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Study of Pre-monsoon Thunderstorms and Associated Thermodynamic Features Over Bangladesh Using Wrf-arw Model

Pappu Paul
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Ashik Imran
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Md. Jafrul Islam
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Alamgir Kabir
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Sahadat Jaman
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Ishtiaque M. Syed
Department of Physics, Dhaka University, Dhaka-1000, Bangladesh

Abstract/ Executive Summary:

Thunderstorm is a mesoscale system (from a km to below thousands of km and sustaining less than one hour). Two premonsoon thunderstorms events are analyzed in this study which are named as event-1 (0030-0150 UTC of 19 April 2018 over Chattogram) and event-2 (0600-1000 UTC of 4 May 2018 over Dhaka). To predict these events Mean Convective Available Potential Energy (mCAPE), Mean Convective Inhibition Energy (mCINE), K Index (KI), Total totals Index (TTI), wind distribution, and relative humidity (RH) are investigated.The model simulated mCAPE and mCINE values, 18 hours before the events, are found greater than 1700 J/Kg and less than 100 J/Kg respectively which satisfies the conditions for thunderstorms to occur.The KI values are close to 40⁰C and TTI values are greater or equal to 45⁰C for both events. The wind patterns and the high value of mid –tropospheric RH also favors the formation of severe thunderstorm.

Keywords: Thunderstorm, mCAPE, mCINE, KI, TTI, RH.

Location: Chittatong and Dhaka

Start Date: 00-04-2018

End Date: 00-05-2018

Program Area: Risk Management in Agriculture

Non-commodity: Thunderstrom

Objectives:

To identify the Study of Pre-Monsoon Thunderstorms and Associated Thermodynamic Features Over Bangladesh Using WRF-ARW Model

Methodology:

The Advanced Research Weather Research and Forecast (ARW) version 3.8.1 mesoscale model developed by the National Center for Atmospheric Research (NCAR) is used in this study. The model is used for both research and operational forecasting and covers different meteorological phenomena. It includes multiple dynamical cores, a three dimensional dimensional variational data assimilation system and software architecture to allow computational parallelism and system extensibility. The model includes fully compressible non-hydrostatic Euler equations and different prognostic variables that have conservation properties. The terrain following hydrostatic pressure is considered as the vertical coordinate. The equations also include the effects of moisture, Coriolis and curvature terms. The dynamics employed and domain configurations in the model for the present study. Model was run using six hourly NCEP (National Center for Environmental Prediction)-FNL datasets on 1⁰ x 1⁰ grids. The model outputs help to investigate the synoptic and environmental characteristics for these events. The Mean Convective Available Potential Energy (mCAPE), Mean Convective Inhibition Energy (mCINE), K-Index(KI), Total totals Index (TTI), wind speed, wind direction, relative humidity are investigated.

Source of Information: Dhaka Univ. J. Sci. 67(2): 151-156, 2019 (July)

Article Link (Online Journal):

Funding Source:

1.

Budget:

Total Budget (Tk.) :

Achievement/Findings:

For predicting the thunderstorm events several stability indices (mCAPE, mCINE, KI, TTI), wind distribution, and RH are analyzed using WRF model. More than 18 hours before the event-1 the model simulated mCAPE and mCINE values are found greater than 1700 J/Kg and less than 100 J/Kg respectively and for event-2 these values are found around 2500 J/Kg and below 50 J/Kg respectively. The KI and TTI values for event-1 are found 43⁰C and 50⁰C respectively and for event-2 these values are found around 40⁰C and 45⁰C respectively, 18 hours before the event in both cases. The value of all these stability indices agrees with the threshold values stated. The wind patterns and the high value of mid –tropospheric RH (>70%) also favors the formation of severe thunderstorm. So, it can be concluded that the WRF-ARW model can predict the thunderstorm pretty well even 18 hours before the event. But for more accurate forecasting more studies with better resolutions are needed.

Knowledge Management: Journal