Back to the Future: Using long-term observational and paleo-proxy reconstructions to improve model projections of Antarctic climate

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 20th 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 21st century and beyond. We identify priorities and suggest next steps to addressing this.

Details

Publication status:
Published
Author(s):
Authors: Bracegirdle, Thomas J., Colleoni, Florence, Abram, Nerilie J., Bertler, Nancy A.N., Dixon, Daniel A., England, Mark, Favier, Vincent, Fogwill, Chris J., Fyfe, John C., Goodwin, Ian, Goose, Hugues, Hobbs, Will, Jones, Julie M., Keller, Elizabeth D., Khan, Alia L., Phipps, Steven J., Raphael, Marilyn N., Russell, Joellen, Sime, Louise, Thomas, Elizabeth R., van den Broeke, Michiel R., Wainer, Ilana

On this site: Liz Thomas, Louise Sime, Thomas Bracegirdle
Date:
7 June, 2019
Journal/Source:
Geosciences / 9
Digital Object Identifier (DOI):
https://doi.org/10.3390/geosciences9060255