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.

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

Effect of the processing methodology on satellite altimetry-based global mean sea level rise over the Jason-1 operating period

2013 ◽  
Vol 88 (4) ◽  
pp. 351-361 ◽  
Author(s):  
Olivier Henry ◽  
Michael Ablain ◽  
Benoit Meyssignac ◽  
Anny Cazenave ◽  
Dallas Masters ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Operating Period ◽  
Mean Sea Level ◽  
Global Mean Sea Level ◽  
Global Mean

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 Sea level accelerations at globally distributed tide gauge stations during the satellite altimetry era

2018 ◽  
Vol 8 (1) ◽  
pp. 130-135 ◽  
Author(s):  
H. Bâki Iz ◽  
C. K. Shum ◽  
C. Y. Kuo
Keyword(s):  
Sea Level ◽  
Satellite Altimetry ◽  
Tide Gauge ◽  
Tide Gauge Data ◽  
Trend Model ◽  
Gauge Data ◽  
Sea Level Variations ◽  
Global Mean Sea Level ◽  
Globally Distributed ◽  
Global Mean

Abstract This observational study reports that several globally distributed tide gauge stations exhibit a propensity of statistically significant sea level accelerations during the satellite altimetry era. However, the magnitudes of the estimated tide gauge accelerations during this period are systematically and noticeably smaller than the global mean sea level acceleration reported by recent analyses of satellite altimetry. The differences are likely to be caused by the interannual, decadal and interdecadal sea level variations, which are modeled using a broken trend model with overlapping harmonics in the analyses of tide gauge data but omitted in the analysis of satellite altimetry.

scholarly journals Recent and future manifestations of a contingent global mean sea level acceleration

2020 ◽  
Vol 10 (1) ◽  
pp. 153-162
Author(s):  
H. Bâki İz ◽  
C.K. Shum
Keyword(s):  
Sea Level ◽  
Kinematic Model ◽  
Autoregressive Process ◽  
Random Errors ◽  
Mean Sea Level ◽  
Uniform Acceleration ◽  
Sea Level Acceleration ◽  
Sea Level Anomalies ◽  
Global Mean Sea Level ◽  
Global Mean

Abstract We analyzed globally averaged satellite altimetry mean sea level time series during 1993 – 2018 and their future manifestations for the following 25 years using a kinematic model, which consists of a trend, a contingent uniform acceleration, and a random error model. The analysis of variance results shows that the model explains 71.7% of the total variation in global mean sea level for which 70.6% is by the secular trend, and 1.07% is due to a contingent uniform acceleration. The remaining 28.3% unexplained variation is due to the random errors, which are dominated by a first order autoregressive process driven mostly by oceanic and atmospheric variations over time. These numbers indicate more bumps and jumps for the future manifestations of the global mean sea level anomalies as illustrated using a one-step ahead predictor in this study. Our findings suggest preponderant random errors are poised to further confound and negatively impact the certitude of published estimates of the uniform global sea level acceleration as well as its prediction under an increasingly warmer Earth.

scholarly journals Year by year closure adjustment of global mean sea level budget, inclusive of lumped snow, water vapor, and permafrost mass components

2020 ◽  
Vol 10 (1) ◽  
pp. 83-90
Author(s):  
H. Bâki Iz ◽  
C. K. Shum
Keyword(s):  
Water Vapor ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Linear Trend ◽  
The Other ◽  
Mean Sea Level ◽  
Lump Sum ◽  
Snow Water ◽  
Global Mean Sea Level ◽  
Global Mean

AbstractGlobal mean sea level budget is rigorously adjusted during the period 2005–2015 with an emphasis on closing the budget on a year by year basis as opposed to using linear trends of global mean sea level components. The adjustment also accounts for the effect of snow, water vapor, and permafrost mass components as a lump sum. The approach provides better resolution for evaluating individual contribution of each budget component year by year in tandem with the other components. Year by year budget misclosures and the confidence intervals of the year by year adjusted budget components are suggestive of an increasing non-linearity in satellite altimetry derived global mean sea level measurements starting in 2012, which are not present in the other components. The solution also generates time series iteratively for the lumped snow, water vapor, and permafrost mass components as well as an estimate for its linear trend, 0.06±0.59 mm/yr. Nonetheless, its standard error is markedly large because of the un-modeled variability in satellite altimetry observed yearly averaged global mean sea level anomalies.

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.

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>

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