A new 200‐year spatial reconstruction of West Antarctic surface mass balance
Wang, Yetang; Huai, Baojuan; Thomas, Elizabeth R. ORCID: https://orcid.org/0000-0002-3010-6493; Broeke, Michiel R.; Wessem, J. Melchior; Schlosser, Elisabeth. 2019 A new 200‐year spatial reconstruction of West Antarctic surface mass balance. Journal of Geophysical Research: Atmospheres, 124 (10). 5282-5295. 10.1029/2018JD029601
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Abstract/Summary
High‐spatial resolution surface mass balance (SMB) over the West Antarctic Ice Sheet (WAIS) spanning 1800‐2010 is reconstructed by means of ice core records combined with the outputs of the European Centre for Medium‐range Weather Forecasts “Interim” reanalysis (ERA‐Interim) and the latest polar version of the Regional Atmospheric Climate Model (RACMO2.3p2). The reconstruction reveals a significant negative trend (‐1.9 ± 2.2 Gt yr‐1 decade‐1) in the SMB over the entire WAIS during the 19th century, but a statistically significant positive trend of 5.4 ± 2.9 Gt yr‐1 decade‐1 between 1900 and 2010, in contrast to insignificant WAIS SMB changes during the 20th century reported earlier. At regional scales, the Antarctic Peninsula (AP) and western WAIS show opposite SMB trends, with different signs in the 19th and 20th centuries. The annual resolution reconstruction allows us to examine the relationships between SMB and large‐scale atmospheric oscillations. Although SMB over the AP and western WAIS correlates significantly with the Southern Annular Mode (SAM) due to the influence of the Amundsen Sea Low (ASL) and El Niño/Southern Oscillation (ENSO) during 1800‐2010, the significant correlations are temporally unstable, associated with the phase of SAM, ENSO and the Pacific decadal oscillation (PDO). In addition, the two climate modes seem to contribute little to variability in SMB over the whole WAIS on decadal‐centennial time scales. This new reconstruction also serves to identify unreliable precipitation trends in ERA‐Interim, and thus has potential for assessing the skill of other reanalyses or climate models to capture precipitation trends and variability.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | 10.1029/2018JD029601 |
ISSN: | 2169-897X |
Date made live: | 07 May 2019 09:11 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/523204 |
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