Bootstrap resampling to detect active zone for extreme rainfall in Indonesia

Abstract

This research aims to develop a methodology to detect active zones related to the extreme rainfall event in one of regions in Indonesia. Active zone is defined as regions or zones on the atmospheric level which have significantly different pattern with other regions prior to the occurrence of extreme event happen in the study area. The detection will be useful for the forecasters to predict the extreme rainfall events, and hence, the risk of the disaster caused by the events can be minimized. In order to predict the active zone, this paper examines statistical procedure that is able to test the significant difference between weather phenomena at the atmospheric level onset with prior to the occurrence.