Effects of meteorological parameters on microwave propagation modeling during dust storm
Dust storms are complex meteorological events that significantly impact the propagation of microwave signals, presenting challenges to prediction models which often rely on theoretical scattering principles without considering various meteorological parameters. In this study, meteorological data-inc...
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Main Authors: | , , , , , |
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Format: | Proceeding Paper |
Language: | English |
Published: |
IEEE
2024
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Subjects: | |
Online Access: | http://irep.iium.edu.my/114353/7/114353_Effects%20of%20meteorological%20parameters.pdf http://irep.iium.edu.my/114353/ https://ieeexplore.ieee.org/xpl/conhome/10651580/proceeding |
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Institution: | Universiti Islam Antarabangsa Malaysia |
Language: | English |
Summary: | Dust storms are complex meteorological events that significantly impact the propagation of microwave signals, presenting challenges to prediction models which often rely on theoretical scattering principles without considering various meteorological parameters. In this study, meteorological data-including pressure, visibility, wind speed, temperature, and humidity-were monitored concurrently with signal levels at a 14.4 GHz microwave link operated in Khartoum, Sudan, over the course of a year. The variations in received signal levels were analyzed in relation to these parameters. Initial theoretical predictions, based on measured visibility and dust characteristics, underestimated the actual attenuation observed. Through detailed analysis, it was observed that humidity directly affects dust particle properties. By reassessing the models to incorporate the influence of humidity and other meteorological factors, the predictive accuracy of microwave signal attenuation during dust storms was significantly increased from 0.096 dB/km to 0.576 dB/km for Rayleigh approximation at the visibility limit of 83 m. This research highlights the importance of including comprehensive meteorological data in prediction models to enhance their accuracy in real-world conditions. |
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