Antarctic Ice Sheet paleo-constraint database

• Published in: Earth System Science Data
• Main Authors: Lecavalier, Benoit S., Tarasov, Lev, Balco, Greg, Spector, Perry, Hillenbrand, Claus-Dieter, Buizert, Christo, Ritz, Catherine, Leduc-Leballeur, Marion, Mulvaney, Robert, Whitehouse, Pippa L., Bentley, Michael J., Bamber, Jonathan
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2023
• Subjects: article; Verlagsveröffentlichung; Antarctic; Briggs; Antarc*; Ice Sheet
• Online Access: https://doi.org/10.5194/essd-15-3573-2023; https://noa.gwlb.de/receive/cop_mods_00068119; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00066553/essd-15-3573-2023.pdf; https://essd.copernicus.org/articles/15/3573/2023/essd-15-3573-2023.pdf

We present a database of observational constraints on past Antarctic Ice Sheet changes during the last glacial cycle intended to consolidate the observations that represent our understanding of past Antarctic changes and for state-space estimation and paleo-model calibrations. The database is a major expansion of the initial work of Briggs and Tarasov (2013). It includes new data types and multi-tier data quality assessment. The updated constraint database, AntICE2 (https://theghub.org/resources/4884, Lecavalier et al., 2022), consists of observations of past grounded- and floating-ice-sheet extent, past ice thickness, past relative sea level, borehole temperature profiles, and present-day bedrock displacement rates. In addition to paleo-observations, the present-day ice sheet geometry and surface ice velocities are incorporated to constrain the present-day ice sheet configuration. The method by which the data are curated using explicitly defined criteria is detailed. Moreover, the observational uncertainties are specified. The methodology by which the constraint database can be applied to evaluate a given ice sheet reconstruction is discussed. The implementation of the AntICE2 database for Antarctic Ice Sheet model calibrations will improve Antarctic Ice Sheet predictions during past warm and cold periods and yield more robust paleo-model spin ups for forecasting future ice sheet changes.