Hostname: page-component-76fb5796d-qxdb6 Total loading time: 0 Render date: 2024-04-27T01:29:45.958Z Has data issue: false hasContentIssue false

Extrapolating cosmic ray variations and impacts on life: Morlet wavelet analysis

Published online by Cambridge University Press:  01 July 2009

N. Zarrouk
Affiliation:
Laboratoire de Physique de la Matière Condensée, Faculté des Sciences de Tunis, Tunisie
R. Bennaceur
Affiliation:
Laboratoire de Physique de la Matière Condensée, Faculté des Sciences de Tunis, Tunisie

Abstract

Exposure to cosmic rays may have both a direct and indirect effect on Earth's organisms. The radiation may lead to higher rates of genetic mutations in organisms, or interfere with their ability to repair DNA damage, potentially leading to diseases such as cancer. Increased cloud cover, which may cool the planet by blocking out more of the Sun's rays, is also associated with cosmic rays. They also interact with molecules in the atmosphere to create nitrogen oxide, a gas that eats away at our planet's ozone layer, which protects us from the Sun's harmful ultraviolet rays. On the ground, humans are protected from cosmic particles by the planet's atmosphere.

In this paper we give estimated results of wavelet analysis from solar modulation and cosmic ray data incorporated in time-dependent cosmic ray variation. Since solar activity can be described as a non-linear chaotic dynamic system, methods such as neural networks and wavelet methods should be very suitable analytical tools. Thus we have computed our results using Morlet wavelets. Many have used wavelet techniques for studying solar activity. Here we have analysed and reconstructed cosmic ray variation, and we have better depicted periods or harmonics other than the 11-year solar modulation cycles.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Attolini, M.R. et al. (1975). Planet. Space Sci. 23, 1603.Google Scholar
Chao, B.F. & Naito, I. (1995). Wavelet analysis provides a new tool for studying Earth's rotation. EOS, Transactions, American, Geophysical Union 76, 161165.Google Scholar
Grzesiac, A.W.M., Sadowski, M. & Rothkaehl, H. (1997). Analysis of ionospheric plasma turbulence with the wavelet transform. In Proc. Int. Symp. “Plasma97”, Jarnoltovek, 1, 391, eds Sadowski, M. & Rothkaehl, H. Space Res. Center, Polish Academy of Sciences, Poland.Google Scholar
Kudela, K. et al. (1991). J. Geophys. Res. 96, 15871.CrossRefGoogle Scholar
Kudela, K., Storini, M., Antalova, A. & Rybak, J. (2001). On the wavelet approach to cosmic ray variability. In Proc of ICRC 2001: 3773 c. Copernicus Gesellschaft.Google Scholar
Lundstedt, H., Liszka, L. & Lundin, R. (2005). Solar activity explored with new wavelet methods. Ann. Geophys. 23, 15011511.Google Scholar
Mallat, S. (1999). A Wavelet Tour of Signal Processing. Ecole Polytechnique, Paris Courant Institute, New York University.Google Scholar
Morlet, J., Arehs, G., Forgeau, I. & Giard, D. (1982). Wave propagation and sampling theory. Geophys. 47, 203.Google Scholar