Statistics seminar - Dr Bao Anh Vu - ANU/RSFAS

A seminar by Dr Bao Anh Vu from RSFAS

Title: Estimating Antarctic subglacial conditions using neural posterior inference

Abstract: The Antarctic ice sheet (AIS) is the largest freshwater reservoir on Earth and a major contributor to sea level rise. Ice loss from the AIS will have significant impact on the biodiversity of Antarctica and its surrounding oceans as well as other coastal communities, including Australia. Therefore, estimates of the AIS's contribution to the sea-level budget are of paramount importance for planning and adaptation. Ice sheet models are routinely used to quantify and project an ice sheet's contribution to sea level rise. In order for an ice sheet model to generate realistic projections, its parameters must first be calibrated using observational data; this is challenging due to the nonlinearity of the model equations, the high dimensionality of the underlying parameters, and limited data availability for validation. This study leverages the emerging field of neural posterior approximation for efficiently calibrating ice sheet model parameters and boundary conditions. We make use of a one-dimensional (flowline) ice sheet model called the Shallow-Shelf Approximation model in a state-space framework. A neural network is trained to infer the underlying parameters, namely the bedrock elevation and basal friction coefficient along the flowline, based on observations of ice surface velocity and surface elevation. We show through a simulation study that our approach yields more accurate estimates of the parameters and states than a state-augmented ensemble Kalman filter, which is the current state-of-the-art. We then apply our approach to infer the bed elevation and basal friction along a flowline in Thwaites Glacier, Antarctica.

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