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.

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

Consolidating Sea Level Acceleration Estimates from Altimetry for the 1991-2019 Period

2020 ◽  
Author(s):  
Ole Baltazar Andersen ◽  
Tadea Veng
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Global Ocean ◽  
Sea Level Changes ◽  
Sea Level Acceleration ◽  
Spatial Coverage ◽  
Pinatubo Eruption ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Global Mean

<p>More than 28 years of high precision satellite altimetry enables analysis of recent global sea level changes. Several studies have determined the trend and acceleration of global mean sea level (GMSL). This is however done almost exclusively with data from the TOPEX/Poseidon, Jason-1, Jason-2 and Jason-3 satellites (TPJ data). In this study we extend the altimetry record in both time and space by including independent data from the ERS-1, ERS-2, Envisat and CryoSat-2 satellites (ESA data). This increases the time-series to span more than 28 years (1991.7-2020.0) and the spatial coverage is extended from ± 66⁰ to ± 82⁰ latitude. Another advantage of the ESA data is that it is independent of the Cal-1 mode issues which introduces a significant uncertainty to the first 6 years of data from the TOPEX altimeter. Resulting GMSL accelerations of 0.080 ± 0.008 mm/yr<sup>2</sup> (TPJ) and 0.095 ± 0.009 mm/yr<sup>2</sup> (ESA).The distribution of sea level acceleration across the global ocean are highly similar between the ESA and TPJ dataset. </p><p>The Pinatubo eruption in 1991 and El-Nino Southern Ocean Oscillation will both affect GMSL. Particularly so as Pinatubo erupted right before the launch of the first ERS-1 satellite. The decrease in GMSL during the first years is seen in the ERS-1 data. We conclude that the effect of the Pinatubo as well as the ENSO effect on GMSL acceleration estimates are below the noise level with the extended time series.</p><p> </p>

Regional Mean Sea Surface Model over the Eastern Mediterranean Sea

2020 ◽  
Author(s):  
Milaa Murshan ◽  
Balaji Devaraju ◽  
Nagarajan Balasubramanium ◽  
Onkar Dikshit
Keyword(s):  
Time Series ◽  
Mediterranean Sea ◽  
Sea Level ◽  
Tide Gauge ◽  
Eastern Mediterranean ◽  
Sea Surface ◽  
Surface Model ◽  
Eastern Mediterranean Sea ◽  
Mean Sea Level ◽  
Mean Sea Surface

<p>The Mean Sea Level is not an equipotential surface because it is subject to several variations, e.g., the tides, currents, winds, etc. Mean Sea Level can be measured either by tide gauges near to coastlines relative to local datum or by satellite altimeter above the reference ellipsoid. From this observable quantity, one can derive a non-observable quantity at which the potential is constant called geoid and differs from mean sea surface by amount of ±1 m. This separation is called Sea Surface Topography. In this research, the data of nine altimetric Exact Repeat Missions (Envisat, ERS_1 of 35 days (phase C and G), ERS_2, GFO, Jason_1, Jason_2, Jason_3, Topex/Poseidon and SARAL) were used for computing the regional mean sea surface model over the eastern Mediterranean Sea. The data of all missions together span approximately 25 years from September -1992 to January-2017 and referenced to Topex ellipsoid.  Which is later transformed to WGS84 ellipsoid, as it is chosen to be a unified datum in this study. Prior to computing the altimetric MSS,  altimetric sea surface height measurements were validated  by comparing  time series of altimetric-MSL with mean sea level time series calculated from three in-situ tide gauge measurements.  The sea surface heights values of the derived MSS model is between 15.6 and 26.7 m. And the linear trend slope is between -3.02 to 6.53 mm/year.</p><p>Keywords: Mean Sea Level, Satellite Altimetry, Tide Gauge, Exact Repeat Missions</p>

Global sea-level and ocean-mass budgets using advanced data products and uncertainty characterisation

2021 ◽  
Author(s):  
Martin Horwath ◽  
Anny Cazenave ◽  
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Sea Level Change ◽  
Mass Change ◽  
Level Change ◽  
Ocean Mass ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Global Mean

<p>Studies of the global sea-level budget (SLB) and ocean-mass budget (OMB) are essential to assess the reliability of our knowledge of sea-level change and its contributors. The SLB is considered closed if the observed sea-level change agrees with the sum of independently assessed steric and mass contributions. The OMB is considered closed if the observed ocean-mass change is compatible with the sum of assessed mass contributions. </p><p>Here we present results from the Sea-Level Budget Closure (SLBC_cci) project conducted in the framework of ESA’s Climate Change Initiative (CCI). We used data products from CCI projects as well as newly-developed products based on CCI products and on additional data sources. Our focus on products developed in the same framework allowed us to exercise a consistent uncertainty characterisation and its propagation to the budget closure analyses, where the SLB and the OMB are assessed simultaneously. </p><p>We present time series of global mean sea-level changes from satellite altimetry; new time series of the global mean steric component generated from Argo drifter data with incorporation of sea surface temperature data; time series of ocean-mass change derived from GRACE satellite gravimetry; time series of global glacier mass change from a global glacier model; time series of mass changes of the Greenland Ice Sheet and the Antarctic Ice Sheet both from satellite radar altimetry and from GRACE; as well as time series of land water storage change from the WaterGAP global hydrological model. Our budget analyses address the periods 1993–2016 (covered by the satellite altimetry records) and 2003–2016 (covered by GRACE and the Argo drifter system). In terms of the mean rates of change (linear trends), the SLB is closed within uncertainties for both periods, and the OMB, assessable for 2003–2016 only, is also closed within uncertainties. Uncertainties (1-sigma) arising from the combined uncertainties of the elements of the different budgets considered are between 0.26 mm/yr and 0.40 mm/yr, that is, on the order of 10% of the magnitude of global mean sea-level rise, which is 3.05 ± 0.24 mm/yr and 3.65 ± 0.26 mm/yr for 1993-2016 and 2003-2016, respectively. We also assessed the budgets on a monthly time series basis. The statistics of monthly misclosure agrees with the combined uncertainties of the budget elements, which amount to typically 2-3 mm for the 2003–2016 period. We discuss possible origins of the residual misclosure.</p>

scholarly journals On the “Cal-Mode” Correction to TOPEX Satellite Altimetry and Its Effect on the Global Mean Sea Level Time Series

2017 ◽  
Vol 122 (11) ◽  
pp. 8371-8384 ◽  
Author(s):  
B. D. Beckley ◽  
P. S. Callahan ◽  
D. W. Hancock ◽  
G. T. Mitchum ◽  
R. D. Ray
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Mean

scholarly journals The certitude of a global sea level acceleration during the satellite altimeter era

2020 ◽  
Vol 10 (1) ◽  
pp. 29-40
Author(s):  
H. Bâki İz ◽  
C.K. Shum
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Mean Sea Level ◽  
Sea Level Acceleration ◽  
Kinematic Models ◽  
Sea Level Variations ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Omission Errors ◽  
Global Mean

AbstractRecent studies reported a uniform global sea level acceleration during the satellite altimetry era (1993–2017) by analyzing globally averaged satellite altimetry measurements. Here, we discuss potential omission errors that were not thoroughly addressed in detecting and estimating the reported global sea level acceleration in these studies. Our analyses results demonstrate that the declared acceleration in recent studies can also be explained equally well by alternative kinematic models based on previously well-established multi-decadal global mean sea level variations of various origins, which suggests prudence before declaring the presence of an accelerating global mean sea level with confidence during the satellite altimetry era.

scholarly journals A statistical protocol for a holistic adjustment of global sea level budget

2020 ◽  
Vol 10 (1) ◽  
pp. 1-6
Author(s):  
H. Bâki Iz ◽  
C. K. Shum
Keyword(s):  
Sea Level ◽  
Science Studies ◽  
The Other ◽  
Error Statistics ◽  
Intergovernmental Panel ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Global Mean ◽  
Assessment Reports

AbstractCurrent studies in global mean sea level, GMSL, studies assess the closure/misclosure of the GMSL budget components and their uncertainties. Because Earth’s hydrosphere conserves water, a closed global mean sea level budget with a consistent set of estimates and their statistics is necessary. An unclosed budget means that there are problems to be addressed such as biases in the budget components, unreliable error statistics about the estimates, unknown or known but unmodeled budget components. In a misclosed global mean sea level budget, as practiced in recent studies, the trend estimates for the budget components and their errors account only for the anomalies of each budget component in isolation. On the other hand, the trend of each series must consider the trends of the other series in tandem such that the global mean sea level budget is closed for a holistic assessment, which can only be achieved by adjusting global mean sea level budget components simultaneously. In this study, we demonstrate a statistical protocol to ameliorate this deficiency, which potentially have implications for future sea level science studies, including the future Intergovernmental Panel on Climate Change (IPCC) Assessment Reports, and the US Climate Assessment Reports.

Correcting Late Cenozoic Sea-Level Records for Dynamic Topography: Examples from Australia

2021 ◽  
Author(s):  
Fred Richards ◽  
Sophie Coulson ◽  
Jacqueline Austermann ◽  
Mark Hoggard ◽  
Jerry Mitrovica
Keyword(s):  
Sea Level ◽  
Upper Mantle ◽  
Ice Sheets ◽  
Dynamic Topography ◽  
Sea Level Changes ◽  
Relative Sea Level ◽  
Mean Sea Level ◽  
Ice Volume ◽  
Global Mean Sea Level ◽  
Global Mean

<p>Much of our understanding of ice sheet sensitivity to climatic forcing is derived from palaeoshoreline records of past sea-level. However, the present-day elevations of these sea-level markers reflect the integrated effect of both ice volume change and solid Earth processes. Accurately quantifying the latter contribution is therefore essential for making reliable inferences of past ice volume. While uncertainties associated with glacial isostatic adjustment (GIA) can be mitigated by focusing on sites far from ice sheets, the same is not true for mantle flow-driven dynamic topography, which is ubiquitous and can generate vertical motions of ~±100 m on million-year timescales. As a result, improved knowledge of the spatio-temporal evolution of this transient topography is required to refine constraints on ice sheet stability and to guide modelling of future trajectories.</p><p>Since the shortest wavelength and fastest evolving contributions to dynamic topography originate in the shallow mantle, reconstructing dynamic topography over 1–10 Myr timescales requires accurate models of Earth’s lithosphere and asthenosphere. Here, we construct these models by mapping upper mantle shear wave velocities from high-resolution surface wave tomographic models into thermomechanical structure using calibrated parameterisations of anelasticity at seismic frequency. Resulting numerical predictions of present-day dynamic topography are in good agreement with residual depth measurements, with particularly good fits obtained around Australia. In this region, predicted temperatures are also compatible with palaeogeotherms extracted from xenolith suites, indicating that present-day upper mantle structure is well characterised and that numerical “retrodictions” of vertical motions are more likely to be reliable. In addition, Australia is sufficiently distant from major ice sheets that uncertainty in GIA contributions to sea-level change are relatively small. These considerations, combined with new compilations of continent-wide sea-level indicators, make Australia a particularly promising location for separating out ice volume-driven global mean sea-level changes from local sea-level variations related to vertical land motions and gravitational effects.</p><p>By back-advecting density perturbations from an ensemble of Earth models, we demonstrate that ~±200 m relative sea-level changes across Australia since the Mid-Pliocene Warm Period (MPWP; ∼3 Ma) can be tied directly to changes in dynamic topography. Significantly, after removing this signal from observed relative sea-level changes,  a consistent global mean sea-level during the MPWP of 12±8 m above present is obtained, towards the lower end of previous estimates.</p>

Global Mean Sea-level Changes in the Last Two Millennia

2021 ◽  
Author(s):  
Nidheesh Gangadharan ◽  
Hugues Goosse ◽  
David Parkes ◽  
Heiko Goelzer
Keyword(s):  
Thermal Expansion ◽  
Sea Level ◽  
Ice Sheets ◽  
Sea Level Changes ◽  
Contributing Factors ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
The Individual ◽  
Instrumental Records ◽  
Global Mean

<p>Instrumental records show that global mean sea level (GMSL) rose by approximately 15 cm in the 20<sup>th</sup> Century, with estimates of contributing factors suggesting the major components are ocean thermal expansion and melting of continental ice sheets and glaciers. However, little is known about the individual contributions to GMSL changes over the preindustrial common era (PCE) and the potential differences in the mechanisms controlling those changes between different time periods. Here, we describe the GMSL changes in the PCE by comparing proxy-based reconstructions with estimates derived from model experiments. The ocean thermal expansion is estimated on the basis of Coupled (Paleoclimate) Model Intercomparison Project (CMIP/PMIP) experiments. The contributions of ice sheets and glaciers are based on simulations with an ice-sheet model (IMAU-ICE) and a global glacier model (The Open Global Glacier Model), respectively. We also describe the thermal expansion response in the different ocean basins over the last millennium. The findings provide new insights on the current anthropogenic warming and sea-level rise in a wider context.</p>

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