Shannon entropy maximization supplemented by neurocomputing to study the consequences of a severe weather phenomenon on some surface parameters
- 14 Downloads
An information theoretic approach based on Shannon entropy is adopted in this study to discern the influence of pre-monsoon thunderstorm on some surface parameters. A few parameters associated with pre-monsoon thunderstorms over a part of east and northeast India are considered. Maximization of Shannon entropy is employed to test the relative contributions of these parameters in creating this weather phenomenon. It follows as a consequence of this information theoretic approach that surface temperature is the most important parameter among those considered. Finally, artificial neural network in the form of multilayer perceptron with backpropagation learning is attempted to develop predictive model for surface temperature.
KeywordsPre-monsoon thunderstorms Probabilistic information theory Shannon entropy Entropy maximization
Sincere thanks are due to the anonymous reviewers for their thoughtful suggestions. Financial support from DST, Govt. of India, under Project Grant No. SR/WOS-A/EA-10/2017(G) is thankfully acknowledged by Goutami Chattopadhyay. Authors Surajit Chattopadhyay and Goutami Chattopadhyay are thankful to IUCAA, Pune, India, for the hospitality.
- Chaudhuri S, Chattopadhyay S (2003) Viewing the relative importance of some surface parameters associated with pre-monsoon thunderstorms through Ampliative Reasoning. Solstice: An Electronic Journal of Geography and Mathematics, Volume XIV, Number 1. Ann Arbor: Institute of Mathematical Geography, 2003. Persistent URL: http://hdl.handle.net/2027.42/60292
- Klir GJ, Folger TA (2009) Fuzzy-sets. Uncertainty and information. Prentice-Hall, New JerseyGoogle Scholar
- Litta AJ, Idicula SM, Mohanty UC (2013) Artificial neural network model in prediction of meteorological parameters during premonsoon thunderstorms. Int J Atmos Sci, (2013), Article ID 525383, 14 pGoogle Scholar
- Özbaya B, Aydin G, Senay K, Dogruparmaka şÇ, Ayberka S (2011) Predicting tropospheric ozone concentrations in different temporal scales by using multilayer perceptron models. Ecological Informatics 6:242–247Google Scholar
- Varotsos C (2007) Power-law correlations in column ozone over Antarctica. Int J Remote Sens 27:3333–3342Google Scholar
- Varotsos CA, Sarlis NV, Efstathiou M (2017) On the association between the recent episode of the quasi-biennial oscillation and the strong El Niño event. Theoretical and Applied Climatology, On-line first, https://doi.org/10.1007/s00704-017-2191-9