Specific rain attenuation derived from a gaussian mixture model for rainfall drop size distribution

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Abstract

Precipitation, particularly rain affects the millimetre and sub-millimetre frequencies more severely than it does for lower frequencies in the Earthspace path. There is therefore a need for accurate models that will enable the rainfall drop size distribution (DSD) to be better predicted for better planning and improved service delivery. Using data captured at Chilbolton Observatory, this paper looks at modelling the DSD using the Gaussian Mixture Model (GMM), and attempts to predict the specific attenuation due to rain based on this model and compares the result with other well-established statistical models (lognormal and gamma). Results show that specific attenuation tends to increase with the drop sizes, and the smaller drops contribute little to the overall attenuation experienced by signals. Specific attenuation was computed based on several standard statistical distributions, and compared with that derived from the ITU recommendation.

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Ekerete, K. M. E., Hunt, F. H., Jeffery, J. L., & Otung, I. E. (2017). Specific rain attenuation derived from a gaussian mixture model for rainfall drop size distribution. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 186 LNICST, pp. 167–177). Springer Verlag. https://doi.org/10.1007/978-3-319-53850-1_17

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