The AntSMB dataset: a comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of...

Full description

Bibliographic Details
Published in:Earth System Science Data
Main Authors: Y. Wang, M. Ding, C. H. Reijmer, P. C. J. P. Smeets, S. Hou, C. Xiao
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2021
Subjects:
Online Access:https://doi.org/10.5194/essd-13-3057-2021
https://doaj.org/article/b7ba8252772c40fbb1252b70a8e13a07
Description
Summary:A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of a variety of published field measurements of the Antarctic Ice Sheet SMB by means of stakes, snow pits, ice cores, ultrasonic sounders, and ground-penetrating radar (GPR). The dataset collects 3579 individual multi-year-averaged observations, 687 annually resolved time series from 675 sites extending back over the past 1000 years, and daily resolved records covering 245 years from 32 sites across the whole ice sheet. These records are derived from ice cores, snow pits, stakes/stake farms, and ultrasonic sounders. Furthermore, GPR multi-year-averaged measurements are included in the dataset, covering an area of 22 025 km 2 . This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual, and multi-year) resolutions from multiple types of measurement and is available at https://doi.org/10.11888/Glacio.tpdc.271148 (Wang et al., 2021). The database has potentially wide applications such as the investigation of temporal and spatial variability in SMB, model validation, assessment of remote sensing retrievals, and data assimilation. As a case of model estimation, records of the AntSMB dataset are used to assess the performance of ERA5 for temporal and spatial variability in SMB over Antarctica.