Noise due to surface wind and temperature is a problem in infrasound. Efficiency of IMS network concerns scientists. It is obvious to find the causes of deficiencies of detection of infrasound station by studying back...Noise due to surface wind and temperature is a problem in infrasound. Efficiency of IMS network concerns scientists. It is obvious to find the causes of deficiencies of detection of infrasound station by studying background noise power with respect to the surface wind and the temperature. Data measured by MB2000 microbarometer of infrasound station I33MG are used for the study. Infrasound records are separated into 4 frequency bands centered respectively at: 1 Hz, 0.25 Hz, 0.0625 Hz and 0.0156 Hz. Effects of surface wind and temperature are studied by plotting the variations of the background noise power with respect to the temperature or wind speed in the four considered frequency bands and compared with the median of background noise power. The influence of temperature is manifested by a reduction in the number of low-frequency detection. The surface wind reduces the number of detection at a high frequency. An exponential function is proposed to predict the variations of the noise power in different observation frequencies and temperature and wind conditions. The views expressed herein are those of the authors and do not necessarily reflect the views of the CTBTO Preparatory Commission.展开更多
文摘Noise due to surface wind and temperature is a problem in infrasound. Efficiency of IMS network concerns scientists. It is obvious to find the causes of deficiencies of detection of infrasound station by studying background noise power with respect to the surface wind and the temperature. Data measured by MB2000 microbarometer of infrasound station I33MG are used for the study. Infrasound records are separated into 4 frequency bands centered respectively at: 1 Hz, 0.25 Hz, 0.0625 Hz and 0.0156 Hz. Effects of surface wind and temperature are studied by plotting the variations of the background noise power with respect to the temperature or wind speed in the four considered frequency bands and compared with the median of background noise power. The influence of temperature is manifested by a reduction in the number of low-frequency detection. The surface wind reduces the number of detection at a high frequency. An exponential function is proposed to predict the variations of the noise power in different observation frequencies and temperature and wind conditions. The views expressed herein are those of the authors and do not necessarily reflect the views of the CTBTO Preparatory Commission.
