Analysis of thunderstorms in Bangladesh using ARIMA model

Document Type : Research Paper


1 Department of Basic and Applied Sciences, National Institute of Food Technology Entrepreneurship and Management, HSIIDC Industrial Estate, Kundli -- 131028, Haryana, India.

2 Institute of Statistical Research \& Training (ISRT),University of Dhaka,Dhaka - 1000, Bangladesh.

3 Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore-632014, India.

4 Department of Statistics and Biostatistics, Florida State University, USA.


In this paper our main goal is to study the climatology and variability of the frequency of thunderstorm days over Bangladesh region throughout the year. It has been found that the mean thunderstorm days increase significantly from March to May, i.e. during the pre-monsoon season, although the graphical devices show that there does not seem to be much deviation from the occurrences of thunderstorms each year. The mean monthly and seasonal thunderstorm days were maximum in 1993, followed by that in 1997; whereas it was a minimum in the year 1980, with an extension in its frequency in the subsequent years 1981 and 1982. The coefficient of variation of both annual and seasonal thunderstorm days is minimum over the areas of maximum frequency of mean thunderstorm days and vice-versa. The time-domain analysis confirms that the occurrence happened to be maximum in the year 1991, although each and every state did not witness thunderstorms every year. Also some other time-domain models like autocorrelation and seasonal integrated moving average provide adequate evidence for exploring the number of thunderstorms which happen to confirm the trend of occurrence of thunderstorm over the years.


[1] R. Adhikari, R. Agarwal, An Introductory Study on Time Series Modelling and Forecasting, 2013 . https:
[2] M. N. Ahasan, S. K. Debsarma, Impact of data assimilation in simulation of thunderstorm (squall line) event over
Bangladesh using WRF model, during SAARC–STORM Pilot Field Experiment 2011, Nat. Hazards, 75(2)(Jan
1) (2015) 1009-22.
[3] J. S. Armstrong, Findings from evidence-bases forecasting: Methods for reducing forecast error, Int. J. Forecasting,
22 (2006) 583-598.
[4] D. Bikos , J. Finch , J. L. Case, The environment associated with significant tornadoes in Bangladesh, Atmos.
Res., 167(Jan 1) (2016) 183-95.[5] S. Karmakar, D. A. Quadir, M. A. Mannan, Trends in maximum temperature and thunderstorms, their correlation
and impacts on the livelihood of Bangladesh, The Atmosphere, (2015)(Jul 5) 113-29.
[6] M. Khatun, M. A. Islam, M. A. Haque, Studies of thunderstorms and lightning on human health, agriculture and
fisheries in Mymensingh and Jamalpur district of Bangladesh, Progressive Agric., 27(1) (2016)(Apr 29) 57-63.
[7] R. Mahmood, Spatial and temporal analysis of a 17–year lightning climatology over Bangladesh with LIS data.
[8] A. Mannan, N. Ahasan, S. Alam, Study of Severe Thunderstorms over Bangladesh and Its Surrounding Areas
During Pre-monsoon Season of 2013 Using WRF-ARW Model, In High-Impact Weather Events over the SAARC
Region, Springer, Cham., 2015, 3-22.
[9] M. A. Mannan, S. Karmakar, S. K. Devsarma, Climate Feature of the Thunderstorm Days and Thunderstorm
Frequency in Bangladesh, Proc. SAARC Seminar on application of Weather and Climate forecasts in the Socioeconomic Development and Disaster mitigation, 05-07 August(2007), Dhaka, Bangladesh, (2008).
[10] P. Paul, A. Imran, M. J. Islam, A. Kabir, S. Jaman, I. M. Syed, Study of Pre-Monsoon Thunderstorms and
Associated Thermodynamic Features Over Bangladesh Using WRF-ARW Model, Dhaka Univ. J. Sci., 67(2) (2019)
[11] A. Tyagi, D. R. Sikka, S. Goyal, M. Bhowmick, A satellite based study of pre-monsoon thunderstorms
(Nor’westers) over eastern India and their organization into mesoscale convective complexes, Mausam, 63(1)(Jan
1) (2012) 29-54.
[12] M. J. Uddin, M. A. Samad, M. A. Mallik, Impact of Horizontal Grid Resolutions for Thunderstorms Simulation
over Bangladesh Using WRF-ARW Model, Dhaka Univ. J. Sci., 69(1) (2021) 43-51.
[13] M. Wahiduzzaman, A. R. Islam, J. J. Luo, S. Shahid, M. Uddin, S. M. Shimul, M. A. Sattar, Trends and
Variabilities of Thunderstorm Days over Bangladesh on the ENSO and IOD Timescales, Atmosphere, 11(11)(Nov)
(2020) 1176.
[14] M. Wang, Y. Wang, X. Wang and Z. Wei, Forecast and Analyze the Telecom Income based on ARIMA Model,
The Open Cbernetics & Syst. J., 9 (2015) 2559-2564.
[15] P. Zhang, A neural network ensemble method with jittered training data for time series forecasting, Inf. Sci., 177
(2007) 5329-5346.
Volume 13, Issue 1
March 2022
Pages 2897-2909
  • Receive Date: 22 October 2020
  • Revise Date: 16 September 2021
  • Accept Date: 23 September 2021
  • First Publish Date: 05 January 2022