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This study investigates and defines the subfault distribution along the Japan-KurilKamchatka subduction zone for the implementation of a far-field tsunami forecast algorithm. Analyses of earthquakes with surface wave magnitude greater than 6.5 from years 1900 to 2000 define the subduction zone, which in turn is divided into 222 subfaults based on the distribution of the fault parameters. For unit slip of the subfaults, a linear long-wave model generates a database of mareograms at water-level stations in and around the subduction zone and at selected warning points away from the source. When a tsunami occurs, an inverse algorithm determines the slip distribution from near-source tsunami records and predicts the tsunami waveforms at the warning points using the precomputed mareograms. The jackknife resampling scheme uses various combinations of input tsunami records to provides a series of predictions for the computation of the confidence interval bounds. The inverse algorithm is applied to hindcast three major tsunamis generated from the Japan-Kuril-Kamchatka source and the computed tsunami heights show good agreement with recorded water-level data.iv

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