CORRELATION REPRESENTATION OF LOCAL AND REGIONAL EXTREME PRECIPITATION EVENTS BY APPLYING SPATIAL EXTREME MODELING

Abstract

 Areal Reduction Factors, which have been used as one method of analyzing regional extreme precipitation events, estimate the ratio of extreme precipitation between a location and a region, but cannot express the relationship between the timing of extreme precipitation events. This study proposes a method to express the likelihood of extreme precipitation events occurring at the same period for a location and a region by applying spatial extreme modeling that can express the spatial autocorrelation of extreme values between locations. Using the database for Policy Decision making for Future climate change for 1,200 years, which is a long-term climate simulation data around Japan, the correlation of extreme precipitation events at a point and a region is expressed by the proposed method. It was confirmed that the proposed method can express how the possibility of extreme precipitation events occurring at the same period is affected by climatic and geographical conditions.