An Investigation of the Influence of the Indian Ocean Dipole, El Nino, and La Nina on the Summer and Winter Season Rainfall over Bangladesh Using Two High Resolution Gridded Datasets

Seasonal precipitation brings much-needed rain for the Bangladeshi subsistence farmer whose livelihood largely depends on rainfed agriculture, carrying water for the 700 rivers and maintaining the river navigation system. However, the seasonal rainfall triggers catastrophic monsoon flooding almost every year in Bangladesh. It creates havoc in the socioeconomic conditions of Bangladesh, a country of more than 170 million people, of which 24.6 % are multi-dimensionally poor, and an additional 18.2 % are classified as vulnerable to multidimensional poverty based on the 2019 global Multidimensional Poverty Index (M.P.I.). Although many studies identified the role of Indian Ocean Dipole (IOD), El Nino, and La Nia on the South Asian Monsoon rainfall separately, a few focused on Bangladesh. A handful of literature on Bangladesh revealed contrasting or poor teleconnection patterns between Bangladesh rainfall and IOD, El Nino, and La Nia. Many recent studies also show a changing teleconnection pattern between large-scale oscillation and South Asian monsoon rainfall. Despite seasonal rainfall significantly impacting Bangladesh's socioeconomic conditions, the interannual variability of rainfall is poorly understood due to the lack of high-quality observed meteorological data at higher spatiotemporal resolution.The current study investigated the influence of different (positive, negative, and neutral) phases of IOD, El Nino, and La Nia on the summer and winter season rainfall over Bangladesh from 1976 to 2020 using two recently published high-resolution gridded datasets: 1) Bangladesh Gridded Rainfall (BDGR) and 2) the Enhancing National Climate Services for Bangladesh Meteorological Department (ENACTS-BMD). The BDGR data was published in 2022 by a team led by Ashraf Dewan of Curtin University, Australia, and is a monthly gridded rainfall data from 1901 to 2018 at 1 km x 1 km resolution. The ENACTS-BMD data started in January 1981 and produced near real-time at daily, monthly, and decadal time resolution and 0.05° x 0.05° horizontal resolution published in 2020 by Nachiketa Acharya of Columbia University, U.S.A. Although both datasets show the summer rainfall, Bangladesh is positively correlated with La Nina and negatively correlated with El Nino years. We find opposite relationships during the winter season. During winter, Bangladesh receives above-average rainfall during El Nino years and below-average rainfall during La Nina years. The higher the amplitude of El Nino and La Nina events, the greater control they play over Bangladesh's rainfall. Bangladesh's summer rainfall is positively correlated with the positive and neutral phases of the IOD. Overall, the two datasets clearly demonstrate the influence of IOD, El Nino, and La Nina on Bangladesh's seasonal rainfall pattern, but rainfall amount and spatial distribution differ significantly. In summary, our study findings will improve our understanding of the characteristics of Bangladesh rainfall and help Bangladeshi farmers select their crop type and disaster agencies to save lives and properties from devastating monsoon flooding.