Ability to Forecast standardized precipitation index in Vietnamese Mekong Delta for dry season months based on sea surface temperature

Abstract

Drought has major impacts on agriculture, society, and ecosystems, so early prediction of drought plays an important role in mitigating its impacts. This study investigates the relationship between the Standardized Precipitation Index (SPI) in the Mekong Delta and global sea surface temperature (SST) in order to find potential variables for improving SPI forecast quality. The method used in determining potential predictors is based on the analysis of multiple correlation coefficients. Based on these potential predictors, SPI is predicted by stepwise regression along with the application of Leave-one-out cross-validation technique. The data used in this study is the rainfall of 15 stations in the Vietnamese Mekong Delta and the global SST from 1977 to 2020. Research results show that there is a pair of variables that have the best relationship with SPI in the study area, they are SST on Niño 3.4 region and SST in the region with latitude from 13 °N to 23 °N and longitude from 116 °E to 126 °E. When the forecast term is from 1 to 2 months, using this pair of variables gives better forecast quality than using only the predictors from the Niño indices.

Keywords

• SST
• SPI
• El Niño and La Niña
• Mekong Delta