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Reseach Article

Prediction of Severe Thunderstorms Applying Neural Network using RSRW Data

by Himadri Chakrabarty, Sonia Bhattacharya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 16
Year of Publication: 2014
Authors: Himadri Chakrabarty, Sonia Bhattacharya
10.5120/15712-4362

Himadri Chakrabarty, Sonia Bhattacharya . Prediction of Severe Thunderstorms Applying Neural Network using RSRW Data. International Journal of Computer Applications. 89, 16 ( March 2014), 1-5. DOI=10.5120/15712-4362

@article{ 10.5120/15712-4362,
author = { Himadri Chakrabarty, Sonia Bhattacharya },
title = { Prediction of Severe Thunderstorms Applying Neural Network using RSRW Data },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 16 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number16/15712-4362/ },
doi = { 10.5120/15712-4362 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:09:53.519007+05:30
%A Himadri Chakrabarty
%A Sonia Bhattacharya
%T Prediction of Severe Thunderstorms Applying Neural Network using RSRW Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 16
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Severe thunderstorm is a seasonal and mesoscale atmospheric event. The sudden increase in wind speed and the other weather features during this event have various destructive effects on the people. Correct forecasting with enough lead time is very important to minimize the damages occurring in day-to-day life. In this paper, artificial neural network technique has been applied to predict the severe thunderstorm. Multilayer Perceptron (MLP) has been applied on the weather parameters of moisture difference, adiabatic lapse rate and vertical wind shear which were recorded by the radiosonde-rawind (RSRW) in the early morning at 06. 00 am local time. MLP classified and predicted 'severe storm' and 'no storm' days in this work correctly nearly up to 70% having around 12 hours lead time.

References
  1. Chakrabarty 1, Himadri, C. A. Murthy, Sonia Bhattacharya and Ashis Das Gupta, May, 2013. "Application of Artificial Neural Network to Predict Squall-Thunderstorms Using RAWIND Data", International Journal of Scientific & Engineering Research, Volume 4, Issue 5, pp. 1313-1318, ISSN 2229-5518.
  2. Ludlam, F. H. , Sept. , 1963. "Severe Local Storms", Meteorological Monographs, American Meteorological Society, Volume 5, Number 27, pp. 1-30.
  3. Newton, C. W. , Sept. , 1963. "Dynamics of Severe Convective Storms", Meteorological Monographs, American Meteorological Society, Volume 5, Number 27, pp. 33-58.
  4. Ramaswami, C. , 1956. "On the sub-tropical jet stream and its role in the development of large-scale convection", Tellus, 8, 26-60.
  5. Chakrabarty, Himadri, 2010. "Synoptic Aspects of Nor'wester and its Impact to the People in Kolkata, North-East India", International Journal of Science in Society, Vol. 1, Issue 4, pp. 135-148.
  6. Chakrabarty 2, Himadri, C. A. Murthy, and Ashish Das Gupta, 2013. "Application of Pattern Recognition Techniques to Predict Severe Thunderstorms", International Journal of Computer Theory and Engineering, Vol. 5, No. 6, pp. 850-855.
  7. Moran, J. M. , M. D. Morgan, and P. M. Pauley, 1997. "Meteorology: The Atmosphere and the Science of Weather", 5th Edition, Prentice Hall.
  8. Jigme Singye, Katsumi Masugata, Tadakuni Murai, Iwao Kitamura and Honda Kontani, 2006. "Thunder Storm Tracking System using Neural Networks and Measures Electric Field from a few Field Mills", Journal of Electrical Engineering, vol 57 No. 2, , 87-92.
  9. Sharma Sanjay, Devajyoti Dutta, J. Das, and R. M. Gariola, 2009. "Nowcasting of severe storms at a station by using the Soft Computing Techniques to the Radar Imagery", 5th European Conference on Severe Storms, Landshut-Germany, 2009.
  10. Marzban Caren, June, 2003. "Neural Networks for Postprocessing Model Output: ARPS", Monthly Weather Review, Volume 131, 1103-1111, June, 2003.
  11. Yegnanarayana B, 1999, Artificial Neural Networks, Prentice Hall of India Pvt Ltd.
  12. Chung, C. Y. C. and V. R. Kumar, 1993. "Knowledge acquisition using a neural network for weather forecasting knowledge-based system," Neural Computing & Applications, Springer, London, Volume 1, Number 3, pages. 215-223.
  13. Volland, H. , 1995. Handbook of Atmospheric Electrodynamics, Vol. 1.
  14. Richard Rotunno and Joseph B. Klemp, 1982. "The Influence of the Shear-Induced Pressure Gradient on Thunderstorm Motion", Monthly Weather Review, Volume 110, pp. 136-151.
Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Network Multilayer Perceptron RSRW Severe Thunderstorm and Wind-shear.