EFEK FENOMENA IKLIM GLOBAL DAN TOPOGRAFI TERHADAP POLA DISTRIBUSI CURAH HUJAN DI PROVINSI JAWA TENGAH DAN D. I. YOGYAKARTA - YUNUS, RODI ([Yogyakarta] : Universitas Gadjah Mada, 2015)
Activity in several fields such as hydrology, climatology and agriculture related and determined by variation of rainfall. Variability of rainfall distribution is influenced by many factors, from global to local scale. In this research, analysis of rainfall variation with global and local scale factors were done. Global scale are in the forms of global climate phenomena, they are the teleconnection sea surface temperature (SST) anomalies of the Pacific Ocean (Nino 3.4 Index) and the difference of SST anomalies between eastern (IODE) and western (IODW) of Indian Ocean (DMI). The regression analysis showed that SST variations occured in both of the ocean significantly influenced rainfall variations in some locations in Central Java and DIY during SON, DJF and JJA periods. Impacts of Nino 3.4 index more apparent in Yogyakarta and eastern part Central Java. IODE and DMI were significantly more influential in western part of Central Java. The influence of these three variables to rainfall variations in significant locations are about 40 % -72 %. SST anomalies in the Pacific Ocean could generated ENSO phenomenon (El Nino or La Nina). Meanwhile, the difference of SST anomalies between western and eastern could generated IOD phenomenon. El Nino event caused average rainfall decrease and the difference is significant compared to neutral conditions during SON period. During DJF period, the reduction of rainfall is more significant in the lowlands (elevation <100 m above sea level/asl) during El Nino and IOD (+) events simultaneously. La Nina event caused rainfall increased during DJF period, and extreme rainfall became more frequent. La Nina impact is more significant in locations that are below 500 m asl . In the local scale, geographical position and topography are factors that influenced rainfall variations. Based on the geographical position, seasonal rainfall (SON, DJF, MAM and JJA) are generally higher in the western than eastern part of the study area and positively correlated with altitude. Spatial rainfall can be obtained by interpolation. To estimate spatial rainfall is used non-linear regression multivariate approach with topography as independent variables. Topographic variables considered are latitude, longitude, altitude, slope and aspect. The rainfall estimation model formed from the combination of topographic variables. The best model, that have performance or better accuracy rate was constructed from latitude, longitude and altitude. This best model is more consistent than IDW spatial model.