Development of a new global rain model for radio regulation

Rimven, Geraldine Rangmoen

Abstract

Signal attenuation due to rain scatter is the dominant fade mechanism on the majority of high-capacity microwave telecommunications links, both terrestrial and Earth-space. These links carry a large proportion of the information that underpins the way modern life functions and is a vital component of national infrastructure. Many studies have established the virtuous cycle that exists between the development of telecommunications infrastructure and economic growth. Therefore, it is important that rain fade models exist for the design and optimisation of telecommunications networks, globally, but especially in developing countries.

A set of internationally recognised and agreed radio propagation models is maintained by the International Telecommunications Union - Radiocommunication Sector (ITU-R) in the form of Recommendations. A fundamental input parameter to many of these models is the point one-minute rain rate exceeded for 0.01% (about 50 minutes) of an average year. Historically, the collection of one-minute rain rates has been rare and so very few regions of the world have measured this important parameter. Where local data are not available, the full distribution of one-minute rain rates, including the 0.01% exceeded rate, can be obtained from Rec. ITU-R P.837-7. The input parameters to this Recommendation are the average monthly temperatures and rain accumulations.

The network of meteorological stations is very sparse in equatorial developing countries. This limits the reliability of monthly rain accumulation statistics. ITU-R models are validated against DBSG3: the database of link and meteorological measurements maintained by ITU-R Study Group 3. However, there is very little data from the Tropics in DBSG3. Therefore, there are legitimate concerns that the ITU-R P.837-7 model may not work accurately in the Tropics.

This thesis uses rain rates derived from the satellite Earth observation Tropical Rain Measuring Mission, TRMM, to estimate point one-minute rain rate distributions in the Tropics. Two distinct uses of these data have been tested. Initially, the measured distributions of TRMM rain rates were used to estimate rain distributions in the Tropics. A method was developed to transform TRMM rain rate distributions to those needed for radio systems, based on UK rain radar data. In many cases, this method performed better than Rec. ITU-R P.837-7, particularly with databases of rain rates not included in DBSG3. To extend the work to global application, TRMM data were used to estimate the monthly rain rate distributions conditional upon monthly temperature and accumulation, as used in Rec. ITU-R P.837-7. These were then used to replace the analytic distributions in the Recommendation. The method worked well on several databases of measurements, but appeared to be biased in temperate regions. The measured TRMM conditional distributions were replaced by curve-fit approximations and a hybrid method was developed that combined the standard Rec. ITU-R P.837-7 prediction with the curve-fit TRMM prediction. This algorithm performed as well as or better than Rec. ITU-R P.837-7 for most test databases and at most time percentages.

The direct use of satellite Earth observation data to produce distributions of point one-minute rain rates is a radical departure from methods used before. This thesis has shown the potential of satellite-based measurements to replace the current methods based on downscaling numerical weather prediction output. In the future when more satellite data are available, spanning the globe, this suggests that direct use of satellite data will become standard.

Citation

Rimven, G. R. (2019). Development of a new global rain model for radio regulation. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4222073

• Thesis Type: Thesis
• Deposit Date: Jan 6, 2020
• Publicly Available Date: Feb 23, 2023
• Keywords: Engineering
• Public URL: https://hull-repository.worktribe.com/output/4222073
• Additional Information: Department of Engineering, The University of Hull
• Award Date: Jul 1, 2019