Interdecadal Variability in Myanmar Rainfall in the Monsoon Season (May–October) Using Eigen Methods

Zin Mie Mie Sein,Irfan Ullah,Kamran Azam,Sidra Syed,Xiefei Zhi,Farhan Saleem

doi:10.3390/w13050729

Abstract

In this study, we investigated the interdecadal variability in monsoon rainfall in the Myanmar region. The gauge-based gridded rainfall dataset of the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit version TS4.0 (CRU TS4.0) were used (1950–2019) to investigate the interdecadal variability in summer monsoon rainfall using empirical orthogonal function (EOF), singular value decomposition (SVD), and correlation approaches. The results reveal relatively negative rainfall anomalies during the 1980s, 1990s, and 2000s, whereas strong positive rainfall anomalies were identified for the 1970s and 2010s. The dominant spatial variability mode showed a dipole pattern with a total variance of 47%. The power spectra of the principal component (PC) from EOF revealed a significant peak during decadal timescales (20–30 years). The Myanmar summer monsoon rainfall positively correlated with Atlantic multidecadal oscillation (AMO) and negatively correlated with Pacific decadal oscillation (PDO). The results reveal that extreme monsoon rainfall (flood) events occurred during the negative phase of the PDO and below-average rainfall (drought) occurred during the positive phase of the PDO. The cold phase (warm phase) of AMO was generally associated with negative (positive) decadal monsoon rainfall. The first SVD mode indicated the Myanmar rainfall pattern associated with the cold and warm phase of the PDO and AMO, suggesting that enhanced rainfall for about 53% of the square covariance fraction was related to heavy rain over the study region except for the central and eastern parts. The second SVD mode demonstrated warm sea surface temperature (SST) in the eastern equatorial Pacific (El Niño pattern) and cold SST in the North Atlantic Ocean, implying a rainfall deficit of about 33% of the square covariance fraction, which could be associated with dry El Niño conditions (drought). The third SVD revealed that cold SSTs in the central and eastern equatorial Pacific (La Niña pattern) caused enhance rainfall with a 6.7% square covariance fraction related to flood conditions. Thus, the extra-subtropical phenomena may affect the average summer monsoon trends over Myanmar by enhancing the cross-equatorial moisture trajectories into the North Atlantic Ocean.

Highlights

Rainfall variability is among the basic indicators of climate and water cycle changes in a region [1]
The findings reported using heterogeneous correlation patterns [11] as the first singular value decomposition (SVD) of sea surface temperature (SST) mode 1 were mainly associated with the cold phase of Pacific decadal oscillation (PDO) in the Pacific Ocean, north of 20◦ N, and the warm phase of Atlantic multidecadal oscillation (AMO) in the North Atlantic Ocean (Figure 15a)
The findings reported using heterogeneous correlation patterns [11] as the first SVD of SST mode 1 were mainly associated with the cold phase of PDO in the Pacific Ocean, north of 20° N, and the warm phase of AMO in the Heterogeneouscorrelations correlationsof ofthe thefirst firstthree threeSVD

Summary

Introduction

Rainfall variability is among the basic indicators of climate and water cycle changes in a region [1]. The. Intergovernmental Panel on Climate Change (IPCC) stated that global -warming-induced climate change has intensified the variability in rainfall over space and time across the globe [7]. It is projected that the spatiotemporal variability in rainfall and related extremes will intensify in the near future [7]. These projections can be used as feedback for the policy makers in water resource management, disaster risk reduction, and regional climate analysis [8]

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Conclusion