simultaneous solution for mass trends on the west antarctic ice sheet
Clicks: 4
ID: 214588
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
0.9
/100
4 views
3 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #131 of 134 articles by views in journal of applied polymer science
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 134 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The Antarctic Ice Sheet is the largest potential source of future sea-level
rise. Mass loss has been increasing over the last 2 decades for the West
Antarctic Ice Sheet (WAIS) but with significant discrepancies between
estimates, especially for the Antarctic Peninsula. Most of these estimates
utilise geophysical models to explicitly correct the observations for
(unobserved) processes. Systematic errors in these models introduce biases in
the results which are difficult to quantify. In this study, we provide a
statistically rigorous error-bounded trend estimate of ice mass loss over the
WAIS from 2003 to 2009 which is almost entirely data driven. Using altimetry,
gravimetry, and GPS data in a hierarchical Bayesian framework, we derive
spatial fields for ice mass change, surface mass balance, and glacial
isostatic adjustment (GIA) without relying explicitly on forward models. The
approach we use separates mass and height change contributions from different
processes, reproducing spatial features found in, for example, regional
climate and GIA forward models, and provides an independent estimate which
can be used to validate and test the models. In addition, spatial error
estimates are derived for each field. The mass loss estimates we obtain are
smaller than some recent results, with a time-averaged mean rate of
−76 ± 15 Gt yr−1 for the WAIS and Antarctic Peninsula,
including the major Antarctic islands. The GIA estimate compares well with
results obtained from recent forward models (IJ05-R2) and inverse methods
(AGE-1). The Bayesian framework is sufficiently flexible that it can,
eventually, be used for the whole of Antarctica, be adapted for other ice
sheets and utilise data from other sources such as ice cores, accumulation
radar data, and other measurements that contain information about any of the
processes that are solved for.
| Reference Key |
schoen2015thesimultaneous
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;N. Schoen;A. Zammit-Mangion;J. C. Rougier;T. Flament;F. Rémy;S. Luthcke;J. L. Bamber |
| Journal | journal of applied polymer science |
| Year | 2015 |
| DOI |
10.5194/tc-9-805-2015
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.