Development and Testing of Conversion Models from 60-min to 1-min Rainfall Distribution over Gqeberha, South Africa for Millimeter Wave Applications
- DOI
- 10.2991/978-94-6463-644-4_24How to use a DOI?
- Keywords
- Empirical Rain Rate Conversion Models; Integration Time; Higher Frequency Bands; Millimeter Wave Applications
- Abstract
Rainfall is the main cause of signal degradation along the communication signal links above 10 GHz frequency. A crucial parameter for accurately determining rain attenuation is the 1-min rainfall integration time which is very scarce. This paper presents a conversion model for Gqeberha in South Africa on a 5-year (2016–2020) rainfall rate from a 60-min integration time to 1 min using three recognized empirical models (Segal, Burgueno, and ITU-R). The root mean square error (RMSE) metric measure has been used to test the performance of the model. The results show that the annual 60-min rainfall rate integration time varies with no significant pattern over the 5-year observation, while compared to other models; the Segal model in this study predicts Gqeberha with greater accuracy based on the lowest RMSE of 10.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Elijah Olusayo Olurotimi AU - Kingsley A. Ogudo PY - 2025 DA - 2025/02/04 TI - Development and Testing of Conversion Models from 60-min to 1-min Rainfall Distribution over Gqeberha, South Africa for Millimeter Wave Applications BT - Proceedings of the 8th URSI-NG Annual Conference (URSI-NG 2024) PB - Atlantis Press SP - 245 EP - 252 SN - 2352-541X UR - https://doi.org/10.2991/978-94-6463-644-4_24 DO - 10.2991/978-94-6463-644-4_24 ID - Olurotimi2025 ER -