Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-617-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-617-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
31 Jan 2017
Research article |
| 31 Jan 2017
Gauge-adjusted rainfall estimates from commercial microwave links
Department of Hydraulics and Hydrology, Czech Technical University in Prague, 166 29 Prague 6, Czech Republic
Michal Dohnal
Department of Hydraulics and Hydrology, Czech Technical University in Prague, 166 29 Prague 6, Czech Republic
Jörg Rieckermann
Eawag: Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
Vojtěch Bareš
Department of Hydraulics and Hydrology, Czech Technical University in Prague, 166 29 Prague 6, Czech Republic
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Cited
28 citations as recorded by crossref.
- Inversion of vertical rainfall field based on earth-space links M. Xian et al. 10.7498/aps.69.20191232
- Low complexity single-layer neural network for enhanced rainfall estimation using microwave links A. Daher et al. 10.2166/hydro.2022.099
- An evaluation of weather radar adjustment algorithms using synthetic data M. Silver et al. 10.1016/j.jhydrol.2019.06.064
- Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives P. Zhang et al. 10.3390/rs15194821
- Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation M. Pasierb et al. 10.1002/met.2218
- Commercial microwave links as a tool for operational rainfall monitoring in Northern Italy G. Roversi et al. 10.5194/amt-13-5779-2020
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Atmospheric observations with E-band microwave links – challenges and opportunities M. Fencl et al. 10.5194/amt-13-6559-2020
- Rainfall retrieval using commercial microwave links: Effect of sampling strategy on retrieval accuracy J. Pudashine et al. 10.1016/j.jhydrol.2021.126909
- Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment J. Pastorek et al. 10.1016/j.jhydrol.2022.129051
- Improved Gridded Precipitation Data Derived from Microwave Link Attenuation M. Silver et al. 10.3390/rs13152953
- A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations A. Špačková et al. 10.5194/essd-13-4219-2021
- Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions F. Zheng et al. 10.1029/2018RG000616
- Using Machine Learning Techniques for Rainfall Estimation Based on Microwave Links of Mobile Telecommunication Networks E. Kamtchoum et al. 10.1007/s42979-022-01458-6
- High‐Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small‐Scale Urban Rainfall L. de Vos et al. 10.1029/2018WR023393
- Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data M. Graf et al. 10.5194/hess-24-2931-2020
- A Machine Learning Approach for the Classification of Wet and Dry Periods Using Commercial Microwave Link Data E. Kamtchoum et al. 10.1007/s42979-022-01143-8
- Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review E. Cristiano et al. 10.5194/hess-21-3859-2017
- Rainfall Monitoring Using a Microwave Links Network: A Long-Term Experiment in East China X. Liu et al. 10.1007/s00376-023-2104-z
- Runoff prediction using rainfall data from microwave links: Tabor case study D. Stransky et al. 10.2166/wst.2018.149
- Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales M. Graf et al. 10.1016/j.ejrh.2021.100883
- Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation M. Kim & B. Kwon 10.3390/atmos9080287
- Comparison of CML Rainfall Data against Rain Gauges and Disdrometers in a Mountainous Environment R. Nebuloni et al. 10.3390/s22093218
- Commercial microwave link networks for rainfall observation: Assessment of the current status and future challenges C. Chwala & H. Kunstmann 10.1002/wat2.1337
- Use of autonomous transmission line-type electromagnetic sensors for classification of dry and wet periods at sub-hourly time intervals V. Mikešová et al. 10.1007/s10661-018-7059-7
- A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks B. Lian et al. 10.3390/s22124395
- Automatic Quality Control of Crowdsourced Rainfall Data With Multiple Noises: A Machine Learning Approach G. Niu et al. 10.1029/2020WR029121
- Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature V. Christofilakis et al. 10.3390/sym12091440
28 citations as recorded by crossref.
- Inversion of vertical rainfall field based on earth-space links M. Xian et al. 10.7498/aps.69.20191232
- Low complexity single-layer neural network for enhanced rainfall estimation using microwave links A. Daher et al. 10.2166/hydro.2022.099
- An evaluation of weather radar adjustment algorithms using synthetic data M. Silver et al. 10.1016/j.jhydrol.2019.06.064
- Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives P. Zhang et al. 10.3390/rs15194821
- Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation M. Pasierb et al. 10.1002/met.2218
- Commercial microwave links as a tool for operational rainfall monitoring in Northern Italy G. Roversi et al. 10.5194/amt-13-5779-2020
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Atmospheric observations with E-band microwave links – challenges and opportunities M. Fencl et al. 10.5194/amt-13-6559-2020
- Rainfall retrieval using commercial microwave links: Effect of sampling strategy on retrieval accuracy J. Pudashine et al. 10.1016/j.jhydrol.2021.126909
- Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment J. Pastorek et al. 10.1016/j.jhydrol.2022.129051
- Improved Gridded Precipitation Data Derived from Microwave Link Attenuation M. Silver et al. 10.3390/rs13152953
- A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations A. Špačková et al. 10.5194/essd-13-4219-2021
- Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions F. Zheng et al. 10.1029/2018RG000616
- Using Machine Learning Techniques for Rainfall Estimation Based on Microwave Links of Mobile Telecommunication Networks E. Kamtchoum et al. 10.1007/s42979-022-01458-6
- High‐Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small‐Scale Urban Rainfall L. de Vos et al. 10.1029/2018WR023393
- Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data M. Graf et al. 10.5194/hess-24-2931-2020
- A Machine Learning Approach for the Classification of Wet and Dry Periods Using Commercial Microwave Link Data E. Kamtchoum et al. 10.1007/s42979-022-01143-8
- Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review E. Cristiano et al. 10.5194/hess-21-3859-2017
- Rainfall Monitoring Using a Microwave Links Network: A Long-Term Experiment in East China X. Liu et al. 10.1007/s00376-023-2104-z
- Runoff prediction using rainfall data from microwave links: Tabor case study D. Stransky et al. 10.2166/wst.2018.149
- Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales M. Graf et al. 10.1016/j.ejrh.2021.100883
- Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation M. Kim & B. Kwon 10.3390/atmos9080287
- Comparison of CML Rainfall Data against Rain Gauges and Disdrometers in a Mountainous Environment R. Nebuloni et al. 10.3390/s22093218
- Commercial microwave link networks for rainfall observation: Assessment of the current status and future challenges C. Chwala & H. Kunstmann 10.1002/wat2.1337
- Use of autonomous transmission line-type electromagnetic sensors for classification of dry and wet periods at sub-hourly time intervals V. Mikešová et al. 10.1007/s10661-018-7059-7
- A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks B. Lian et al. 10.3390/s22124395
- Automatic Quality Control of Crowdsourced Rainfall Data With Multiple Noises: A Machine Learning Approach G. Niu et al. 10.1029/2020WR029121
- Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature V. Christofilakis et al. 10.3390/sym12091440
Latest update: 14 Dec 2024
Short summary
Commercial microwave links (CMLs) can provide rainfall observations with high space–time resolution. Unfortunately, CML rainfall estimates are often biased because we lack detailed information on the processes that attenuate the transmitted microwaves. We suggest removing the bias by continuously adjusting CMLs to cumulative data from rain gauges (RGs), which can be remote from the CMLs. Our approach practically eliminates the bias, which we demonstrate on unique data from several CMLs and RGs.
Commercial microwave links (CMLs) can provide rainfall observations with high space–time...
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