Luaran simulasi model iklim regional perlu dikoreksi karena memiliki bias sistematis secara spasial dan temporal. Kajian ini membahas simulasi koreksi bias menggunakan metode statistik. Data yang dikoreksi adalah data curah hujan luaran simulasi RegCM4.4 pada periode 1981-2005. Dari simulasi koreksi bias tersebut kami mendapati bahwa koreksi bias menggunakan regeresi linear tidak mampu memperbaiki distribusi spasial maupun pola hujan. Namun, dengan menggunakan regresi polinomial, koreksi bias menunjukkan luaran yang lebih baik terutama dengan regresi polinomial orde 3. Lebih dari itu, regresi polinomial orde 3 yang dikombinasikan dengan intersep yang dikembalikan pada nilai nol memberikan luaran koreksi bias yang terbaik dan dapat digunakan untuk melakukan analisis kekeringan lahan. Kami mendapati bahwa analisis kekeringan dengan metode Standardized Precipitation Index (SPI) yang diuji menggunakan skala waktu 1, 3, 6 dan 12 bulan memberikan hasil terbaik jika menggunakan skala waktu lebih dari 1 bulan. Hal ini dapat dilihat dari hubungannya dengan nilai anomali curah hujan dan jejak kekeringan yang terjadi pada tahun El-Nino seperti
Future rainfall projection can be predicted by using Global Climate Model (GCM). In spite of low resolution, we are not able specifically to describe a local or regional information. Therefore, we applied downscaling technique of GCM output using Regional Climate Model (RCM). In this case, Regional Climate Model version 3 (RegCM3) is used to accomplish this purpose. RegCM3 is regional climate model which atmospheric properties are calculated by solving equations of motion and thermodynamics. Thus, RegCM3 is also called as dynamic downscaling model. RegCM3 has reliable capability to evaluate local or regional climate in high spatial resolution up to 10 × 10 km. In this study, dynamically downscaling techniques was applied to produce high spatial resolution (20 × 20 km) from GCM EH5OM output which commonly has rough spatial resolution (1.875<sup>o</sup> × 1.875<sup>o</sup>). Simulation show that future rainfall in Indramayu is relatively decreased compared to the baseline condition. Decreased rainfall generally occurs during the dry season (July-June-August/JJA) in a range 10-20%. Study of extreme daily rainfall indicates that there is no significant increase or decrease value.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.