Wahidah Sanusi, Sahlan Sidjara, Sudarmin, Muhammad Abdy
A multivariate analysis of rainfall variables is needed to understand relationships among characteristics of rainfall variables. The monthly rainfall amount of records from three stations during the period of 1985-2014 in Makassar is used. The Standardized Precipitation Index (SPI) is employed to classify data into the wet category. The study aims are to investigate the most appropriate joint distribution function of wet duration and wet severity based on bivariate Archimedean copulas. The copulas are Gumbel-Hougaard, Frank, Joe, and Clayton. Parameter of copulas is estimated by Kendall's tau correlation coefficient. The study result shows that the Frank copula was identified as the best copula in joint modeling between wet duration and wet severity at Meteorologi Maritim Paotere (MMP) and Biring Romang Panakkukang (BRP) stations, meanwhile the Gumbel-Hougaard copula at Balai Besar Meteorologi, Klimatologi, and Geofisika (BBMKG) station. This result could be useful information for determining return periods of wet condition characteristics. Copyright © 2020 EAI
Department of Mathematics, Universitas Negeri Makassar, Parangtambung, Makassar, 90224, Indonesia; Department of Statistics, Universitas Negeri Makassar, Parangtambung, Makassar, 90224, Indonesia
