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The Ant-Iso dataset: a compilation of Antarctic surface snow isotopic observations.

Authors :
Jiajia Wang
Hongxi Pang
Shuangye Wu
Schoenemann, Spruce W.
Ryu Uemura
Ekaykin, Alexey
Werner, Martin
Cauquoin, Alexandre
Oger, Sentia Goursaud
Rupper, Summer
Shugui Hou
Source :
Earth System Science Data Discussions. 11/30/2022, p1-23. 23p.
Publication Year :
2022

Abstract

Stable water isotopic observations in surface snow over Antarctica provide a foundation for validating isotopic models and interpreting Antarctic ice core records. Here, we present a new compilation of Antarctic surface snow isotopic dataset with strict quality control from published and unpublished sources including measurements from snow pits, snow cores, ice cores, deep surface snow, and precipitation (multi-year average values). The dataset contains a total of 1867 data points, including 1604 locations for oxygen isotope ratio (d18O) and 1278 locations for deuterium isotope ratio (d2H). 1204 locations have both d18O and d2H, from which d-excess (d-excess = d2H - 8 × d18O) can be calculated. The dataset also contains geographic and climate information. The database has a wide range of potential applications, such as the study of the spatial distribution of water isotopes in Antarctica, the evaluation of climate models, and the reconstruction and interpretation of Antarctic ice core records. As an example of model evaluation, the compiled isotopic dataset is used to assess the performance of isotope-enabled atmospheric general circulation models (AGCMs) on simulating the spatial distribution of water isotopes over Antarctica. This dataset is the most comprehensive compilation so far of observed water isotope records at multi-year average scale from multiple sources for Antarctica. It is available for download at https://doi.org/10.5281/zenodo.7294183 (Wang et al., 2022). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18663591
Database :
Academic Search Index
Journal :
Earth System Science Data Discussions
Publication Type :
Academic Journal
Accession number :
160550987
Full Text :
https://doi.org/10.5194/essd-2022-384