Assessing Global Ocean and Continental Mass Change from 17 years of GRACE/-FO: the role of coastal buffer zones

2020 ◽  
Author(s):  
Benjamin D. Gutknecht ◽  
Andreas Groh ◽  
Denise Cáceres ◽  
Martin Horwath
Keyword(s):  
Sea Level ◽  
Linear Trend ◽  
Mass Change ◽  
Global Ocean ◽  
Buffer Zones ◽  
Systematic Analysis ◽  
Ocean Mass ◽  
Phase Bias ◽  
Land Water

<p>Following the ESA CCI Sea Level Budget Closure (SLBC) project's work of 2017–2019, we present updated time-series of</p><ul><li>Global Ocean Mass Change (OMC) and</li> <li>Continental Mass Change (CMC),</li> </ul><p>both including continuous measurements by GRACE-FO. By least-squares adjusting a multi-parameter fit to monthly resolved OMC, we estimate the linear trend of Global Ocean mass change over all presently available GRACE/-FO months since April 2002 to be 2.41 ± 0.22 mm/a, with an acceleration of 0.10 mm a<sup>-</sup><sup>2</sup> over the same period.</p><p>A systematic analysis of the computed ocean response ("monthly fingerprints") to on-shore mass changes by means of solving the sea level equation implies that the common method of re-scaling the 'inner' buffered ocean may lead to OMC overestimations up to 10 per cent. We present this effect as a function of coastal buffer width for a global and for a 'truncated' global ocean (Lat ≤ ±65°), since the latter case, as seen e.g. in conjunction with radar altimetry, can lead to more than five per cent overestimated OMC. Furthermore, the use of coastal buffers seems to induce phase bias in the annual oscillation, which may explain the observed phase shift in the monthly budget between GRACE OMC and the sum of contributing continental components (i.e. ice sheets, glaciers, land water storage).</p><p>As a supplementary product of the SLBC project, we present GRACE/-FO derived mass change series 2002-04/present for continents (excluding Greenland and Antarctica). Consistent integration of out-leaking signal over coastal buffer zones, and subtraction of GAD-corrected mean OMC therein, leads to agreement with independently-assessed joint land water and glacier mass change data, well within uncertainty bounds.</p>

Interannual Variability in Global Ocean Mass Derived from 18+ Years of GRACE and GRACE-FO Satellite Gravimetry

2021 ◽  
Author(s):  
Benjamin D. Gutknecht ◽  
Andreas Groh ◽  
Martin Horwath
Keyword(s):  
Gravity Field ◽  
Sea Level ◽  
Linear Trend ◽  
Mass Change ◽  
Global Ocean ◽  
Mass System ◽  
Quasi Biennial Oscillation ◽  
Data Set ◽  
Ocean Mass ◽  
Major Mode

<p>The combined 18+ years long time series of observations of the Earth's gravity field from the satellite missions GRACE and GRACE-FO provides us with an unprecedented opportunity to analyse mass change and re-distribution in the Earth system. Furthermore, as the mission continues, we may also gain more insight into those types of variability in the water mass system that act over time scales of several years and possibly even decades.</p><p>For our analysis presented here, we updated the previous Ocean Mass Change (OMC) product by the ESA CCI Sea Level Budget Closure project, including (1) corrections for Glacial Isostatic Adjustment, (2) restorement of GAD background fields, (3) subtraction of atmospheric mean fields, and (4) replacement of dedicated low-degree coefficients for centre-of-mass, oblateness (TN14) and C30 (TN14) in the spherical harmonic gravity field solutions. We applied least-squares minimisation of the residual of a multi-parameter functional fit to the OMC series, including i.a. linear trend, semi-/annual signals, and an optional quadratic fit. We analysed the complete residual series based on the four monthly GRACE and GRACE-FO RL06 solutions from CSR/GFZ/JPL and ITSG-Grace2018 after removal of linear trend and seasonal cycles.</p><p>The remaining signal shows clear evidence of interannual oscillations and correlates (>0.5) with the Multivariate ENSO index (MEI). By spectral analysis and by an independent simulated-annealing approach, we locate several primary modes of the residual between 130 and 29 months. The phase of the lowest of these partial frequencies approximates that of solar flux data representing the solar cycle and the shortest major mode resembles the frequency of the Quasi Biennial Oscillation. However, minor phase-shifts and a direct physical link in this regard are not yet fully understood. When we include the extra modes in our OMC minimisation approach, it can be shown that recent acceleration in global ocean mass may indeed be smaller than previously anticipated by quadratic fitting while neglecting longer wavelengths.</p><p>Furthermore, the extrapolation of the fit including three prominent interannual modes between 29 and 130 months is able to predict recent La Niña related negative ocean mass anomalies. Our findings might support and integrate in similar analyses of the global sea level and other ECVs elsewhere. However, we must emphasise that an analysis of near-decadal oscillations from a sub-20 year lasting data set is yet to become more stable with increasing observation length from GRACE-FO.</p>

Sensitivity of Global Ocean Mass Calculations to Different Methods and Models

2020 ◽  
Author(s):  
Don Chambers ◽  
Jennifer Bonin ◽  
Mark Tamisiea
Keyword(s):  
Sea Level ◽  
Kernel Methods ◽  
Kernel Method ◽  
Linear Trend ◽  
Systematic Errors ◽  
Global Ocean ◽  
Hudson Bay ◽  
Direct Computation ◽  
Ocean Mass ◽  
Global Oceans

<p>Global ocean mass (or barystatic sea level) is an important component of the sea level budget. It can be computed directly from the GRACE and GRACE-FO data, or it can be computed by summing contributions from the cryosphere and hydrosphere. Here, we present a sensitivity analysis of the direct computation, using both averaging of mascon solutions as well as avering kernel methods applied to the spherical harmonics. We will discuss sensitivity to various geocenter models and GIA models, as well as discuss whether scaling is required for the averaging kernel method. For the scaling tests, we will utilize a simulation that includes trend fingerprints from icesheets and glaciers. We also discuss the effect of using different averaging areas (global oceans, global oceans excluding Hudson Bay, oceans with a 300km mask).</p> <p>We find consisent results between the spherical harmonic and mascon calculations within the estimated uncertainy of fits based on the residuals to the linear trend + annual sinuspid model. Trends will change by up to 0.2 mm/year if geocenter models based on GRACE and ocean moddel data are used, or up to 0.4 mm/year if SLR-based geocenter is used. Different versions of glacial isostatic models introduce trend differences of order 0.1-0.2 mm/year. These systematic errors should be considered in addition to uncertainty from least squares fits when assesing closure to the sea level budget.</p>

scholarly journals Reduced misclosure of global sea-level budget with updated Tongji-Grace2018 solution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fengwei Wang ◽  
Yunzhong Shen ◽  
Qiujie Chen ◽  
Yu Sun
Keyword(s):  
Sea Level ◽  
Spherical Harmonic ◽  
Mass Change ◽  
Global Ocean ◽  
Argo Data ◽  
Ocean Mass ◽  
Grace Data ◽  
Budget Equation ◽  
Global Sea Level ◽  
Gravity Recovery

AbstractThe global sea-level budget is studied using the Gravity Recovery and Climate Experiment (GRACE) solutions, Satellite Altimetry and Argo observations based on the updated budget equation. When the global ocean mass change is estimated with the updated Tongji-Grace2018 solution, the misclosure of the global sea-level budget can be reduced by 0.11–0.22 mm/year compared to four other recent solutions (i.e. CSR RL06, GFZ RL06, JPL RL06 and ITSG-Grace2018) over the period January 2005 to December 2016. When the same missing months as the GRACE solution are deleted from altimetry and Argo data, the misclosure will be reduced by 0.06 mm/year. Once retained the GRACE C20 term, the linear trends of Tongji-Grace2018 and ITSG-Grace2018 solutions are 2.60 ± 0.16 and 2.54 ± 0.16 mm/year, closer to 2.60 ± 0.14 mm/year from Altimetry–Argo than the three RL06 official solutions. Therefore, the Tongji-Grace2018 solution can reduce the misclosure between altimetry, Argo and GRACE data, regardless of whether the C20 term is replaced or not, since the low-degree spherical harmonic coefficients of the Tongji-Grace2018 solution can capture more ocean signals, which are confirmed by the statistical results of the time series of global mean ocean mass change derived from five GRACE solutions with the spherical harmonic coefficients truncated to different degrees and orders.

scholarly journals The Balance and Abnormal Increase of Global Ocean Mass Change From Land Using GRACE

2020 ◽  
Vol 7 (5) ◽  
Author(s):  
Taoyong Jin ◽  
Xiaolong Li ◽  
C. K. Shum ◽  
Hao Ding ◽  
Xinyu Xu
Keyword(s):  
Mass Change ◽  
Global Ocean ◽  
Ocean Mass ◽  
Abnormal Increase ◽  
Land Using

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 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.

Impact of Low-Degree Stokes Coefficients and Spatial Leakage on Barystatic Sea-Level Rise from GRACE/GRACE-FO

2021 ◽  
Author(s):  
Maik Thomas ◽  
Henryk Dobslaw ◽  
Meike Bagge ◽  
Robert Dill ◽  
Volker Klemann ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Temporal Variations ◽  
Ocean Bottom ◽  
Spatial Integration ◽  
Buffer Zones ◽  
Ocean Mass ◽  
Low Degree ◽  
Gravity Fields ◽  
The Impact

<p>Temporal variations in the total ocean mass representing the barystatic part of present-day global-mean sea-level rise can be directly inferred from time-series of global gravity fields as provided by the GRACE and GRACE-FO missions. A spatial integration over all ocean regions, however, largely underestimates present-day rates as long as the effects of spatial leakage along the coasts of in particular Antarctica, Greenland, and the various islands of the Canadian Archipelago are not properly considered.</p><p>Based on the latest release 06 of monthly gravity fields processed at GFZ, we quantify (and subsequently correct) the contribution of spatial leakage to the post-processed mass anomalies of continental water storage and ocean bottom pressure. We find that by utilizing the sea level equation to predict spatially variable ocean mass trends out of the (leakage-corrected) terrrestial mass distributions from GRACE and GRACE-FO consistent results are obtained also from spatial integrations over ocean masks with different coastal buffer zones ranging from 400 to 1000 km. However, the results are critically dependent on coefficients of degree 1, 2 and 3, that are not precisely determined from GRACE data alone and need to be augemented by information from satellite laser ranging. We will particularly discuss the impact of those low-degree harmonics on the secular rates in global barystatic sea-level.</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>

Global Ocean Mass Change From GRACE and GRACE Follow‐On and Altimeter and Argo Measurements

2020 ◽  
Vol 47 (22) ◽  
Author(s):  
Jianli Chen ◽  
Byron Tapley ◽  
Clark Wilson ◽  
Anny Cazenave ◽  
Ki‐Weon Seo ◽  
...  
Keyword(s):  
Mass Change ◽  
Global Ocean ◽  
Ocean Mass

scholarly journals Assessing global water mass transfers from continents to oceans over the period 1948–2016

2020 ◽  
Vol 24 (10) ◽  
pp. 4831-4851
Author(s):  
Denise Cáceres ◽  
Ben Marzeion ◽  
Jan Hendrik Malles ◽  
Benjamin Daniel Gutknecht ◽  
Hannes Müller Schmied ◽  
...  
Keyword(s):  
Mass Loss ◽  
Sea Level ◽  
Water Use ◽  
Irrigation Water ◽  
Linear Trend ◽  
Water Storage ◽  
Ocean Mass ◽  
Irrigation Water Use ◽  
Highly Sensitive ◽  
Artificial Reservoirs

Abstract. Ocean mass and thus sea level is significantly affected by water storage on the continents. However, assessing the net contribution of continental water storage change to ocean mass change remains a challenge. We present an integrated version of the WaterGAP global hydrological model that is able to consistently simulate total water storage anomalies (TWSAs) over the global continental area (except Greenland and Antarctica) by integrating the output from the global glacier model of Marzeion et al. (2012) as an input to WaterGAP. Monthly time series of global mean TWSAs obtained with an ensemble of four variants of the integrated model, corresponding to different precipitation input and irrigation water use assumptions, were validated against an ensemble of four TWSA solutions based on the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry from January 2003 to August 2016. With a mean Nash–Sutcliffe efficiency (NSE) of 0.87, simulated TWSAs fit well to observations. By decomposing the original TWSA signal into its seasonal, linear trend and interannual components, we found that seasonal and interannual variability are almost exclusively caused by the glacier-free land water storage anomalies (LWSAs). Seasonal amplitude and phase are very well reproduced (NSE=0.88). The linear trend is overestimated by 30 %–50 % (NSE=0.65), and interannual variability is captured to a certain extent (NSE=0.57) by the integrated model. During the period 1948–2016, we find that continents lost 34–41 mm of sea level equivalent (SLE) to the oceans, with global glacier mass loss accounting for 81 % of the cumulated mass loss and LWSAs accounting for the remaining 19 %. Over 1948–2016, the mass gain on land from the impoundment of water in artificial reservoirs, equivalent to 8 mm SLE, was offset by the mass loss from water abstractions, amounting to 15–21 mm SLE and reflecting a cumulated groundwater depletion of 13–19 mm SLE. Climate-driven LWSAs are highly sensitive to precipitation input and correlate with El Niño Southern Oscillation multi-year modulations. Significant uncertainty remains in the trends of modelled LWSAs, which are highly sensitive to the simulation of irrigation water use and artificial reservoirs.

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