BITE, a Bayesian glacier thickness estimation model
Mauro Werder
BITE is a new glacier thickness estimation model based on a mass-conserving forward model and a Bayesian inversion scheme. The model is fitted to available data using a Markov chain Monte Carlo (MCMC) method. The model is applied to more than 30,000 glaciers representing about 1/6 of the total. Thanks to Julia's speed it was possible to calculate the 1e8 glacier thickness maps necessary for the MCMC procedure.
