Abstract
Accurate and real-time rainfall estimation is a pressing need for forecasting the flood disaster and reducing the loss. In this study, we exploit the potential of estimating the rainfall by microwave links in East China. Eight microwave links at 15 GHz and 23 GHz, operated by China Mobile, are used for estimating the rain rate in real-time in Jiangyin, China from June to July 2020. First, we analyze the correlation between the rain-induced attenuation of microwave links and the rain rate measured by rain gauges. The correlation coefficient values are higher than 0.77 with the highest one over 0.9, showing a strong positive correlation. The real-time results indicate that microwave links estimate the rainfall with a higher temporal resolution than the rain gauges. Meanwhile, the rain rate that was estimated by microwave links also correlates well with the actual rain rate, and most of the values of the mean absolute error are less than 1.50 mm/h. Besides, the total rainfall’s relative deviation values are less than 5% with the smallest one reaching 1%. The quantitative results also indicate that microwave links could lead to better forecasting of water levels and, hence, better warnings for flood disasters.
Highlights
East China during the Plum RainAccurate and real-time rainfall estimation is essential for forecasting flood disaster and reducing the loss of life and property
In 2010, the near-surface rain rate in the alpine region of Southern Germany has been estimated by commercial microwave links (CML), and the result positively correlates with the rainfall being estimated by radars [11]
[33], eight microwave links in our study are operated by CML-based rainfall estimationcommunication in China
Summary
Accurate and real-time rainfall estimation is essential for forecasting flood disaster and reducing the loss of life and property. The rain gauge (RG) is considered to be an accurate ground-based estimation. It does not provide rain data with high spatial resolution [1,2]. It is necessary to develop an accurate, real-time, and ground-based approach to be a complement to the RG and the weather radar. In 2010, the near-surface rain rate in the alpine region of Southern Germany has been estimated by CMLs, and the result positively correlates with the rainfall being estimated by radars [11]. We estimate the rainfall by CMLs during the plum rain season in 2020 in Jiangyin, China. This study is the first CML-based rainfall estimation in China. The advantages and limitations of this approach are pointed in this study
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