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The present study examines the effects of convective available potential energy (CAPE), temperature and humidity on the spatiotemporal variation of thunderstorm (TS) frequency over Bangladesh using an Empirical Orthogonal Function (EOF) approach. TS and CAPE, temperature, humidity data have been used for 38-year (1980–2017) and collected from the Bangladesh Meteorological Department and ERA-40 reanalysis, respectively. Mann-Kendall nonparametric trend test, Sen's slope, Pearson's correlation and EOF modes are applied to understand the variability of TS and the effects of CAPE, temperature and humidity on it. Results show a decrease in TS frequency in Bangladesh at a rate of −0.408/year annually and − 0.384/year during pre-monsoon, when it is most prevalent. The TS frequency spatially varies widely over Bangladesh. The present study shows an increase in TS in the areas where it is less prevalent and a decrease in the areas where it occurs more. CAPE shows a decreasing trend during winter and an increasing trend during post-monsoon and at an annual scale. TS frequency is positively correlated with CAPE and humidity and negatively with temperature. Therefore, the rising temperature may be the cause of decreasing TS frequency in Bangladesh. The findings can be useful for hazard management planning in Bangladesh. [ABSTRACT FROM AUTHOR]

The present study analyzed a long-term record of major floods over Bangladesh under the influence of El Niño–Southern Oscillation (ENSO). Bangladesh is highly vulnerable to floods, and ENSO has a great influence on it. El Niño (La Niña) represents the warm (cold) phase of the ENSO cycle. Southern Oscillation Index data and a long-term flood records have been identified from National Oceanic and Atmospheric Administration, Bureau of Meteorology, Australia, and historical archives, respectively. Synoptic features—precipitation, wind, geopotential height, precipitable water, relative humidity, and surface runoff data—were used to examine the influence of ENSO. Result shows that the Indian summer monsoon contributes the major flood events and largely influenced by both El Niño and La Niña events, with a slightly higher frequency for the latter. Physical mechanisms (distribution of precipitation, wind, geopotential height, precipitable water, relative humidity, and surface runoff) supported these flood events; however, they are quite distinct during El Niño and La Niña condition. Moreover, ENSO's impacts to the Bangladesh region are different to the west part of the monsoon region. Therefore, if ENSO forecast is reliable, the predictability of the monsoon-related flood events can be improved. [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) is one of the most devastating weather systems that causes enormous loss of life and property in the coastal regions of Bay of Bengal (BoB). Statistical forecasting of TC occurrence can help decision-makers and inhabitants in shoreline zones to take necessary planning and actions in advance. In this study, we have investigated the impact of El Niño–Southern Oscillation (ENSO) on the frequency of TC over the BoB by using 100 years TC and Southern Oscillation Index data. The frequency of TC is approximated through observation and Markov Chain Monte Carlo (MCMC) simulation. Two-sample Student's t test has been applied for examining the statistical significance where the results are significant at 5% level for all cyclonic disturbances. The monthly and seasonal distribution show this feature more distinctly. The total annual frequency of depressions and cyclonic storms in El Niño and La Niña conditions does not differ much, but the monthly/seasonal distribution shows high differences for certain months and seasons. The simulated frequency of TC landfall using MCMC matches well with the observation. The proposed methodology is illustrated through a case study in BoB rim countries-Bangladesh, India, Sri Lanka and Myanmar. Poisson and Bayesian regression have also been used to predict the probabilities of TC frequency over the BoB. Both the regression approaches show 10 and 32% improvement than climatology for the forecast and cross-validation skill respectively. We have also analyzed TC impact over Bangladesh as a case study. Possible links of the variation of TC activities with the largescale geographical distribution of sea surface temperature, vertical wind shear, vorticity, moisture and relative humidity are also explored. [ABSTRACT FROM AUTHOR]

In this study, the contribution of El Niño–Southern Oscillation (ENSO) to the rainfall and temperature over Bangladesh has been investigated. Rainfall, temperature, and ENSO data have been used for a period of 60 years (1958–2017). This paper examines the spatial distribution of rainfall and temperature across Bangladesh and the results suggest that the distribution of rainfall and temperature varies with seasons. A geographically weighted regression, Student's t test, correlation coefficient, and cross-wavelet transform were used to reveal whether different types of ENSO contribute strongly or weakly to rainfall and temperature in Bangladesh. Findings indicate that the ENSO has a strong connection with rainfall and temperature over Bangladesh. [ABSTRACT FROM AUTHOR]

In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model's fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh. [ABSTRACT FROM AUTHOR]

Thunderstorms (TS) are one of the most devastating atmospheric phenomena, which causes massive damage and adverse losses in various sectors, including agriculture and infrastructure. This study investigates the spatiotemporal variabilities of TS days over Bangladesh and their connection with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The TS, ENSO and IOD years' data for 42 years (1975–2016) are used. The trend in TS days at the spatiotemporal scale is calculated using Mann Kendall and Spearman's rho test. Results suggest that the trend in TS days is positive for all months except December and January. The significant trends are found for May and June, particularly in the northern and northeastern regions of Bangladesh. In the decadal scale, most of the regions show a significant upward trend in TS days. Results from the Weibull probability distribution model show the highest TS days in the northeastern region. The connection between TS days and ENSO/IOD indicates a decrease in TS activities in Bangladesh during the El Niño and positive IOD years. [ABSTRACT FROM AUTHOR]