Project Title: Collaborative Research: P2C2 -- Statistical estimation of past ice sheet volumes from paleo-sea level records (Award# 1203414)
PI:Mitrovica, Jerry X (firstname.lastname@example.org) Phone:(617) 945.2564 Institute/Department:Harvard University, Department of Earth and Planetary Sciences IPY Project? Funding Agency:US\Federal\NSF\GEO\OPP\ARC\ANS Program Manager:Dr. William Wiseman (email@example.com) Discipline(s): |Geological Sciences |
Science Summary: The PIs will develop a statistical model for inferring past mean global sea level (GSL) and ice sheet volumes from geological indicators of changes in local sea levels. This model will employ a Bayesian statistical framework to combine geological observations and their uncertainties with a geophysical model of the spatial and temporal sea level patterns associated with different meltwater sources. The work focuses on three specific applications:
(1) evaluating the contribution of different ice sheets to high GSL during the Last Interglacial stage, ~130-115 thousand years ago;
(2) assessing ice sheet history from the Last Glacial Maximum (LGM) to the present, in particular estimating the net ice volume change across this time interval and assessing the relative contributions of the Laurentide and Antarctic ice sheets to meltwater pulse 1a at ~14.3 thousand years ago; and
(3) over a broader sweep of the Quaternary and Pliocene, investigating the relationship between Northern and Southern hemisphere ice volumes and paleoclimate proxies.
The geological record of past ice sheet responses to climate change can serve as a key data source for testing forward physical models of ice sheet dynamics under different climate scenarios. The model developed in this project will be an effort to synthesize such a data set, evaluate its associated uncertainties, and employ it to strengthen understanding of the relationship between key climate parameters (such as polar and circum-polar temperatures) and ice sheet stability.
Logistics Summary: This collaboration between Kopp (1203415, Rutgers) and Mitrovica (1203414, Harvard) will develop a statistical model for inferring past mean
global sea level (GSL) and ice sheet volumes from geological indicators of local sea level changes.
Researchers willl use a Bayesian statistical framework to combine geological observations and their uncertainties with a geophysical model of the spatial and temporal sea level patterns associated with different meltwater sources.
No fieldwork is conducted.
Parameters used to generate this report:, Grant# = "1203414", IPY = "ALL"
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