Abstract

AbstractWe perform Bayesian inference of the parameters of a time-dependent model of ice flow and calving at Helheim Glacier, East Greenland. We find that, while a time-independent calving parameterization can recover the mean observed terminus position, such a model is unable to recover sub-annual variability, even when forced with seasonally varying climate. To address this, we develop a simple stochastic model relating surface runoff rates and calving threshold. Again inferring model parameters from observations, we find that this parameterization is able to reproduce observations with respect to both mean position and characteristic temporal variability. This result demonstrates the importance of considering potential sub-annual controls on calving rates in numerical models, which may include variable undercutting rates or surface runoff-dependent surface crevasse propagation.

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