Journal of Nigerian Society of Physical Sciences (Dec 2022)

Estimation of some Radio Propagation Parameters using Measurements of Surface Meteorological Variables in Ede, Southwest Nigeria

  • A. A. Willoughby,
  • M. E. Sanyaolu,
  • M. O. Osinowo,
  • A. O. Soge,
  • O. F. Dairo

DOI
https://doi.org/10.46481/jnsps.2023.875
Journal volume & issue
Vol. 5, no. 1

Abstract

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A data acquisition system that utilised the open-source Arduino platform was developed to take real-time ground measurements of primary radio climatological variables of pressure, temperature, and relative humidity at Ede, a tropical station in southwest Nigeria (7.7349^{o} N, 4.4439^{o} E). Surface radio refractivity was deduced from these variables and used to estimate refractivity gradients at 100 m and 1000 m heights from the exponential reference atmosphere model for terrestrial propagation. Secondary radio propagation parameters such as refractivity gradients, the effective-earth-radius-factor, k, and geoclimatic factor, K, essential parameters for quick application in the planning and design of line-of-sight radio link systems, were also deduced. Data acquired from the device were compared to those obtained from the Re-Analyses (ERA-5) satellite database of the European Centre for Medium-Range Weather Forecast (ECMWF) 2020/2021. Aside from logging data on a micro secure digital (SD) card, measurements were displayed on a liquid crystal display (LCD). The peripheral Arduino-compatible meteorological sensors were connected to the analog inputs of the ATMega328 in the Arduino independent development environment (IDE), and the unit was powered by a 12 V battery charged by a 50-watt solar module. Results showed that slightly higher values of the ERA-5 data characterise the dry months from November to March, while the wet months displayed higher values of the Arduino-derived measured data. The accuracies of the data collected were compared using Mean Percentage Error (MPE) performance indicator. The interpretation is that the mean difference between the Arduino inferred measurements and the ERA-5 data is less than 10%, which is an indication of the measurement accuracy.

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