Constraining Wind Stress Products with Sea Surface Height Observations and Implications for Pacific Ocean Sea Level Trend Attribution*

2012 ◽  
Vol 25 (23) ◽  
pp. 8164-8176 ◽  
Author(s):  
Shayne McGregor ◽  
Alexander Sen Gupta ◽  
Matthew H. England
Keyword(s):  
Sea Level ◽  
Wind Stress ◽  
Surface Wind ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Water Model ◽  
Mean Sea Level ◽  
Sea Level Trend ◽  
Global Mean Sea Level ◽  
Global Mean

Abstract A number of global surface wind datasets are available that are commonly used to examine climate variability or trends and as boundary conditions for ocean circulation models. However, discrepancies exist among these products. This study uses observed Archiving, Validation, and Interpretation of Satellite Oceanographic (AVISO) sea surface height anomalies (SSHAs) as a means to help constrain the fidelity of these products in the tropical region. Each wind stress product is used to force a linear shallow water model (SWM) and the resulting hindcast thermocline depth anomalies are converted to SSHAs. The resulting SSHAs are then assessed to see how well they reproduce the dominant EOF modes of observed variability and the regional (global mean removed) sea level trend (1993–2007) in each of the three ocean basins. While the results suggest that all wind datasets reproduce the observed interannual variability with reasonable fidelity, the two SWM hindcasts that produce the observed linear trend with the highest fidelity are those incorporating interim ECMWF Re-Analysis (ERA-Interim) and Wave- and Anemometer-Based Sea Surface Wind (WASWind) forcing. The role of surface wind forcing (i.e., upper ocean heat content redistribution) versus global mean sea level change (i.e., including the additional contributions of glacier and ice sheet melt along with ocean thermal expansion) on the recent dramatic increase in western equatorial Pacific island sea level is then reassessed. The results suggest that the recent sea level increase cannot be explained solely by wind stress forcing, regardless of the dataset used; rather, the global mean sea level signal is required to fully explain this observed recent abrupt sea level rise and to better explain the sea level variability of the last 50–60 years.

Assessment of the Jason-2 Extension to the TOPEX/Poseidon, Jason-1 Sea-Surface Height Time Series for Global Mean Sea Level Monitoring

2010 ◽  
Vol 33 (sup1) ◽  
pp. 447-471 ◽  
Author(s):  
B. D. Beckley ◽  
N. P. Zelensky ◽  
S. A. Holmes ◽  
F. G. Lemoine ◽  
R. D. Ray ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Mean ◽  
Level Monitoring

scholarly journals Sea State Bias Variability in Satellite Altimetry Data

2019 ◽  
Vol 11 (10) ◽  
pp. 1176
Author(s):  
Yongcun Cheng ◽  
Qing Xu ◽  
Le Gao ◽  
Xiaofeng Li ◽  
Bin Zou ◽  
...  
Keyword(s):  
Sea Level ◽  
Sea Level Change ◽  
Sea State ◽  
Mean Sea Level ◽  
Level Change ◽  
Sea State Bias ◽  
Regional Sea Level ◽  
Sea Level Trend ◽  
Global Mean Sea Level ◽  
Global Mean

Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability.

scholarly journals Kinematics of global mean thermosteric sea level during 1993–2019

2021 ◽  
Vol 11 (1) ◽  
pp. 75-82
Author(s):  
H. Bâki İz
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Temperature Gradients ◽  
Sea Surface ◽  
Sea Level Changes ◽  
Mean Sea Level ◽  
Mean Sea Surface ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Global Mean

Abstract Because oceans cover 71% of Earth’s surface, ocean warming, consequential for thermal expansion of sea water, has been the largest contributor to the global mean sea level rise averaged over the 20 th and the early 21 st century. This study first generates quasi-observed monthly globally averaged thermosteric sea level time series by removing the contributions of global mean sea level budget components, namely, Glaciers, Greenland, Antarctica, and Terrestrial Water Storage from satellite altimetry measured global sea level changes during 1993–2019. A baseline kinematic model with global mean thermosteric sea level trend and a uniform acceleration is solved to evaluate the performance of a rigorous mixed kinematic model. The model also includes coefficients of monthly lagged 60 yearlong cumulative global mean sea surface temperature gradients and control variables of lunisolar origins and representations for first order autoregressive disturbances. The mixed kinematic model explains 94% (Adjusted R 2)1 of the total variability in quasi-observed monthly and globally averaged thermosteric time series compared to the 46% of the baseline kinematic model’s Adjusted R 2. The estimated trend, 1.19±0.03 mm/yr., is attributed to the long-term ocean warming. Whereas eleven statistically significant (α = 0.05) monthly lagged cumulative global mean sea surface temperature gradients each having a memory of 60 years explain the remainder transient global mean thermosteric sea level changes due to the episodic ocean surface warming and cooling during this period. The series also exhibit signatures of a statistically significant contingent uniform global sea level acceleration and periodic lunisolar forcings.

Contributions of Wind Forcing and Surface Heating to Interannual Sea Level Variations in the Atlantic Ocean

2006 ◽  
Vol 36 (9) ◽  
pp. 1739-1750 ◽  
Author(s):  
Cécile Cabanes ◽  
Thierry Huck ◽  
Alain Colin de Verdière
Keyword(s):  
Atlantic Ocean ◽  
Sea Level ◽  
Wind Stress ◽  
Large Scale ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Altimeter Data ◽  
Local Response ◽  
Sea Level Variability ◽  
Sea Level Variations

Abstract Interannual sea surface height variations in the Atlantic Ocean are examined from 10 years of high-precision altimeter data in light of simple mechanisms that describe the ocean response to atmospheric forcing: 1) local steric changes due to surface buoyancy forcing and a local response to wind stress via Ekman pumping and 2) baroclinic and barotropic oceanic adjustment via propagating Rossby waves and quasi-steady Sverdrup balance, respectively. The relevance of these simple mechanisms in explaining interannual sea level variability in the whole Atlantic Ocean is investigated. It is shown that, in various regions, a large part of the interannual sea level variability is related to local response to heat flux changes (more than 50% in the eastern North Atlantic). Except in a few places, a local response to wind stress forcing is less successful in explaining sea surface height observations. In this case, it is necessary to consider large-scale oceanic adjustments: the first baroclinic mode forced by wind stress explains about 70% of interannual sea level variations in the latitude band 18°–20°N. A quasi-steady barotropic Sverdrup response is observed between 40° and 50°N.

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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