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>

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.

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 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.

Data products from the ESA CCI Sea Level Budget Closure project

2020 ◽  
Author(s):  
Martin Horwath ◽  
Keyword(s):  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Sea Level Changes ◽  
Ocean Mass ◽  
Data Products ◽  
Global Mean Sea Level ◽  
The Individual ◽  
Land Water ◽  
Global Mean

<p>Studies of the sea-level budget are a means of assessing our ability to quantify and understand sea-level changes and their causes. ESA's Climate Change Initiative (CCI) projects include Sea Level CCI, Greenland Ice Sheet CCI, Antarctic Ice Sheet CCI, Glaciers CCI and the Sea Surface Temperature CCI, all addressing Essential Climate Variables (ECVs) related to sea level. The cross-ECV project CCI Sea Level Budget Closure used different products for the sea level and its components, based on the above CCI projects in conjunction with in situ data for ocean thermal expansion (e.g., Argo), GRACE-based assessments of ocean mass change, land water and land ice mass change, and model-based data for glaciers and land hydrology. The involvement of the authors of the individual data products facilitated consistency and enabled a unified treatment of uncertainties and their propagation to the overall budget closure. </p><p>After conclusion of the project, the developed data products are now available for science users and the public. This poster summarizes the project results with a focus on presenting these data products. They include time series (for the periods 1993-2016 and 2003-2016) of global mean sea level changes and global mean sea level contributions from the steric component, from the ocean mass component and from the individual mass contributions by glaciers, the Greenland Ice Sheet, the Antarctic Ice Sheet and changes in land water storage. They are designed and documented in the consistent framework of ESA SLBC_cci and include uncertainty measures per datum. Additional more comprehensive information, such as geographic grids underlying the global means, are available for some components.</p><p>For the long-term trend, the budget is closed within uncertainties on the order of 0.3 mm/yr (1 sigma). Moreover, the budget is also closed within uncertainties for interannual variations.</p>

scholarly journals Monthly Crustal Loading Corrections for Satellite Altimetry

2013 ◽  
Vol 30 (5) ◽  
pp. 999-1005 ◽  
Author(s):  
R. D. Ray ◽  
S. B. Luthcke ◽  
T. van Dam
Keyword(s):  
Sea Level ◽  
Vertical Motion ◽  
Altimeter Data ◽  
Small Contribution ◽  
Satellite Altimeter ◽  
Significant Correction ◽  
Global Mean Sea Level ◽  
Global Sea Level ◽  
Gravity Recovery ◽  
Global Mean

Abstract Satellite altimeter measurements of sea surface height include a small contribution from vertical motion of the seafloor caused by crustal loading. Loading by ocean tides is routinely allowed for in altimeter data processing. Here, loading by nontidal fluids of the atmosphere, ocean, and terrestrial hydrosphere is examined. The crustal deformation can be computed from either geophysical models or from Gravity Recovery and Climate Experiment (GRACE) gravity inversions of mass variability. The loading corrections are found to be very small, rarely exceeding a few millimeters. Nonetheless, they form a significant correction to altimetric determinations of global mean sea level. The correction is most important at the annual cycle and should be accounted for when attempting to balance the global sea level budget.

scholarly journals Global ocean freshening, ocean mass increase and global mean sea level rise over 2005–2015

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
William Llovel ◽  
S. Purkey ◽  
B. Meyssignac ◽  
A. Blazquez ◽  
N. Kolodziejczyk ◽  
...  
Keyword(s):  
Sea Level ◽  
Global Ocean ◽  
Last Deglaciation ◽  
Mean Sea Level ◽  
Isostatic Adjustment ◽  
Ocean Mass ◽  
Grace Data ◽  
Global Mean Sea Level ◽  
Gravity Recovery ◽  
Global Mean

AbstractGlobal mean sea level has experienced an unabated rise over the 20th century. This observed rise is due to both ocean warming and increasing continental freshwater discharge. We estimate the net ocean mass contribution to sea level by assessing the global ocean salt budget based on the unprecedented amount of in situ data over 2005–2015. We obtain the ocean mass trends of 1.30 ± 1.13 mm · yr−1 (0–2000 m) and 1.55 ± 1.20 mm · yr−1 (full depth). These new ocean mass trends are smaller by 0.63–0.88 mm · yr−1 compared to the ocean mass trend estimated through the sea level budget approach. Our result provides an independent validation of Gravity Recovery And Climate Experiment (GRACE)-based ocean mass trend and, in addition, places an independent constraint on the combined Glacial Isostatic Adjustment – the Earth’s delayed viscoelastic response to the redistribution of mass that accompanied the last deglaciation- and geocenter variations needed to directly infer the ocean mass trend based on GRACE data.

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

Closing the global and regional sea level budgets by combining multi-mission altimetry and GRACE(-FO) data

2020 ◽  
Author(s):  
Bernd Uebbing ◽  
Christina Lück ◽  
Roelof Rietbroek ◽  
Kristin Vielberg ◽  
Jürgen Kusche
Keyword(s):  
Time Series ◽  
Sea Level ◽  
Sea Level Change ◽  
Inversion Method ◽  
Data Sets ◽  
Sea Level Changes ◽  
Steric Sea Level ◽  
Level Change ◽  
Spatial Coverage ◽  
Regional Sea Level

<p>Understanding present day sea level changes and their drivers requires the separation of the total sea level change into individual mass and steric related contributions. Total sea level rise has been observed continuously since 1993 providing a more than 25 year long time series of global and regional sea level variations. However, direct monitoring of ocean mass change has only been done since the start of the Gravity Recovery And Climate Experiment (GRACE) mission in 2002. It ended in 2017 and was succeeded by the follow-on mission (GRACE-FO) in 2018 leaving a gap of about 1 year. In the same time period of GRACE, since the early 2000s, a global array of freely drifting Argo floats samples temperature and salinity profiles of up to 2000m depth which can be converted to steric sea level change.</p><p>By combining altimetry, GRACE(-FO) and Argo data sets it is possible to derive global and regional sea level budgets. The conventional approach is to analyze at least two of the data sets and derive the residual, or compare with the third one. A more recent approach is the global joint inversion method (Rietbroek et al., 2016) which fits forward-modeled spatial fingerprints to a combination of GRACE gravity data and Jason-1/-2 satellite altimetry data. This enables us, additionally, to separate altimetric sea level change into mass contributions from terrestrial hydrology, the melting of land glaciers and the ice-sheets in Greenland and Antarctica as well as contributions from steric sea level changes due to variations in ocean temperature and salinity. It also allows to include a data weighting scheme in the analysis.</p><p>Here, we present global and regional sea level budget results from an updated inversion based on multi-mission altimetry (Jason-1/-2/-3, Envisat, Cryosat-2, Sentinel-3, …) providing better spatial coverage as well as new RL06 GRACE and GRACE-FO data which enables us to extend the time series of individual components of the sea level budget beyond the GRACE era from 2002-04 till 2019-06. The presented sea level budget is closed on global scale with a residual (unexplained) contribution of about 0.1 mm/yr, globally, originating in eddy-active regions. We provide consistent validation of our results against conventionally analyzed altimetry and GRACE data sets where we find agreement on global scales to be better than 0.1 mm/yr but a larger disagreement at regional scales as well as the implications of our results for deriving ocean heat content. We will also provide first results for filling the gap in the sea level budget estimates due to the gap between the GRACE and GRACE-FO missions by additionally incorporating time-variable gravity information from the Swarm mission as well as from Satellite Laser Ranging (SLR) to 5 satellites (Lageos-1/-2, Stella, Starlette, Ajisai).</p>

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 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.

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