Rainfall Monitoring Using a Microwave Links Network: A Long-Term Experiment in East China

Liu, Xichuan; Zhao, Kun; Zou, Mingzhong; Pu, Kang; Song, Kun

doi:10.1007/s00376-023-2104-z

Cited by 4 publications

(3 citation statements)

References 57 publications

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“…Zheng et al [191] focus particularly on the capability of CML data to provide good area rainfall data in urban areas. Recent studies in general confirm that with careful processing, CML data can provide distributed rainfall data that can be applied with confidence to studies of urban hydrology and flooding problems (Liu et al [192], Pastorek et al [183]).…”

Section: Microwave Attenuation (Cellular Phone Links Satellite Links ...mentioning

confidence: 92%

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Dunkerley

2023

Water

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Many design principles for rain gauges that have the capacity to record rainfall intensity have been proposed or developed. These are here grouped into 15 categories, and the abilities and limitations of each are discussed. No standard or optimum method has emerged, despite more than 80 years of effort in the last two centuries, together with prior work from the 17th C onwards. Indeed, new methods continue to be explored for both point-based and area-wide collections of intensity data. Examples include the use of signal attenuation by rain along the tower-to-tower links of cellular phone networks, monitoring the speed of vehicle windscreen wipers, and exploiting the sound or vision from security and traffic-monitoring cameras. Many of these approaches have the potential to provide vastly more observation sites than conventional meteorological stations equipped with rain gauges. Some of these contemporary approaches seek to harness the potential of crowdsourced or citizen-science data. It is hoped that the present overview of methods will provide a guide for those wishing to collect or analyses rainfall intensity data for application in areas such as soil erosion processes, ecohydrology, agrochemical washoff, or urban flash flooding. Because rainfall intensity is one of the key aspects of the hydrologic cycle likely to respond as climate change and variability proceed, the choice of appropriate data collection methods has additional contemporary importance for the monitoring of regional and global precipitation changes.

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Section: Microwave Attenuation (Cellular Phone Links Satellite Links ...mentioning

confidence: 92%

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Dunkerley

2023

Water

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“…In addition, raindrops in DSDs with unmatched D ‐ V (normal D / V vs. excessively large or small V / D ) were also considered to be unreliable data, which could be produced under strong wind shear conditions or by raindrops splashing on the surface of the instrument. We compared the measured D ‐ V of OTT data with the Atlas diameter‐velocity empirical model (Atlas et al., 1973), and data with more than 50% deviation between theoretical and measured velocity were removed by quality control (Liu et al., 2023):

{V}_{\text{Atlas}}\left({D}_{i}\right)=9.65-10.3{e}^{-0.6{D}_{i}}.

In this experiment, the OTT data from July to November 2021 are used to calibrate the γ rain ‐ R relationship. The fitted γ rain ‐ R relationship and ITU‐R model are shown in Figure 5.…”

Section: Methodsmentioning

confidence: 99%

“…We compared the measured D-V of OTT data with the Atlas diameter-velocity empirical model (Atlas et al, 1973), and data with more than 50% deviation between theoretical and measured velocity were removed by quality control (Liu et al, 2023):…”

Section: Calibration Of the Power-law Relationshipmentioning

confidence: 99%

Reconstructing and Nowcasting the Rainfall Field by a CML Network

Zhang,

Liu,

Zou

2023

Earth and Space Science

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Currently, the opportunistic method to estimate rainfall using commercial microwave links (CMLs) has been shown as an efficient way to complement traditional instruments in terms of spatial‐temporal resolution and coverage. In this paper, we collected data from 26 CMLs in Jiangyin City, Jiangsu Province, and conducted experiments on rainfall field reconstruction and nowcasting. First, the raw CML data were processed to invert the path‐averaged rainfall intensity. Second, the algorithms of inverse distance weighting (IDW) and ordinary kriging (OK) interpolation were employed to reconstruct the rainfall field. Then a 10‐min prediction of the rainfall field was achieved using a nowcasting model based on the long short‐term memory neural network and a setup window was introduced to improve the prediction performance of the first few minutes. The reconstruction results show that the average correlation coefficient (ACC) and the average root mean square error (ARMSE) between the IDW‐based results and daily cumulative rainfall from rain gauges (RGs) are 0.89 and 8.69 mm, respectively, while the ACC and ARMSE between the OK‐based results and RG data are 0.89 and 9.13 mm, respectively. The nowcasting results show that the ACC between the prediction results with a 5‐min setup window and the IDW‐retrieved rainfall fields can reach 0.91 at the first minute and gradually decrease to 0.20 within 10 min. Furthermore, the model has better nowcasting performance for stratiform precipitation and mixed precipitation compared to convective precipitation.

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On the Potential of Using Emerging Microwave Links for City Rainfall Monitoring

Han,

Zhang,

et al. 2023

IEEE Commun. Mag.

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Rainfall Monitoring Using a Microwave Links Network: A Long-Term Experiment in East China

Cited by 4 publications

References 57 publications

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Recording Rainfall Intensity: Has an Optimum Method Been Found?

Reconstructing and Nowcasting the Rainfall Field by a CML Network

On the Potential of Using Emerging Microwave Links for City Rainfall Monitoring

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