Author(s): Bin Lian; Zhongcheng Wei; Lili Huang; Jijun Zhao

Linked Author(s):

Keywords: Commercial microwave link; Power-law model; Rainfall measurement; Uncertainty analysis

Abstract: Commercial Microwave Links (CMLs) are becoming effective methods for measuring rainfall, but there are numerous uncertainties that affect the performance of CML-based rainfall measurement. This paper first introduces the theoretical background, and then the uncertainties are categorized into two types: attribute uncertainty and model uncertainty. Furthermore, we utilize two open-source datasets to validate and discuss the impact of key parameters such as rain characteristics, sampling rate, and frequency on the performance of CML-based rainfall retrieval. The findings indicate that the time-frequency feature significantly varies with different rain characteristics. The sampling rate directly influences the selection of parameter values in the models for CML data processing, with a higher sampling rate being preferred due to its superior capability to capture the real-time variability of CML time series. Frequencies between 20 GHz and 35 GHz are found to be more suitable for rainfall retrieval using the ITU power law model.

DOI: https://doi.org/10.3850/iahr-hic2483430201-353

Year: 2024