Model Development of NIí‘O 3.4 and Indian Ocean Dipole (IOD) Anomalies Teleconnection
DOI:
https://doi.org/10.21831/jsd.v7i2.38551Keywords:
Anomalies Teleconnection, Indian Ocean Dipole, Niño 3.4Abstract
The purpose of this research is to develop the teleconnection model of Niño 3.4 and IOD anomalies which can be used as reference to explain precipitation anomalies. El-Niño and IOD cycles are shown as the warming process of sea surface temperatures where for El-Niño is in the Pacific Ocean and IOD is in the Indian Ocean and each of them forms a cycle over a certain period of time. The method used to determine the dominant oscillation of the teleconnection of Niño 3.4 and IOD anomalies is Power Spectral Density (PSD), and to model the teleconnection of Niño 3.4 and IOD anomalies is ARIMA (Autoregressive Integrated Moving Average). The data used are Niño 3.4 index which is one type of index for El-Niño and IOD index. The results are Power Spectral Density (PSD) graphs for the teleconnection of Niño 3.4 and IOD anomalies which oscillates around 5 years. By the ARIMA method, the approximate model for the data of teleconnection of Niño 3.4 and IOD is ARIMA (1,1,2) with equation of Zt = 1.516 Zt-1 - 0.516 Zt-2 - 0.256 at-1 + 0.021 at-2.
References
Kovats, R. S., Bouma, M. J., Hajat, S., Worrall, E., & Haines, A. (2003). El Niño and health. The Lancet, 362(9394), 1481–1489.
Trenberth, KE, dan National Center for Atmospheric Research Staff. (2016). The Climate Data Guide: Nino SST Indices (Nino 1+2, 3, 3.4, 4; ONI and TNI). From https://climatedataguide.ucar.edu/climatedata/nino-sst-indices-nino-12-3-34-4-oni-andtni.
Yamagata, T., Behera, S. K., Luo, J.-J., Masson, S., Jury, M. R., & Rao, S. A. (2013). Coupled Ocean-Atmosphere Variability in the Tropical Indian Ocean. Geophysical Monograph Series, 189–211.
Saji, H. N., dan T. Yamagata. (2003). Structure of SST and Surface Wind Variability during Indian Ocean Dipole Mode Events: COADS Observations. Journal of Climatology, 16, 2735-2751.
Hermawan, Eddy. (2012). Model Interkoneksi Kejadian El-Nino dan Dipole Mode sebagai Indikasi Awal Datangnya Musim Kering/Basah Panjang di Kawasan Barat Indonesia. Jakarta: Lembaga Penerbangan dan Antariksa Nasional.
Lestari, Astuti Widya. (2012). Pengembangan Model Prediksi Anomali Curah Hujan di Sentra Tanaman Pangan Kalimantan Timur Berbasis ARIMA. Yogyakarta: Program Studi Fisika FMIPA UNY.
Makridakis, S., Steven C. Wheelwright, dan Victor E. McGree.(1993). Metode dan Aplikasi Peramalan. Jakarta: Penerbit Erlangga.
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