thermosteric contribution. We estimate and correct for the drift of the wet tropospheric correction of the Jason-3 altimetry mission computed from the on-board radiometer. It accounts for about 40 % of the budget residual trend beyond 2015. After correction, the remaining residual trend amounts to -0.90 ± 0.78 mm/yr over 2015–2018 and -0.96 ± 0.48 mm/yr over 2015–2020. GRACE and GRACE Follow-On data might be responsible for part of the observed non-closure of the ocean mass budgets since 2015. However, we show that significant interannual variability is not well accounted for by the data used for the other components of the budget, including the thermosteric sea level and the terrestrial water storage. Besides, missing contributions from the evolution of the deep ocean or the atmospheric water vapour may also contribute.

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Uncertainty of low-degree space gravimetry observations: surface processes versus internal signal

Lecomte

Rosat

Mandea

et al. 2022

Preprint

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Space gravity measurements have been mainly used to study the temporal mass variations at the Earth's surface and within the mantle. Nevertheless, mass variations due to the Earth's core might be observable in the variations of the gravity field as measured by GRACE and GRACE-FO satellites. Moreover, a possible correlation between the time-variable gravity and magnetic fields has been pointed out at inter-annual time scales. Earth's core dynamical processes inferred from geomagnetic field measurements are characterized by large-scale patterns associated with low spherical harmonic degrees of the potential fields. Studying Earth's core processes via gravity field observations involves the use of large spatial and inter-annual temporal filters. To access gravity variations related to the Earth's core, surface effects must be corrected, including hydrological, oceanic or atmospheric loading. This study estimates the uncertainty associated with gravity-field products and geophysical models used to minimise the surface process signatures in gravity field data. Here, we estimate the dispersion for GRACE solutions as about 0.34 cm of Equivalent Water Height (EWH) or 20% of the total signal. Uncertainty for hydrological models is as large as 0.89 to 2.10 cm of EWH. Loading products contain mostly different signals at inter-annuals time scales. We also show that a remaining hydrological signal in a very localized region can affect the low-degree components of the gravity field. The results presented here underline how challenging is to get new information about the dynamics of the Earth's core via high-accuracy gravity data.

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Analysis of the interannual variability in satellite gravity solutions: detection of climate modes fingerprints in water mass displacements across continents and oceans

Cited by 21 publications

References 117 publications

Attributing decadal climate variability in coastal sea-level trends

Attributing decadal climate variability in coastal sea-level trends

Revisiting the global mean ocean mass budget over 2005–2020

Uncertainty of low-degree space gravimetry observations: surface processes versus internal signal

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