Global Lightning Activity on the Basis of Inversions of Natural ELF Electromagnetic Data Observed at Multiple Stations around the World |
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| Authors: | Alexander Shvets Masashi Hayakawa |
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| Institution: | (1) Usikov Institute of Radiophysics and Electronics, National Academy of Sciences of Ukraine, 12 Academician Proskura St., Kharkov, 61085, Ukraine;(2) Advanced Wireless Communications Research Center, University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan; |
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| Abstract: | The monitoring of global lightning activity and its spatial and temporal variations is known to be very essential for the
study of global warming, the subject of greatest concern to human beings on planet Earth today. As a method of remote sensing
for the global lightning distribution, we have proposed an inverse problem by using the data of natural electromagnetic noise
in the ELF (extremely low frequency) Schumann resonance (SR) band observed simultaneously at a few stations around the world.
The fundamentals of this inversion problem (or ELF tomography) to the SR data have been presented and the first attempt to
deduce the global lightning distribution by means of the real SR data has been performed, which has indicated a possibility
of snapshots of well-known thunderstorm centers on the globe. This ELF tomography consists of two stages. The first stage
is the inversion of the ELF field power spectra to the distribution of lightning intensity by distance relative to an observation
point. The obtained distance profiles of intensity of sources at a few stations are used as tomographic projections for reconstructing
a spatial distribution of sources in the second stage. Maps of the global lightning distributions constructed by the result
of inversions of ELF background field spectra obtained from three stations around the world show that the most active regions
vary meridionally on the diurnal time scale being connected mainly with continental areas in the tropics. We do hope that
this kind of inversion method to multi-stationed ELF data will be of great importance in the future. |
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