Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

Song, Kun; Liu, Xichuan; Gao, Taichang; Zhang, Peng

doi:10.3390/rs13081409

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…In addition, deep learning methods have also been applied to water vapor estimation by CMLs. Song et al [104] trained an SVM model using prior data from RSL and water vapor density to mitigate the estimation error introduced by the process of extracting water vapor attenuation from RSL. Pu et al [105] achieved high temporal resolution (5-min) water vapor retrieval based on E-band CMLs using an LSTM deep learning model.…”

Section: Monitoring Phenomena Related To Water Vapormentioning

confidence: 99%

Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives

Zhang,

Liu,

2023

Remote Sensing

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As rainfall exhibits high spatiotemporal variability, accurate and real-time rainfall monitoring is vitally important in fields such as hydrometeorological research, agriculture and disaster prevention and control. Nevertheless, the current dedicated rain sensors cannot fulfill the requirement for comprehensive precipitation observation, owing to their respective limitations. Within the last two decades, the utilization of commercial microwave links (CMLs) for rainfall estimation, as an opportunistic sensing method, has generated considerable attention. Relying on CML networks deployed and maintained by mobile network operators can provide near-surface precipitation information over large areas at a low cost. Although scholars have developed several algorithms for obtaining rainfall estimates from CML data, the rainfall estimation technique based on CMLs remains challenging due to the complex effect in the microwave radiation transmission process. In this paper, we provide a comprehensive review of the technical principles, developments and workflows for this technology, alongside its application in environmental monitoring and hydrological modeling. Furthermore, this paper outlines the current challenges and future research directions, which will hopefully draw the attention of researchers and provide valuable guidance.

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Section: Monitoring Phenomena Related To Water Vapormentioning

confidence: 99%

Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives

Zhang,

Liu,

2023

Remote Sensing

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“…In addition, CML-based measurement can estimate not only rainfall, but also water vapor, solid particles, fog, snow, sleet, hail, and so on [26][27][28][29].…”

Section: Basic Principlementioning

confidence: 99%

A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks

Lian

Wei

Sun

et al. 2022

Sensors

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As one of the most critical elements in the hydrological cycle, real-time and accurate rainfall measurement is of great significance to flood and drought disaster risk assessment and early warning. Using commercial microwave links (CMLs) to conduct rainfall measure is a promising solution due to the advantages of high spatial resolution, low implementation cost, near-surface measurement, and so on. However, because of the temporal and spatial dynamics of rainfall and the atmospheric influence, it is necessary to go through complicated signal processing steps from signal attenuation analysis of a CML to rainfall map. This article first introduces the basic principle and the revolution of CML-based rainfall measurement. Then, the article illustrates different steps of signal process in CML-based rainfall measurement, reviewing the state of the art solutions in each step. In addition, uncertainties and errors involved in each step of signal process as well as their impacts on the accuracy of rainfall measurement are analyzed. Moreover, the article also discusses how machine learning technologies facilitate CML-based rainfall measurement. Additionally, the applications of CML in monitoring phenomena other than rain and the hydrological simulation are summarized. Finally, the challenges and future directions are discussed.

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“…Recent studies have shown the potential and the ability of harnessing the CML at high frequencies (E-bands) which are more sensitive to the changes of humidity but are often shorter, and thus are not always compatible for humidity detection [13,14]. In addition, research on the ability to measure the humidity based on low CML frequencies was also performed [15]. This study emphasizes the potential of the cellular infrastructure to provide large amounts of data which can potentially be used as humidity observations at a high temporal and spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Challenges in Diurnal Humidity Analysis from Cellular Microwave Links (CML) over Germany

et al. 2022

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Near-surface humidity is a crucial variable in many atmospheric processes, mostly related to the development of clouds and rain. The humidity at the height of a few tens of meters above ground level is highly influenced by surface characteristics. Measuring the near-surface humidity at high resolution, where most of the humidity’s sinks and sources are found, is a challenging task using classical tools. A novel approach for measuring the humidity is based on commercial microwave links (CML), which provide a large part of the cellular networks backhaul. This study focuses on employing humidity measurements with high spatio–temporal resolution in Germany. One major goal is to assess the errors and the environmental influence by comparing the CML-derived humidity to in-situ humidity measurements at weather stations and reanalysis (COSMO-Rea6) products. The method of retrieving humidity from the CML has been improved as compared to previous studies due to the use of new data at high temporal resolution. The results show a similar correlation on average and generally good agreement between both the CML retrievals and the reanalysis, and 32 weather stations near Siegen, West Germany (CML—0.84, Rea6—0.85). Higher correlations are observed for CML-derived humidity during the daytime (0.85), especially between 9–17 LT (0.87) and a maximum at 12 LT (0.90). During the night, the correlations are lower on average (0.81), with a minimum at 3 LT (0.74). These results are discussed with attention to the diurnal boundary layer (BL) height variation which has a strong effect on the BL humidity temporal profile. Further metrics including root mean square errors, mean values and standard deviations, were also calculated.

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Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

Cited by 6 publications

References 24 publications

Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives

Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives

A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks

Challenges in Diurnal Humidity Analysis from Cellular Microwave Links (CML) over Germany

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