The Sensitivity of Microphysical Parameterization Schemes on the Prediction of Tropical Cyclone Mora Over the Bay of Bengal using WRF-ARW Model

Authors

  • Md Jafrul Islam Department of Physics, Dhaka University, Dhaka-1000, Bangladesh
  • Ashik Imran Department of Physics, Dhaka University, Dhaka-1000, Bangladesh
  • Ishtiaque M Syed Department of Physics, Dhaka University, Dhaka-1000, Bangladesh
  • SM Quamrul Hassan Bangladesh Meteorological Department, Agargaon, Dhaka-1207, Bangladesh
  • Md Idris Ali Department of Physics, Khulna University of Engineering & Technology, Khulna, Bangladesh

DOI:

https://doi.org/10.3329/dujs.v67i1.54567

Keywords:

TC, Bay of Bengal, Microphysical parameterization.

Abstract

The sensitivity of Microphysics Parameterization (MP) schemes has been analyzed in the prediction of intensity and track of tropical cyclone (TC) Mora (28th May-31st May, 2017), over the Bay of Bengal (BoB) using WRF model. The study of MP schemes in numerical simulation is important because it includes microphysical process and cloud dynamics that controls the latent heat release in clouds. In this study seven MP schemes (Kessler, Lin, WSM3, Eta, WSM6, MYDM7, and WDM5) are used to study the variation in Mean Sea Level Pressure (MSLP), Maximum Wind Speed (MWS), rainfall distributions, and Tracks. The root mean square error (RMSE) of MSLP, MWS and 72-h simulated tracks are found minimum for WSM3 scheme while the RMSE of rainfall, 48 and 24-h simulated tracks are found minimum for WDM5 scheme. In conclusion, WSM3 and WDM5 schemes may give better results in the prediction of slowly intensifying TC like Mora.

Dhaka Univ. J. Sci. 67(1): 33-40, 2019 (January)

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Published

2019-01-30

How to Cite

Islam, M. J., Imran, A., Syed, I. M., Hassan, S. Q., & Ali, M. I. (2019). The Sensitivity of Microphysical Parameterization Schemes on the Prediction of Tropical Cyclone Mora Over the Bay of Bengal using WRF-ARW Model. Dhaka University Journal of Science, 67(1), 33–40. https://doi.org/10.3329/dujs.v67i1.54567

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Articles