Consequently, some of the most recent work in this domain has been analyzed in this paper with a view to determine optimal techniques for different scenarios. It is also established through the work that there is lack of a suitably accurate model for prediction of rain attenuation for geographical regions prone to greater variations in weather, such as the tropical regions. Findings: The systems and mechanisms reviewed allow the identification of opportunities in establishment of novel techniques for prediction of meteorological effects and their influence on parameters such as communication signal attenuation. Recent work in the domain has been compared, largely in tabular format, with respect to critical statistics such as correlation coefficient, root mean square error, and computational complexity of the techniques.
Methods: Multiple types of prediction systems and mechanisms are reviewed, with focus on estimation of atmospheric phenomena using standard statistical models and radiometric measurements, with additional focus on the application of modern machine learning-based techniques for accurate estimate generation. Objectives: The present work illustrates an extensive review of the field of prediction of meteorological phenomena using radiometric measurements and machine learning with specific focus on rain events and their effects on satellite communication.
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