Hurricane genesis modelling based on the relationship between solar activity and hurricanes

Yaroslav Vyklyuk, Milan Radovanović, Boško Milovanović, Taras Leko, Milan Milenković, Zoran Milošević, Ana Milanović Pešić and Dejana Jakovljević ()
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Yaroslav Vyklyuk: Bukovinian University
Milan Radovanović: Serbian Academy of Sciences and Arts
Boško Milovanović: Serbian Academy of Sciences and Arts
Taras Leko: Bukovinian University
Milan Milenković: Serbian Academy of Sciences and Arts
Zoran Milošević: Primary School Janko Veselinović
Ana Milanović Pešić: Serbian Academy of Sciences and Arts
Dejana Jakovljević: Serbian Academy of Sciences and Arts

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 85, issue 2, No 21, 1043-1062

Abstract: Abstract The work examines the potential causative link between the flow of charged particles that are coming from the Sun and hurricanes. For establishing eventual link, the method of correlation analysis is applied, but with the phase shift of 0–5 days. There are nine parameters which are observed as an input, and daily values of the hurricane phenomenon are observed as an output in the period May–October 1999–2013. The results that have been obtained are considerably weak, leading to the need of applying the method of nonlinear analysis. The R/S analysis was conducted to determine the degree of randomness for time series of input and output parameters. The calculated Hurst index of variables X 4–X 9 is persistent (0.71–0.96). That allows us to conclude that the dynamics of these time series is heavily dependent on the same factors or on each other. Unlike the previous index, we have concluded that the behavior of high-energy protons (X 1–X 3) and the number of hurricane time series are completely stochastic. The problem of finding hidden dependencies in large databases refers to problems of data mining. The Sugeno function of zero order was selected as a method of output fuzzy system. Bearing in mind the available equipment, the models had to be shortened to the phase shift of 0–3 days. The “brute-force attack” method was used to find the most significant factors from all data. Within the experiments, six input factors were calculated which became the basis for building the final ANFIS models. These models can predict 22–26 % of the hurricanes.

Keywords: Solar activity; Hurricanes; Hurst index; ANFIS models (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11069-016-2620-6

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