Showing papers in "Journal of atmospheric electricity in 2011"

A study on global temperature and thunderstorm activity by using the data of Schumann resonance observed at Nakatsugawa, Japan

Abstract: In this paper we use a long-term record of the Schumann resonance (SR) intensity observed in Nakatsugawa, Japan and global lightning activity to study the global temperature change. The cumulative magnetic field energy from the first and second modes of SR intensity for 4 years is derived for two horizontal components. The monthly dependence of field energy is compared with the global lightning and temperature data for the corresponding time period. As a result SR energy is found to be correlated well with the temperature in the middle latitude and global lightning activity. Furthermore the principal component analysis (PCA) is applied to extract the periodical component in each data set. The annual component of SR energy has a significant correlation with the middle latitude temperature, whilst the semi-annual component of the SR energy has a significant correlation with low latitude temperature. The correlation pattern varies with magnetic components and the contribution from African and Asian thunderstorm activity to the global SR is studied.

Source models for “parametric” Q-burst

Abstract: Changes are modeled of parameters of the global electric circuit caused by the giant gamma ray burst arrived at the Earth’s dayside on December 27 2004. Modification of the air conductivity by gamma rays alters the leakage current of the Earth–ionosphere cavity and causes a discrete radio pulse. Electric parameters of the air at the tropopause–troposphere altitudes play the key role. ELF spectrum of the “parametric” current moment is ‘red’ or ‘white’ depending on the particular model. Sample spectra and waveforms are presented of the parametric Q–burst.

2010 AGU Fall Meeting 参加報告

Abstract: A Cyber-Infrastructure for a Virtual Observatory and Ecological Informatics System – VOEIS C. Izurieta1; G. Poole2; B. L. McGlynn2; W. F. Cross2; L. A. Marshall2; G. A. Jacobs3; S. Cleveland3; I. Judson3; F. R. Hauer4; B. Kucera5 1. Computer Science, Montana State University, Bozeman, MT, United States. 2. Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, United States. 3. Center for Computational Biology, Montana State University, Bozeman, MT, United States. 4. Division of Biological Sciences, University of Montana, Missoula, MT, United States. 5. Center for Computational Sciences, University of Kentucky, Lexington, KY, United States.