Towards Estimating Postseismic Parameters and Processes Using Ensemble Data Assimilation

Abstract

Geodetic observations of vertical land motion following a megathrust
earthquake are key to a better understanding of processes and parameters
controlling the dynamics at subduction margins. The relative
contributions of dominant drivers during the postseismic phase, such as
viscoelastic relaxation, afterslip and relocking, remain difficult to
estimate individually and are often derived at the end of an observation
period. Data assimilation can provide the means to estimate model
parameters by combining physical models with observations whilst taking
their uncertainties into account. We use Bayesian inference in the form
of an ensemble smoother to estimate geodynamic parameters during the
postseismic phase of the megathrust earthquake cycle. The ensemble
smoother uses a Monte Carlo approach to represent the probability
density distribution (pdf) of model states with a finite number of
realizations. Prior estimates of the imperfect physical model are
combined with the likelihood of noisy observations to estimate the
posterior pdf of model parameters. We discuss a synthetic data
experiment where observations are sampled from a 3D finite element model
with noise added to represent errors in the data. With a smoother,
observations at all time steps are assimilated in one go, to ensure
consistency between estimated parameters and model outputs. We
assimilate vertical and horizontal surface displacements into a 2D
finite element viscoelastic earthquake cycle model with a power-law
rheology. We incorporate heterogeneity into the viscoelastic structure
and estimate the viscosity field based on a heterogeneous temperature
field and experimental flow laws. Preliminary results show that model
parameters, such as the extent of the cold nose, maximum depth of
afterslip and flow law parameters can be recovered remarkably well by
assimilating synthetic on- and offshore surface observations. We will
apply the smoother to postseismic surface displacements of the Tohoku
2011 earthquake to estimate model parameters and driving processes
across spatio-temporal domains.