Variations in Non-Linearity in Vertical Distribution of Microwave Radio Refractivity.

Adediji, A. T.; Ogunjo, Samuel

doi:10.2528/pierm14041606

Cited by 16 publications

(8 citation statements)

References 25 publications

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“…Points that are greater than a threshold are marked as false neighbors. The dimension with the lowest normalize distance is chosen as the optimal embedding dimension (Adediji & Ogunjo, 2014).…”

Section: Methodsmentioning

confidence: 99%

Evolution of Dynamical Complexities in Geospace as Captured by Dst Over Four Solar Cycles 1964–2008.

et al. 2021

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Geospace refers to the region of the outer space near Earth; this includes the upper atmosphere, ionosphere as well as the magnetosphere. Geospace basically span through region of space which goes from the solar photosphere to the mesosphere of the Earth. The studies of the dynamics of geospace has continued to attract attention due to its significant impact on the present day space-dependent technological operations. Today, health and functionality of thousands of satellites domiciled in space environment, has made the understanding of space weather which is defined as the conditions in the outer space a global concern. The Earth's magnetosphere which is the intermediary region between the Earth's ionosphere and the outer space has been described by Donner et al. (2019) as a complex system composed of several nonlinearly coupled subsystems, within which multiple interconnected processes act on a wide range of spatial and tem-

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Section: Methodsmentioning

confidence: 99%

Evolution of Dynamical Complexities in Geospace as Captured by Dst Over Four Solar Cycles 1964–2008.

et al. 2021

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“…Refractivity gradient in 1 km interval above ground are important for the estimation of super–refraction and ducting phenomena, and their effects on radar observations and Very high frequency (VHF) the field strength at points beyond the horizon cannot be undermined [7]. It is a well-known fact that refractivity gradients can be determined either by the direct method using refractometers or indirectly using a fixed measuring methods such as TV tower, radiosonde measurement, remote sensing techniques, statistical and deterministic model [8]. In this paper, there is still the need to further extend the research to different locations and compare the complexity and the chaotic trends vividly.…”

Section: Introductionmentioning

confidence: 99%

“…Aside from time series and phase plot reconstruction, the paper also employed Average Mutual Information (AMI), False Nearest Neighbor (FNN), Lyapunov Exponent (LE), Tsallis Entropy (TE) and Recurrence Plot (RP) to analyze radio refractivity gradient between 2011 and 2012 using Atmospheric data. Unlike previous research, where the focus is mainly on a single station “Akure” in Nigeria using different heights [8], [9], while the present research actually covers selected stations across Nigeria with emphasis on rainy season, dry season and transition periods. The onset of the dry season, October and November, and the onset of the rainy season, March and April, serves as the rain-harmattan transition phase and it was chosen for consideration.…”

Section: Introductionmentioning

confidence: 99%

Comparative study on Radio Refractivity Gradient in the troposphere using Chaotic Quantifiers

Ojo

Adelakun

Edward

2019

Heliyon

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Complexity and nonlinear trend in the internal activities of the troposphere has been a great factor affecting the transmission and receiving of good quality of signals globally. In lieu of this, prediction of chaos and positive refractivity gradients for line-of-sight microwave radio paths is necessary for designing radio systems. Complexity in the troposphere due to changes in meteorological parameters can lead to the strong negative gradient (or super-refraction) which afterward lead to interference between terrestrial links and satellite earth stations. In this paper, a comparative study on the degree of complexity of Radio Refractivity Gradient (RRG) using Chaotic Quantifiers (CQ) such as Phase Plot Reconstruction (PPR), Average Mutual Information (AMI), False Nearest Neighbor (FNN), Lyapunov Exponent (LE), Tsallis Entropy (TS) and Recurrence Plot (RP) are discussed extensively. The RRG data (2011-2012) used in this work were obtained for 0 m to 100 m, from the archives of Tropospheric Data Acquisition Network (TRODAN) from five different stations namely; Akure ( Geo . ), Enugu ( Geo . ), Jos ( Geo . ), Minna ( Geo . ) and Sokoto ( Geo . ). The chaotic quantifiers are used to investigate the degree of complexity in the 30 minutes interval atmospheric data from the selected locations which is specified into rainy, dry and transition season months. The parallel and short diagonal lines observed depicts the evidence of chaos. However, the observed result shows that the RRG is higher during the rainy season than the dry season. In other words, the information is valid for the proposed data analysis, since the LE is actually directly proportional to the TE. Also, the results further show that the rainy season months exhibit higher chaoticity than the dry season months, which is equivalent to high radio refractivity gradient observed across the selected stations.

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“…One of the most common ways of characterizing the effect of local climate on propagation is through the computation of radio refractivity [2]. At frequencies below 10 GHz, radio waves show different degrees of bending in the atmosphere depending on the prevailing atmospheric conditions [3]. Also, leaves being part of the basic components of any vegetation canopy, whose moisture content act as electromagnetic scatterer, must be modelled to determine the total reflectivity of any given vegetation canopy.…”

Section: Introductionmentioning

confidence: 99%

Variation of Surface Refractivity with Soil Permittivity and Leaf Wetness in a Tropical Location

Kayode¹,

Ashidi²,

Oni³

et al. 2019

IJWMT

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Radio signal transmitting above the ground surface experiences attenuation as a result of absorption by vegetation and hydrometeors, refraction due to turbulence in weather parameters; and reflection from ground surface. In this study, attempt was made to compute surface refractivity from its constituent parameters, and investigate its variation with leaf wetness and soil permittivity, at seven (7) different stations across Ondo state, Nigeria. Data for the research were obtained by in-situ measurement using Davis 3125 Vantage Pro2 weather station having sensors for measuring temperature, pressure, relative humidity, leaf wetness and soil moisture content. Measurement was carried out round the clock at 10 minutes integration time for a period of two weeks at each of the study locations, and for each of rainy and dry seasons. The soil moisture content was obtained at 30cm soil depth while leaf wetness was measured by attaching its sensor directly to a projected leaf-branch; and surface refractivity was computed from pressure, temperature and humidity data. Correlation analysis was employed to measure the strength and direction of the relationship between surface refractivity and each of soil permittivity and leaf wetness. Across the locations, R ranges from 0.38 to 0.9; and 0.04 to 0.7 for rainy and dry season respectively. The value of R is statistically significant at all the stations during the rainy season and majority of the stations during the dry season; signifying that surface refractivity exhibits good spatial and temporal relationship with soil permittivity and leaf wetness across the stations albeit with varying intensities.

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Variations in Non-Linearity in Vertical Distribution of Microwave Radio Refractivity.

Cited by 16 publications

References 25 publications

Evolution of Dynamical Complexities in Geospace as Captured by Dst Over Four Solar Cycles 1964–2008.

Evolution of Dynamical Complexities in Geospace as Captured by Dst Over Four Solar Cycles 1964–2008.

Comparative study on Radio Refractivity Gradient in the troposphere using Chaotic Quantifiers

Variation of Surface Refractivity with Soil Permittivity and Leaf Wetness in a Tropical Location

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