Back to the Future: Using Long-Term Observational and Paleo-Proxy Reconstructions to Improve Model Projections of Antarctic Climate

• Published in: Geosciences
• Main Authors: Thomas J. Bracegirdle, Florence Colleoni, Nerilie J. Abram, Nancy A. N. Bertler, Daniel A. Dixon, Mark England, Vincent Favier, Chris J. Fogwill, John C. Fyfe, Ian Goodwin, Hugues Goosse, Will Hobbs, Julie M. Jones, Elizabeth D. Keller, Alia L. Khan, Steven J. Phipps, Marilyn N. Raphael, Joellen Russell, Louise Sime, Elizabeth R. Thomas, Michiel R. van den Broeke, Ilana Wainer
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2019
• Subjects: Antarctic; Southern Ocean; climate; paleoclimate; CMIP; PMIP; projections; Geology; QE1-996.5; The Antarctic; Antarc*; ice core
• Online Access: https://doi.org/10.3390/geosciences9060255; https://doaj.org/article/7d546f82778344feb56853ce4db390c1

Quantitative estimates of future Antarctic climate change are derived from numerical global climate models. Evaluation of the reliability of climate model projections involves many lines of evidence on past performance combined with knowledge of the processes that need to be represented. Routine model evaluation is mainly based on the modern observational period, which started with the establishment of a network of Antarctic weather stations in 1957/58. This period is too short to evaluate many fundamental aspects of the Antarctic and Southern Ocean climate system, such as decadal-to-century time-scale climate variability and trends. To help address this gap, we present a new evaluation of potential ways in which long-term observational and paleo-proxy reconstructions may be used, with a particular focus on improving projections. A wide range of data sources and time periods is included, ranging from ship observations of the early 20 th century to ice core records spanning hundreds to hundreds of thousands of years to sediment records dating back 34 million years. We conclude that paleo-proxy records and long-term observational datasets are an underused resource in terms of strategies for improving Antarctic climate projections for the 21 st century and beyond. We identify priorities and suggest next steps to addressing this.