Empirical orthogonal functions (EOF) analysis of spatial patterns of dominant variability in the Indian Ocean

Willy Bonanja Manik, Yahya Darmawan, Munawar Munawar, Nardi Nardi, Fendy Arifianto, Ervan Ferdiansyah

Abstract


The Indian Ocean plays a crucial role in the global climate system, particularly in influencing the seasons in Indonesia. Sea surface temperature (SST) variability in the Indian Ocean affects rainfall patterns, extreme events, such as droughts and floods, in Indonesia. This study analyzes SST variability during the dry season (June – July – August, JJA) and rainy season (December – January – February, DJF) using satellite and reanalysis data from 1981 to 2023 with the empirical orthogonal function (EOF) method. The analysis shows that the dominant SST variability pattern during JJA is related to the Indian Ocean dipole (IOD), which influences rainfall and temperature patterns in Indonesia. In DJF, SST variability is more associated with the Asian-Australian monsoon, affecting rainfall patterns and the potential for floods. This research enhances the understanding of climate dynamics in the Indian Ocean and its impact on Indonesia, and it can be used to predict extreme climate events associated with SST variability.

Keywords


EOF; Indian Ocean; IOD; sea surface temperature (SST)

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References


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DOI: http://dx.doi.org/10.31258/jkfi.22.1.23-26

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