Differential Influences of Teleconnections from the Indian and Pacific Oceans on Rainfall Variability in Southeast Asia

Abstract

This study investigates the individual and combined impacts of El Niño and the positive Indian Ocean Dipole (IOD) on the Southeast Asia (SEA) rainfall variability. Using composite and partial correlation techniques, it is shown that both inter-annual events have individually distinct impacts on the SEA rainfall anomaly distribution. The results showed that the impacts of the co-occurrence of El Niño and IOD events are significant compared to the individual effects of pure El Niño or pure IOD. During June-July-August and September-October-November, the individual impacts of the pure El Niño and IOD events are similar but less significant. Both events caused negative impacts over the southern part of SEA during June-July-August (JJA) and propagated northeastward/eastward during September-October-November (SON). Thus, there are significant negative impacts over the southern part of SEA during the co-occurrence of both events. The differential impacts on the anomalous rainfall patterns are due to the changes in the sea surface temperature (SST) surrounding the region. Additionally, the differences are also related to the anomalous regional atmospheric circulations that interact with the regional SST. The anomalous Walker circulation that connects the Indian Ocean and tropical Pacific Ocean also plays a significant role in determining the regional anomalous rainfall patterns.

Independent ENSO and IOD impacts on rainfall extremes over Indonesia

“…The influence of ENSO is investigated during the four seasonal periods December–February (DJF, wet), March–May (MAM, transition), June–August (JJA, dry), and September–November (SON, transition) while IOD influences are examined only during JJA and SON (Saji et al ., 1999; Hendon, 2003; Aldrian et al ., 2007; Supari et al ., 2018; Amirudin et al ., 2020). Data and analysis period spans 39 years from 1981 to 2019.…”

“…Indonesia, the largest archipelago in the world, forms a large part of the Maritime Continent that straddles the Equator between the Indian and Pacific Oceans. Overall, the mean rainfall is significantly modulated by natural inter‐annual climate variability modes, such as the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) (Aldrian and Dwi Susanto, 2003; Nur'utami and Hidayat, 2016; Lestari et al ., 2019; Amirudin et al ., 2020). For example, El Niño (La Niña) events lead to similar impacts on Indonesian rainfall to that of positive (negative) IOD events, causing drier (wetter) conditions, of which have been increasingly linked to widespread hazards such as floods or drought/forest fires throughout the Indonesia continent.…”

“…Several studies show that ENSO affects Indonesia's rainfall more over the eastern parts, whereas IOD affects the western parts more (Saji and Yamagata, 2003; Hamada et al ., 2012; Villafuerte and Matsumoto, 2015; Supari et al ., 2018). Further, when ENSO and IOD events occur concurrently they have a more significant widespread impact (Nur'utami and Hidayat, 2016; Amirudin et al ., 2020). The impact of ENSO and IOD is also suggested to spread to the northeast/east once they reach their active phase (Juneng and Tangang, 2005; Supari et al ., 2018; Amirudin et al ., 2020).…”

“…Further, when ENSO and IOD events occur concurrently they have a more significant widespread impact (Nur'utami and Hidayat, 2016; Amirudin et al ., 2020). The impact of ENSO and IOD is also suggested to spread to the northeast/east once they reach their active phase (Juneng and Tangang, 2005; Supari et al ., 2018; Amirudin et al ., 2020).…”

“…However, limited studies have investigated the impact of ENSO and IOD on the extreme precipitation in Indonesia, using either select stations (e.g., Lestari et al ., 2016; Supari et al ., 2017; Lestari et al ., 2019), or examining the spatial extent of dominant climate mode impacts using composite (Setiawan et al ., 2017; Amirudin et al ., 2020) or generalized extreme value (GEV; Villafuerte and Matsumoto, 2015) analysis. Further, in these previous efforts, such studies have not accounted for the known covariation of the large‐scale climate variability drivers (Behera and Yamagata, 2003; Behera et al ., 2006; Meyers et al ., 2007; Hong et al ., 2008a; Quan and Yamagata, 2015; Lestari and Koh, 2016; Nur'utami and Hidayat, 2016; Fan et al ., 2017).…”