Group travel to the Past Antarctic Ice Sheet Dynamics (PAIS) 2017 Conference, Trieste, Italy

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

The first international Past Antarctic Ice Sheet dynamics (PAIS) conference will be held September 10-15, 2017 in Trieste, Italy. The PAIS research program was recently formed by the Scientific Committee on Antarctic Research (SCAR), and grew out of the 2009 Antarctic Climate Evolution symposium. The goal of the workshop is to address key questions about the sensitivity of the Antarctic Ice Sheet to climate change and its contribution to past and future sea level change. The funds will be used to support travel costs for approximately 7-10 U.S. scientists, including early career researchers and graduate students, enabling them to present their scientific findings and benefit from the scholarly exchange of ideas. Travel support requests will be reviewed by an ad hoc review committee made up of standing PAIS advisory committee members. The committee members include both international and U.S. scientists. The review committee will follow NSF guidelines on conflicts of interest in their review process. The future response of the Antarctic Ice Sheet to a warming atmosphere and ocean will have a fundamental impact on global and local sea level rise, coastal cities, communities, and strategic infrastructure. The PAIS conference will facilitate the integration of the latest developments in numerical climate-ocean-ice-Earth modeling with the latest information on recent and past changes in the ice sheet, to better inform projections of the region's physical and ecological future. This grant will allow US researchers, early career scientists, and graduate students to attend the 2017 PAIS Conference and associated workshops. Symposium presentations and publications will provide an important record of research activities in Antarctic Earth Sciences and Glaciology. The key outcomes of the conference and ancillary workshops will set the stage for future international and interdisciplinary collaborations and research proposals- particularly those linking observations and numerical modeling.