Abstract
Severe atmospheric event can cause huge damage to civilization. Severe thunderstorm is one of those weather events. Analysis of cloud imageries can be used to forecast severe thunderstorm. Convective clouds are one of the main reasons for the formation of severe thunderstorm. Analysis of such cloud imageries by image processing can be used to predict severe thunderstorm. Analysis of RGB values of pixel of cloud imageries can be used to show the formation of severe thunderstorm. Histogram analysis of such cloud imageries can also be used to predict severe thunderstorm. In this study analysis of RGB values of pixels and histograms of cloud imageries has been used to now cast severe thunderstorm with a lead time of 6 to 8 h. This lead time is necessary to save life and property from huge damages.
This is here by certified that this paper has not been submitted, accepted or published anywhere and the work done in the manuscript is original.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Mladjen, C., Janc, D., Vujovic, D., Vuckovic, V.: The effects of a river valley on an isolated cumulonimbus cloud development. Atmos. Res. 66, 123–139 (2003)
Lin, Y.L., Joyce, L.E.: A further study of mechanisms of cell regeneration, development and propagation within a two-dimensional multicell storm. J. Atmos. Sci. 58, 2957–2988 (2001)
Lin, Y.-L., Deal, R.L., Kulie, M.S.: Mechanisms of cell regeneration, propagation, and development within two-dimensional multicell storms. J. Atmos. Sci. 55, 1867–1886 (1998)
Fovell, R.G., Tan, P.-H.: Why multicell storms oscillate. In: 18th Conference on Severe Local Storms. American Meteorological Society, San Francisco, CA, pp. 186–189. Preprints (1996)
Anil Kumar, P., Anuradha, B., Arunachalam, M.S.: Extraction of time series convective cloud profile from doppler weather radar MAX (Z) product using a novel image processing technique. Int. J. Adv. Eng. Res. Dev. 4(7), 2348–4470 (2017)
Gil, J.Y., Kimmel, R.: Efficient dilation, erosion, opening, and closing algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 24(12), 1606–1617 (2002)
Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Wang, W., Powers, J.G.: A description of the advanced research WRF, Version 2. NCAR Tech. Note NCAR/TN-4681STR, p. 88 (2008)
Gryschka, M., Witha, B., Etling, D.: Scale analysis of convective clouds. Meteorol. Z. 17(6), 785–791 (2008)
Souza-Echer, M.P., Pereira, E.B., Bins, L.S., Andrade, M.A.R.: A simple method for the assessment of the cloud cover state in high-latitude regions by a ground-based digital camera. J. Atmos. Ocean. Technol. 23(3), 437–447 (2006)
Hutchison, K.D., Hardy, K.R., Gao, B.C.: Improved detection of optically thin cirrus clouds in nighttime multispectral meteorological satellite using total integrated water vapor information. J. Appl. Meteorol. 34, 1161–1168 (1995)
Jolivet, D., Feijt, A.J.: Cloud thermodynamic phase and particle size estimation using the 0.67 and 1.6 mm channels from meteorological satellites. Atmos. Chem. Phys. Discuss. 3, 4461–4488 (2003)
Glantz, P.: Satellite retrieved cloud optical thickness sensitive to surface wind speed in the subarcticmarine boundary layer. Environ. Res. Lett. 5, 034002 (2010). https://doi.org/10.1088/1748-9326/5/3/034002
Ghonima, M.S., Urquhart, B., Chow, C.W., Shields, J.E., Cazorla, A., Kleiss, J.: A Method for Cloud Detection and Opacity Classification Based on Ground Based Sky Imagery, pp. 4535–4569. Copernicus Publications, Göttingen (2012)
McAndrew, A.: An Introduction to Digital Image Processing with Matlab Notes for SCM2511 Image Processing 1. School of Computer Science and Mathematics Victoria University of Technology, Footscray (2004)
Himadri Chakrabarty, C.A., Murthy, S.Bhattacharya, Gupta, A.D.: Application of artificial neural network to predict squall-thunderstorms using RAWIND data. Int. J. Sci. Eng. Res. 4(5), 1313–1318 (2013). (ISSN 2229-5518)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bhattacharya, S., Chakrabarty, H.B. (2020). Studies on Radar Imageries of Thundercloud by Image Processing Technique. In: Sharma, N., Chakrabarti, A., Balas, V. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 1042. Springer, Singapore. https://doi.org/10.1007/978-981-32-9949-8_25
Download citation
DOI: https://doi.org/10.1007/978-981-32-9949-8_25
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-32-9948-1
Online ISBN: 978-981-32-9949-8
eBook Packages: EngineeringEngineering (R0)