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http://repository.ipb.ac.id/handle/123456789/57781
Title: | Pengembangan Model Telekoneksi antara Kejadian El-Niño dengan IOD dan Pengaruhnya Terhadap Fluktuasi Curah Hujan di Daerah Sentra Produksi Pangan (Studi Kasus : Sukamandi dan Padang Panjang). |
Authors: | Setiwawan, Sonni Hermawan, Eddy Krisnanto, Rizki |
Keywords: | Bogor Agricultural University (IPB) ARIMA(p,d,q) Equation Cross Correlation Rainfall Fluctuation in Sukamandi and Padang Panjang Niño3.4+IOD Teleconnection |
Issue Date: | 2012 |
Abstract: | Geoss4th (Global Earth Observation System to System) Asia-Pacific Symposium, March 2010 in Bali, suggested that teleconnection between all the global climate data and their impacts to the rainfall variability over Indonesia, especially between SST Nino 3.4 and IOD when both phenomena come simultaneously in the same time is very important to be investigated comprehensively. Based on that suggestion, this paper objective is to develop a model that can explain how teleconnection between El-Niño and IOD influence rainfall fluctuation in Indonesia. Location that used in this paper are Sukamandi and Padang Panjang, those are food centre region in Indonesia. First point of this paper is short term analysis. Methods to accomplish the goal of this analysis are spectral analysis and cross correlation. The idea is to combine Anomaly SST Niño 3.4 with IOD (Niño 3.4+IOD) to form a new index that present teleconnection and then check the cross correlation between Niño 3.4+IOD and rainfall anomaly on two cities mentioned above. The result from cross correlation between those data are the response about teleconnection from those cities are different and also there is a lag time before teleconnection take effect to those cities. After the short term analysis is complete, which is analyze response of two cities to teleconnection, it was continued by long term analysis. The target of this analysis is to develop a model from Niño3.4+IOD, the model is used as a precursor when will the teleconnection will have a very bad effect to our climate. This analysis is done by using ARIMA (Autoregressive Integrated Moving Average) method. The result of this analysis is an ARIMA(p,d,q) equation that can predict until few next month, so preventive action can be taken to minimalise the impact of long wet season or long dry season |
URI: | http://repository.ipb.ac.id/handle/123456789/57781 |
Appears in Collections: | UT - Geophysics and Meteorology |
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G12rkr.pdf Restricted Access | Full text | 2.68 MB | Adobe PDF | View/Open |
G12rkr_Abstrak.pdf Restricted Access | Abstrak | 384.08 kB | Adobe PDF | View/Open |
G12rkr_BAB I Pendahuluan.pdf Restricted Access | BAB I | 424.9 kB | Adobe PDF | View/Open |
G12rkr_BAB II Tinjauan Pustaka.pdf Restricted Access | BAB II | 879.69 kB | Adobe PDF | View/Open |
G12rkr_BAB III Metode Penelitian.pdf Restricted Access | BAB III | 659.77 kB | Adobe PDF | View/Open |
G12rkr_BAB IV Hasil dan Pembahasan.pdf Restricted Access | BAB IV | 1.08 MB | Adobe PDF | View/Open |
G12rkr_BAB V Penutup.pdf Restricted Access | BAB V | 434.62 kB | Adobe PDF | View/Open |
G12rkr_Cover.pdf Restricted Access | Cover | 487.98 kB | Adobe PDF | View/Open |
G12rkr_Daftar Pustaka.pdf Restricted Access | daftar pustaka | 429.8 kB | Adobe PDF | View/Open |
G12rkr_Lampiran.pdf Restricted Access | Lampiran | 1.52 MB | Adobe PDF | View/Open |
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