Analysis of the trend of dry spells and how ocean factors affect its patterns during the summer monsoon in Bangladesh using the Mann-Kendall and Frontier Atmospheric General Circulation Model

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Abstract

To assess drought risk, susceptibility to food security, and water resource utilization, it is crucial to comprehend dry spell patterns from a hydrological perspective. Some regional studies have noted an extension of dry spells on a global and regional scale, but it is still unclear how often dry spells occur during the summer monsoon season, which is dominated by rainfall. This study uses the Mann-Kendall trend test to examine the trend of dry spells during Bangladesh's summer monsoon from 1985 to 2022 to close this gap. Using the Frontier Atmospheric General Circulation model and remote sensing methods to examine the effects of ocean elements such as Indian Ocean Dipole (IOD), Sea Surface Temperature (SST), El Niño-Southern Oscillation (ENSO) conditions, and the zonal wind. Daily rainfall data for 34 weather stations were obtained from the Bangladesh Meteorological Department, while surface water occurrence and change intensity data were retrieved from the JRC Global Surface Water Mapping Layers, v1.3 (FAO, UN). The NOAA Physical Sciences Laboratory (PSL) and the Tokyo Climate Center/WMO Regional Climate Centre in RA II (Asia) provided the IOD, SST, ENSO, and zonal wind data. A notable dry spell anomaly over Bangladesh was also noted in this research, with the short, medium-length, and long dry spells increasing in 82.35%, 73.53%, and 50% of weather stations. When El Niño was present, there was less of a dry spell and more during La Niña. The climatic variability of IOD events and SST anomalies in the eastern and western tropical Indian Ocean were also noted by this study to be connected to these anomalous events. The correlation coefficient between summer monsoon rainfall and DMI is 0.34. Throughout the study period, there were changes in the upper atmosphere's and lower troposphere's wind circulation. The study allows the prioritization of regions for drought, effective water resource management, and food scarcity preparedness.

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