Koreksi Bias Luaran Model Iklim Regional untuk Analisis Kekeringan

Jadmiko, Syamsu Dwi; Post Graduate Student on Applied Climatology of Bogor Agricultural University (IPB)

Center for Climate Risk and Opportunity Management in Southeast Asia and Pacific (CCROM-SEAP); Murdiyarso, Daniel; Lecturer on Geophysic and Meteorology Departemen, Bogor Agricultural University (IPB)

Center for International Forestry Research (CIFOR); Faqih, Akhmad; Center for Climate Risk and Opportunity Management in Southeast Asia and Pacific (CCROM-SEAP)

Lecturer on Geophysic and Meteorology Departemen, Bogor Agricultural University (IPB)

Koreksi Bias Luaran Model Iklim Regional untuk Analisis Kekeringan

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Authors

Jadmiko, Syamsu Dwi; Post Graduate Student on Applied Climatology of Bogor Agricultural University (IPB) Center for Climate Risk and Opportunity Management in Southeast Asia and Pacific (CCROM-SEAP)

Murdiyarso, Daniel; Lecturer on Geophysic and Meteorology Departemen, Bogor Agricultural University (IPB) Center for International Forestry Research (CIFOR)

Faqih, Akhmad; Center for Climate Risk and Opportunity Management in Southeast Asia and Pacific (CCROM-SEAP) Lecturer on Geophysic and Meteorology Departemen, Bogor Agricultural University (IPB)

Publisher

Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian

Description

Abstrak: 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 tahun 1982/1983, 1986/1987 dan 1997/1998.Abstract. The outputs of regional climate model simulations need to be corrected because of their systematic spatial and temporal biases. This study simulates bias correction using the statistical methods on rainfall data outputs generated by RegCM4.4 during the period of 1981-2005. We found that linier regression did not improve the spatial distribution and pattern of rainfall data. However, by using polynomial regression better results were performed especially third order polynomial. Moreover, when the third order of polynomial regression was combined with the zero intercept, it gave the best bias correction and therefore, can be further used for drought analysis. Standardized Precipitation Index (SPI) method was used to analyze drought index with different time scale of 1, 3, 6 and 12-months. We found that SPI performed well when implemented for time scale more than 1-month. This was demonstrated by the relationship with the rainfall anomaly and drought history during El-Nino years of 1982/1983, 1986/1987 and 1997/1998.

Keywords

Agriculture; Climate; Agroclimate; Hydrology, koreksi bias; simulasi koreksi bias; persamaan regresi; standardized precipitation index; skala waktu; bias correction; simulation of bias correction; regression equation; standardized precipitation index; time scale, Agroclimate

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Jurnal Tanah dan Iklim

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