Characterisation of the chaotic variability of the regional sea level and its components over 1993-2015 at interannual time scales

2021 ◽  
Author(s):  
Alice Carret ◽  
William Llovel ◽  
Thierry Penduff ◽  
Jean-Marc Molines
Keyword(s):  
Interannual Variability ◽  
Sea Level ◽  
Global Ocean ◽  
Atmospheric Forcing ◽  
Sea Level Changes ◽  
Ensemble Simulation ◽  
Ocean Variability ◽  
Ocean Area ◽  
Regional Sea Level ◽  
Global Mean Sea Level

<p>Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level trend variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability that spontaneously emerges from the ocean may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims at complementing this work by first focusing on the atmospherically-forced and chaotic contributions of regional sea level interannual variability and its components (steric and manometric sea level interannual variability). A global ¼° ocean/sea-ice 50-member ensemble simulation is considered to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability over 1993-2015. The atmospherically-forced and chaotic interannual variabilities of sea level mainly have a steric origin , except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic oceans than in the Indian ocean. The chaotic part of the interannual variability of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. As the chaotic part of the regional sea level interannual variability has a substantial imprint, this study then interested in quantifying the periods when it becomes dominant over the atmospherically-forced contribution. This is assessed using spectral analysis on the ensemble simulation in the frequency domain for the sea level and its steric and manometric components over the global ocean as well as in some basins of interest. This enables us to better characterise and quantify the chaotic ocean variability contribution to regional sea level changes and its components.</p>

Forced and chaotic variability of interannual variability of regional sea level and its causes scale over 1993-2015

2020 ◽  
Author(s):  
Alice Carret ◽  
William Llovel ◽  
Thierry Penduff ◽  
Jean-Marc Molines ◽  
Benoît Meyssignac
Keyword(s):  
Interannual Variability ◽  
Sea Level ◽  
Satellite Altimetry ◽  
Global Ocean ◽  
Western Boundary ◽  
Western Boundary Currents ◽  
Steric Sea Level ◽  
Boundary Currents ◽  
Ocean Variability ◽  
Regional Sea Level

<p>Since the early 1990s, satellite altimetry has become the main observing system for continuously measuring the sea level variations with a near global coverage. Satellite altimetry has revealed a global mean sea level rise of 3.3 mm/yr since 1993 with large regional sea level variability that differs from the mean estimate. These measurements highlight complex structures especially for the western boundary currents or the Antarctic Circumpolar Current. A recent study shows that the chaotic ocean variability may mask atmospherically-forced regional sea level trends over 38% of the global ocean area from 1993 to 2015. The chaotic variability is large for the western boundary currents and in the Southern Ocean. The present study aims to complement this previous work in focusing on the interannual variability of regional sea level. A global ¼° ocean/sea-ice 50-member ensemble simulation is considered to disentangle the imprints of the atmospheric forcing and the chaotic ocean variability on the interannual variability of regional sea level over 1993-2015. We investigate the forced (i.e., ensemble mean) versus the chaotic variability (i.e., ensemble standard deviation) for the interannual variability of regional sea level and its causes (i.e., steric sea level and manometric sea level contribution). We complement our investigations by partitioning the steric component into thermosteric sea level (i.e., temperature change only) and halosteric sea level (i.e., salinity change only). One of the goals of the study is to highlight the hot spots region of large chaotic variability for regional sea level and its different components.</p>

scholarly journals Contributions of Atmospheric Forcing and Chaotic Ocean Variability to Regional Sea Level Trends Over 1993–2015

2018 ◽  
Vol 45 (24) ◽  
Author(s):  
William Llovel ◽  
Thierry Penduff ◽  
Benoit Meyssignac ◽  
Jean‐Marc Molines ◽  
Laurent Terray ◽  
...  
Keyword(s):  
Sea Level ◽  
Atmospheric Forcing ◽  
Ocean Variability ◽  
Regional Sea Level

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 Ocean mass, sterodynamic effects, and vertical land motion largely explain US coast relative sea level rise

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
T. C. Harvey ◽  
B. D. Hamlington ◽  
T. Frederikse ◽  
R. S. Nerem ◽  
C. G. Piecuch ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Tide Gauge ◽  
Sea Level Changes ◽  
Relative Sea Level ◽  
Vertical Land Motion ◽  
Ocean Mass ◽  
Coastal Sea ◽  
Regional Sea Level ◽  
Global Mean Sea Level

AbstractRegional sea-level changes are caused by several physical processes that vary both in space and time. As a result of these processes, large regional departures from the long-term rate of global mean sea-level rise can occur. Identifying and understanding these processes at particular locations is the first step toward generating reliable projections and assisting in improved decision making. Here we quantify to what degree contemporary ocean mass change, sterodynamic effects, and vertical land motion influence sea-level rise observed by tide-gauge locations around the contiguous U.S. from 1993 to 2018. We are able to explain tide gauge-observed relative sea-level trends at 47 of 55 sampled locations. Locations where we cannot explain observed trends are potentially indicative of shortcomings in our coastal sea-level observational network or estimates of uncertainty.

Causes for Contemporary Regional Sea Level Changes

2013 ◽  
Vol 5 (1) ◽  
pp. 21-46 ◽  
Author(s):  
Detlef Stammer ◽  
Anny Cazenave ◽  
Rui M. Ponte ◽  
Mark E. Tamisiea
Keyword(s):  
Sea Level ◽  
Sea Level Changes ◽  
Regional Sea Level

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>

How Salty Is the Global Ocean: Weighting It All or Tasting It a Sip at a Time?

2020 ◽  
Author(s):  
Rui Ponte ◽  
Qiang Sun ◽  
Chao Liu ◽  
Xinfeng Liang
Keyword(s):  
Sea Ice ◽  
Sea Level ◽  
Hydrological Cycle ◽  
Global Ocean ◽  
Data Quality Control ◽  
Argo Data ◽  
Terrestrial Water ◽  
Control Procedures ◽  
Global Mean Sea Level

<div class="page" title="Page 1"> <div class="section"> <div class="layoutArea"> <div class="column"> <p>Global ocean mean salinity <em>S </em>is a key indicator of the Earth's hydrological cycle and the exchanges of freshwater between the terrestrial water and ice reservoirs and the ocean. We explore two different ways of determining how salty the ocean is: (1) use in situ salinity measurements to taste the ocean a sip at a time and obtain a sample average; (2) use space gravimetry to weigh the whole ocean including sea-ice, and then separate sea-ice effects to infer changes in liquid freshwater content and thus <em>S</em>. Focusing on the 2005-2019 period, we assess monthly series of <em>S </em>derived from five different in situ gridded products, based mostly but not exclusively on Argo data, versus a series obtained from GRACE and GRACE Follow-On data and available sea ice mass estimates.</p> <p>There is little consistency in <em>S </em>series from the two methods for all time scales examined (seasonal, interannual, long-term trend). In situ series show larger variability, particularly at the longest scales, and are somewhat incoherent with the GRACE-derived series. In addition, there are wide spread differences among all the in situ <em>S </em>series, which denote their considerable sensitivity to choice of data, quality control procedures, and mapping methods. Results also suggest that in situ <em>S </em>values are prone to systematic biases, with most series showing increases after around 2014 that are equivalent to a drop in barystatic sea level of tens of centimeters! Estimates derived from GRACE are much smaller in magnitude and consistent with contributions of freshwater to the global mean sea level budgets, and they are thus more reliable than in situ-based <em>S </em>estimates. The existence of GRACE-derived estimates can serve as a consistency check on in situ measurements, revealing potential unknown biases and providing a way to cross-calibrate the latter data.</p> </div> </div> </div> </div>

scholarly journals Low-Frequency Sea Level Variability and the Inverted Barometer Effect

2006 ◽  
Vol 23 (4) ◽  
pp. 619-629 ◽  
Author(s):  
Rui M. Ponte
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Low Frequency ◽  
Anomalous Behavior ◽  
Global Ocean ◽  
Sea Level Pressure ◽  
Seasonal Signals ◽  
Global Mean Sea Level ◽  
Inverted Barometer ◽  
Linear Trends

Abstract For a dynamical interpretation of sea level records, estimates are needed of the isostatic, or so-called inverted barometer, signals (ηib) associated with the ocean response to atmospheric loading. Seasonal and longer-period ηib signals are evaluated over the global ocean for the period 1958–2000 using monthly sea level pressure fields from two different atmospheric reanalyses. Variability and linear trends in ηib agree well for the two reanalyses in most regions but less so over the Southern Ocean, where uncertainties in ηib seem to be largest. The standard deviation of ηib ranges from <1 cm in equatorial regions to >7 cm in the regions of the Aleutian and Iceland lows and parts of the Southern and Arctic Oceans. When compared to a global tide gauge dataset, both seasonal and interannual ηib signals are found to contribute importantly to the sea level variance in many mid- and high-latitude records, with seasonal signals important as well in tropical records from India and Southeast Asia. For these records, subtracting ηib from the data can lead to changes in variance of 40% or more. Over the period of study, linear trends in ηib are mostly negative at low and midlatitudes and can cause negative biases in tide gauge estimates of global mean sea level rise that are comparable in magnitude to the effects of postglacial rebound. In agreement with previous findings, ηib signals are found to introduce anomalous behavior in local records (e.g., substantially weaker upward trends in the Mediterranean), and their removal can also reduce formal trend uncertainties. Accounting for ηib effects can be even more important when analyzing relatively short (decadal) records, such as those available from satellite altimetry.

scholarly journals Greenland uplift and regional sea level changes from ICESat observations and GIA modelling

2012 ◽  
Vol 189 (3) ◽  
pp. 1457-1474 ◽  
Author(s):  
G. Spada ◽  
G. Ruggieri ◽  
L. S. Sørensen ◽  
K. Nielsen ◽  
D. Melini ◽  
...  
Keyword(s):  
Sea Level ◽  
Sea Level Changes ◽  
Regional Sea Level
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