Covariability of decadal surface air temperature variability over Myanmar with sea surface temperature based on singular value decomposition analysis

Abstract

Abstract The Myanmar’ Southeast Asian country is currently experiencing environmental changes, with temperature change being one the major contributing factors. Although many studies have shown the contribution of anthropogenic activities, the factors sustaining the observed increase in air temperature (TEMP) are not fully understood. We examined the interdependence of the surface TEMP with the sea surface temperature (SST) from 1971 to 2020 on a decadal timescale to predict changes in TEMP over a longer time period. Our analysis showed a pronounced interdecadal change in TEMP, with the highest intensity observed in the 2010s. The results show that the dominant modes of the global SST significantly influence the TEMP variation in the region at the decadal time scale. Indian Ocean (IO) SST-singular value decomposition (SVD)1 presents significant positive (negative) correlations in the southeast, and central (southwest) related to warming (cooling) TEMP in the east, northern tip, and northwest (south-Yangon and Taninthayi, and some parts of the north). The second and third modes of SST-SVD are cooling (warming) SST over the east of the Bay of Bengal (BoB), and along the Myanmar coast, which are associated with cooling(warming) TEMP patterns in the region. Significant negative correlations of decadal TEMP at the annual scale with Pacific Decadal Oscillation (PDO) and North Pacific (NP), the MAMJ with Atlantic Multidecadal Oscillation (AMO) and November–December–January–February (NDJF) with PDO were evidenced. Meanwhile, significant positive correlations were obtained between TEMP and AMO (NP) at the annual scale (NDJF), respectively. These findings provide valuable insights into decadal-scale TEMP patterns and their relationships with SSTs, contributing to a better understanding of TEMP variability in Myanmar, which may be helpful in climate prediction. Predicting surface TEMP on a decadal timescale is helpful in environmental management.