atmospheric duct
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Author(s):  
Hanzhong Zhang ◽  
Ting Zhou ◽  
Tianheng Xu ◽  
Yuzhen Wang ◽  
Honglin Hu

2020 ◽  
Vol 10 (02) ◽  
Author(s):  
Imran Ullah Khan

The propagation of microwave (MW) of frequencies above 300 MHz is affected by the existence and properties of the atmospheric duct. Atmospheric ducts exist in many areas of the world ocean, including the Arabian Sea. Located in the Hadley Cell and monsoon region, different seasons bring air masses of different properties into the area under investigation, which has a significant impact on the formation and strength of the atmospheric duct. In this paper, we have done the modeling to analyze the patterns of electromagnetic ducting, which is significant in the southern region of Pakistan in the Arabian Sea. To analyze the real-time scenario, data were collected from three different areas off the southern coast of Pakistan in the northern Arabian Sea to observe the electromagnetic wave's effect on the evaporation ducts. Our analysis results reveal that rising temperature plays a significant role where ducts occur above 30% in the summer months and less than 7% in the spring, autumn, and winter months. It is due to an increase in temperature, especially in summer and autumn months, where humidity gradients play an essential role in creating a higher frequency of duct. The same observations were simulated to view the time analysis of pressure, humidity, and potential temperature in this region, depending upon the refractive index.


Author(s):  
Xiaojing Hao ◽  
Yan-An Liu ◽  
Yixing Zhang ◽  
Hung-Lung Allen Huang

2019 ◽  
Vol 36 (4) ◽  
pp. 557-565
Author(s):  
Hua Wang ◽  
Shipeng Su ◽  
Haichuan Tang ◽  
Lin Jiao ◽  
Yunbo Li

AbstractA method of detecting atmospheric ducts using a wind profiler radar (WPR) and a radio acoustic sounding system (RASS) is proposed. The method uses the RASS to measure the virtual temperature profile and calculate the Brunt–Väisälä frequency; it also uses the WPR to measure the spectral width of the atmosphere and the atmospheric refractive index structure constant. Then the profile of the atmospheric refractive index gradient and modified refractivity are calculated using virtual temperature, spectral width, and the atmospheric refractive index structure constant. Finally, the height and intensity of the atmospheric duct are calculated to achieve continuous monitoring of the atmospheric duct. To verify the height and intensity of the atmospheric duct, comparison experiments between WPR-RASS and radiosondes were carried out from June 2014 to June 2015 in Dalian, Liaoning Province, China. The results show that the profile of modified refractivity by WPR-RASS has exactly the same trend as the radiosondes, the two methods have a good consistency, and the atmospheric duct value from WPR-RASS is in good agreement with that from radiosondes.


Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4428 ◽  
Author(s):  
Qixiang Liao ◽  
Zheng Sheng ◽  
Hanqing Shi ◽  
Lei Zhang ◽  
Lesong Zhou ◽  
...  

The problem of atmospheric duct inversion is usually solved as a single objective optimization problem. Based on ground-based Global Positioning System (GPS) phase delay and propagation loss, this paper develops a multi-objective method including the effect of source frequency and receiving antenna height. The diversity and convergence of solution sets are evaluated for seven multi-objective evolutionary algorithms with three performance metrics: Hypervolume (HV), Inverted Generational Distance (IGD), and the averaged Hausdorff distance (Δ2). The inversion results are compared with the simulation results, and the experimental comparison is conducted on three groups of test situations. The results demonstrate that the ranking of algorithm performance varies because of the different methods used to calculate performance metrics. Moreover, when the algorithms show overwhelming performance using performance metrics, the inversion result is not more close to the real value. In the comparison of computational experiments, it was found that, as the retrieved parameter dimension increases, the inversion result becomes more unstable. When the observed data are sufficient, the inversion result seems to be improved.


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