Big Data Enhancement of R _0.01 Reliability for Rain Attenuation Model Optimization in Thailand

Abstract

Rain attenuation prediction is crucial for satellite communication, particularly in tropical regions like Thailand. A key parameter in rain attenuation modeling is the rainfall rate exceeded for 0.01% of the time (R0.01). This study collects big data from rain gauges across Thailand, recorded at 1-minute intervals over three years (2022-2024), and analyzes the Data Reception Rate (DRR) by comparing annual rainfall rates. This analysis also monitors the development and quality of the rain gauge network. The results, showing a high DRR, indicate the reliability of R0.01. This reliable R0.01 can then be used to accurately calculate the predicted attenuation exceeded for 0.01% of the time (A0.01), derived from slant-path measurements following the ITU-R model, using existing satellites serving Thailand.