Detecting Indonesian Monsoon Signals and Related Features Using Space–Time Singular Value Decomposition (SVD)

Abstract

Several investigations have proven the existence of monsoons in Indonesia. However, this has received little attention due to the scientific argument that the region of 10° N–10° S is not monsoonal because it receives precipitation all year round. This study used space–time SVD analysis of atmospheric and oceanic field data for 30 years (1990–2020) to detect monsoon signals and related features. The single-field SVD analysis of rainfall revealed that the first mode accounts for only 33% of the total variance, suggesting it is highly variable. Both the PC space and time series show the well-known monsoon pattern. Further, the Indonesian monsoon regimes and phases are defined based on the revealed rainfall features. The wet season lasts from November to April, accounting for more than 77% of annual precipitation. The coupled-field SVD analyses show that Indonesian monsoon rainfall strongly correlates with local SST (PC1 accounts for 70.4%), and the pattern is associated with the Asian winter monsoon. The heterogonous vector correlation map analysis revealed that the related features during the monsoon, including the strengthening and weakening of subtropical anticyclones, the intertwining of westerly wind in the Indian Ocean, and variations in the north–south dipole structure of the ocean temperature, are linked to variations in Indonesia’s monsoon rainfall. This result can serve as the dynamic basis for defining the Indonesian monsoon index in the context of the center of action.

Keywords

• Indonesian monsoon
• rainfall variability
• singular value decomposition
• sea surface temperature