scholarly journals Global Sea Level Budget 1993–Present

2018 ◽  
Author(s):  
Keyword(s):  
Sea Level ◽  
Average Rate ◽  
Grand Challenge ◽  
Data Sets ◽  
Mean Sea Level ◽  
Climate Research ◽  
Global Mean Sea Level ◽  
Land Water ◽  
Global Mean ◽  
Individual Mass

Abstract. Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows detecting changes (e.g., acceleration) in one or more components. Study of the sea level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitled ``Regional Sea Level and Coastal Impacts'', an international effort involving the sea level community worldwide has been recently initiated with the objective of assessing the various data sets used to estimate components of the sea level budget during the altimetry era (1993 to present). These data sets are based on the combination of a broad range of space-based and in situ observations, model estimates and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about sixty research teams/institutions worldwide (http://www.wcrp-climate.org/grand-challenges/gc-sea-level). The results presented in this paper are a synthesis of the first assessment performed during 2017–2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 ± 0.3 mm/yr and acceleration of 0.1 mm/yr2 over 1993–present), as well as of the different components of the sea level budget (doi:10.17882/54854). We further examine closure of the sea level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute by 42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993–present. We also study the sea level budget over 2005–present, using GRACE-based ocean mass estimates instead of sum of individual mass components. Results show closure of the sea level budget within 0.3 mm/yr. Substantial uncertainty remains for the land water storage component, as shown in examining individual mass contributions to sea level.

scholarly journals Global sea-level budget 1993–present

2018 ◽  
Vol 10 (3) ◽  
pp. 1551-1590 ◽  
Author(s):  
Keyword(s):  
Sea Level ◽  
Average Rate ◽  
Deep Ocean ◽  
Grand Challenge ◽  
Mean Sea Level ◽  
Climate Research ◽  
Global Mean Sea Level ◽  
Land Water ◽  
Global Mean ◽  
Individual Mass

Abstract. Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows changes (e.g., acceleration) to be detected in one or more components. Study of the sea-level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitled Regional Sea Level and Coastal Impacts, an international effort involving the sea-level community worldwide has been recently initiated with the objective of assessing the various datasets used to estimate components of the sea-level budget during the altimetry era (1993 to present). These datasets are based on the combination of a broad range of space-based and in situ observations, model estimates, and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about 50 research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea-level, last access: 22 August 2018). The results presented in this paper are a synthesis of the first assessment performed during 2017–2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 ± 0.3 mm yr−1 and acceleration of 0.1 mm yr−2 over 1993–present), as well as of the different components of the sea-level budget (http://doi.org/10.17882/54854, last access: 22 August 2018). We further examine closure of the sea-level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute 42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993–present period. We also study the sea-level budget over 2005–present, using GRACE-based ocean mass estimates instead of the sum of individual mass components. Our results demonstrate that the global mean sea level can be closed to within 0.3 mm yr−1 (1σ). Substantial uncertainty remains for the land water storage component, as shown when examining individual mass contributions to sea level.

The rate and acceleration of the global mean sea level revisited

2020 ◽  
Author(s):  
Lorena Moreira ◽  
Anny Cazenave ◽  
Denise Cáceres ◽  
Hindumathi Palanisamy ◽  
Habib Dieng
Keyword(s):  
Thermal Expansion ◽  
Global Warming ◽  
Sea Level Rise ◽  
Interannual Variability ◽  
Sea Level ◽  
Water Storage ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Land Water ◽  
Global Mean

<p>Since nearly 3 decades, high-precision satellite altimetry allows us to precisely measure the mean sea level evolution at global and regional scales. In terms of global mean, sea level is rising at a mean rate of 3.2 mm/yr. The altimetry record is also suggesting that the global mean sea level rise is accelerating. However, the exact value of the acceleration and even its mere existence are still debated. Determination of the global warming-related sea level rate and acceleration are somewhat hindered by the interannual signal caused by natural climate variability. During the recent years, several studies have shown that at interannual time scale, the global mean sea level is mostly due to ENSO-driven land water storage variations. But thermal expansion fluctuations may also contribute. Thus, to isolate the global warming signal in the global mean sea level, we need to remove the ENSO-related interannual variability. For that purpose we use the Water Gap Global Hydrological model developed by the University of Frankfurt for land water storage as well as GRACE space gravimetry data on land and empirical models based on ENSO indices. We also extract the ENSO-related signal in thermal expansion. After removing the total interannual variability signal due to both mass and steric components, we compute the evolution with time of the ‘residual’ rate of sea level rise over successive 5-year moving windows, as well as the associated acceleration. Using time series of thermal expansion and ice sheet mass balances, we also estimate the respective contributions of each component to the global mean sea level acceleration.</p>

scholarly journals Is there a 60-year oscillation in global mean sea level?

2012 ◽  
Vol 39 (18) ◽  
Author(s):  
Don P. Chambers ◽  
Mark A. Merrifield ◽  
R. Steven Nerem
Keyword(s):  
Sea Level ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Mean

A 25-Year Satellite Altimetry-Based Global Mean Sea Level Record

2017 ◽  
pp. 187-210 ◽  
Author(s):  
R. Steven Nerem ◽  
Michaël Ablain ◽  
Anny Cazenave ◽  
John Church ◽  
Eric Leuliette
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Mean

scholarly journals The effect of lateral variations in Earth structure on Last Interglacial sea level

2021 ◽  
Author(s):  
Jacqueline Austermann ◽  
Mark Hoggard ◽  
Konstantin Latychev ◽  
Fred Richards ◽  
Jerry Mitrovica
Keyword(s):  
Sea Level ◽  
Earth Structure ◽  
Last Interglacial ◽  
Level Indicator ◽  
Mean Sea Level ◽  
Mineral Physics ◽  
Shear Wave Speed ◽  
Global Mean Sea Level ◽  
Lateral Variations ◽  
Global Mean

It is generally agreed that the Last Interglacial (LIG; ~130-115ka) was a time when global average temperatures and global mean sea level were higher than they are today. However, the exact timing, magnitude, and spatial pattern of ice melt is much debated. One difficulty in extracting past global mean sea level from local observations is that their elevations need to be corrected for glacial isostatic adjustment (GIA), which requires knowledge of Earth’s internal viscoelastic structure. While this structure is generally assumed to be radially symmetric, evidence from seismology, geodynamics, and mineral physics indicates that large lateral variations in viscosity exist within the mantle. In this study, we construct a new model of Earth’s internal structure by converting shear wave speed into viscosity using parameterisations from mineral physics experiments and geodynamical constraints on Earth’s thermal structure. We use this 3D Earth structure, which includes both variations in lithospheric thickness and lateral variations in viscosity, to calculate the first 3D GIA prediction for LIG sea level. We find that the difference between predictions with and without lateral Earth structure can be meters to 10s of meters in the near field of former ice sheets, and up to a few meters in their far field. We demonstrate how forebulge dynamics and continental levering are affected by laterally varying Earth structure, with a particular focus on those sites with prominent LIG sea level records. Results from three 3D GIA calculations show that accounting for lateral structure acts to increase local sea level by up to ~1.5m at the Seychelles and minimally decrease it in Western Australia. We acknowledge that this result is only based on a few simulations, but if robust, this shift brings estimates of global mean sea level from these two sites into closer agreement with each other. We further demonstrate that simulations with a suitable radial viscosity profile can be used to locally approximate the 3D GIA result, but that these radial profiles cannot be found by simply averaging viscosity below the sea level indicator site.

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