Alik Ismail-Zadeh
Geophysical Institute,
International Institute of Earthquake Prediction
Theory and Mathematical Geophysics,
e-mail: Alik.Ismail-Zadeh@gpi.uka.de
Modern seismic tomography of the Earth's interior facilitates the
inference of the complex trajectories of contemporary mantle movements. To
understand the dynamics of the crust and mantle in the geological past a
quantitative tool is required to solve the inverse problem of thermal
convection. Data assimilation techniques can be used to constrain the initial
conditions for the mantle velocity and temperature from their present
observations. Data assimilation in this case is defined as the incorporation of
present (observations) and past data (initial conditions) in an explicit
dynamic model to provide time continuity and coupling among the physical
fields. The basic principle of data assimilation is to consider the initial
condition as a control variable and to optimise the initial condition in order
to minimize the discrepancy between the observations and the solution of the
model. A
practical implementation of data assimilation techniques in modelling of
geodynamic processes depends strongly on data accuracy (e.g., uncertainties in
the present temperature distribution in the Earth's interior). Since there are
no direct measurements of mantle temperatures, the temperatures can be
estimated indirectly from either seismic wave (and
their anomalies), geochemical analysis or through the extrapolation of surface
heat flow observations. Many models of mantle temperature are based on the
conversion of seismic tomography data into temperature; and seismic tomography
data incorporate their own errors. If the present
mantle temperature models are significantly biased, information on temperature
can be improperly propagated to the geological past, and the resulting
reconstruction will have nothing with true dynamics of the region in the past.