Model Development of NIÑO 3.4 and Indian Ocean Dipole (IOD) Anomalies Teleconnection

Antonni Saputra; Eddy Hermawan; Denny Darmawan

doi:10.21831/jsd.v7i2.38551

Model Development of NIÑO 3.4 and Indian Ocean Dipole (IOD) Anomalies Teleconnection

Antonni Saputra, Physics Study Programs at Yogyakarta State University, Indonesia
Eddy Hermawan, Center of Atmospheric Science and Technology at National Institute of Aeronautics and Space, Indonesia
Denny Darmawan, Physics Study Programs at Yogyakarta State University, Indonesia

10.21831/jsd.v7i2.38551

Abstract

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 Z_t = 1.516 Z_t-1 - 0.516 Z_t-2 - 0.256 a_t-1 + 0.021 a_t-2.

Keywords

Anomalies Teleconnection; Indian Ocean Dipole; Niño 3.4

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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.

DOI: https://doi.org/10.21831/jsd.v7i2.38551