Low frequency wind noise contributions in measurement microphones

2008 ◽  
Vol 123 (3) ◽  
pp. 1260-1269 ◽  
Author(s):  
Richard Raspet ◽  
Jiao Yu ◽  
Jeremy Webster
Keyword(s):  
Low Frequency ◽  
Wind Noise

Spatial structure of low-frequency wind noise

2007 ◽  
Vol 122 (6) ◽  
pp. EL223-EL228 ◽  
Author(s):  
D. Keith Wilson ◽  
Roy J. Greenfield ◽  
Michael J. White
Keyword(s):  
Spatial Structure ◽  
Low Frequency ◽  
Wind Noise

Wind Noise Reduction for Outdoor Measurement Microphones With Windscreens

2008 ◽  
Author(s):  
Z. C. Zheng ◽  
Ying Xu
Keyword(s):  
Noise Reduction ◽  
High Frequency ◽  
Low Frequency ◽  
High Flow ◽  
Low Flow ◽  
Computational Techniques ◽  
Wind Noise ◽  
Flow Resistivity ◽  
Materials Used ◽  
Wind Noise Reduction

In this study, effects of windscreen material property on wind noise reduction are investigated at different frequencies of incoming wind turbulence. The properties of porous materials used for the windscreen are represented by flow resistivity. Computational techniques are developed to study the detailed flow around the windscreen as well as flow inside the windscreen that uses a porous material as the medium. The coupled simulation shows that for low-frequency turbulence, the windscreens with low flow resistivity are more effective in noise reduction. Contrarily, for high-frequency turbulence, the windscreens with high flow resistivity are more effective.

Low‐frequency wind noise reduction by spherical windscreens

2007 ◽  
Vol 121 (5) ◽  
pp. 3063-3063 ◽  
Author(s):  
Richard Raspet ◽  
Jeremy Webster ◽  
Jiao Yu
Keyword(s):  
Noise Reduction ◽  
Low Frequency ◽  
Wind Noise ◽  
Wind Noise Reduction

scholarly journals Study on Wind Noise Estimation Method Included in Measurement Data of Low Frequency Sound

2018 ◽  
Vol 43 (2) ◽  
pp. 56-72
Author(s):  
Toshikazu OSAFUNE ◽  
Masayuki SHIMURA ◽  
Takashi NOMURA ◽  
Hiroshi IWABUKI ◽  
Hideaki YASUDA ◽  
...  
Keyword(s):  
Measurement Data ◽  
Estimation Method ◽  
Low Frequency ◽  
Noise Estimation ◽  
Wind Noise ◽  
Frequency Sound

Global gravity wave detections at infrasound stations of the International Monitoring System

2020 ◽  
Author(s):  
Patrick Hupe ◽  
Lars Ceranna ◽  
Alexis Le Pichon
Keyword(s):  
Monitoring System ◽  
Deep Convection ◽  
Weather Prediction ◽  
Low Frequency ◽  
Correlation Method ◽  
International Monitoring System ◽  
Wind Noise ◽  
Global Gravity ◽  
International Monitoring ◽  
Energy And Momentum

<p>Atmospheric gravity waves (GWs) transport energy and momentum horizontally and vertically. The dissipation of GWs can modify the atmospheric circulation at different altitude layers. Knowledge about the occurrence of GWs is thus essential for Numerical Weather Prediction (NWP). However, uniform networks for global GW measurements are rare, and satellite observations generally allow to derive GW parameters in the middle and upper atmosphere only. The barometric sensors of the International Monitoring System (IMS) infrasound network can potentially fill this gap of global GW observations at the Earth’s surface. This infrasound network has been established for monitoring the atmosphere to verify compliance with the Comprehensive Nuclear-Test-Ban Treaty.<br>Two alternative configurations of the Progressive Multi-Channel Correlation Method (PMCC) are discussed for deriving GW detections from the differential pressure data. These configurations focus on GW frequencies equivalent to periods of between 5 min and 150 min. This range covers sources of deep convection, particularly in the tropics, whereas at mid-latitudes, GWs are hard to distinguish from other low-frequency signals, e.g. coherent wind noise. Challenges and perspectives of using the IMS infrasound data for deriving ground-based GW parameters useful for NWP will be discussed.</p>

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