Research papersStudy of rainfall variabilities in Southeast Asia using long-term gridded rainfall and its substantiation through global climate indices
Graphical abstract
Southeast Asia map with different sub-regions for study.
Introduction
The Southeast Asia (SEA) region has significant variability in their monsoon systems which is strongly correlated with other weather systems such as Siberian high and Arctic Oscillation (Misra and DiNapoli, 2014, Loo et al., 2015). The countries of SEA such as Myanmar, Vietnam, Thailand, Laos, Cambodia and Philippines (except for a few island areas) are largely influenced by South Asian summer monsoon system that brings heavy rainfall during May to September. While, those like Malaysia, Singapore, Indonesia and Papua New Guinea regions and near Islands receive heavy rainfall over boreal winter monsoon, mostly during November to March (Johnson, 1987, Feng et al., 2010, Tyrlis et al., 2013, Xavier et al., 2014, Ngo-Duc et al., 2017). Over the past decades, many studies revealed complex variations in the annual cycle of rainfall over SEA regions (Aldrian and Dwi Susanto, 2003, Juneng and Tangang, 2005, Lau and Wang, 2006), elaborated the interactions of wind-terrain-rainfall and monsoon circulations (Wang and Chang, 2012, Misra and DiNapoli, 2014), and explored the impact of climate change at both local and large scales (IPCC, 2013, Loo et al., 2015, Lu et al., 2015, Singh et al., 2019, Raghavan et al., 2017).
In terms of climate extreme events in SEA region, a few studies predicted significant changes in the monsoon system of SEA due to increasing temperature and shifting of monsoon rainfall in the late 21st century (Schewe and Levermann, 2012, Shamshuddin et al., 2016). Cruz et al. (2012) found significant variabilities in South Asia summer monsoon rainfall and observed a decrease in rainfall amount (total) over Philippines. Based on the APHRODITE rainfall (1951–2007), Misra and DiNapoli (2014) analyzed that the length of the wet period of SEA summer monsoon system seems to be a very strong climate system of the SEA. Loo et al. (2015) found a large shift in the monsoon rainfall over SEA (around 70% from the normal) in the late 21st century and early 22nd century. Tangang et al. (2017) studied over Indonesia utilizing daily rainfall data (1971–2012) from 97 gauges and demonstrated that frequent fluctuations in consecutive wet and dry conditions mostly occurred in the west and east, respectively. Wong et al. (2018) indicated that the rainfall amount increased over Malaysia during 1975 to 2006 due to winter monsoon. Li et al. (2018) studied Singapore region utilizing observed rainfall data (1980–2013) and revealed a significant increase in both wet day rainfall amount and intensity. These regional studies showed that the SEA regions have highly variable rainfall patterns during monsoons and are potentially under significant impact from climate change.
Many studies also analyzed the interactions of rainfall variabilities in SEA monsoons with the coupled ocean-atmospheric phenomenon (Wang and Chang, 2012, Misra and DiNapoli, 2014, Loo et al., 2015, Mandapaka et al., 2017). Mandapaka et al. (2017) indicated that the extremity of the SEA monsoon (in terms of rainfall events) would increase with the decrease of the Madden-Julian Oscillation (MJO) active phases. Xavier et al. (2014) concluded that the convectively suppressed phases of MJO tend to reduce the probability of rainfall extremes and the stronger MJO events would enhance the probability of extreme rainfall events. The SEA region is also highly vulnerable to the influence of El Nino Southern Oscillation (ENSO), which is known to have direct impact on the extreme events such as droughts and floods (e.g. Ward et al., 2014, Villafuerte and Matsumoto, 2015, Sun et al., 2015, Räsänen et al., 2016, Kondo et al., 2018, Li et al., 2018). Räsänen et al. (2016) found that most of the extreme events (i.e. wet and dry) over SEA occurred during ENSO events, especially during March to May. Li et al. (2018) found a correlation between extreme rainfall events and ENSO over Singapore during 1980–2013 and an enhanced intra-annual variability in extreme rainfall during ENSO periods. Furthermore, a few studies explored the impact of other global climate indices, such as Southern Oscillation Index (SOI), Northern Oscillation Index (NOI), and Quasi-Biennial Oscillation (QBO) index over the SEA regions, and mentioned about their significance on the prediction of monsoon rainfall and extreme rainfall (Mandapaka et al., 2017, Lee, 2015). Tangang (2001) found a strong correlation between QBO and Malaysian rainfall anomalies and linked the Malaysian Peninsula climate variabilities with the QBO band. Yan et al. (2011) explained the significance of SOI index to quantify the seasonal climatic variabilities in western and eastern pacific equatorial regions with relation to El Nino and La Nina events. The direct correlation of NOI was not well evaluated over SEA regions but their effects on SOI and ENSO were explained by Mandapaka et al. (2017). A study conducted by Stilgoe (2016) showed a correlation between NOI and Darwin and Equatorial region rainfall (Australia). Melgarejo et al. (2017) explored the ENSO and SOI based indices to analyze the precipitation extremes over Mexican region.
Generally, the spatial and temporal correlations between rainfall and the highly variable SEA monsoon conditions, especially over long time scales, are poorly studied. Villafuerte and Matsumoto (2015) studied over SEA utilizing APHRODITE rainfall (1951–2007) and observed higher extreme rainfall during La Nina and low rainfall during El Nino. Kim et al. (2018) utilized seven different sources of datasets including APHRODITE for the rainfall analysis over the Asia region and revealed that there are robust differences among the datasets exhibiting extreme precipitation statistics. Nevertheless, APHRODITE dataset still shows some limitations over SEA region (Yatagai et al., 2012, Van den Besselaar et al., 2017). Singh and Qin (2019) studied gridded rainfall over SEA and indicated that APHRODITE rainfall is somewhat underestimating in some regions in comparison to the gap-filled version of SA-OBS gridded datasets and other gridded rainfall products. In addition, a holistic study on the direct correlations between global climate indices (i.e. SOI, NOI, QBO and NOI) and seasonal rainfall of SEA is rather limited. Thus, the objective of this study is to utilize a long-term (1951–2014) grid-based (0.5°×0.5°) rainfall dataset for exploring the historical rainfall characteristics in SEA region. The rainfall dataset was produced by merging SA-OBS (Van den Besselaar et al., 2017) and PRINCETON (Sheffield et al., 2006, El Kenawy and McCabe, 2016) grid-based rainfall, with a few data assimilation operations (Singh et al., 2019). The spatiotemporal seasonality and extreme rainfall variabilities will be investigated and compared with findings from other studies. Moreover, multiple global climate indices will be utilized to find out their potential linkages to rainfall variabilities over SEA regions.
Section snippets
General climatology of SEA and data utilized
Fig. 1 shows the Southeast Asia map with different sub-regions to be studied. The selected study domain has latitudes ranging from −13°S to 26°N and longitudes ranging from 89°E to 149°E, covering around 4.5 million km2. The SEA region includes both mainland and maritime portions and is characterized by tropical hot and humid climate and abundant rainfall. Most of SEA region owns wet and dry seasons driven by seasonal changes in winds or monsoon (Mandapaka et al., 2017). The mainland SEA region
SEA monsoon characteristics and seasonality over the region
The monthly changes of rainfall over SEA region is analyzed first, with details provided in Fig. S1 of the Supplementary Material. Overall, the monthly rainfall over SEA is highly variable from January to December. The areas including Thailand, Myanmar (few area), Laos, Cambodia, Vietnam and Luzon (Philippines) receive maximum rainfall during April to September months. These regions are mainly characterized by South Asian Summer Monsoon (SASM) system. Over these regions, the maximum rainfall is
Conclusion
This study investigated the rainfall variability and their causes over the SEA region based on a grid-based long-term (1951–2014) dataset. The seasonality of SEA monsoon system has been explored and the spatial distribution of rainfall was analyzed over the region. The rainfall extreme indices were generated and analyzed in the intra-decadal time series domains. The change in rainfall was observed in each intra-decadal time scales. The results highlighted a significant change in the rainfall
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
This project was supported by Start-Up Grant (M4081327.030) from School of Civil and Environmental Engineering, Nanyang Technological University, Singapore. Note, the first author is previously affiliated with School of Civil and Environmental Engineering, Nanyang Technological University, Singapore.
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