  We demonstrate the efficacy of a Bayesian statistical inversion framework for
reconstructing the likely characteristics of large pre-instrumentation
earthquakes from historical records of tsunami observations. Our framework is
designed and implemented for the estimation of the location and magnitude of
seismic events from anecdotal accounts of tsunamis including shoreline wave
arrival times, heights, and inundation lengths over a variety of spatially
separated observation locations. As an initial test case we use our framework
to reconstruct the great 1852 earthquake and tsunami of eastern Indonesia.
Relying on the assumption that these observations were produced by a subducting
thrust event, the posterior distribution indicates that the observables were
the result of a massive mega-thrust event with magnitude near 8.8 Mw and a
likely rupture zone in the north-eastern Banda arc. The distribution of
predicted epicentral locations overlaps with the largest major seismic gap in
the region as indicated by instrumentally recorded seismic events. These
results provide a geologic and seismic context for hazard risk assessment in
coastal communities experiencing growing population and urbanization in
Indonesia. In addition, the methodology demonstrated here highlights the
potential for applying a Bayesian approach to enhance understanding of the
seismic history of other subduction zones around the world.
