We present a two-stage nonlinear technique to invert strong motions records and
geodetic data to retrieve the rupture history of an earthquake on a finite fault. To account
for the actual rupture complexity, the fault parameters are spatially variable peak slip
velocity, slip direction, rupture time and risetime. The unknown parameters are given at
the nodes of the subfaults, whereas the parameters within a subfault are allowed to
vary through a bilinear interpolation of the nodal values. The forward modeling is
performed with a discrete wave number technique, whose Green’s functions include the
complete response of the vertically varying Earth structure. During the first stage, an
algorithm based on the heat-bath simulated annealing generates an ensemble of models
that efficiently sample the good data-fitting regions of parameter space. In the second
stage (appraisal), the algorithm performs a statistical analysis of the model ensemble and
computes a weighted mean model and its standard deviation. This technique, rather than
simply looking at the best model, extracts the most stable features of the earthquake
rupture that are consistent with the data and gives an estimate of the variability of each
model parameter. We present some synthetic tests to show the effectiveness of the method
and its robustness to uncertainty of the adopted crustal model. Finally, we apply this
inverse technique to the well recorded 2000 western Tottori, Japan, earthquake (Mw 6.6);
we confirm that the rupture process is characterized by large slip (3-4 m) at very shallow
depths but, differently from previous studies, we imaged a new slip patch (2-2.5 m)
located deeper, between 14 and 18 km depth