Analysis of radiosonde data on tropospheric water vapour in Nigeria

Willoughby, AA; Adimula, IA; Aro, TO; Owolabi, I.E.

doi:10.4314/njphy.v20i2.46149

Cited by 2 publications

(2 citation statements)

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“…More advanced methods for estimating precipitable water vapor include the use of radiosonde/dropsonde data ( Willoughby et al., 2008 ; Adeyemi, 2008 ; Chang-Geun et al., 2012 ; Adeyemi and Joerg, 2012 ), microwave radiometers ( Han et al., 1994 ), star photometers ( Pérez-Ramírez et al., 2012 ), Raman lidars ( Whiteman et al., 1992 ), Fourier transform spectrometers ( Leblanc et al., 2011 ) and GPS/satellite data ( Bevis et al., 1992 , Bevis et al., 1994 ; Ware et al., 1997 ; Jade et al., 2005 , Sharifi et al., 2015 , Li et al., 2018 ) which use the principle of tropospheric delays.…”

Section: Methodsmentioning

confidence: 99%

Multi-technique analysis of precipitable water vapor estimates in the sub-Sahel West Africa

Falaiye

Abimbola

Pinker

et al. 2018

Heliyon

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Precipitable water vapor (PWV) is an important climate parameter indicative of available moisture in the atmosphere; it is also an important greenhouse gas. Observations of precipitable water vapor in sub-Sahel West Africa are almost non-existent. Several Aerosol Robotic Network (AERONET) sites have been established across West Africa, and observations from four of them, namely, Ilorin (4.34° E, 8.32° N), Cinzana (5.93° W, 13.28° N), Banizoumbou (2.67° E, 13.54° N) and Dakar (16.96° W, 14.39° N) are being used in this study. Data spanning the period from 2004 to 2014 have been selected; they include conventional humidity parameters, remotely sensed aerosol and precipitable water information and numerical model outputs. Since in Africa, only conventional information on humidity parameters is available, it is important to utilize the unique observations from the AERONET network to calibrate empirical formulas frequently used to estimate precipitable water vapor from humidity measurements. An empirical formula of the form PWV=aTd+b where Td is the surface dew point temperature, a and b are constants, was fitted to the data and is proposed as applicable to the climatic condition of the sub-Sahel. Moreover, we have also used the AERONET information to evaluate the capabilities of well-established numerical weather prediction (NWP) models such as ERA Interim Reanalysis, NCEP-DOE Reanalysis II and NCEP-CFSR, to estimate precipitable water vapor in the sub-Sahel West Africa; it was found that the models tend to overestimate the amount of precipitable water at the selected sites by about 25 %.

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Section: Methodsmentioning

confidence: 99%

Multi-technique analysis of precipitable water vapor estimates in the sub-Sahel West Africa

Falaiye

Abimbola

Pinker

et al. 2018

Heliyon

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“…One of the important properties of the atmosphere that varies with changes in the weather is its density [36][37][38]. Changes in the density of the atmosphere can afect the properties of propagating electromagnetic waves, mainly its refraction [1,[39][40][41][42][43]. Refraction is just the deviation in the path of a propagating wave as a result of the dissimilarity in the density of the media or medium which it propagates through.…”

Section: Introductionmentioning

confidence: 99%

Radio Refractivity Impact on Signal Strength of Mobile Communication

Amajama,

Asagha,

Ushie

et al. 2023

Journal of Electrical and Computer Engineering

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This research investigated radio refractivity impact on signal strength of mobile communication. The mobile communication signal strengths of two popular networks in Nigeria, 9Mobile and MTN, were considered. In the 2100 MHz-3 G band, 9Mobile transmits in the downlink spectrum of 2130.00–2140.00 MHz, while MTN transmits in the downlink spectrum of 2110.00–2120.00 MHz. Also, 9Mobile transmits in the downlink spectrum of 791–821 MHz in the 800 MHz band and 1805–1880 MHz in the 1800 MHz, while MTN transmits in the downlink spectrums of 2620–2690 MHz in the 2600 MHz band; all in the 4 G band. Using the instrument of a mobile station in each station (location) in some selected cities in southern Nigeria, the signal strengths were measured. A cell signal monitor (version 5.1.1) mobile application installed in an Android (transceiver) device (having two SIM slots) constituted the mobile station. To achieve high accuracy, there was a restriction in measuring transmission from specific cells. Hourly measurement of signal strengths was carried out and instantaneously corresponding weather parameters were recorded. Weather parameters for this investigation; atmospheric temperature and pressure; and relative humidity were excerpted online from the Nigeria Meteorological Agency (NIMET) hourly weather report for the various cities where the stations were situated. The hourly radio refractivity was computed using the 2015 International Telecommunication Union–Radio-communication sector (ITU-R) recommended model. Overall, the results indicate that there was no established linear relationship between signal strength and radio refractivity since the overall average R value is 0.0123691 and the overall average standard deviation of R values is 0.1112165. The inconsistencies in the linear relationships obtained from different locations and cells could be due to variations in topography, antenna properties, seasonal variations, wind and position, and distance of the receiver from the transmitter.

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Analysis of radiosonde data on tropospheric water vapour in Nigeria

Cited by 2 publications

References 0 publications

Multi-technique analysis of precipitable water vapor estimates in the sub-Sahel West Africa

Multi-technique analysis of precipitable water vapor estimates in the sub-Sahel West Africa

Radio Refractivity Impact on Signal Strength of Mobile Communication

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