Open AccessExtreme rainfall prediction using spatial extreme value by Max Stable Process (MSP) Smith model approach
Author(s) -
Hasbi Yasin,
Arief Rachman Hakim,
Budi Warsito,
Rukun Santoso
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1217/1/012110
Subject(s) - gumbel distribution , extreme value theory , generalized extreme value distribution , weibull distribution , mathematics , return period , maxima , generalized pareto distribution , extreme weather , statistics , geography , geology , history , archaeology , performance art , art history , flood myth , oceanography , climate change
This research covers Spatial Extreme Value method application with Max-Stable Process (MSP) approach that will be used to analysis Extreme Rainfall in Semarang city. Extreme value sample are selected by Block Maxima methods, it will be estimated into Spatial Extreme Value form by including location factors. Then it transform to Frechet distribution because it has a Heavy tail pattern. Max Stable Process (MSP) is an extension of the multivariate extreme value distribution into infinite dimension of the Extreme Value Theory. MSP using Generalized Extreme Value (GEV) approach, it has three forms distribution that is Gumbel, Frechet and Weibull. Extreme Value Samples that are selected by Block Maxima will follow GEV distribution. The best model that obtained based on Max-Stable with Smith model can be used to predict Extreme Rainfall by count Return Level. Then can be further analysis of various aspects, so it can provide a suggestion about the potential of natural disasters which are caused by extreme rainfall. Extreme rainfall prediction using the Smith model in the return period of the next two years, at the Semarang City Climatology, Tanjung Mas and Ahmad Yani Station is predicted to be a maximum of 100.7539 mm, 100.1052 mm, and 109.9379 mm.