Spatiotemporal changes and modulations of extreme climatic indices in monsoon-dominated climate region linkage with large-scale atmospheric oscillation

Abstract

Spatiotemporal changes in six precipitation and five temperature extreme indices of Bangladesh and their linkage with nine ocean-atmospheric oscillation indices have been evaluated in this study to provide necessary information for adaptation planning and development of early warning systems. Daily maximum and minimum temperatures and precipitation for the period 1980–2017 recorded at 20 stations, homogeneously distributed over the country, were employed for this purpose. Modified Mann-Kendall (MMK) test was used to evaluate trends in weather extremes, and detrended fluctuation analysis (DFA) was employed to anticipate the possible continuation of existing trends in the future. The cross-wavelet transform (CWT) was used to evaluate the linkage of weather extremes with oscillation indices in the time-frequency domain. The results indicate an increase in hot extremes and a decrease in cool indices in Bangladesh. An increase in the continuous dry day (CDD) and one-day maximum precipitation (RX1day) was also observed, indicating gradual drying and more susceptibility to flash floods at the same time. DFA revealed the possible continuation of existing trends in temperature and precipitation indices. Almost all the climatic extreme indices of Bangladesh were found to follow periodic cycles with different frequencies. The hot extremes were significantly associated with five out of nine oscillation indices, including Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), East Asian Summer Monsoon Index (EASMI), Sunspot, and South Asian Summer Monsoon Index (SASMI), while cool indices were linked with AMO only. Among the precipitation indices, only CDD was positively related to AO, El Niño Southern Oscillation (ENSO), and Southern Oscillation Index (SOI) and negatively associated with the Pacific Decadal Oscillation (PDO). Analysis of circulation patterns using reanalysis datasets explored that elevated summer geopotential height, no visible anticyclonic center, reduced high cloud cover, and enhanced low cloud covers contributed to increasing hot extremes in Bangladesh.