Lightning Prediction by Wavelet Analysis of Atmospheric Pressure, Wind Speed and Electrostatic Field Signals
Project/Area Number |
04650231
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Research Category |
Grant-in-Aid for General Scientific Research (C)
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Allocation Type | Single-year Grants |
Research Field |
電力工学
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Research Institution | Tohoku University |
Principal Investigator |
TAKEUCHI Nobunao Tohoku University, Electrical Engineering, Research Associate, 工学部, 助手 (80005420)
|
Co-Investigator(Kenkyū-buntansha) |
NARITA Ken'ichi Miyagi Polytechnic College, Lecturer, 講師
|
Project Period (FY) |
1992 – 1993
|
Project Status |
Completed (Fiscal Year 1993)
|
Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1993: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1992: ¥1,100,000 (Direct Cost: ¥1,100,000)
|
Keywords | Winter Thounderstorm / Wavelet Analysis / Meso-Scale Perturbation / Surface Electric Field / Lightning Prediction / メソスケール擾乱 / 地表面電界 / 冬季雷 / メソスケールじょう乱 / 襲雷予測 |
Research Abstract |
To investigate a winter thundercloud structure, we have bee acquiring data of the electrostatic field and the meteorological variables (atmospheric pressure and wind speed) over a full winter season. These obtained data have been investigating by a wavelet transform method that is a mathematical technique introduced recently for analyzing seismic and acoustic signals. Microscopic variations in time series of the pressure and the wind speed are extracted from not-processed ones using a moving average method, then analyzed by a wavelet method. For each variable, wavelet transform coefficients (modules) are displayd using gray scales as its grade. These figures provide a clearly interpretable visual representation of time series signals. Namely, it is easily understood what the significant scales exist at the concerned time. Mutual correlation coefficients of modules between the pressure and the wind speed variation are also calculated to clarify how these two variables are relted each other. A scale parameter and a phase shift in time are adopted as two dimensional coordinates in the same manner as the wavelet transform. This figure shows whether there is a strong correlation between two elements or not, and if it was, its time and/or position. When thunderclouds pass nearby the observation station, characteristic oscilations are detected in a pressure variation. A strong correlation between the pressure and the wind speed has been proved by a method of a wavelet transform analysis. On the other hand, when a climate is quiet, there is no correlation. A correlation between the presuure variation and the electrostatic fiield at the ground has been also clarified.
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Report
(3 results)
Research Products
(6 results)