scholarly journals Global sea level change signatures observed by GRACE satellite gravimetry

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Taehwan Jeon ◽  
Ki-Weon Seo ◽  
Kookhyoun Youm ◽  
Jianli Chen ◽  
Clark R. Wilson
The Holocene ◽  
2016 ◽  
Vol 27 (1) ◽  
pp. 164-171 ◽  
Author(s):  
Tron Laumann ◽  
Atle Nesje

Over the recent decades, glaciers have in general continued to lose mass, causing surface lowering, volume reduction and frontal retreat, thus contributing to global sea-level rise. When making assessments of present and future sea-level change and management of water resources in glaciated catchments, precise estimates of glacier volume are important. The glacier volume cannot be measured on every single glacier. Therefore, the global glacier volume must be estimated from models or scaling approaches. Volume–area scaling is mostly applied for estimating volumes of glaciers and ice caps on a regional and global scale by using a statistical–theoretical relationship between glacier volume ( V) and area ( A) ( V =  cAγ) (for explanation of the parameters c and γ, see Eq. 1). In this paper, a two-dimensional (2D) glacier model has been applied on four Norwegian ice caps (Hardangerjøkulen, Nordre Folgefonna, Spørteggbreen and Vestre Svartisen) in order to obtain values for the volume–area relationship on ice caps. The curve obtained for valley glaciers gives the best fit to the smallest plateau glaciers when c = 0.027 km3−2 γ and γ = 1.375, and a slightly poorer fit when the glacier increases in size. For ice caps, c = 0.056 km3−2 γ and γ = 1.25 fit reasonably well for the largest, but yield less fit to the smaller.


2020 ◽  
Vol 11 (4) ◽  
pp. 953-976
Author(s):  
Jonas Van Breedam ◽  
Heiko Goelzer ◽  
Philippe Huybrechts

Abstract. The emphasis for informing policy makers on future sea-level rise has been on projections by the end of the 21st century. However, due to the long lifetime of atmospheric CO2, the thermal inertia of the climate system and the slow equilibration of the ice sheets, global sea level will continue to rise on a multi-millennial timescale even when anthropogenic CO2 emissions cease completely during the coming decades to centuries. Here we present global sea-level change projections due to the melting of land ice combined with steric sea effects during the next 10 000 years calculated in a fully interactive way with the Earth system model of intermediate complexity LOVECLIMv1.3. The greenhouse forcing is based on the Extended Concentration Pathways defined until 2300 CE with no carbon dioxide emissions thereafter, equivalent to a cumulative CO2 release of between 460 and 5300 GtC. We performed one additional experiment for the highest-forcing scenario with the inclusion of a methane emission feedback where methane is slowly released due to a strong increase in surface and oceanic temperatures. After 10 000 years, the sea-level change rate drops below 0.05 m per century and a semi-equilibrated state is reached. The Greenland ice sheet is found to nearly disappear for all forcing scenarios. The Antarctic ice sheet contributes only about 1.6 m to sea level for the lowest forcing scenario with a limited retreat of the grounding line in West Antarctica. For the higher-forcing scenarios, the marine basins of the East Antarctic Ice Sheet also become ice free, resulting in a sea-level rise of up to 27 m. The global mean sea-level change after 10 000 years ranges from 9.2 to more than 37 m. For the highest-forcing scenario, the model uncertainty does not exclude the complete melting of the Antarctic ice sheet during the next 10 000 years.


2021 ◽  
Author(s):  
Martin Horwath ◽  
Anny Cazenave ◽  

<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>


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