Abstract
Using NASA’s TRMM Lightning Imaging Sensor (LIS) data from 1998 to 2014, this paper presents a 17-year lightning climatology of Bangladesh, at 0.5° × 0.5° spatial resolution. Diurnal, seasonal, monthly and annual variations in the occurrence of lightning flashes were explored. The diurnal regime of lightning is dominated by afternoon/evening events. Overall, peak lightning activity occurs in the early morning (0200 LST) and evening (1900 LST). The distribution of lightning flash counts by season over Bangladesh landmass is as follows: pre-monsoon (69.2%), monsoon (24.1%), post-monsoon (4.6%) and winter (2.1%). Flash rate density (FRD) hotspots were primarily located in the north and north-eastern parts of Bangladesh, with a maximum of 72 fl km−2 year−1. Spatially, the distribution of FRD increases from the Bay of Bengal in the south to relatively higher elevations (of the Himalayan foothills) in the north. A spatial shift in FRD hotspots occurs with change in season. For example, in monsoon season, hotspots of lightning activity move in a south-westerly direction from their pre-monsoon location (i.e. north-eastern Bangladesh) towards West Bengal in India. South and south-eastern parts of Bangladesh experience high lightning activity during post-monsoon season due to regional orographic lifting and low-pressure systems (i.e. cyclone) in the Bay of Bengal. To the best of our knowledge, this is the first study focused on LIS-based lightning climatology over Bangladesh. This baseline study, therefore, is an essential first step towards effective management of lightning-related hazards in Bangladesh.
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Acknowledgements
We would like to express our gratitude to Professor Daniel Cecil, Dr Dennis E. Buechler, Ronald Holle and M.I.R. Tinmaker for assisting us on various occasions during the progress of this work. In addition, comments on the original submission from anonymous reviewers are highly appreciated.
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Dewan, A., Ongee, E.T., Rahman, M.M. et al. Spatial and temporal analysis of a 17-year lightning climatology over Bangladesh with LIS data. Theor Appl Climatol 134, 347–362 (2018). https://doi.org/10.1007/s00704-017-2278-3
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DOI: https://doi.org/10.1007/s00704-017-2278-3